Supervised Learning : Modelling Multiclass Categorical Responses for Prediction
John Pauline Pineda
December 5, 2022
- 1.
Table of Contents
- 1.1 Sample Data
- 1.2 Data Quality Assessment
- 1.3 Data Preprocessing
- 1.4 Data Exploration
- 1.5 Predictive Model
Development
- 1.5.1 Penalized Multinomial Regression (PMR)
- 1.5.2 Linear Discriminant Analysis (LDA)
- 1.5.3 Flexible Discriminant Analysis (FDA)
- 1.5.4 Mixture Discriminant Analysis (MDA)
- 1.5.5 Naive Bayes (NB)
- 1.5.6 Nearest Shrunken Centroids (NSC)
- 1.5.7 Averaged Neural Network (AVNN)
- 1.5.8 Support Vector Machine - Radial Basis Function Kernel (SVM_R)
- 1.5.9 Support Vector Machine - Polynomial Kernel (SVM_P)
- 1.5.10 K-Nearest Neighbors (KNN)
- 1.5.11 Classification and Regression Trees (CART)
- 1.5.12 Conditional Inference Trees (CTREE)
- 1.5.13 C5.0 Decision Trees (C50)
- 1.5.14 Random Forest (RF)
- 1.5.15 Bagged Trees (BTREE)
- 1.6 Consolidated Findings
- 2. Summary
- 3. References
1. Table of Contents
This project implements different predictive modelling procedures for multiclass categorical responses using various helpful packages in R. Models applied in the analysis to predict multiclass categorical responses included the Penalized Multinomial Regression, Linear Discriminant Analysis, Flexible Discriminant Analysis, Mixture Discriminant Analysis, Naive Bayes, Nearest Shrunken Centroids, Averaged Neural Network, Support Vector Machine (Radial Basis Function Kernel, Polynomial Kernel), K-Nearest Neighbors, Classification and Regression Trees, Conditional Inference Trees, C5.0 Decision Trees, Random Forest and Bagged Trees algorithms. The resulting predictions derived from the candidate models were evaluated in terms of their classification performance using the accuracy metric. All results were consolidated in a Summary presented at the end of the document.
Multiclass classification learning refers to a predictive modelling problem where more than two class labels are predicted for a given sample of input data. These models use the training data set and calculate how to best map instances of input data to the specific class labels. Multiclass classification does not have the notion of normal and abnormal outcomes. Instead, instances are classified as belonging to one among a range of known classes. It is common to model a multiclass classification task with a model that predicts a Multinoulli probability distribution for each instance. The Multinoulli distribution is a discrete probability distribution that covers a case where an event will have a categorical outcome. For classification, this means that the model predicts the probability of an instance belonging to each class label. The algorithms applied in this study (mostly contained in the caret package) attempt to categorize the input data and form polytomous groups based on their similarities.
1.1 Sample Data
The Solubility dataset from the AppliedPredictiveModeling package was used for this illustrated example. The original numeric response was transformed to simulate a multiclass variable.
Preliminary dataset assessment:
[A] 1267 rows (observations)
[A.1] Train Set = 951 observations
[A.2] Test Set = 316 observations
[B] 229 columns (variables)
[B.1] 1/229 response = Log_Solubility_Class variable (factor)
[B.1.1] Levels = Log_Solubility_Class=Low < Log_Solubility_Class=Mid < Log_Solubility_Class=High
[B.2] 228/229 predictors = All remaining variables (208/228 factor + 20/228 numeric)
Code Chunk | Output
##################################
# Loading R libraries
##################################
library(AppliedPredictiveModeling)
library(caret)
library(rpart)
library(lattice)
library(dplyr)
library(tidyr)
library(moments)
library(skimr)
library(RANN)
library(pls)
library(corrplot)
library(tidyverse)
library(lares)
library(DMwR2)
library(gridExtra)
library(rattle)
library(rpart.plot)
library(RColorBrewer)
library(stats)
library(nnet)
library(elasticnet)
library(earth)
library(party)
library(kernlab)
library(randomForest)
library(Cubist)
library(pROC)
library(mda)
library(klaR)
library(pamr)
library(MLmetrics)
library(ordinalNet)
library(C50)
##################################
# Loading source and
# formulating the train set
##################################
data(solubility)
Solubility_Train <- as.data.frame(cbind(solTrainY,solTrainX))
Solubility_Test <- as.data.frame(cbind(solTestY,solTestX))
##################################
# Computing the thresholds
# for converting the numeric response
# to a multiclass response
##################################
Log_Solubility_Mean <- mean(Solubility_Train$solTrainY)
Log_Solubility_75Percentile <- quantile(Solubility_Train$solTrainY, probs = 0.75)[1]
##################################
# Applying dichotomization and
# defining the response variable
##################################
Solubility_Train$Log_Solubility_Class <- ifelse(Solubility_Train$solTrainY<Log_Solubility_Mean,
"Low",ifelse(Solubility_Train$solTrainY<Log_Solubility_75Percentile,
"Mid","High"))
Solubility_Train$Log_Solubility_Class <- factor(Solubility_Train$Log_Solubility_Class,
levels = c("Low","Mid","High"))
Solubility_Test$Log_Solubility_Class <- ifelse(Solubility_Test$solTestY<Log_Solubility_Mean,
"Low",ifelse(Solubility_Test$solTestY<Log_Solubility_75Percentile,
"Mid","High"))
Solubility_Test$Log_Solubility_Class <- factor(Solubility_Test$Log_Solubility_Class,
levels = c("Low","Mid","High"))
Solubility_Train$solTrainY <- NULL
Solubility_Test$solTestY <- NULL
##################################
# Performing a general exploration of the train set
##################################
dim(Solubility_Train)## [1] 951 229str(Solubility_Train)## 'data.frame': 951 obs. of 229 variables:
## $ FP001 : int 0 0 1 0 0 1 0 1 1 1 ...
## $ FP002 : int 1 1 1 0 0 0 1 0 0 1 ...
## $ FP003 : int 0 0 1 1 1 1 0 1 1 1 ...
## $ FP004 : int 0 1 1 0 1 1 1 1 1 1 ...
## $ FP005 : int 1 1 1 0 1 0 1 0 0 1 ...
## $ FP006 : int 0 1 0 0 1 0 0 0 1 1 ...
## $ FP007 : int 0 1 0 1 0 0 0 1 1 1 ...
## $ FP008 : int 1 1 1 0 0 0 1 0 0 0 ...
## $ FP009 : int 0 0 0 0 1 1 1 0 1 0 ...
## $ FP010 : int 0 0 1 0 0 0 0 0 0 0 ...
## $ FP011 : int 0 1 0 0 0 0 0 0 1 0 ...
## $ FP012 : int 0 0 0 0 0 1 0 1 0 0 ...
## $ FP013 : int 0 0 0 0 1 0 1 0 0 0 ...
## $ FP014 : int 0 0 0 0 0 0 1 0 0 0 ...
## $ FP015 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ FP016 : int 0 1 0 0 1 1 0 1 0 0 ...
## $ FP017 : int 0 0 1 1 0 0 0 0 1 1 ...
## $ FP018 : int 0 1 0 0 0 0 0 0 0 0 ...
## $ FP019 : int 1 0 0 0 1 0 1 0 0 0 ...
## $ FP020 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP021 : int 0 0 0 0 0 1 0 0 1 0 ...
## $ FP022 : int 0 0 0 0 0 0 0 0 0 1 ...
## $ FP023 : int 0 0 0 1 0 0 0 0 1 0 ...
## $ FP024 : int 1 0 0 0 1 0 0 0 0 0 ...
## $ FP025 : int 0 0 1 0 0 0 0 0 0 0 ...
## $ FP026 : int 1 0 0 0 0 0 1 0 0 0 ...
## $ FP027 : int 0 0 0 0 0 0 0 0 0 1 ...
## $ FP028 : int 0 1 0 0 0 0 0 0 1 1 ...
## $ FP029 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP030 : int 0 0 0 0 1 0 0 0 0 0 ...
## $ FP031 : int 0 0 0 0 0 0 0 1 0 0 ...
## $ FP032 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP033 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP034 : int 0 0 0 0 1 0 0 0 0 1 ...
## $ FP035 : int 0 0 0 0 0 0 0 0 1 0 ...
## $ FP036 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP037 : int 0 0 0 0 0 0 0 0 1 0 ...
## $ FP038 : int 0 0 1 0 0 0 0 0 0 0 ...
## $ FP039 : int 1 0 0 0 0 0 0 0 0 0 ...
## $ FP040 : int 1 0 0 0 0 0 0 0 0 0 ...
## $ FP041 : int 0 0 0 1 0 0 0 0 1 0 ...
## $ FP042 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP043 : int 0 1 0 0 0 0 0 0 0 0 ...
## $ FP044 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP045 : int 0 0 1 0 0 0 0 0 0 0 ...
## $ FP046 : int 0 1 0 0 0 0 1 0 0 1 ...
## $ FP047 : int 0 1 1 0 0 0 1 0 0 0 ...
## $ FP048 : int 0 0 0 0 0 0 0 1 0 0 ...
## $ FP049 : int 0 0 0 0 0 0 1 0 0 0 ...
## $ FP050 : int 0 0 0 0 0 0 0 1 0 1 ...
## $ FP051 : int 0 1 0 0 0 0 0 0 0 0 ...
## $ FP052 : int 0 0 0 0 0 0 0 0 0 1 ...
## $ FP053 : int 0 0 0 0 0 0 1 0 0 0 ...
## $ FP054 : int 0 0 0 1 0 0 0 0 1 1 ...
## $ FP055 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP056 : int 1 0 0 0 0 0 0 0 0 0 ...
## $ FP057 : int 0 0 0 0 0 0 1 0 0 0 ...
## $ FP058 : int 0 0 0 0 0 0 0 0 0 1 ...
## $ FP059 : int 0 0 0 0 0 0 0 1 0 0 ...
## $ FP060 : int 0 1 1 0 0 0 0 1 1 0 ...
## $ FP061 : int 0 0 1 0 0 0 0 1 1 0 ...
## $ FP062 : int 0 0 1 0 0 1 0 1 1 1 ...
## $ FP063 : int 1 1 0 0 1 1 1 0 0 1 ...
## $ FP064 : int 0 1 1 0 1 1 0 1 0 0 ...
## $ FP065 : int 1 1 0 0 1 0 1 0 1 1 ...
## $ FP066 : int 1 0 1 1 1 1 1 1 1 1 ...
## $ FP067 : int 1 1 0 0 1 1 1 0 0 1 ...
## $ FP068 : int 0 1 0 0 1 1 1 0 0 1 ...
## $ FP069 : int 1 0 1 1 1 1 0 1 1 0 ...
## $ FP070 : int 1 1 0 1 0 0 1 0 1 0 ...
## $ FP071 : int 0 0 0 0 0 0 1 0 1 1 ...
## $ FP072 : int 0 1 1 0 0 1 0 1 1 1 ...
## $ FP073 : int 0 1 1 0 0 0 0 0 1 0 ...
## $ FP074 : int 0 1 0 0 0 0 0 0 1 0 ...
## $ FP075 : int 0 1 0 0 1 1 1 0 0 1 ...
## $ FP076 : int 1 1 0 0 0 0 1 0 1 1 ...
## $ FP077 : int 0 1 0 1 0 0 0 1 1 1 ...
## $ FP078 : int 0 1 0 0 0 0 0 0 1 0 ...
## $ FP079 : int 1 1 1 1 1 0 1 0 1 1 ...
## $ FP080 : int 0 1 0 0 1 1 1 1 0 0 ...
## $ FP081 : int 0 0 1 1 0 0 0 1 1 1 ...
## $ FP082 : int 1 1 1 0 1 1 1 0 1 1 ...
## $ FP083 : int 0 0 0 0 1 0 0 0 0 1 ...
## $ FP084 : int 1 1 0 0 1 0 1 0 0 0 ...
## $ FP085 : int 0 1 0 0 0 0 1 0 0 0 ...
## $ FP086 : int 0 0 0 1 1 0 0 1 1 1 ...
## $ FP087 : int 1 1 1 1 1 0 1 0 1 1 ...
## $ FP088 : int 0 1 0 0 0 0 0 1 1 0 ...
## $ FP089 : int 1 1 0 0 0 0 1 0 0 0 ...
## $ FP090 : int 0 1 0 1 0 0 0 1 1 1 ...
## $ FP091 : int 1 1 0 0 1 0 1 0 0 1 ...
## $ FP092 : int 0 0 0 0 1 1 1 0 1 0 ...
## $ FP093 : int 0 1 0 1 0 0 0 1 1 1 ...
## $ FP094 : int 0 0 0 0 1 0 0 1 0 0 ...
## $ FP095 : int 0 0 0 0 0 0 0 0 1 1 ...
## $ FP096 : int 0 0 0 0 0 0 0 0 1 0 ...
## $ FP097 : int 1 1 0 0 0 0 1 0 1 0 ...
## $ FP098 : int 0 0 1 0 0 0 0 1 0 0 ...
## $ FP099 : int 0 0 0 0 0 0 0 0 1 0 ...
## [list output truncated]summary(Solubility_Train)## FP001 FP002 FP003 FP004
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :1.0000 Median :0.0000 Median :1.0000
## Mean :0.4932 Mean :0.5394 Mean :0.4364 Mean :0.5846
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP005 FP006 FP007 FP008
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000
## Median :1.0000 Median :0.0000 Median :0.0000 Median :0.000
## Mean :0.5794 Mean :0.4006 Mean :0.3638 Mean :0.326
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.000
## FP009 FP010 FP011 FP012
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.2797 Mean :0.1788 Mean :0.2145 Mean :0.1767
## 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP013 FP014 FP015 FP016
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:1.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :1.0000 Median :0.0000
## Mean :0.1661 Mean :0.1609 Mean :0.8601 Mean :0.1462
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:1.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP017 FP018 FP019 FP020
## Min. :0.0000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.000 Median :0.0000
## Mean :0.1441 Mean :0.1314 Mean :0.122 Mean :0.1199
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.000 Max. :1.0000
## FP021 FP022 FP023 FP024
## Min. :0.0000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.000 Median :0.0000
## Mean :0.1209 Mean :0.1041 Mean :0.123 Mean :0.1125
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.000 Max. :1.0000
## FP025 FP026 FP027 FP028
## Min. :0.0000 Min. :0.00000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.0000 Median :0.00000 Median :0.00000 Median :0.0000
## Mean :0.1157 Mean :0.08412 Mean :0.09779 Mean :0.1062
## 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.00000 Max. :1.00000 Max. :1.0000
## FP029 FP030 FP031 FP032
## Min. :0.000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.102 Mean :0.09359 Mean :0.08938 Mean :0.07361
## 3rd Qu.:0.000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP033 FP034 FP035 FP036
## Min. :0.0000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.0000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.0694 Mean :0.07992 Mean :0.07256 Mean :0.07571
## 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.0000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP037 FP038 FP039 FP040
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.07045 Mean :0.08622 Mean :0.07466 Mean :0.06835
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP041 FP042 FP043 FP044
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.06309 Mean :0.05678 Mean :0.06625 Mean :0.05994
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP045 FP046 FP047 FP048
## Min. :0.00000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.00000 Median :0.0000 Median :0.000 Median :0.0000
## Mean :0.05573 Mean :0.3155 Mean :0.266 Mean :0.1241
## 3rd Qu.:0.00000 3rd Qu.:1.0000 3rd Qu.:1.000 3rd Qu.:0.0000
## Max. :1.00000 Max. :1.0000 Max. :1.000 Max. :1.0000
## FP049 FP050 FP051 FP052
## Min. :0.000 Min. :0.0000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.000 Median :0.0000 Median :0.0000 Median :0.00000
## Mean :0.122 Mean :0.1125 Mean :0.1094 Mean :0.09148
## 3rd Qu.:0.000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.000 Max. :1.0000 Max. :1.0000 Max. :1.00000
## FP053 FP054 FP055 FP056
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.09359 Mean :0.07571 Mean :0.05363 Mean :0.06519
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP057 FP058 FP059 FP060
## Min. :0.0000 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.00000 Median :0.0000
## Mean :0.1199 Mean :0.1136 Mean :0.05468 Mean :0.4816
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.00000 Max. :1.0000
## FP061 FP062 FP063 FP064
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.4469 Mean :0.4374 Mean :0.4259 Mean :0.4164
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP065 FP066 FP067 FP068
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :1.0000 Median :1.0000 Median :0.0000 Median :0.0000
## Mean :0.5931 Mean :0.6099 Mean :0.3796 Mean :0.3617
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP069 FP070 FP071 FP072
## Min. :0.0000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.000 Median :1.0000
## Mean :0.3617 Mean :0.3554 Mean :0.327 Mean :0.6583
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.000 Max. :1.0000
## FP073 FP074 FP075 FP076
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.3102 Mean :0.3249 Mean :0.3386 Mean :0.3281
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP077 FP078 FP079 FP080
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :1.0000 Median :0.0000
## Mean :0.3207 Mean :0.3039 Mean :0.6898 Mean :0.3028
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP081 FP082 FP083 FP084
## Min. :0.0000 Min. :0.000 Min. :0.0000 Min. :0.000
## 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.000
## Median :0.0000 Median :1.000 Median :0.0000 Median :0.000
## Mean :0.2787 Mean :0.714 Mean :0.2734 Mean :0.286
## 3rd Qu.:1.0000 3rd Qu.:1.000 3rd Qu.:1.0000 3rd Qu.:1.000
## Max. :1.0000 Max. :1.000 Max. :1.0000 Max. :1.000
## FP085 FP086 FP087 FP088
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :1.0000 Median :0.0000
## Mean :0.2555 Mean :0.2692 Mean :0.7266 Mean :0.2629
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP089 FP090 FP091 FP092
## Min. :0.0000 Min. :0.0000 Min. :0.000 Min. :0.000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.000
## Median :0.0000 Median :0.0000 Median :0.000 Median :0.000
## Mean :0.2471 Mean :0.2492 Mean :0.225 Mean :0.244
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.000
## Max. :1.0000 Max. :1.0000 Max. :1.000 Max. :1.000
## FP093 FP094 FP095 FP096
## Min. :0.000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.244 Mean :0.2313 Mean :0.2198 Mean :0.2177
## 3rd Qu.:0.000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP097 FP098 FP099 FP100
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.2355 Mean :0.2376 Mean :0.2271 Mean :0.2313
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP101 FP102 FP103 FP104
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.2366 Mean :0.2019 Mean :0.2187 Mean :0.2229
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP105 FP106 FP107 FP108
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.000
## Mean :0.2156 Mean :0.1914 Mean :0.2114 Mean :0.205
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.000
## FP109 FP110 FP111 FP112
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1767 Mean :0.2061 Mean :0.1966 Mean :0.1945
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP113 FP114 FP115 FP116
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1956 Mean :0.1556 Mean :0.1788 Mean :0.1924
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP117 FP118 FP119 FP120
## Min. :0.0000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.000 Median :0.0000
## Mean :0.1788 Mean :0.1924 Mean :0.163 Mean :0.1661
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.000 Max. :1.0000
## FP121 FP122 FP123 FP124
## Min. :0.0000 Min. :0.000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.000 Median :0.0000 Median :0.0000
## Mean :0.1399 Mean :0.164 Mean :0.1672 Mean :0.1619
## 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.000 Max. :1.0000 Max. :1.0000
## FP125 FP126 FP127 FP128
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1556 Mean :0.1483 Mean :0.1399 Mean :0.1483
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP129 FP130 FP131 FP132
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1388 Mean :0.1052 Mean :0.1262 Mean :0.1251
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP133 FP134 FP135 FP136
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1262 Mean :0.1272 Mean :0.1262 Mean :0.1209
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP137 FP138 FP139 FP140
## Min. :0.0000 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.00000 Median :0.0000
## Mean :0.1157 Mean :0.1115 Mean :0.08202 Mean :0.1115
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.00000 Max. :1.0000
## FP141 FP142 FP143 FP144
## Min. :0.0000 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.00000 Median :0.0000
## Mean :0.1167 Mean :0.1094 Mean :0.08097 Mean :0.1041
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.00000 Max. :1.0000
## FP145 FP146 FP147 FP148
## Min. :0.0000 Min. :0.000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.0000 Median :0.000 Median :0.0000 Median :0.00000
## Mean :0.1041 Mean :0.103 Mean :0.1052 Mean :0.08728
## 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.0000 Max. :1.000 Max. :1.0000 Max. :1.00000
## FP149 FP150 FP151 FP152
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.09043 Mean :0.07886 Mean :0.05573 Mean :0.08202
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP153 FP154 FP155 FP156
## Min. :0.00000 Min. :0.00000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.0000 Median :0.00000
## Mean :0.07781 Mean :0.03785 Mean :0.0694 Mean :0.07045
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.0000 Max. :1.00000
## FP157 FP158 FP159 FP160
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.06204 Mean :0.05363 Mean :0.07045 Mean :0.06835
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP161 FP162 FP163 FP164
## Min. :0.00000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.00000 Median :0.0000 Median :0.0000 Median :1.0000
## Mean :0.06625 Mean :0.4953 Mean :0.4763 Mean :0.6278
## 3rd Qu.:0.00000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.00000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP165 FP166 FP167 FP168
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :1.0000
## Mean :0.3491 Mean :0.3312 Mean :0.3281 Mean :0.6656
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP169 FP170 FP171 FP172
## Min. :0.0000 Min. :0.000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.000 Median :0.0000 Median :0.0000
## Mean :0.1861 Mean :0.184 Mean :0.1693 Mean :0.1514
## 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.000 Max. :1.0000 Max. :1.0000
## FP173 FP174 FP175 FP176
## Min. :0.000 Min. :0.0000 Min. :0.0000 Min. :0.000
## 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000
## Median :0.000 Median :0.0000 Median :0.0000 Median :0.000
## Mean :0.142 Mean :0.1304 Mean :0.1346 Mean :0.122
## 3rd Qu.:0.000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.000
## Max. :1.000 Max. :1.0000 Max. :1.0000 Max. :1.000
## FP177 FP178 FP179 FP180
## Min. :0.0000 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.00000 Median :0.0000
## Mean :0.1209 Mean :0.1209 Mean :0.09779 Mean :0.1073
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.00000 Max. :1.0000
## FP181 FP182 FP183 FP184
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.09359 Mean :0.09884 Mean :0.07571 Mean :0.08412
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP185 FP186 FP187 FP188
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.08517 Mean :0.07676 Mean :0.07256 Mean :0.06835
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP189 FP190 FP191 FP192
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.07676 Mean :0.07256 Mean :0.07045 Mean :0.06099
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP193 FP194 FP195 FP196
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.06204 Mean :0.05889 Mean :0.06099 Mean :0.05678
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP197 FP198 FP199 FP200
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.05258 Mean :0.05678 Mean :0.04732 Mean :0.04942
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP201 FP202 FP203 FP204
## Min. :0.00000 Min. :0.0000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.00000 Median :0.0000 Median :0.0000 Median :0.00000
## Mean :0.05258 Mean :0.2576 Mean :0.1146 Mean :0.09884
## 3rd Qu.:0.00000 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.0000 Max. :1.0000 Max. :1.00000
## FP205 FP206 FP207 FP208
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.0000
## Mean :0.07781 Mean :0.05994 Mean :0.05678 Mean :0.1125
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.0000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.0000
## MolWeight NumAtoms NumNonHAtoms NumBonds
## Min. : 46.09 Min. : 5.00 Min. : 2.00 Min. : 4.00
## 1st Qu.:122.61 1st Qu.:17.00 1st Qu.: 8.00 1st Qu.:17.00
## Median :179.23 Median :22.00 Median :12.00 Median :23.00
## Mean :201.65 Mean :25.51 Mean :13.16 Mean :25.91
## 3rd Qu.:264.34 3rd Qu.:31.00 3rd Qu.:17.00 3rd Qu.:31.50
## Max. :665.81 Max. :94.00 Max. :47.00 Max. :97.00
## NumNonHBonds NumMultBonds NumRotBonds NumDblBonds
## Min. : 1.00 Min. : 0.000 Min. : 0.000 Min. :0.000
## 1st Qu.: 8.00 1st Qu.: 1.000 1st Qu.: 0.000 1st Qu.:0.000
## Median :12.00 Median : 6.000 Median : 2.000 Median :1.000
## Mean :13.56 Mean : 6.148 Mean : 2.251 Mean :1.006
## 3rd Qu.:18.00 3rd Qu.:10.000 3rd Qu.: 3.500 3rd Qu.:2.000
## Max. :50.00 Max. :25.000 Max. :16.000 Max. :7.000
## NumAromaticBonds NumHydrogen NumCarbon NumNitrogen
## Min. : 0.000 Min. : 0.00 Min. : 1.000 Min. :0.0000
## 1st Qu.: 0.000 1st Qu.: 7.00 1st Qu.: 6.000 1st Qu.:0.0000
## Median : 6.000 Median :11.00 Median : 9.000 Median :0.0000
## Mean : 5.121 Mean :12.35 Mean : 9.893 Mean :0.8128
## 3rd Qu.: 6.000 3rd Qu.:16.00 3rd Qu.:12.000 3rd Qu.:1.0000
## Max. :25.000 Max. :47.00 Max. :33.000 Max. :6.0000
## NumOxygen NumSulfer NumChlorine NumHalogen
## Min. : 0.000 Min. :0.000 Min. : 0.0000 Min. : 0.0000
## 1st Qu.: 0.000 1st Qu.:0.000 1st Qu.: 0.0000 1st Qu.: 0.0000
## Median : 1.000 Median :0.000 Median : 0.0000 Median : 0.0000
## Mean : 1.574 Mean :0.164 Mean : 0.5563 Mean : 0.6982
## 3rd Qu.: 2.000 3rd Qu.:0.000 3rd Qu.: 0.0000 3rd Qu.: 1.0000
## Max. :13.000 Max. :4.000 Max. :10.0000 Max. :10.0000
## NumRings HydrophilicFactor SurfaceArea1 SurfaceArea2
## Min. :0.000 Min. :-0.98500 Min. : 0.00 Min. : 0.00
## 1st Qu.:0.000 1st Qu.:-0.76300 1st Qu.: 9.23 1st Qu.: 10.63
## Median :1.000 Median :-0.31400 Median : 29.10 Median : 33.12
## Mean :1.402 Mean :-0.02059 Mean : 36.46 Mean : 40.23
## 3rd Qu.:2.000 3rd Qu.: 0.31300 3rd Qu.: 53.28 3rd Qu.: 60.66
## Max. :7.000 Max. :13.48300 Max. :331.94 Max. :331.94
## Log_Solubility_Class
## Low :427
## Mid :283
## High:241
##
##
## ##################################
# Performing a general exploration of the test set
##################################
dim(Solubility_Test)## [1] 316 229str(Solubility_Test)## 'data.frame': 316 obs. of 229 variables:
## $ FP001 : int 1 1 0 0 1 1 1 0 1 0 ...
## $ FP002 : int 0 0 1 0 1 0 0 0 0 1 ...
## $ FP003 : int 0 1 0 1 0 0 0 0 1 0 ...
## $ FP004 : int 1 1 0 0 1 1 1 1 1 0 ...
## $ FP005 : int 0 0 1 0 1 0 0 0 0 1 ...
## $ FP006 : int 0 1 0 1 1 0 0 0 0 0 ...
## $ FP007 : int 0 0 0 0 0 0 0 1 1 0 ...
## $ FP008 : int 0 0 0 0 1 0 0 0 0 0 ...
## $ FP009 : int 1 0 0 0 0 0 0 0 0 0 ...
## $ FP010 : int 1 0 1 0 0 0 0 0 0 0 ...
## $ FP011 : int 0 1 0 0 1 0 0 0 0 0 ...
## $ FP012 : int 0 1 0 0 0 1 0 1 0 0 ...
## $ FP013 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP014 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP015 : int 1 1 0 1 1 1 1 1 1 1 ...
## $ FP016 : int 0 1 0 0 0 0 0 1 0 0 ...
## $ FP017 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP018 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP019 : int 0 0 0 0 1 0 0 0 0 1 ...
## $ FP020 : int 0 0 0 0 0 1 0 0 0 0 ...
## $ FP021 : int 1 0 0 0 0 0 0 0 0 0 ...
## $ FP022 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP023 : int 0 0 0 0 0 0 1 0 0 0 ...
## $ FP024 : int 0 0 0 0 1 0 0 0 0 1 ...
## $ FP025 : int 1 0 0 0 0 0 0 0 0 0 ...
## $ FP026 : int 0 0 0 0 0 0 0 0 0 1 ...
## $ FP027 : int 0 0 0 1 0 0 0 0 0 0 ...
## $ FP028 : int 0 0 0 1 0 0 0 0 0 0 ...
## $ FP029 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP030 : int 0 0 0 1 0 0 0 0 0 0 ...
## $ FP031 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP032 : int 0 0 1 0 0 0 0 0 0 0 ...
## $ FP033 : int 0 0 1 0 0 0 0 0 0 0 ...
## $ FP034 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP035 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP036 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP037 : int 0 0 0 0 0 0 0 0 1 0 ...
## $ FP038 : int 1 0 0 0 0 0 0 0 0 0 ...
## $ FP039 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP040 : int 0 0 0 0 1 0 0 0 0 0 ...
## $ FP041 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP042 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP043 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP044 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP045 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP046 : int 0 0 1 0 0 0 0 0 0 1 ...
## $ FP047 : int 0 0 0 0 1 0 0 0 0 0 ...
## $ FP048 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP049 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP050 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP051 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP052 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP053 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP054 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP055 : int 0 0 1 0 0 0 0 0 0 0 ...
## $ FP056 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP057 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP058 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP059 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP060 : int 1 1 1 0 0 1 0 1 0 0 ...
## $ FP061 : int 1 1 1 0 0 1 0 0 0 0 ...
## $ FP062 : int 1 1 0 0 1 1 1 0 1 0 ...
## $ FP063 : int 0 1 0 1 1 0 0 0 0 1 ...
## $ FP064 : int 1 1 0 0 0 0 0 0 1 0 ...
## $ FP065 : int 0 0 1 0 0 0 0 0 0 0 ...
## $ FP066 : int 0 1 0 1 0 1 0 0 1 1 ...
## $ FP067 : int 0 1 0 1 1 0 0 0 0 1 ...
## $ FP068 : int 0 1 0 1 1 0 0 0 0 0 ...
## $ FP069 : int 0 0 0 0 0 0 0 0 1 1 ...
## $ FP070 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP071 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP072 : int 1 1 1 0 1 1 1 1 1 0 ...
## $ FP073 : int 1 0 1 0 0 0 0 0 0 0 ...
## $ FP074 : int 0 0 1 0 0 0 0 0 1 0 ...
## $ FP075 : int 0 1 0 1 0 0 0 1 0 0 ...
## $ FP076 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP077 : int 0 0 0 1 0 0 0 1 0 0 ...
## $ FP078 : int 0 0 1 0 0 0 0 0 0 0 ...
## $ FP079 : int 0 0 1 1 1 0 0 0 0 1 ...
## $ FP080 : int 1 1 0 1 0 0 0 1 0 0 ...
## $ FP081 : int 0 0 0 1 0 0 0 0 1 0 ...
## $ FP082 : int 0 0 1 0 1 0 0 0 0 1 ...
## $ FP083 : int 0 1 0 1 1 0 0 0 0 0 ...
## $ FP084 : int 0 0 0 1 1 0 0 1 0 1 ...
## $ FP085 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP086 : int 0 0 0 1 0 0 0 0 0 0 ...
## $ FP087 : int 0 0 1 1 1 0 0 1 0 1 ...
## $ FP088 : int 1 0 0 0 0 0 0 1 1 0 ...
## $ FP089 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP090 : int 0 0 0 1 0 0 0 1 0 0 ...
## $ FP091 : int 0 0 0 1 1 0 0 0 0 0 ...
## $ FP092 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP093 : int 0 0 0 1 0 0 0 1 0 0 ...
## $ FP094 : int 0 1 0 0 0 0 0 0 1 0 ...
## $ FP095 : int 0 0 1 1 0 0 0 0 0 0 ...
## $ FP096 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP097 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FP098 : int 1 1 0 0 0 1 0 0 0 0 ...
## $ FP099 : int 0 0 0 0 0 0 0 0 0 0 ...
## [list output truncated]summary(Solubility_Test)## FP001 FP002 FP003 FP004
## Min. :0.0000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :1.0000 Median :0.000 Median :1.0000
## Mean :0.4684 Mean :0.5854 Mean :0.443 Mean :0.5316
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.000 Max. :1.0000
## FP005 FP006 FP007 FP008
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :1.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.6171 Mean :0.3513 Mean :0.3544 Mean :0.3608
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP009 FP010 FP011 FP012
## Min. :0.0000 Min. :0.000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.000 Median :0.0000 Median :0.0000
## Mean :0.2627 Mean :0.193 Mean :0.1741 Mean :0.1677
## 3rd Qu.:1.0000 3rd Qu.:0.000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.000 Max. :1.0000 Max. :1.0000
## FP013 FP014 FP015 FP016
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:1.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :1.0000 Median :0.0000
## Mean :0.1646 Mean :0.1582 Mean :0.8291 Mean :0.1424
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:1.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP017 FP018 FP019 FP020
## Min. :0.0000 Min. :0.00000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.00000 Median :0.0000 Median :0.0000
## Mean :0.1487 Mean :0.08544 Mean :0.1139 Mean :0.1076
## 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.00000 Max. :1.0000 Max. :1.0000
## FP021 FP022 FP023 FP024
## Min. :0.0000 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.00000 Median :0.0000
## Mean :0.1076 Mean :0.1171 Mean :0.08544 Mean :0.0981
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.00000 Max. :1.0000
## FP025 FP026 FP027 FP028
## Min. :0.00000 Min. :0.0000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.0000 Median :0.00000 Median :0.00000
## Mean :0.07911 Mean :0.1171 Mean :0.07911 Mean :0.05696
## 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.0000 Max. :1.00000 Max. :1.00000
## FP029 FP030 FP031 FP032
## Min. :0.00000 Min. :0.00000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.00000 Median :0.00000 Median :0.0000 Median :0.0000
## Mean :0.05063 Mean :0.08228 Mean :0.0981 Mean :0.1297
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.00000 Max. :1.00000 Max. :1.0000 Max. :1.0000
## FP033 FP034 FP035 FP036
## Min. :0.0000 Min. :0.00000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.0000 Median :0.00000 Median :0.0000 Median :0.00000
## Mean :0.1203 Mean :0.06646 Mean :0.0981 Mean :0.06013
## 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.0000 Max. :1.00000 Max. :1.0000 Max. :1.00000
## FP037 FP038 FP039 FP040
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.09494 Mean :0.03165 Mean :0.06329 Mean :0.05696
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP041 FP042 FP043 FP044
## Min. :0.00000 Min. :0.00000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.0000 Median :0.00000
## Mean :0.06013 Mean :0.06013 Mean :0.0443 Mean :0.06013
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.0000 Max. :1.00000
## FP045 FP046 FP047 FP048
## Min. :0.00000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.00000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.06329 Mean :0.3259 Mean :0.2975 Mean :0.1139
## 3rd Qu.:0.00000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:0.0000
## Max. :1.00000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP049 FP050 FP051 FP052
## Min. :0.0000 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.00000 Median :0.0000
## Mean :0.1076 Mean :0.1139 Mean :0.05696 Mean :0.1044
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.00000 Max. :1.0000
## FP053 FP054 FP055 FP056
## Min. :0.00000 Min. :0.0000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.0000 Median :0.00000 Median :0.00000
## Mean :0.06013 Mean :0.0981 Mean :0.09177 Mean :0.06329
## 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.0000 Max. :1.00000 Max. :1.00000
## FP057 FP058 FP059 FP060
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1234 Mean :0.1361 Mean :0.0443 Mean :0.4525
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP061 FP062 FP063 FP064
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.3924 Mean :0.4272 Mean :0.3576 Mean :0.3892
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP065 FP066 FP067 FP068
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :1.0000 Median :1.0000 Median :0.0000 Median :0.0000
## Mean :0.5981 Mean :0.6171 Mean :0.3259 Mean :0.2911
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP069 FP070 FP071 FP072
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :1.0000
## Mean :0.3734 Mean :0.3323 Mean :0.3449 Mean :0.6456
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP073 FP074 FP075 FP076
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.2911 Mean :0.3259 Mean :0.2563 Mean :0.3165
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP077 FP078 FP079 FP080
## Min. :0.000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.000 Median :0.0000 Median :1.0000 Median :0.0000
## Mean :0.307 Mean :0.3101 Mean :0.7278 Mean :0.2627
## 3rd Qu.:1.000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP081 FP082 FP083 FP084
## Min. :0.000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.000 Median :1.0000 Median :0.0000 Median :0.0000
## Mean :0.288 Mean :0.7437 Mean :0.2532 Mean :0.2247
## 3rd Qu.:1.000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:0.0000
## Max. :1.000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP085 FP086 FP087 FP088
## Min. :0.000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:1.0000 1st Qu.:0.0000
## Median :0.000 Median :0.0000 Median :1.0000 Median :0.0000
## Mean :0.269 Mean :0.2722 Mean :0.7627 Mean :0.2437
## 3rd Qu.:1.000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:0.0000
## Max. :1.000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP089 FP090 FP091 FP092
## Min. :0.0000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.000 Median :0.0000
## Mean :0.2532 Mean :0.2278 Mean :0.231 Mean :0.2184
## 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.000 Max. :1.0000
## FP093 FP094 FP095 FP096
## Min. :0.0000 Min. :0.00 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.00 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.00 Median :0.0000 Median :0.0000
## Mean :0.2152 Mean :0.25 Mean :0.2057 Mean :0.1867
## 3rd Qu.:0.0000 3rd Qu.:0.25 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.00 Max. :1.0000 Max. :1.0000
## FP097 FP098 FP099 FP100
## Min. :0.0000 Min. :0.0000 Min. :0.000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.000 Median :0.0000
## Mean :0.2089 Mean :0.2025 Mean :0.212 Mean :0.1804
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.000 Max. :1.0000
## FP101 FP102 FP103 FP104
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1772 Mean :0.1456 Mean :0.2184 Mean :0.1835
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP105 FP106 FP107 FP108
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.2152 Mean :0.1361 Mean :0.1962 Mean :0.1804
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP109 FP110 FP111 FP112
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1741 Mean :0.1646 Mean :0.1804 Mean :0.1772
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP113 FP114 FP115 FP116
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1646 Mean :0.1772 Mean :0.1582 Mean :0.1487
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP117 FP118 FP119 FP120
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1709 Mean :0.1171 Mean :0.1677 Mean :0.1551
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP121 FP122 FP123 FP124
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1076 Mean :0.1361 Mean :0.1456 Mean :0.1329
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP125 FP126 FP127 FP128
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1203 Mean :0.1139 Mean :0.1487 Mean :0.1076
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP129 FP130 FP131 FP132
## Min. :0.0000 Min. :0.00000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.00000 Median :0.0000 Median :0.0000
## Mean :0.1392 Mean :0.08228 Mean :0.1076 Mean :0.1266
## 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.00000 Max. :1.0000 Max. :1.0000
## FP133 FP134 FP135 FP136
## Min. :0.0000 Min. :0.00000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.0000 Median :0.00000 Median :0.00000 Median :0.0000
## Mean :0.1361 Mean :0.08544 Mean :0.06329 Mean :0.1013
## 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.00000 Max. :1.00000 Max. :1.0000
## FP137 FP138 FP139 FP140
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.08861 Mean :0.08228 Mean :0.06329 Mean :0.08861
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP141 FP142 FP143 FP144
## Min. :0.00000 Min. :0.00000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.0000 Median :0.00000
## Mean :0.06962 Mean :0.09494 Mean :0.0538 Mean :0.09177
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.0000 Max. :1.00000
## FP145 FP146 FP147 FP148
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.06329 Mean :0.09177 Mean :0.06962 Mean :0.07911
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP149 FP150 FP151 FP152
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.0000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.0000
## Mean :0.08228 Mean :0.06646 Mean :0.03165 Mean :0.0538
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.0000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.0000
## FP153 FP154 FP155 FP156
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.03481 Mean :0.03165 Mean :0.06646 Mean :0.04747
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP157 FP158 FP159 FP160
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.05696 Mean :0.07911 Mean :0.03481 Mean :0.03481
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP161 FP162 FP163 FP164
## Min. :0.00000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.00000 Median :1.0000 Median :0.0000 Median :1.0000
## Mean :0.03481 Mean :0.5316 Mean :0.4525 Mean :0.6551
## 3rd Qu.:0.00000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.00000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP165 FP166 FP167 FP168
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :1.0000
## Mean :0.3196 Mean :0.3386 Mean :0.3006 Mean :0.7152
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP169 FP170 FP171 FP172
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1867 Mean :0.1551 Mean :0.1297 Mean :0.1487
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP173 FP174 FP175 FP176
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.0000
## Mean :0.1361 Mean :0.1551 Mean :0.1329 Mean :0.1076
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000
## FP177 FP178 FP179 FP180
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.0000 Median :0.0000 Median :0.0000 Median :0.00000
## Mean :0.1013 Mean :0.1076 Mean :0.1392 Mean :0.06962
## 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.0000 Max. :1.0000 Max. :1.0000 Max. :1.00000
## FP181 FP182 FP183 FP184
## Min. :0.0000 Min. :0.00000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.0000 Median :0.00000 Median :0.0000 Median :0.00000
## Mean :0.1044 Mean :0.07595 Mean :0.1329 Mean :0.09494
## 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.0000 Max. :1.00000 Max. :1.0000 Max. :1.00000
## FP185 FP186 FP187 FP188
## Min. :0.0000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.0000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.0981 Mean :0.06013 Mean :0.06646 Mean :0.06962
## 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.0000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP189 FP190 FP191 FP192
## Min. :0.00000 Min. :0.0000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.0000 Median :0.00000 Median :0.00000
## Mean :0.04114 Mean :0.0538 Mean :0.05696 Mean :0.06962
## 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.0000 Max. :1.00000 Max. :1.00000
## FP193 FP194 FP195 FP196
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.00000 Median :0.00000 Median :0.00000
## Mean :0.06962 Mean :0.06646 Mean :0.05063 Mean :0.06962
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.00000 Max. :1.00000 Max. :1.00000
## FP197 FP198 FP199 FP200
## Min. :0.00000 Min. :0.0000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.:0.00000
## Median :0.00000 Median :0.0000 Median :0.00000 Median :0.00000
## Mean :0.06329 Mean :0.0443 Mean :0.07278 Mean :0.06329
## 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.0000 Max. :1.00000 Max. :1.00000
## FP201 FP202 FP203 FP204
## Min. :0.00000 Min. :0.0000 Min. :0.0000 Min. :0.00000
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.00000 Median :0.0000 Median :0.0000 Median :0.00000
## Mean :0.04114 Mean :0.2658 Mean :0.1361 Mean :0.09494
## 3rd Qu.:0.00000 3rd Qu.:1.0000 3rd Qu.:0.0000 3rd Qu.:0.00000
## Max. :1.00000 Max. :1.0000 Max. :1.0000 Max. :1.00000
## FP205 FP206 FP207 FP208
## Min. :0.00000 Min. :0.00000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.00000 Median :0.00000 Median :0.0000 Median :0.0000
## Mean :0.07911 Mean :0.05063 Mean :0.0443 Mean :0.1361
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :1.00000 Max. :1.00000 Max. :1.0000 Max. :1.0000
## MolWeight NumAtoms NumNonHAtoms NumBonds NumNonHBonds
## Min. : 56.07 Min. : 5.0 Min. : 3.00 Min. : 4 Min. : 2.0
## 1st Qu.:121.91 1st Qu.:17.0 1st Qu.: 8.00 1st Qu.:16 1st Qu.: 8.0
## Median :170.11 Median :22.0 Median :11.00 Median :23 Median :12.0
## Mean :194.12 Mean :24.6 Mean :12.71 Mean :25 Mean :13.1
## 3rd Qu.:253.82 3rd Qu.:29.0 3rd Qu.:16.00 3rd Qu.:30 3rd Qu.:17.0
## Max. :478.92 Max. :68.0 Max. :33.00 Max. :71 Max. :36.0
## NumMultBonds NumRotBonds NumDblBonds NumAromaticBonds
## Min. : 0.000 Min. : 0.000 Min. :0.0000 Min. : 0.000
## 1st Qu.: 1.000 1st Qu.: 0.000 1st Qu.:0.0000 1st Qu.: 0.000
## Median : 6.000 Median : 1.000 Median :1.0000 Median : 6.000
## Mean : 6.313 Mean : 1.949 Mean :0.8892 Mean : 5.399
## 3rd Qu.:10.000 3rd Qu.: 3.000 3rd Qu.:1.0000 3rd Qu.:10.000
## Max. :27.000 Max. :16.000 Max. :6.0000 Max. :27.000
## NumHydrogen NumCarbon NumNitrogen NumOxygen
## Min. : 0.0 Min. : 1.000 Min. :0.0000 Min. :0.000
## 1st Qu.: 7.0 1st Qu.: 6.000 1st Qu.:0.0000 1st Qu.:0.000
## Median :11.0 Median : 8.000 Median :0.0000 Median :1.000
## Mean :11.9 Mean : 9.785 Mean :0.7089 Mean :1.389
## 3rd Qu.:15.0 3rd Qu.:12.000 3rd Qu.:1.0000 3rd Qu.:2.000
## Max. :40.0 Max. :24.000 Max. :6.0000 Max. :9.000
## NumSulfer NumChlorine NumHalogen NumRings
## Min. :0.0000 Min. :0.000 Min. :0.0000 Min. :0.000
## 1st Qu.:0.0000 1st Qu.:0.000 1st Qu.:0.0000 1st Qu.:1.000
## Median :0.0000 Median :0.000 Median :0.0000 Median :1.000
## Mean :0.1013 Mean :0.557 Mean :0.7089 Mean :1.399
## 3rd Qu.:0.0000 3rd Qu.:0.000 3rd Qu.:1.0000 3rd Qu.:2.000
## Max. :3.0000 Max. :9.000 Max. :9.0000 Max. :6.000
## HydrophilicFactor SurfaceArea1 SurfaceArea2 Log_Solubility_Class
## Min. :-0.9860 Min. : 0.00 Min. : 0.00 Low :143
## 1st Qu.:-0.7670 1st Qu.: 9.23 1st Qu.: 9.23 Mid : 94
## Median :-0.3970 Median : 26.30 Median : 26.30 High: 79
## Mean :-0.1022 Mean : 32.76 Mean : 35.04
## 3rd Qu.: 0.2140 3rd Qu.: 49.55 3rd Qu.: 52.32
## Max. : 5.0000 Max. :201.85 Max. :201.85##################################
# Formulating a data type assessment summary
##################################
PDA <- Solubility_Train
(PDA.Summary <- data.frame(
Column.Index=c(1:length(names(PDA))),
Column.Name= names(PDA),
Column.Type=sapply(PDA, function(x) class(x)),
row.names=NULL)
)## Column.Index Column.Name Column.Type
## 1 1 FP001 integer
## 2 2 FP002 integer
## 3 3 FP003 integer
## 4 4 FP004 integer
## 5 5 FP005 integer
## 6 6 FP006 integer
## 7 7 FP007 integer
## 8 8 FP008 integer
## 9 9 FP009 integer
## 10 10 FP010 integer
## 11 11 FP011 integer
## 12 12 FP012 integer
## 13 13 FP013 integer
## 14 14 FP014 integer
## 15 15 FP015 integer
## 16 16 FP016 integer
## 17 17 FP017 integer
## 18 18 FP018 integer
## 19 19 FP019 integer
## 20 20 FP020 integer
## 21 21 FP021 integer
## 22 22 FP022 integer
## 23 23 FP023 integer
## 24 24 FP024 integer
## 25 25 FP025 integer
## 26 26 FP026 integer
## 27 27 FP027 integer
## 28 28 FP028 integer
## 29 29 FP029 integer
## 30 30 FP030 integer
## 31 31 FP031 integer
## 32 32 FP032 integer
## 33 33 FP033 integer
## 34 34 FP034 integer
## 35 35 FP035 integer
## 36 36 FP036 integer
## 37 37 FP037 integer
## 38 38 FP038 integer
## 39 39 FP039 integer
## 40 40 FP040 integer
## 41 41 FP041 integer
## 42 42 FP042 integer
## 43 43 FP043 integer
## 44 44 FP044 integer
## 45 45 FP045 integer
## 46 46 FP046 integer
## 47 47 FP047 integer
## 48 48 FP048 integer
## 49 49 FP049 integer
## 50 50 FP050 integer
## 51 51 FP051 integer
## 52 52 FP052 integer
## 53 53 FP053 integer
## 54 54 FP054 integer
## 55 55 FP055 integer
## 56 56 FP056 integer
## 57 57 FP057 integer
## 58 58 FP058 integer
## 59 59 FP059 integer
## 60 60 FP060 integer
## 61 61 FP061 integer
## 62 62 FP062 integer
## 63 63 FP063 integer
## 64 64 FP064 integer
## 65 65 FP065 integer
## 66 66 FP066 integer
## 67 67 FP067 integer
## 68 68 FP068 integer
## 69 69 FP069 integer
## 70 70 FP070 integer
## 71 71 FP071 integer
## 72 72 FP072 integer
## 73 73 FP073 integer
## 74 74 FP074 integer
## 75 75 FP075 integer
## 76 76 FP076 integer
## 77 77 FP077 integer
## 78 78 FP078 integer
## 79 79 FP079 integer
## 80 80 FP080 integer
## 81 81 FP081 integer
## 82 82 FP082 integer
## 83 83 FP083 integer
## 84 84 FP084 integer
## 85 85 FP085 integer
## 86 86 FP086 integer
## 87 87 FP087 integer
## 88 88 FP088 integer
## 89 89 FP089 integer
## 90 90 FP090 integer
## 91 91 FP091 integer
## 92 92 FP092 integer
## 93 93 FP093 integer
## 94 94 FP094 integer
## 95 95 FP095 integer
## 96 96 FP096 integer
## 97 97 FP097 integer
## 98 98 FP098 integer
## 99 99 FP099 integer
## 100 100 FP100 integer
## 101 101 FP101 integer
## 102 102 FP102 integer
## 103 103 FP103 integer
## 104 104 FP104 integer
## 105 105 FP105 integer
## 106 106 FP106 integer
## 107 107 FP107 integer
## 108 108 FP108 integer
## 109 109 FP109 integer
## 110 110 FP110 integer
## 111 111 FP111 integer
## 112 112 FP112 integer
## 113 113 FP113 integer
## 114 114 FP114 integer
## 115 115 FP115 integer
## 116 116 FP116 integer
## 117 117 FP117 integer
## 118 118 FP118 integer
## 119 119 FP119 integer
## 120 120 FP120 integer
## 121 121 FP121 integer
## 122 122 FP122 integer
## 123 123 FP123 integer
## 124 124 FP124 integer
## 125 125 FP125 integer
## 126 126 FP126 integer
## 127 127 FP127 integer
## 128 128 FP128 integer
## 129 129 FP129 integer
## 130 130 FP130 integer
## 131 131 FP131 integer
## 132 132 FP132 integer
## 133 133 FP133 integer
## 134 134 FP134 integer
## 135 135 FP135 integer
## 136 136 FP136 integer
## 137 137 FP137 integer
## 138 138 FP138 integer
## 139 139 FP139 integer
## 140 140 FP140 integer
## 141 141 FP141 integer
## 142 142 FP142 integer
## 143 143 FP143 integer
## 144 144 FP144 integer
## 145 145 FP145 integer
## 146 146 FP146 integer
## 147 147 FP147 integer
## 148 148 FP148 integer
## 149 149 FP149 integer
## 150 150 FP150 integer
## 151 151 FP151 integer
## 152 152 FP152 integer
## 153 153 FP153 integer
## 154 154 FP154 integer
## 155 155 FP155 integer
## 156 156 FP156 integer
## 157 157 FP157 integer
## 158 158 FP158 integer
## 159 159 FP159 integer
## 160 160 FP160 integer
## 161 161 FP161 integer
## 162 162 FP162 integer
## 163 163 FP163 integer
## 164 164 FP164 integer
## 165 165 FP165 integer
## 166 166 FP166 integer
## 167 167 FP167 integer
## 168 168 FP168 integer
## 169 169 FP169 integer
## 170 170 FP170 integer
## 171 171 FP171 integer
## 172 172 FP172 integer
## 173 173 FP173 integer
## 174 174 FP174 integer
## 175 175 FP175 integer
## 176 176 FP176 integer
## 177 177 FP177 integer
## 178 178 FP178 integer
## 179 179 FP179 integer
## 180 180 FP180 integer
## 181 181 FP181 integer
## 182 182 FP182 integer
## 183 183 FP183 integer
## 184 184 FP184 integer
## 185 185 FP185 integer
## 186 186 FP186 integer
## 187 187 FP187 integer
## 188 188 FP188 integer
## 189 189 FP189 integer
## 190 190 FP190 integer
## 191 191 FP191 integer
## 192 192 FP192 integer
## 193 193 FP193 integer
## 194 194 FP194 integer
## 195 195 FP195 integer
## 196 196 FP196 integer
## 197 197 FP197 integer
## 198 198 FP198 integer
## 199 199 FP199 integer
## 200 200 FP200 integer
## 201 201 FP201 integer
## 202 202 FP202 integer
## 203 203 FP203 integer
## 204 204 FP204 integer
## 205 205 FP205 integer
## 206 206 FP206 integer
## 207 207 FP207 integer
## 208 208 FP208 integer
## 209 209 MolWeight numeric
## 210 210 NumAtoms integer
## 211 211 NumNonHAtoms integer
## 212 212 NumBonds integer
## 213 213 NumNonHBonds integer
## 214 214 NumMultBonds integer
## 215 215 NumRotBonds integer
## 216 216 NumDblBonds integer
## 217 217 NumAromaticBonds integer
## 218 218 NumHydrogen integer
## 219 219 NumCarbon integer
## 220 220 NumNitrogen integer
## 221 221 NumOxygen integer
## 222 222 NumSulfer integer
## 223 223 NumChlorine integer
## 224 224 NumHalogen integer
## 225 225 NumRings integer
## 226 226 HydrophilicFactor numeric
## 227 227 SurfaceArea1 numeric
## 228 228 SurfaceArea2 numeric
## 229 229 Log_Solubility_Class factor1.2 Data Quality Assessment
[A] No missing observations noted for any variable.
[B] Low variance observed for 127 variables with First.Second.Mode.Ratio>5.
[B.1]-[B.33] FP013 to FP045 variables (factor)
[B.34]-[B.45] FP048 to FP059 variables (factor)
[B.46] FP114 variable (factor)
[B.47]-[B.50] FP119 to FP122 variable (factor)
[B.51]-[B.88] FP124 to FP161 variables (factor)
[B.89]-[B.118] FP172 to FP201 variables (factor)
[B.119]-[B.124] FP203 to FP208 variables (factor)
[B.125] NumSulfer variable (numeric)
[B.126] NumChlorine variable (numeric)
[B.127] NumHalogen variable (numeric)
[C] Low variance observed for 4 variables with Unique.Count.Ratio<0.01.
[C.1] NumDblBonds variable (numeric)
[C.2] NumNitrogen variable (numeric)
[C.3] NumSulfer variable (numeric)
[C.4] NumRings variable (numeric)
[D] High skewness observed for 3 variables with Skewness>3 or Skewness<(-3).
[D.1] NumSulfer variable (numeric)
[D.2] NumChlorine variable (numeric)
[D.3] HydrophilicFactor variable (numeric)
Code Chunk | Output
##################################
# Loading dataset
##################################
DQA <- Solubility_Train
##################################
# Formulating an overall data quality assessment summary
##################################
(DQA.Summary <- data.frame(
Column.Index=c(1:length(names(DQA))),
Column.Name= names(DQA),
Column.Type=sapply(DQA, function(x) class(x)),
Row.Count=sapply(DQA, function(x) nrow(DQA)),
NA.Count=sapply(DQA,function(x)sum(is.na(x))),
Fill.Rate=sapply(DQA,function(x)format(round((sum(!is.na(x))/nrow(DQA)),3),nsmall=3)),
row.names=NULL)
)## Column.Index Column.Name Column.Type Row.Count NA.Count Fill.Rate
## 1 1 FP001 integer 951 0 1.000
## 2 2 FP002 integer 951 0 1.000
## 3 3 FP003 integer 951 0 1.000
## 4 4 FP004 integer 951 0 1.000
## 5 5 FP005 integer 951 0 1.000
## 6 6 FP006 integer 951 0 1.000
## 7 7 FP007 integer 951 0 1.000
## 8 8 FP008 integer 951 0 1.000
## 9 9 FP009 integer 951 0 1.000
## 10 10 FP010 integer 951 0 1.000
## 11 11 FP011 integer 951 0 1.000
## 12 12 FP012 integer 951 0 1.000
## 13 13 FP013 integer 951 0 1.000
## 14 14 FP014 integer 951 0 1.000
## 15 15 FP015 integer 951 0 1.000
## 16 16 FP016 integer 951 0 1.000
## 17 17 FP017 integer 951 0 1.000
## 18 18 FP018 integer 951 0 1.000
## 19 19 FP019 integer 951 0 1.000
## 20 20 FP020 integer 951 0 1.000
## 21 21 FP021 integer 951 0 1.000
## 22 22 FP022 integer 951 0 1.000
## 23 23 FP023 integer 951 0 1.000
## 24 24 FP024 integer 951 0 1.000
## 25 25 FP025 integer 951 0 1.000
## 26 26 FP026 integer 951 0 1.000
## 27 27 FP027 integer 951 0 1.000
## 28 28 FP028 integer 951 0 1.000
## 29 29 FP029 integer 951 0 1.000
## 30 30 FP030 integer 951 0 1.000
## 31 31 FP031 integer 951 0 1.000
## 32 32 FP032 integer 951 0 1.000
## 33 33 FP033 integer 951 0 1.000
## 34 34 FP034 integer 951 0 1.000
## 35 35 FP035 integer 951 0 1.000
## 36 36 FP036 integer 951 0 1.000
## 37 37 FP037 integer 951 0 1.000
## 38 38 FP038 integer 951 0 1.000
## 39 39 FP039 integer 951 0 1.000
## 40 40 FP040 integer 951 0 1.000
## 41 41 FP041 integer 951 0 1.000
## 42 42 FP042 integer 951 0 1.000
## 43 43 FP043 integer 951 0 1.000
## 44 44 FP044 integer 951 0 1.000
## 45 45 FP045 integer 951 0 1.000
## 46 46 FP046 integer 951 0 1.000
## 47 47 FP047 integer 951 0 1.000
## 48 48 FP048 integer 951 0 1.000
## 49 49 FP049 integer 951 0 1.000
## 50 50 FP050 integer 951 0 1.000
## 51 51 FP051 integer 951 0 1.000
## 52 52 FP052 integer 951 0 1.000
## 53 53 FP053 integer 951 0 1.000
## 54 54 FP054 integer 951 0 1.000
## 55 55 FP055 integer 951 0 1.000
## 56 56 FP056 integer 951 0 1.000
## 57 57 FP057 integer 951 0 1.000
## 58 58 FP058 integer 951 0 1.000
## 59 59 FP059 integer 951 0 1.000
## 60 60 FP060 integer 951 0 1.000
## 61 61 FP061 integer 951 0 1.000
## 62 62 FP062 integer 951 0 1.000
## 63 63 FP063 integer 951 0 1.000
## 64 64 FP064 integer 951 0 1.000
## 65 65 FP065 integer 951 0 1.000
## 66 66 FP066 integer 951 0 1.000
## 67 67 FP067 integer 951 0 1.000
## 68 68 FP068 integer 951 0 1.000
## 69 69 FP069 integer 951 0 1.000
## 70 70 FP070 integer 951 0 1.000
## 71 71 FP071 integer 951 0 1.000
## 72 72 FP072 integer 951 0 1.000
## 73 73 FP073 integer 951 0 1.000
## 74 74 FP074 integer 951 0 1.000
## 75 75 FP075 integer 951 0 1.000
## 76 76 FP076 integer 951 0 1.000
## 77 77 FP077 integer 951 0 1.000
## 78 78 FP078 integer 951 0 1.000
## 79 79 FP079 integer 951 0 1.000
## 80 80 FP080 integer 951 0 1.000
## 81 81 FP081 integer 951 0 1.000
## 82 82 FP082 integer 951 0 1.000
## 83 83 FP083 integer 951 0 1.000
## 84 84 FP084 integer 951 0 1.000
## 85 85 FP085 integer 951 0 1.000
## 86 86 FP086 integer 951 0 1.000
## 87 87 FP087 integer 951 0 1.000
## 88 88 FP088 integer 951 0 1.000
## 89 89 FP089 integer 951 0 1.000
## 90 90 FP090 integer 951 0 1.000
## 91 91 FP091 integer 951 0 1.000
## 92 92 FP092 integer 951 0 1.000
## 93 93 FP093 integer 951 0 1.000
## 94 94 FP094 integer 951 0 1.000
## 95 95 FP095 integer 951 0 1.000
## 96 96 FP096 integer 951 0 1.000
## 97 97 FP097 integer 951 0 1.000
## 98 98 FP098 integer 951 0 1.000
## 99 99 FP099 integer 951 0 1.000
## 100 100 FP100 integer 951 0 1.000
## 101 101 FP101 integer 951 0 1.000
## 102 102 FP102 integer 951 0 1.000
## 103 103 FP103 integer 951 0 1.000
## 104 104 FP104 integer 951 0 1.000
## 105 105 FP105 integer 951 0 1.000
## 106 106 FP106 integer 951 0 1.000
## 107 107 FP107 integer 951 0 1.000
## 108 108 FP108 integer 951 0 1.000
## 109 109 FP109 integer 951 0 1.000
## 110 110 FP110 integer 951 0 1.000
## 111 111 FP111 integer 951 0 1.000
## 112 112 FP112 integer 951 0 1.000
## 113 113 FP113 integer 951 0 1.000
## 114 114 FP114 integer 951 0 1.000
## 115 115 FP115 integer 951 0 1.000
## 116 116 FP116 integer 951 0 1.000
## 117 117 FP117 integer 951 0 1.000
## 118 118 FP118 integer 951 0 1.000
## 119 119 FP119 integer 951 0 1.000
## 120 120 FP120 integer 951 0 1.000
## 121 121 FP121 integer 951 0 1.000
## 122 122 FP122 integer 951 0 1.000
## 123 123 FP123 integer 951 0 1.000
## 124 124 FP124 integer 951 0 1.000
## 125 125 FP125 integer 951 0 1.000
## 126 126 FP126 integer 951 0 1.000
## 127 127 FP127 integer 951 0 1.000
## 128 128 FP128 integer 951 0 1.000
## 129 129 FP129 integer 951 0 1.000
## 130 130 FP130 integer 951 0 1.000
## 131 131 FP131 integer 951 0 1.000
## 132 132 FP132 integer 951 0 1.000
## 133 133 FP133 integer 951 0 1.000
## 134 134 FP134 integer 951 0 1.000
## 135 135 FP135 integer 951 0 1.000
## 136 136 FP136 integer 951 0 1.000
## 137 137 FP137 integer 951 0 1.000
## 138 138 FP138 integer 951 0 1.000
## 139 139 FP139 integer 951 0 1.000
## 140 140 FP140 integer 951 0 1.000
## 141 141 FP141 integer 951 0 1.000
## 142 142 FP142 integer 951 0 1.000
## 143 143 FP143 integer 951 0 1.000
## 144 144 FP144 integer 951 0 1.000
## 145 145 FP145 integer 951 0 1.000
## 146 146 FP146 integer 951 0 1.000
## 147 147 FP147 integer 951 0 1.000
## 148 148 FP148 integer 951 0 1.000
## 149 149 FP149 integer 951 0 1.000
## 150 150 FP150 integer 951 0 1.000
## 151 151 FP151 integer 951 0 1.000
## 152 152 FP152 integer 951 0 1.000
## 153 153 FP153 integer 951 0 1.000
## 154 154 FP154 integer 951 0 1.000
## 155 155 FP155 integer 951 0 1.000
## 156 156 FP156 integer 951 0 1.000
## 157 157 FP157 integer 951 0 1.000
## 158 158 FP158 integer 951 0 1.000
## 159 159 FP159 integer 951 0 1.000
## 160 160 FP160 integer 951 0 1.000
## 161 161 FP161 integer 951 0 1.000
## 162 162 FP162 integer 951 0 1.000
## 163 163 FP163 integer 951 0 1.000
## 164 164 FP164 integer 951 0 1.000
## 165 165 FP165 integer 951 0 1.000
## 166 166 FP166 integer 951 0 1.000
## 167 167 FP167 integer 951 0 1.000
## 168 168 FP168 integer 951 0 1.000
## 169 169 FP169 integer 951 0 1.000
## 170 170 FP170 integer 951 0 1.000
## 171 171 FP171 integer 951 0 1.000
## 172 172 FP172 integer 951 0 1.000
## 173 173 FP173 integer 951 0 1.000
## 174 174 FP174 integer 951 0 1.000
## 175 175 FP175 integer 951 0 1.000
## 176 176 FP176 integer 951 0 1.000
## 177 177 FP177 integer 951 0 1.000
## 178 178 FP178 integer 951 0 1.000
## 179 179 FP179 integer 951 0 1.000
## 180 180 FP180 integer 951 0 1.000
## 181 181 FP181 integer 951 0 1.000
## 182 182 FP182 integer 951 0 1.000
## 183 183 FP183 integer 951 0 1.000
## 184 184 FP184 integer 951 0 1.000
## 185 185 FP185 integer 951 0 1.000
## 186 186 FP186 integer 951 0 1.000
## 187 187 FP187 integer 951 0 1.000
## 188 188 FP188 integer 951 0 1.000
## 189 189 FP189 integer 951 0 1.000
## 190 190 FP190 integer 951 0 1.000
## 191 191 FP191 integer 951 0 1.000
## 192 192 FP192 integer 951 0 1.000
## 193 193 FP193 integer 951 0 1.000
## 194 194 FP194 integer 951 0 1.000
## 195 195 FP195 integer 951 0 1.000
## 196 196 FP196 integer 951 0 1.000
## 197 197 FP197 integer 951 0 1.000
## 198 198 FP198 integer 951 0 1.000
## 199 199 FP199 integer 951 0 1.000
## 200 200 FP200 integer 951 0 1.000
## 201 201 FP201 integer 951 0 1.000
## 202 202 FP202 integer 951 0 1.000
## 203 203 FP203 integer 951 0 1.000
## 204 204 FP204 integer 951 0 1.000
## 205 205 FP205 integer 951 0 1.000
## 206 206 FP206 integer 951 0 1.000
## 207 207 FP207 integer 951 0 1.000
## 208 208 FP208 integer 951 0 1.000
## 209 209 MolWeight numeric 951 0 1.000
## 210 210 NumAtoms integer 951 0 1.000
## 211 211 NumNonHAtoms integer 951 0 1.000
## 212 212 NumBonds integer 951 0 1.000
## 213 213 NumNonHBonds integer 951 0 1.000
## 214 214 NumMultBonds integer 951 0 1.000
## 215 215 NumRotBonds integer 951 0 1.000
## 216 216 NumDblBonds integer 951 0 1.000
## 217 217 NumAromaticBonds integer 951 0 1.000
## 218 218 NumHydrogen integer 951 0 1.000
## 219 219 NumCarbon integer 951 0 1.000
## 220 220 NumNitrogen integer 951 0 1.000
## 221 221 NumOxygen integer 951 0 1.000
## 222 222 NumSulfer integer 951 0 1.000
## 223 223 NumChlorine integer 951 0 1.000
## 224 224 NumHalogen integer 951 0 1.000
## 225 225 NumRings integer 951 0 1.000
## 226 226 HydrophilicFactor numeric 951 0 1.000
## 227 227 SurfaceArea1 numeric 951 0 1.000
## 228 228 SurfaceArea2 numeric 951 0 1.000
## 229 229 Log_Solubility_Class factor 951 0 1.000##################################
# Listing all predictors
##################################
DQA.Predictors <- DQA[,!names(DQA) %in% c("Log_Solubility_Class")]
##################################
# Listing all numeric predictors
##################################
DQA.Predictors.Numeric <- DQA.Predictors[,-(grep("FP", names(DQA.Predictors)))]
if (length(names(DQA.Predictors.Numeric))>0) {
print(paste0("There are ",
(length(names(DQA.Predictors.Numeric))),
" numeric predictor variable(s)."))
} else {
print("There are no numeric predictor variables.")
}## [1] "There are 20 numeric predictor variable(s)."##################################
# Listing all factor predictors
##################################
DQA.Predictors.Factor <-as.data.frame(lapply(DQA.Predictors[(grep("FP", names(DQA.Predictors)))],factor))
if (length(names(DQA.Predictors.Factor))>0) {
print(paste0("There are ",
(length(names(DQA.Predictors.Factor))),
" factor predictor variable(s)."))
} else {
print("There are no factor predictor variables.")
}## [1] "There are 208 factor predictor variable(s)."##################################
# Formulating a data quality assessment summary for factor predictors
##################################
if (length(names(DQA.Predictors.Factor))>0) {
##################################
# Formulating a function to determine the first mode
##################################
FirstModes <- function(x) {
ux <- unique(na.omit(x))
tab <- tabulate(match(x, ux))
ux[tab == max(tab)]
}
##################################
# Formulating a function to determine the second mode
##################################
SecondModes <- function(x) {
ux <- unique(na.omit(x))
tab <- tabulate(match(x, ux))
fm = ux[tab == max(tab)]
sm = x[!(x %in% fm)]
usm <- unique(sm)
tabsm <- tabulate(match(sm, usm))
ifelse(is.na(usm[tabsm == max(tabsm)])==TRUE,
return("x"),
return(usm[tabsm == max(tabsm)]))
}
(DQA.Predictors.Factor.Summary <- data.frame(
Column.Name= names(DQA.Predictors.Factor),
Column.Type=sapply(DQA.Predictors.Factor, function(x) class(x)),
Unique.Count=sapply(DQA.Predictors.Factor, function(x) length(unique(x))),
First.Mode.Value=sapply(DQA.Predictors.Factor, function(x) as.character(FirstModes(x)[1])),
Second.Mode.Value=sapply(DQA.Predictors.Factor, function(x) as.character(SecondModes(x)[1])),
First.Mode.Count=sapply(DQA.Predictors.Factor, function(x) sum(na.omit(x) == FirstModes(x)[1])),
Second.Mode.Count=sapply(DQA.Predictors.Factor, function(x) sum(na.omit(x) == SecondModes(x)[1])),
Unique.Count.Ratio=sapply(DQA.Predictors.Factor, function(x) format(round((length(unique(x))/nrow(DQA.Predictors.Factor)),3), nsmall=3)),
First.Second.Mode.Ratio=sapply(DQA.Predictors.Factor, function(x) format(round((sum(na.omit(x) == FirstModes(x)[1])/sum(na.omit(x) == SecondModes(x)[1])),3), nsmall=3)),
row.names=NULL)
)
} ## Column.Name Column.Type Unique.Count First.Mode.Value Second.Mode.Value
## 1 FP001 factor 2 0 1
## 2 FP002 factor 2 1 0
## 3 FP003 factor 2 0 1
## 4 FP004 factor 2 1 0
## 5 FP005 factor 2 1 0
## 6 FP006 factor 2 0 1
## 7 FP007 factor 2 0 1
## 8 FP008 factor 2 0 1
## 9 FP009 factor 2 0 1
## 10 FP010 factor 2 0 1
## 11 FP011 factor 2 0 1
## 12 FP012 factor 2 0 1
## 13 FP013 factor 2 0 1
## 14 FP014 factor 2 0 1
## 15 FP015 factor 2 1 0
## 16 FP016 factor 2 0 1
## 17 FP017 factor 2 0 1
## 18 FP018 factor 2 0 1
## 19 FP019 factor 2 0 1
## 20 FP020 factor 2 0 1
## 21 FP021 factor 2 0 1
## 22 FP022 factor 2 0 1
## 23 FP023 factor 2 0 1
## 24 FP024 factor 2 0 1
## 25 FP025 factor 2 0 1
## 26 FP026 factor 2 0 1
## 27 FP027 factor 2 0 1
## 28 FP028 factor 2 0 1
## 29 FP029 factor 2 0 1
## 30 FP030 factor 2 0 1
## 31 FP031 factor 2 0 1
## 32 FP032 factor 2 0 1
## 33 FP033 factor 2 0 1
## 34 FP034 factor 2 0 1
## 35 FP035 factor 2 0 1
## 36 FP036 factor 2 0 1
## 37 FP037 factor 2 0 1
## 38 FP038 factor 2 0 1
## 39 FP039 factor 2 0 1
## 40 FP040 factor 2 0 1
## 41 FP041 factor 2 0 1
## 42 FP042 factor 2 0 1
## 43 FP043 factor 2 0 1
## 44 FP044 factor 2 0 1
## 45 FP045 factor 2 0 1
## 46 FP046 factor 2 0 1
## 47 FP047 factor 2 0 1
## 48 FP048 factor 2 0 1
## 49 FP049 factor 2 0 1
## 50 FP050 factor 2 0 1
## 51 FP051 factor 2 0 1
## 52 FP052 factor 2 0 1
## 53 FP053 factor 2 0 1
## 54 FP054 factor 2 0 1
## 55 FP055 factor 2 0 1
## 56 FP056 factor 2 0 1
## 57 FP057 factor 2 0 1
## 58 FP058 factor 2 0 1
## 59 FP059 factor 2 0 1
## 60 FP060 factor 2 0 1
## 61 FP061 factor 2 0 1
## 62 FP062 factor 2 0 1
## 63 FP063 factor 2 0 1
## 64 FP064 factor 2 0 1
## 65 FP065 factor 2 1 0
## 66 FP066 factor 2 1 0
## 67 FP067 factor 2 0 1
## 68 FP068 factor 2 0 1
## 69 FP069 factor 2 0 1
## 70 FP070 factor 2 0 1
## 71 FP071 factor 2 0 1
## 72 FP072 factor 2 1 0
## 73 FP073 factor 2 0 1
## 74 FP074 factor 2 0 1
## 75 FP075 factor 2 0 1
## 76 FP076 factor 2 0 1
## 77 FP077 factor 2 0 1
## 78 FP078 factor 2 0 1
## 79 FP079 factor 2 1 0
## 80 FP080 factor 2 0 1
## 81 FP081 factor 2 0 1
## 82 FP082 factor 2 1 0
## 83 FP083 factor 2 0 1
## 84 FP084 factor 2 0 1
## 85 FP085 factor 2 0 1
## 86 FP086 factor 2 0 1
## 87 FP087 factor 2 1 0
## 88 FP088 factor 2 0 1
## 89 FP089 factor 2 0 1
## 90 FP090 factor 2 0 1
## 91 FP091 factor 2 0 1
## 92 FP092 factor 2 0 1
## 93 FP093 factor 2 0 1
## 94 FP094 factor 2 0 1
## 95 FP095 factor 2 0 1
## 96 FP096 factor 2 0 1
## 97 FP097 factor 2 0 1
## 98 FP098 factor 2 0 1
## 99 FP099 factor 2 0 1
## 100 FP100 factor 2 0 1
## 101 FP101 factor 2 0 1
## 102 FP102 factor 2 0 1
## 103 FP103 factor 2 0 1
## 104 FP104 factor 2 0 1
## 105 FP105 factor 2 0 1
## 106 FP106 factor 2 0 1
## 107 FP107 factor 2 0 1
## 108 FP108 factor 2 0 1
## 109 FP109 factor 2 0 1
## 110 FP110 factor 2 0 1
## 111 FP111 factor 2 0 1
## 112 FP112 factor 2 0 1
## 113 FP113 factor 2 0 1
## 114 FP114 factor 2 0 1
## 115 FP115 factor 2 0 1
## 116 FP116 factor 2 0 1
## 117 FP117 factor 2 0 1
## 118 FP118 factor 2 0 1
## 119 FP119 factor 2 0 1
## 120 FP120 factor 2 0 1
## 121 FP121 factor 2 0 1
## 122 FP122 factor 2 0 1
## 123 FP123 factor 2 0 1
## 124 FP124 factor 2 0 1
## 125 FP125 factor 2 0 1
## 126 FP126 factor 2 0 1
## 127 FP127 factor 2 0 1
## 128 FP128 factor 2 0 1
## 129 FP129 factor 2 0 1
## 130 FP130 factor 2 0 1
## 131 FP131 factor 2 0 1
## 132 FP132 factor 2 0 1
## 133 FP133 factor 2 0 1
## 134 FP134 factor 2 0 1
## 135 FP135 factor 2 0 1
## 136 FP136 factor 2 0 1
## 137 FP137 factor 2 0 1
## 138 FP138 factor 2 0 1
## 139 FP139 factor 2 0 1
## 140 FP140 factor 2 0 1
## 141 FP141 factor 2 0 1
## 142 FP142 factor 2 0 1
## 143 FP143 factor 2 0 1
## 144 FP144 factor 2 0 1
## 145 FP145 factor 2 0 1
## 146 FP146 factor 2 0 1
## 147 FP147 factor 2 0 1
## 148 FP148 factor 2 0 1
## 149 FP149 factor 2 0 1
## 150 FP150 factor 2 0 1
## 151 FP151 factor 2 0 1
## 152 FP152 factor 2 0 1
## 153 FP153 factor 2 0 1
## 154 FP154 factor 2 0 1
## 155 FP155 factor 2 0 1
## 156 FP156 factor 2 0 1
## 157 FP157 factor 2 0 1
## 158 FP158 factor 2 0 1
## 159 FP159 factor 2 0 1
## 160 FP160 factor 2 0 1
## 161 FP161 factor 2 0 1
## 162 FP162 factor 2 0 1
## 163 FP163 factor 2 0 1
## 164 FP164 factor 2 1 0
## 165 FP165 factor 2 0 1
## 166 FP166 factor 2 0 1
## 167 FP167 factor 2 0 1
## 168 FP168 factor 2 1 0
## 169 FP169 factor 2 0 1
## 170 FP170 factor 2 0 1
## 171 FP171 factor 2 0 1
## 172 FP172 factor 2 0 1
## 173 FP173 factor 2 0 1
## 174 FP174 factor 2 0 1
## 175 FP175 factor 2 0 1
## 176 FP176 factor 2 0 1
## 177 FP177 factor 2 0 1
## 178 FP178 factor 2 0 1
## 179 FP179 factor 2 0 1
## 180 FP180 factor 2 0 1
## 181 FP181 factor 2 0 1
## 182 FP182 factor 2 0 1
## 183 FP183 factor 2 0 1
## 184 FP184 factor 2 0 1
## 185 FP185 factor 2 0 1
## 186 FP186 factor 2 0 1
## 187 FP187 factor 2 0 1
## 188 FP188 factor 2 0 1
## 189 FP189 factor 2 0 1
## 190 FP190 factor 2 0 1
## 191 FP191 factor 2 0 1
## 192 FP192 factor 2 0 1
## 193 FP193 factor 2 0 1
## 194 FP194 factor 2 0 1
## 195 FP195 factor 2 0 1
## 196 FP196 factor 2 0 1
## 197 FP197 factor 2 0 1
## 198 FP198 factor 2 0 1
## 199 FP199 factor 2 0 1
## 200 FP200 factor 2 0 1
## 201 FP201 factor 2 0 1
## 202 FP202 factor 2 0 1
## 203 FP203 factor 2 0 1
## 204 FP204 factor 2 0 1
## 205 FP205 factor 2 0 1
## 206 FP206 factor 2 0 1
## 207 FP207 factor 2 0 1
## 208 FP208 factor 2 0 1
## First.Mode.Count Second.Mode.Count Unique.Count.Ratio
## 1 482 469 0.002
## 2 513 438 0.002
## 3 536 415 0.002
## 4 556 395 0.002
## 5 551 400 0.002
## 6 570 381 0.002
## 7 605 346 0.002
## 8 641 310 0.002
## 9 685 266 0.002
## 10 781 170 0.002
## 11 747 204 0.002
## 12 783 168 0.002
## 13 793 158 0.002
## 14 798 153 0.002
## 15 818 133 0.002
## 16 812 139 0.002
## 17 814 137 0.002
## 18 826 125 0.002
## 19 835 116 0.002
## 20 837 114 0.002
## 21 836 115 0.002
## 22 852 99 0.002
## 23 834 117 0.002
## 24 844 107 0.002
## 25 841 110 0.002
## 26 871 80 0.002
## 27 858 93 0.002
## 28 850 101 0.002
## 29 854 97 0.002
## 30 862 89 0.002
## 31 866 85 0.002
## 32 881 70 0.002
## 33 885 66 0.002
## 34 875 76 0.002
## 35 882 69 0.002
## 36 879 72 0.002
## 37 884 67 0.002
## 38 869 82 0.002
## 39 880 71 0.002
## 40 886 65 0.002
## 41 891 60 0.002
## 42 897 54 0.002
## 43 888 63 0.002
## 44 894 57 0.002
## 45 898 53 0.002
## 46 651 300 0.002
## 47 698 253 0.002
## 48 833 118 0.002
## 49 835 116 0.002
## 50 844 107 0.002
## 51 847 104 0.002
## 52 864 87 0.002
## 53 862 89 0.002
## 54 879 72 0.002
## 55 900 51 0.002
## 56 889 62 0.002
## 57 837 114 0.002
## 58 843 108 0.002
## 59 899 52 0.002
## 60 493 458 0.002
## 61 526 425 0.002
## 62 535 416 0.002
## 63 546 405 0.002
## 64 555 396 0.002
## 65 564 387 0.002
## 66 580 371 0.002
## 67 590 361 0.002
## 68 607 344 0.002
## 69 607 344 0.002
## 70 613 338 0.002
## 71 640 311 0.002
## 72 626 325 0.002
## 73 656 295 0.002
## 74 642 309 0.002
## 75 629 322 0.002
## 76 639 312 0.002
## 77 646 305 0.002
## 78 662 289 0.002
## 79 656 295 0.002
## 80 663 288 0.002
## 81 686 265 0.002
## 82 679 272 0.002
## 83 691 260 0.002
## 84 679 272 0.002
## 85 708 243 0.002
## 86 695 256 0.002
## 87 691 260 0.002
## 88 701 250 0.002
## 89 716 235 0.002
## 90 714 237 0.002
## 91 737 214 0.002
## 92 719 232 0.002
## 93 719 232 0.002
## 94 731 220 0.002
## 95 742 209 0.002
## 96 744 207 0.002
## 97 727 224 0.002
## 98 725 226 0.002
## 99 735 216 0.002
## 100 731 220 0.002
## 101 726 225 0.002
## 102 759 192 0.002
## 103 743 208 0.002
## 104 739 212 0.002
## 105 746 205 0.002
## 106 769 182 0.002
## 107 750 201 0.002
## 108 756 195 0.002
## 109 783 168 0.002
## 110 755 196 0.002
## 111 764 187 0.002
## 112 766 185 0.002
## 113 765 186 0.002
## 114 803 148 0.002
## 115 781 170 0.002
## 116 768 183 0.002
## 117 781 170 0.002
## 118 768 183 0.002
## 119 796 155 0.002
## 120 793 158 0.002
## 121 818 133 0.002
## 122 795 156 0.002
## 123 792 159 0.002
## 124 797 154 0.002
## 125 803 148 0.002
## 126 810 141 0.002
## 127 818 133 0.002
## 128 810 141 0.002
## 129 819 132 0.002
## 130 851 100 0.002
## 131 831 120 0.002
## 132 832 119 0.002
## 133 831 120 0.002
## 134 830 121 0.002
## 135 831 120 0.002
## 136 836 115 0.002
## 137 841 110 0.002
## 138 845 106 0.002
## 139 873 78 0.002
## 140 845 106 0.002
## 141 840 111 0.002
## 142 847 104 0.002
## 143 874 77 0.002
## 144 852 99 0.002
## 145 852 99 0.002
## 146 853 98 0.002
## 147 851 100 0.002
## 148 868 83 0.002
## 149 865 86 0.002
## 150 876 75 0.002
## 151 898 53 0.002
## 152 873 78 0.002
## 153 877 74 0.002
## 154 915 36 0.002
## 155 885 66 0.002
## 156 884 67 0.002
## 157 892 59 0.002
## 158 900 51 0.002
## 159 884 67 0.002
## 160 886 65 0.002
## 161 888 63 0.002
## 162 480 471 0.002
## 163 498 453 0.002
## 164 597 354 0.002
## 165 619 332 0.002
## 166 636 315 0.002
## 167 639 312 0.002
## 168 633 318 0.002
## 169 774 177 0.002
## 170 776 175 0.002
## 171 790 161 0.002
## 172 807 144 0.002
## 173 816 135 0.002
## 174 827 124 0.002
## 175 823 128 0.002
## 176 835 116 0.002
## 177 836 115 0.002
## 178 836 115 0.002
## 179 858 93 0.002
## 180 849 102 0.002
## 181 862 89 0.002
## 182 857 94 0.002
## 183 879 72 0.002
## 184 871 80 0.002
## 185 870 81 0.002
## 186 878 73 0.002
## 187 882 69 0.002
## 188 886 65 0.002
## 189 878 73 0.002
## 190 882 69 0.002
## 191 884 67 0.002
## 192 893 58 0.002
## 193 892 59 0.002
## 194 895 56 0.002
## 195 893 58 0.002
## 196 897 54 0.002
## 197 901 50 0.002
## 198 897 54 0.002
## 199 906 45 0.002
## 200 904 47 0.002
## 201 901 50 0.002
## 202 706 245 0.002
## 203 842 109 0.002
## 204 857 94 0.002
## 205 877 74 0.002
## 206 894 57 0.002
## 207 897 54 0.002
## 208 844 107 0.002
## First.Second.Mode.Ratio
## 1 1.028
## 2 1.171
## 3 1.292
## 4 1.408
## 5 1.378
## 6 1.496
## 7 1.749
## 8 2.068
## 9 2.575
## 10 4.594
## 11 3.662
## 12 4.661
## 13 5.019
## 14 5.216
## 15 6.150
## 16 5.842
## 17 5.942
## 18 6.608
## 19 7.198
## 20 7.342
## 21 7.270
## 22 8.606
## 23 7.128
## 24 7.888
## 25 7.645
## 26 10.887
## 27 9.226
## 28 8.416
## 29 8.804
## 30 9.685
## 31 10.188
## 32 12.586
## 33 13.409
## 34 11.513
## 35 12.783
## 36 12.208
## 37 13.194
## 38 10.598
## 39 12.394
## 40 13.631
## 41 14.850
## 42 16.611
## 43 14.095
## 44 15.684
## 45 16.943
## 46 2.170
## 47 2.759
## 48 7.059
## 49 7.198
## 50 7.888
## 51 8.144
## 52 9.931
## 53 9.685
## 54 12.208
## 55 17.647
## 56 14.339
## 57 7.342
## 58 7.806
## 59 17.288
## 60 1.076
## 61 1.238
## 62 1.286
## 63 1.348
## 64 1.402
## 65 1.457
## 66 1.563
## 67 1.634
## 68 1.765
## 69 1.765
## 70 1.814
## 71 2.058
## 72 1.926
## 73 2.224
## 74 2.078
## 75 1.953
## 76 2.048
## 77 2.118
## 78 2.291
## 79 2.224
## 80 2.302
## 81 2.589
## 82 2.496
## 83 2.658
## 84 2.496
## 85 2.914
## 86 2.715
## 87 2.658
## 88 2.804
## 89 3.047
## 90 3.013
## 91 3.444
## 92 3.099
## 93 3.099
## 94 3.323
## 95 3.550
## 96 3.594
## 97 3.246
## 98 3.208
## 99 3.403
## 100 3.323
## 101 3.227
## 102 3.953
## 103 3.572
## 104 3.486
## 105 3.639
## 106 4.225
## 107 3.731
## 108 3.877
## 109 4.661
## 110 3.852
## 111 4.086
## 112 4.141
## 113 4.113
## 114 5.426
## 115 4.594
## 116 4.197
## 117 4.594
## 118 4.197
## 119 5.135
## 120 5.019
## 121 6.150
## 122 5.096
## 123 4.981
## 124 5.175
## 125 5.426
## 126 5.745
## 127 6.150
## 128 5.745
## 129 6.205
## 130 8.510
## 131 6.925
## 132 6.992
## 133 6.925
## 134 6.860
## 135 6.925
## 136 7.270
## 137 7.645
## 138 7.972
## 139 11.192
## 140 7.972
## 141 7.568
## 142 8.144
## 143 11.351
## 144 8.606
## 145 8.606
## 146 8.704
## 147 8.510
## 148 10.458
## 149 10.058
## 150 11.680
## 151 16.943
## 152 11.192
## 153 11.851
## 154 25.417
## 155 13.409
## 156 13.194
## 157 15.119
## 158 17.647
## 159 13.194
## 160 13.631
## 161 14.095
## 162 1.019
## 163 1.099
## 164 1.686
## 165 1.864
## 166 2.019
## 167 2.048
## 168 1.991
## 169 4.373
## 170 4.434
## 171 4.907
## 172 5.604
## 173 6.044
## 174 6.669
## 175 6.430
## 176 7.198
## 177 7.270
## 178 7.270
## 179 9.226
## 180 8.324
## 181 9.685
## 182 9.117
## 183 12.208
## 184 10.887
## 185 10.741
## 186 12.027
## 187 12.783
## 188 13.631
## 189 12.027
## 190 12.783
## 191 13.194
## 192 15.397
## 193 15.119
## 194 15.982
## 195 15.397
## 196 16.611
## 197 18.020
## 198 16.611
## 199 20.133
## 200 19.234
## 201 18.020
## 202 2.882
## 203 7.725
## 204 9.117
## 205 11.851
## 206 15.684
## 207 16.611
## 208 7.888##################################
# Formulating a data quality assessment summary for numeric predictors
##################################
if (length(names(DQA.Predictors.Numeric))>0) {
##################################
# Formulating a function to determine the first mode
##################################
FirstModes <- function(x) {
ux <- unique(na.omit(x))
tab <- tabulate(match(x, ux))
ux[tab == max(tab)]
}
##################################
# Formulating a function to determine the second mode
##################################
SecondModes <- function(x) {
ux <- unique(na.omit(x))
tab <- tabulate(match(x, ux))
fm = ux[tab == max(tab)]
sm = na.omit(x)[!(na.omit(x) %in% fm)]
usm <- unique(sm)
tabsm <- tabulate(match(sm, usm))
ifelse(is.na(usm[tabsm == max(tabsm)])==TRUE,
return(0.00001),
return(usm[tabsm == max(tabsm)]))
}
(DQA.Predictors.Numeric.Summary <- data.frame(
Column.Name= names(DQA.Predictors.Numeric),
Column.Type=sapply(DQA.Predictors.Numeric, function(x) class(x)),
Unique.Count=sapply(DQA.Predictors.Numeric, function(x) length(unique(x))),
Unique.Count.Ratio=sapply(DQA.Predictors.Numeric, function(x) format(round((length(unique(x))/nrow(DQA.Predictors.Numeric)),3), nsmall=3)),
First.Mode.Value=sapply(DQA.Predictors.Numeric, function(x) format(round((FirstModes(x)[1]),3),nsmall=3)),
Second.Mode.Value=sapply(DQA.Predictors.Numeric, function(x) format(round((SecondModes(x)[1]),3),nsmall=3)),
First.Mode.Count=sapply(DQA.Predictors.Numeric, function(x) sum(na.omit(x) == FirstModes(x)[1])),
Second.Mode.Count=sapply(DQA.Predictors.Numeric, function(x) sum(na.omit(x) == SecondModes(x)[1])),
First.Second.Mode.Ratio=sapply(DQA.Predictors.Numeric, function(x) format(round((sum(na.omit(x) == FirstModes(x)[1])/sum(na.omit(x) == SecondModes(x)[1])),3), nsmall=3)),
Minimum=sapply(DQA.Predictors.Numeric, function(x) format(round(min(x,na.rm = TRUE),3), nsmall=3)),
Mean=sapply(DQA.Predictors.Numeric, function(x) format(round(mean(x,na.rm = TRUE),3), nsmall=3)),
Median=sapply(DQA.Predictors.Numeric, function(x) format(round(median(x,na.rm = TRUE),3), nsmall=3)),
Maximum=sapply(DQA.Predictors.Numeric, function(x) format(round(max(x,na.rm = TRUE),3), nsmall=3)),
Skewness=sapply(DQA.Predictors.Numeric, function(x) format(round(skewness(x,na.rm = TRUE),3), nsmall=3)),
Kurtosis=sapply(DQA.Predictors.Numeric, function(x) format(round(kurtosis(x,na.rm = TRUE),3), nsmall=3)),
Percentile25th=sapply(DQA.Predictors.Numeric, function(x) format(round(quantile(x,probs=0.25,na.rm = TRUE),3), nsmall=3)),
Percentile75th=sapply(DQA.Predictors.Numeric, function(x) format(round(quantile(x,probs=0.75,na.rm = TRUE),3), nsmall=3)),
row.names=NULL)
)
}## Column.Name Column.Type Unique.Count Unique.Count.Ratio
## 1 MolWeight numeric 646 0.679
## 2 NumAtoms integer 66 0.069
## 3 NumNonHAtoms integer 36 0.038
## 4 NumBonds integer 72 0.076
## 5 NumNonHBonds integer 39 0.041
## 6 NumMultBonds integer 25 0.026
## 7 NumRotBonds integer 15 0.016
## 8 NumDblBonds integer 8 0.008
## 9 NumAromaticBonds integer 16 0.017
## 10 NumHydrogen integer 41 0.043
## 11 NumCarbon integer 28 0.029
## 12 NumNitrogen integer 7 0.007
## 13 NumOxygen integer 11 0.012
## 14 NumSulfer integer 5 0.005
## 15 NumChlorine integer 11 0.012
## 16 NumHalogen integer 11 0.012
## 17 NumRings integer 8 0.008
## 18 HydrophilicFactor numeric 369 0.388
## 19 SurfaceArea1 numeric 252 0.265
## 20 SurfaceArea2 numeric 287 0.302
## First.Mode.Value Second.Mode.Value First.Mode.Count Second.Mode.Count
## 1 102.200 116.230 16 14
## 2 22.000 24.000 73 51
## 3 8.000 11.000 104 73
## 4 23.000 19.000 69 56
## 5 8.000 7.000 82 66
## 6 0.000 7.000 158 122
## 7 0.000 1.000 272 186
## 8 0.000 1.000 427 268
## 9 0.000 6.000 400 302
## 10 12.000 8.000 83 79
## 11 6.000 7.000 105 97
## 12 0.000 1.000 546 191
## 13 0.000 2.000 325 218
## 14 0.000 1.000 830 96
## 15 0.000 1.000 750 81
## 16 0.000 1.000 685 107
## 17 1.000 0.000 323 260
## 18 -0.828 -0.158 21 20
## 19 0.000 20.230 218 76
## 20 0.000 20.230 211 75
## First.Second.Mode.Ratio Minimum Mean Median Maximum Skewness Kurtosis
## 1 1.143 46.090 201.654 179.230 665.810 0.988 3.945
## 2 1.431 5.000 25.507 22.000 94.000 1.364 5.523
## 3 1.425 2.000 13.161 12.000 47.000 0.993 4.129
## 4 1.232 4.000 25.909 23.000 97.000 1.360 5.408
## 5 1.242 1.000 13.563 12.000 50.000 0.969 3.842
## 6 1.295 0.000 6.148 6.000 25.000 0.670 3.053
## 7 1.462 0.000 2.251 2.000 16.000 1.577 6.437
## 8 1.593 0.000 1.006 1.000 7.000 1.360 4.760
## 9 1.325 0.000 5.121 6.000 25.000 0.796 3.241
## 10 1.051 0.000 12.346 11.000 47.000 1.262 5.261
## 11 1.082 1.000 9.893 9.000 33.000 0.927 3.616
## 12 2.859 0.000 0.813 0.000 6.000 1.554 4.831
## 13 1.491 0.000 1.574 1.000 13.000 1.772 8.494
## 14 8.646 0.000 0.164 0.000 4.000 3.842 21.526
## 15 9.259 0.000 0.556 0.000 10.000 3.178 13.780
## 16 6.402 0.000 0.698 0.000 10.000 2.691 10.808
## 17 1.242 0.000 1.402 1.000 7.000 1.034 3.875
## 18 1.050 -0.985 -0.021 -0.314 13.483 3.404 27.504
## 19 2.868 0.000 36.459 29.100 331.940 1.714 9.714
## 20 2.813 0.000 40.234 33.120 331.940 1.475 7.485
## Percentile25th Percentile75th
## 1 122.605 264.340
## 2 17.000 31.000
## 3 8.000 17.000
## 4 17.000 31.500
## 5 8.000 18.000
## 6 1.000 10.000
## 7 0.000 3.500
## 8 0.000 2.000
## 9 0.000 6.000
## 10 7.000 16.000
## 11 6.000 12.000
## 12 0.000 1.000
## 13 0.000 2.000
## 14 0.000 0.000
## 15 0.000 0.000
## 16 0.000 1.000
## 17 0.000 2.000
## 18 -0.763 0.313
## 19 9.230 53.280
## 20 10.630 60.660##################################
# Identifying potential data quality issues
##################################
##################################
# Checking for missing observations
##################################
if ((nrow(DQA.Summary[DQA.Summary$NA.Count>0,]))>0){
print(paste0("Missing observations noted for ",
(nrow(DQA.Summary[DQA.Summary$NA.Count>0,])),
" variable(s) with NA.Count>0 and Fill.Rate<1.0."))
DQA.Summary[DQA.Summary$NA.Count>0,]
} else {
print("No missing observations noted.")
}## [1] "No missing observations noted."##################################
# Checking for zero or near-zero variance predictors
##################################
if (length(names(DQA.Predictors.Factor))==0) {
print("No factor predictors noted.")
} else if (nrow(DQA.Predictors.Factor.Summary[as.numeric(as.character(DQA.Predictors.Factor.Summary$First.Second.Mode.Ratio))>5,])>0){
print(paste0("Low variance observed for ",
(nrow(DQA.Predictors.Factor.Summary[as.numeric(as.character(DQA.Predictors.Factor.Summary$First.Second.Mode.Ratio))>5,])),
" factor variable(s) with First.Second.Mode.Ratio>5."))
DQA.Predictors.Factor.Summary[as.numeric(as.character(DQA.Predictors.Factor.Summary$First.Second.Mode.Ratio))>5,]
} else {
print("No low variance factor predictors due to high first-second mode ratio noted.")
}## [1] "Low variance observed for 124 factor variable(s) with First.Second.Mode.Ratio>5."## Column.Name Column.Type Unique.Count First.Mode.Value Second.Mode.Value
## 13 FP013 factor 2 0 1
## 14 FP014 factor 2 0 1
## 15 FP015 factor 2 1 0
## 16 FP016 factor 2 0 1
## 17 FP017 factor 2 0 1
## 18 FP018 factor 2 0 1
## 19 FP019 factor 2 0 1
## 20 FP020 factor 2 0 1
## 21 FP021 factor 2 0 1
## 22 FP022 factor 2 0 1
## 23 FP023 factor 2 0 1
## 24 FP024 factor 2 0 1
## 25 FP025 factor 2 0 1
## 26 FP026 factor 2 0 1
## 27 FP027 factor 2 0 1
## 28 FP028 factor 2 0 1
## 29 FP029 factor 2 0 1
## 30 FP030 factor 2 0 1
## 31 FP031 factor 2 0 1
## 32 FP032 factor 2 0 1
## 33 FP033 factor 2 0 1
## 34 FP034 factor 2 0 1
## 35 FP035 factor 2 0 1
## 36 FP036 factor 2 0 1
## 37 FP037 factor 2 0 1
## 38 FP038 factor 2 0 1
## 39 FP039 factor 2 0 1
## 40 FP040 factor 2 0 1
## 41 FP041 factor 2 0 1
## 42 FP042 factor 2 0 1
## 43 FP043 factor 2 0 1
## 44 FP044 factor 2 0 1
## 45 FP045 factor 2 0 1
## 48 FP048 factor 2 0 1
## 49 FP049 factor 2 0 1
## 50 FP050 factor 2 0 1
## 51 FP051 factor 2 0 1
## 52 FP052 factor 2 0 1
## 53 FP053 factor 2 0 1
## 54 FP054 factor 2 0 1
## 55 FP055 factor 2 0 1
## 56 FP056 factor 2 0 1
## 57 FP057 factor 2 0 1
## 58 FP058 factor 2 0 1
## 59 FP059 factor 2 0 1
## 114 FP114 factor 2 0 1
## 119 FP119 factor 2 0 1
## 120 FP120 factor 2 0 1
## 121 FP121 factor 2 0 1
## 122 FP122 factor 2 0 1
## 124 FP124 factor 2 0 1
## 125 FP125 factor 2 0 1
## 126 FP126 factor 2 0 1
## 127 FP127 factor 2 0 1
## 128 FP128 factor 2 0 1
## 129 FP129 factor 2 0 1
## 130 FP130 factor 2 0 1
## 131 FP131 factor 2 0 1
## 132 FP132 factor 2 0 1
## 133 FP133 factor 2 0 1
## 134 FP134 factor 2 0 1
## 135 FP135 factor 2 0 1
## 136 FP136 factor 2 0 1
## 137 FP137 factor 2 0 1
## 138 FP138 factor 2 0 1
## 139 FP139 factor 2 0 1
## 140 FP140 factor 2 0 1
## 141 FP141 factor 2 0 1
## 142 FP142 factor 2 0 1
## 143 FP143 factor 2 0 1
## 144 FP144 factor 2 0 1
## 145 FP145 factor 2 0 1
## 146 FP146 factor 2 0 1
## 147 FP147 factor 2 0 1
## 148 FP148 factor 2 0 1
## 149 FP149 factor 2 0 1
## 150 FP150 factor 2 0 1
## 151 FP151 factor 2 0 1
## 152 FP152 factor 2 0 1
## 153 FP153 factor 2 0 1
## 154 FP154 factor 2 0 1
## 155 FP155 factor 2 0 1
## 156 FP156 factor 2 0 1
## 157 FP157 factor 2 0 1
## 158 FP158 factor 2 0 1
## 159 FP159 factor 2 0 1
## 160 FP160 factor 2 0 1
## 161 FP161 factor 2 0 1
## 172 FP172 factor 2 0 1
## 173 FP173 factor 2 0 1
## 174 FP174 factor 2 0 1
## 175 FP175 factor 2 0 1
## 176 FP176 factor 2 0 1
## 177 FP177 factor 2 0 1
## 178 FP178 factor 2 0 1
## 179 FP179 factor 2 0 1
## 180 FP180 factor 2 0 1
## 181 FP181 factor 2 0 1
## 182 FP182 factor 2 0 1
## 183 FP183 factor 2 0 1
## 184 FP184 factor 2 0 1
## 185 FP185 factor 2 0 1
## 186 FP186 factor 2 0 1
## 187 FP187 factor 2 0 1
## 188 FP188 factor 2 0 1
## 189 FP189 factor 2 0 1
## 190 FP190 factor 2 0 1
## 191 FP191 factor 2 0 1
## 192 FP192 factor 2 0 1
## 193 FP193 factor 2 0 1
## 194 FP194 factor 2 0 1
## 195 FP195 factor 2 0 1
## 196 FP196 factor 2 0 1
## 197 FP197 factor 2 0 1
## 198 FP198 factor 2 0 1
## 199 FP199 factor 2 0 1
## 200 FP200 factor 2 0 1
## 201 FP201 factor 2 0 1
## 203 FP203 factor 2 0 1
## 204 FP204 factor 2 0 1
## 205 FP205 factor 2 0 1
## 206 FP206 factor 2 0 1
## 207 FP207 factor 2 0 1
## 208 FP208 factor 2 0 1
## First.Mode.Count Second.Mode.Count Unique.Count.Ratio
## 13 793 158 0.002
## 14 798 153 0.002
## 15 818 133 0.002
## 16 812 139 0.002
## 17 814 137 0.002
## 18 826 125 0.002
## 19 835 116 0.002
## 20 837 114 0.002
## 21 836 115 0.002
## 22 852 99 0.002
## 23 834 117 0.002
## 24 844 107 0.002
## 25 841 110 0.002
## 26 871 80 0.002
## 27 858 93 0.002
## 28 850 101 0.002
## 29 854 97 0.002
## 30 862 89 0.002
## 31 866 85 0.002
## 32 881 70 0.002
## 33 885 66 0.002
## 34 875 76 0.002
## 35 882 69 0.002
## 36 879 72 0.002
## 37 884 67 0.002
## 38 869 82 0.002
## 39 880 71 0.002
## 40 886 65 0.002
## 41 891 60 0.002
## 42 897 54 0.002
## 43 888 63 0.002
## 44 894 57 0.002
## 45 898 53 0.002
## 48 833 118 0.002
## 49 835 116 0.002
## 50 844 107 0.002
## 51 847 104 0.002
## 52 864 87 0.002
## 53 862 89 0.002
## 54 879 72 0.002
## 55 900 51 0.002
## 56 889 62 0.002
## 57 837 114 0.002
## 58 843 108 0.002
## 59 899 52 0.002
## 114 803 148 0.002
## 119 796 155 0.002
## 120 793 158 0.002
## 121 818 133 0.002
## 122 795 156 0.002
## 124 797 154 0.002
## 125 803 148 0.002
## 126 810 141 0.002
## 127 818 133 0.002
## 128 810 141 0.002
## 129 819 132 0.002
## 130 851 100 0.002
## 131 831 120 0.002
## 132 832 119 0.002
## 133 831 120 0.002
## 134 830 121 0.002
## 135 831 120 0.002
## 136 836 115 0.002
## 137 841 110 0.002
## 138 845 106 0.002
## 139 873 78 0.002
## 140 845 106 0.002
## 141 840 111 0.002
## 142 847 104 0.002
## 143 874 77 0.002
## 144 852 99 0.002
## 145 852 99 0.002
## 146 853 98 0.002
## 147 851 100 0.002
## 148 868 83 0.002
## 149 865 86 0.002
## 150 876 75 0.002
## 151 898 53 0.002
## 152 873 78 0.002
## 153 877 74 0.002
## 154 915 36 0.002
## 155 885 66 0.002
## 156 884 67 0.002
## 157 892 59 0.002
## 158 900 51 0.002
## 159 884 67 0.002
## 160 886 65 0.002
## 161 888 63 0.002
## 172 807 144 0.002
## 173 816 135 0.002
## 174 827 124 0.002
## 175 823 128 0.002
## 176 835 116 0.002
## 177 836 115 0.002
## 178 836 115 0.002
## 179 858 93 0.002
## 180 849 102 0.002
## 181 862 89 0.002
## 182 857 94 0.002
## 183 879 72 0.002
## 184 871 80 0.002
## 185 870 81 0.002
## 186 878 73 0.002
## 187 882 69 0.002
## 188 886 65 0.002
## 189 878 73 0.002
## 190 882 69 0.002
## 191 884 67 0.002
## 192 893 58 0.002
## 193 892 59 0.002
## 194 895 56 0.002
## 195 893 58 0.002
## 196 897 54 0.002
## 197 901 50 0.002
## 198 897 54 0.002
## 199 906 45 0.002
## 200 904 47 0.002
## 201 901 50 0.002
## 203 842 109 0.002
## 204 857 94 0.002
## 205 877 74 0.002
## 206 894 57 0.002
## 207 897 54 0.002
## 208 844 107 0.002
## First.Second.Mode.Ratio
## 13 5.019
## 14 5.216
## 15 6.150
## 16 5.842
## 17 5.942
## 18 6.608
## 19 7.198
## 20 7.342
## 21 7.270
## 22 8.606
## 23 7.128
## 24 7.888
## 25 7.645
## 26 10.887
## 27 9.226
## 28 8.416
## 29 8.804
## 30 9.685
## 31 10.188
## 32 12.586
## 33 13.409
## 34 11.513
## 35 12.783
## 36 12.208
## 37 13.194
## 38 10.598
## 39 12.394
## 40 13.631
## 41 14.850
## 42 16.611
## 43 14.095
## 44 15.684
## 45 16.943
## 48 7.059
## 49 7.198
## 50 7.888
## 51 8.144
## 52 9.931
## 53 9.685
## 54 12.208
## 55 17.647
## 56 14.339
## 57 7.342
## 58 7.806
## 59 17.288
## 114 5.426
## 119 5.135
## 120 5.019
## 121 6.150
## 122 5.096
## 124 5.175
## 125 5.426
## 126 5.745
## 127 6.150
## 128 5.745
## 129 6.205
## 130 8.510
## 131 6.925
## 132 6.992
## 133 6.925
## 134 6.860
## 135 6.925
## 136 7.270
## 137 7.645
## 138 7.972
## 139 11.192
## 140 7.972
## 141 7.568
## 142 8.144
## 143 11.351
## 144 8.606
## 145 8.606
## 146 8.704
## 147 8.510
## 148 10.458
## 149 10.058
## 150 11.680
## 151 16.943
## 152 11.192
## 153 11.851
## 154 25.417
## 155 13.409
## 156 13.194
## 157 15.119
## 158 17.647
## 159 13.194
## 160 13.631
## 161 14.095
## 172 5.604
## 173 6.044
## 174 6.669
## 175 6.430
## 176 7.198
## 177 7.270
## 178 7.270
## 179 9.226
## 180 8.324
## 181 9.685
## 182 9.117
## 183 12.208
## 184 10.887
## 185 10.741
## 186 12.027
## 187 12.783
## 188 13.631
## 189 12.027
## 190 12.783
## 191 13.194
## 192 15.397
## 193 15.119
## 194 15.982
## 195 15.397
## 196 16.611
## 197 18.020
## 198 16.611
## 199 20.133
## 200 19.234
## 201 18.020
## 203 7.725
## 204 9.117
## 205 11.851
## 206 15.684
## 207 16.611
## 208 7.888if (length(names(DQA.Predictors.Numeric))==0) {
print("No numeric predictors noted.")
} else if (nrow(DQA.Predictors.Numeric.Summary[as.numeric(as.character(DQA.Predictors.Numeric.Summary$First.Second.Mode.Ratio))>5,])>0){
print(paste0("Low variance observed for ",
(nrow(DQA.Predictors.Numeric.Summary[as.numeric(as.character(DQA.Predictors.Numeric.Summary$First.Second.Mode.Ratio))>5,])),
" numeric variable(s) with First.Second.Mode.Ratio>5."))
DQA.Predictors.Numeric.Summary[as.numeric(as.character(DQA.Predictors.Numeric.Summary$First.Second.Mode.Ratio))>5,]
} else {
print("No low variance numeric predictors due to high first-second mode ratio noted.")
}## [1] "Low variance observed for 3 numeric variable(s) with First.Second.Mode.Ratio>5."## Column.Name Column.Type Unique.Count Unique.Count.Ratio First.Mode.Value
## 14 NumSulfer integer 5 0.005 0.000
## 15 NumChlorine integer 11 0.012 0.000
## 16 NumHalogen integer 11 0.012 0.000
## Second.Mode.Value First.Mode.Count Second.Mode.Count First.Second.Mode.Ratio
## 14 1.000 830 96 8.646
## 15 1.000 750 81 9.259
## 16 1.000 685 107 6.402
## Minimum Mean Median Maximum Skewness Kurtosis Percentile25th Percentile75th
## 14 0.000 0.164 0.000 4.000 3.842 21.526 0.000 0.000
## 15 0.000 0.556 0.000 10.000 3.178 13.780 0.000 0.000
## 16 0.000 0.698 0.000 10.000 2.691 10.808 0.000 1.000if (length(names(DQA.Predictors.Numeric))==0) {
print("No numeric predictors noted.")
} else if (nrow(DQA.Predictors.Numeric.Summary[as.numeric(as.character(DQA.Predictors.Numeric.Summary$Unique.Count.Ratio))<0.01,])>0){
print(paste0("Low variance observed for ",
(nrow(DQA.Predictors.Numeric.Summary[as.numeric(as.character(DQA.Predictors.Numeric.Summary$Unique.Count.Ratio))<0.01,])),
" numeric variable(s) with Unique.Count.Ratio<0.01."))
DQA.Predictors.Numeric.Summary[as.numeric(as.character(DQA.Predictors.Numeric.Summary$Unique.Count.Ratio))<0.01,]
} else {
print("No low variance numeric predictors due to low unique count ratio noted.")
}## [1] "Low variance observed for 4 numeric variable(s) with Unique.Count.Ratio<0.01."## Column.Name Column.Type Unique.Count Unique.Count.Ratio First.Mode.Value
## 8 NumDblBonds integer 8 0.008 0.000
## 12 NumNitrogen integer 7 0.007 0.000
## 14 NumSulfer integer 5 0.005 0.000
## 17 NumRings integer 8 0.008 1.000
## Second.Mode.Value First.Mode.Count Second.Mode.Count First.Second.Mode.Ratio
## 8 1.000 427 268 1.593
## 12 1.000 546 191 2.859
## 14 1.000 830 96 8.646
## 17 0.000 323 260 1.242
## Minimum Mean Median Maximum Skewness Kurtosis Percentile25th Percentile75th
## 8 0.000 1.006 1.000 7.000 1.360 4.760 0.000 2.000
## 12 0.000 0.813 0.000 6.000 1.554 4.831 0.000 1.000
## 14 0.000 0.164 0.000 4.000 3.842 21.526 0.000 0.000
## 17 0.000 1.402 1.000 7.000 1.034 3.875 0.000 2.000##################################
# Checking for skewed predictors
##################################
if (length(names(DQA.Predictors.Numeric))==0) {
print("No numeric predictors noted.")
} else if (nrow(DQA.Predictors.Numeric.Summary[as.numeric(as.character(DQA.Predictors.Numeric.Summary$Skewness))>3 |
as.numeric(as.character(DQA.Predictors.Numeric.Summary$Skewness))<(-3),])>0){
print(paste0("High skewness observed for ",
(nrow(DQA.Predictors.Numeric.Summary[as.numeric(as.character(DQA.Predictors.Numeric.Summary$Skewness))>3 |
as.numeric(as.character(DQA.Predictors.Numeric.Summary$Skewness))<(-3),])),
" numeric variable(s) with Skewness>3 or Skewness<(-3)."))
DQA.Predictors.Numeric.Summary[as.numeric(as.character(DQA.Predictors.Numeric.Summary$Skewness))>3 |
as.numeric(as.character(DQA.Predictors.Numeric.Summary$Skewness))<(-3),]
} else {
print("No skewed numeric predictors noted.")
}## [1] "High skewness observed for 3 numeric variable(s) with Skewness>3 or Skewness<(-3)."## Column.Name Column.Type Unique.Count Unique.Count.Ratio
## 14 NumSulfer integer 5 0.005
## 15 NumChlorine integer 11 0.012
## 18 HydrophilicFactor numeric 369 0.388
## First.Mode.Value Second.Mode.Value First.Mode.Count Second.Mode.Count
## 14 0.000 1.000 830 96
## 15 0.000 1.000 750 81
## 18 -0.828 -0.158 21 20
## First.Second.Mode.Ratio Minimum Mean Median Maximum Skewness Kurtosis
## 14 8.646 0.000 0.164 0.000 4.000 3.842 21.526
## 15 9.259 0.000 0.556 0.000 10.000 3.178 13.780
## 18 1.050 -0.985 -0.021 -0.314 13.483 3.404 27.504
## Percentile25th Percentile75th
## 14 0.000 0.000
## 15 0.000 0.000
## 18 -0.763 0.3131.3 Data Preprocessing
1.3.1 Outlier
[A] Outliers noted for 20 variables with the numeric data visualized through a boxplot including observations classified as suspected outliers using the IQR criterion. The IQR criterion means that all observations above the (75th percentile + 1.5 x IQR) or below the (25th percentile - 1.5 x IQR) are suspected outliers, where IQR is the difference between the third quartile (75th percentile) and first quartile (25th percentile). Outlier treatment for numerical stability remains optional depending on potential model requirements for the subsequent steps.
[A.1] MolWeight variable (8 outliers detected)
[A.2] NumAtoms variable (44 outliers detected)
[A.3] NumNonHAtoms variable (15 outliers detected)
[A.4] NumBonds variable (51 outliers detected)
[A.5] NumNonHBonds variable (18 outliers detected)
[A.6] NumMultBonds variable (6 outliers detected)
[A.7] NumRotBonds variable (23 outliers detected)
[A.8] NumDblBonds variable (3 outliers detected)
[A.9] NumAromaticBonds variable (35 outliers detected)
[A.10] NumHydrogen variable (32 outliers detected)
[A.11] NumCarbon variable (35 outliers detected)
[A.12] NumNitrogen variable (91 outliers detected)
[A.13] NumOxygen variable (36 outliers detected)
[A.14] NumSulfer variable (121 outliers detected)
[A.15] NumChlorine variable (201 outliers detected)
[A.16] NumHalogen variable (99 outliers detected)
[A.17] NumRings variable (4 outliers detected)
[A.18] HydrophilicFactor variable (53 outliers detected)
[A.19] SurfaceArea1 variable (19 outliers detected)
[A.20] SurfaceArea2 variable (12 outliers detected)
Code Chunk | Output
##################################
# Loading dataset
##################################
DPA <- Solubility_Train
##################################
# Listing all predictors
##################################
DPA.Predictors <- DPA[,!names(DPA) %in% c("Log_Solubility_Class")]
##################################
# Listing all numeric predictors
##################################
DPA.Predictors.Numeric <- DPA.Predictors[,-(grep("FP", names(DPA.Predictors)))]
##################################
# Identifying outliers for the numeric predictors
##################################
OutlierCountList <- c()
for (i in 1:ncol(DPA.Predictors.Numeric)) {
Outliers <- boxplot.stats(DPA.Predictors.Numeric[,i])$out
OutlierCount <- length(Outliers)
OutlierCountList <- append(OutlierCountList,OutlierCount)
OutlierIndices <- which(DPA.Predictors.Numeric[,i] %in% c(Outliers))
boxplot(DPA.Predictors.Numeric[,i],
ylab = names(DPA.Predictors.Numeric)[i],
main = names(DPA.Predictors.Numeric)[i],
horizontal=TRUE)
mtext(paste0(OutlierCount, " Outlier(s) Detected"))
}
OutlierCountSummary <- as.data.frame(cbind(names(DPA.Predictors.Numeric),(OutlierCountList)))
names(OutlierCountSummary) <- c("NumericPredictors","OutlierCount")
OutlierCountSummary$OutlierCount <- as.numeric(as.character(OutlierCountSummary$OutlierCount))
NumericPredictorWithOutlierCount <- nrow(OutlierCountSummary[OutlierCountSummary$OutlierCount>0,])
print(paste0(NumericPredictorWithOutlierCount, " numeric variable(s) were noted with outlier(s)." ))## [1] "20 numeric variable(s) were noted with outlier(s)."##################################
# Gathering descriptive statistics
##################################
(DPA_Skimmed <- skim(DPA.Predictors.Numeric))| Name | DPA.Predictors.Numeric |
| Number of rows | 951 |
| Number of columns | 20 |
| _______________________ | |
| Column type frequency: | |
| numeric | 20 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| MolWeight | 0 | 1 | 201.65 | 97.91 | 46.09 | 122.60 | 179.23 | 264.34 | 665.81 | ▇▆▂▁▁ |
| NumAtoms | 0 | 1 | 25.51 | 12.61 | 5.00 | 17.00 | 22.00 | 31.00 | 94.00 | ▇▆▂▁▁ |
| NumNonHAtoms | 0 | 1 | 13.16 | 6.50 | 2.00 | 8.00 | 12.00 | 17.00 | 47.00 | ▇▆▂▁▁ |
| NumBonds | 0 | 1 | 25.91 | 13.48 | 4.00 | 17.00 | 23.00 | 31.50 | 97.00 | ▇▇▂▁▁ |
| NumNonHBonds | 0 | 1 | 13.56 | 7.57 | 1.00 | 8.00 | 12.00 | 18.00 | 50.00 | ▇▇▂▁▁ |
| NumMultBonds | 0 | 1 | 6.15 | 5.17 | 0.00 | 1.00 | 6.00 | 10.00 | 25.00 | ▇▆▃▁▁ |
| NumRotBonds | 0 | 1 | 2.25 | 2.41 | 0.00 | 0.00 | 2.00 | 3.50 | 16.00 | ▇▂▁▁▁ |
| NumDblBonds | 0 | 1 | 1.01 | 1.21 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▂▁▁▁ |
| NumAromaticBonds | 0 | 1 | 5.12 | 5.26 | 0.00 | 0.00 | 6.00 | 6.00 | 25.00 | ▇▆▃▁▁ |
| NumHydrogen | 0 | 1 | 12.35 | 7.32 | 0.00 | 7.00 | 11.00 | 16.00 | 47.00 | ▇▇▂▁▁ |
| NumCarbon | 0 | 1 | 9.89 | 5.29 | 1.00 | 6.00 | 9.00 | 12.00 | 33.00 | ▇▇▃▁▁ |
| NumNitrogen | 0 | 1 | 0.81 | 1.19 | 0.00 | 0.00 | 0.00 | 1.00 | 6.00 | ▇▂▁▁▁ |
| NumOxygen | 0 | 1 | 1.57 | 1.73 | 0.00 | 0.00 | 1.00 | 2.00 | 13.00 | ▇▂▁▁▁ |
| NumSulfer | 0 | 1 | 0.16 | 0.49 | 0.00 | 0.00 | 0.00 | 0.00 | 4.00 | ▇▁▁▁▁ |
| NumChlorine | 0 | 1 | 0.56 | 1.40 | 0.00 | 0.00 | 0.00 | 0.00 | 10.00 | ▇▁▁▁▁ |
| NumHalogen | 0 | 1 | 0.70 | 1.47 | 0.00 | 0.00 | 0.00 | 1.00 | 10.00 | ▇▁▁▁▁ |
| NumRings | 0 | 1 | 1.40 | 1.30 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▃▂▁▁ |
| HydrophilicFactor | 0 | 1 | -0.02 | 1.13 | -0.98 | -0.76 | -0.31 | 0.31 | 13.48 | ▇▁▁▁▁ |
| SurfaceArea1 | 0 | 1 | 36.46 | 35.29 | 0.00 | 9.23 | 29.10 | 53.28 | 331.94 | ▇▂▁▁▁ |
| SurfaceArea2 | 0 | 1 | 40.23 | 38.12 | 0.00 | 10.63 | 33.12 | 60.66 | 331.94 | ▇▂▁▁▁ |
###################################
# Verifying the data dimensions
###################################
dim(DPA.Predictors.Numeric)## [1] 951 201.3.2 Zero and Near-Zero Variance
[A] Low variance noted for 127 variables from the previous data quality assessment using a lower threshold.
[B] Low variance noted for 3 variables using a preprocessing summary from the caret package. The nearZeroVar method using both the freqCut and uniqueCut criteria set at 95/5 and 10, respectively, were applied on the dataset.
[B.1] FP154 variable (factor)
[B.2] FP199 variable (factor)
[B.3] FP200 variable (factor)
Code Chunk | Output
##################################
# Loading dataset
##################################
DPA <- Solubility_Train
##################################
# Gathering descriptive statistics
##################################
(DPA_Skimmed <- skim(DPA))| Name | DPA |
| Number of rows | 951 |
| Number of columns | 229 |
| _______________________ | |
| Column type frequency: | |
| factor | 1 |
| numeric | 228 |
| ________________________ | |
| Group variables | None |
Variable type: factor
| skim_variable | n_missing | complete_rate | ordered | n_unique | top_counts |
|---|---|---|---|---|---|
| Log_Solubility_Class | 0 | 1 | FALSE | 3 | Low: 427, Mid: 283, Hig: 241 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| FP001 | 0 | 1 | 0.49 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP002 | 0 | 1 | 0.54 | 0.50 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP003 | 0 | 1 | 0.44 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP004 | 0 | 1 | 0.58 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP005 | 0 | 1 | 0.58 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP006 | 0 | 1 | 0.40 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP007 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP008 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP009 | 0 | 1 | 0.28 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP010 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP011 | 0 | 1 | 0.21 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP012 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP013 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP014 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP015 | 0 | 1 | 0.86 | 0.35 | 0.00 | 1.00 | 1.00 | 1.00 | 1.00 | ▁▁▁▁▇ |
| FP016 | 0 | 1 | 0.15 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP017 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP018 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP019 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP020 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP021 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP022 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP023 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP024 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP025 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP026 | 0 | 1 | 0.08 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP027 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP028 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP029 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP030 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP031 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP032 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP033 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP034 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP035 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP036 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP037 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP038 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP039 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP040 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP041 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP042 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP043 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP044 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP045 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP046 | 0 | 1 | 0.32 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP047 | 0 | 1 | 0.27 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP048 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP049 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP050 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP051 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP052 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP053 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP054 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP055 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP056 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP057 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP058 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP059 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP060 | 0 | 1 | 0.48 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP061 | 0 | 1 | 0.45 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP062 | 0 | 1 | 0.44 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP063 | 0 | 1 | 0.43 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP064 | 0 | 1 | 0.42 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP065 | 0 | 1 | 0.59 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP066 | 0 | 1 | 0.61 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP067 | 0 | 1 | 0.38 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP068 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP069 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP070 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP071 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP072 | 0 | 1 | 0.66 | 0.47 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP073 | 0 | 1 | 0.31 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP074 | 0 | 1 | 0.32 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP075 | 0 | 1 | 0.34 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP076 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP077 | 0 | 1 | 0.32 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP078 | 0 | 1 | 0.30 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP079 | 0 | 1 | 0.69 | 0.46 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP080 | 0 | 1 | 0.30 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP081 | 0 | 1 | 0.28 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP082 | 0 | 1 | 0.71 | 0.45 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP083 | 0 | 1 | 0.27 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP084 | 0 | 1 | 0.29 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP085 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP086 | 0 | 1 | 0.27 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP087 | 0 | 1 | 0.73 | 0.45 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP088 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP089 | 0 | 1 | 0.25 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP090 | 0 | 1 | 0.25 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP091 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP092 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP093 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP094 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP095 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP096 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP097 | 0 | 1 | 0.24 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP098 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP099 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP100 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP101 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP102 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP103 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP104 | 0 | 1 | 0.22 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP105 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP106 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP107 | 0 | 1 | 0.21 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP108 | 0 | 1 | 0.21 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP109 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP110 | 0 | 1 | 0.21 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP111 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP112 | 0 | 1 | 0.19 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP113 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP114 | 0 | 1 | 0.16 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP115 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP116 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP117 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP118 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP119 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP120 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP121 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP122 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP123 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP124 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP125 | 0 | 1 | 0.16 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP126 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP127 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP128 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP129 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP130 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP131 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP132 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP133 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP134 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP135 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP136 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP137 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP138 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP139 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP140 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP141 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP142 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP143 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP144 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP145 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP146 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP147 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP148 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP149 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP150 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP151 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP152 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP153 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP154 | 0 | 1 | 0.04 | 0.19 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP155 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP156 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP157 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP158 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP159 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP160 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP161 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP162 | 0 | 1 | 0.50 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP163 | 0 | 1 | 0.48 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP164 | 0 | 1 | 0.63 | 0.48 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP165 | 0 | 1 | 0.35 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP166 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP167 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP168 | 0 | 1 | 0.67 | 0.47 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP169 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP170 | 0 | 1 | 0.18 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP171 | 0 | 1 | 0.17 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP172 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP173 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP174 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP175 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP176 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP177 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP178 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP179 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP180 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP181 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP182 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP183 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP184 | 0 | 1 | 0.08 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP185 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP186 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP187 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP188 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP189 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP190 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP191 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP192 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP193 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP194 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP195 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP196 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP197 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP198 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP199 | 0 | 1 | 0.05 | 0.21 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP200 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP201 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP202 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP203 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP204 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP205 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP206 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP207 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP208 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| MolWeight | 0 | 1 | 201.65 | 97.91 | 46.09 | 122.60 | 179.23 | 264.34 | 665.81 | ▇▆▂▁▁ |
| NumAtoms | 0 | 1 | 25.51 | 12.61 | 5.00 | 17.00 | 22.00 | 31.00 | 94.00 | ▇▆▂▁▁ |
| NumNonHAtoms | 0 | 1 | 13.16 | 6.50 | 2.00 | 8.00 | 12.00 | 17.00 | 47.00 | ▇▆▂▁▁ |
| NumBonds | 0 | 1 | 25.91 | 13.48 | 4.00 | 17.00 | 23.00 | 31.50 | 97.00 | ▇▇▂▁▁ |
| NumNonHBonds | 0 | 1 | 13.56 | 7.57 | 1.00 | 8.00 | 12.00 | 18.00 | 50.00 | ▇▇▂▁▁ |
| NumMultBonds | 0 | 1 | 6.15 | 5.17 | 0.00 | 1.00 | 6.00 | 10.00 | 25.00 | ▇▆▃▁▁ |
| NumRotBonds | 0 | 1 | 2.25 | 2.41 | 0.00 | 0.00 | 2.00 | 3.50 | 16.00 | ▇▂▁▁▁ |
| NumDblBonds | 0 | 1 | 1.01 | 1.21 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▂▁▁▁ |
| NumAromaticBonds | 0 | 1 | 5.12 | 5.26 | 0.00 | 0.00 | 6.00 | 6.00 | 25.00 | ▇▆▃▁▁ |
| NumHydrogen | 0 | 1 | 12.35 | 7.32 | 0.00 | 7.00 | 11.00 | 16.00 | 47.00 | ▇▇▂▁▁ |
| NumCarbon | 0 | 1 | 9.89 | 5.29 | 1.00 | 6.00 | 9.00 | 12.00 | 33.00 | ▇▇▃▁▁ |
| NumNitrogen | 0 | 1 | 0.81 | 1.19 | 0.00 | 0.00 | 0.00 | 1.00 | 6.00 | ▇▂▁▁▁ |
| NumOxygen | 0 | 1 | 1.57 | 1.73 | 0.00 | 0.00 | 1.00 | 2.00 | 13.00 | ▇▂▁▁▁ |
| NumSulfer | 0 | 1 | 0.16 | 0.49 | 0.00 | 0.00 | 0.00 | 0.00 | 4.00 | ▇▁▁▁▁ |
| NumChlorine | 0 | 1 | 0.56 | 1.40 | 0.00 | 0.00 | 0.00 | 0.00 | 10.00 | ▇▁▁▁▁ |
| NumHalogen | 0 | 1 | 0.70 | 1.47 | 0.00 | 0.00 | 0.00 | 1.00 | 10.00 | ▇▁▁▁▁ |
| NumRings | 0 | 1 | 1.40 | 1.30 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▃▂▁▁ |
| HydrophilicFactor | 0 | 1 | -0.02 | 1.13 | -0.98 | -0.76 | -0.31 | 0.31 | 13.48 | ▇▁▁▁▁ |
| SurfaceArea1 | 0 | 1 | 36.46 | 35.29 | 0.00 | 9.23 | 29.10 | 53.28 | 331.94 | ▇▂▁▁▁ |
| SurfaceArea2 | 0 | 1 | 40.23 | 38.12 | 0.00 | 10.63 | 33.12 | 60.66 | 331.94 | ▇▂▁▁▁ |
##################################
# Identifying columns with low variance
###################################
DPA_LowVariance <- nearZeroVar(DPA,
freqCut = 95/5,
uniqueCut = 10,
saveMetrics= TRUE)
(DPA_LowVariance[DPA_LowVariance$nzv,])## freqRatio percentUnique zeroVar nzv
## FP154 25.41667 0.2103049 FALSE TRUE
## FP199 20.13333 0.2103049 FALSE TRUE
## FP200 19.23404 0.2103049 FALSE TRUEif ((nrow(DPA_LowVariance[DPA_LowVariance$nzv,]))==0){
print("No low variance predictors noted.")
} else {
print(paste0("Low variance observed for ",
(nrow(DPA_LowVariance[DPA_LowVariance$nzv,])),
" numeric variable(s) with First.Second.Mode.Ratio>4 and Unique.Count.Ratio<0.10."))
DPA_LowVarianceForRemoval <- (nrow(DPA_LowVariance[DPA_LowVariance$nzv,]))
print(paste0("Low variance can be resolved by removing ",
(nrow(DPA_LowVariance[DPA_LowVariance$nzv,])),
" numeric variable(s)."))
for (j in 1:DPA_LowVarianceForRemoval) {
DPA_LowVarianceRemovedVariable <- rownames(DPA_LowVariance[DPA_LowVariance$nzv,])[j]
print(paste0("Variable ",
j,
" for removal: ",
DPA_LowVarianceRemovedVariable))
}
DPA %>%
skim() %>%
dplyr::filter(skim_variable %in% rownames(DPA_LowVariance[DPA_LowVariance$nzv,]))
##################################
# Filtering out columns with low variance
#################################
DPA_ExcludedLowVariance <- DPA[,!names(DPA) %in% rownames(DPA_LowVariance[DPA_LowVariance$nzv,])]
##################################
# Gathering descriptive statistics
##################################
(DPA_ExcludedLowVariance_Skimmed <- skim(DPA_ExcludedLowVariance))
}## [1] "Low variance observed for 3 numeric variable(s) with First.Second.Mode.Ratio>4 and Unique.Count.Ratio<0.10."
## [1] "Low variance can be resolved by removing 3 numeric variable(s)."
## [1] "Variable 1 for removal: FP154"
## [1] "Variable 2 for removal: FP199"
## [1] "Variable 3 for removal: FP200"| Name | DPA_ExcludedLowVariance |
| Number of rows | 951 |
| Number of columns | 226 |
| _______________________ | |
| Column type frequency: | |
| factor | 1 |
| numeric | 225 |
| ________________________ | |
| Group variables | None |
Variable type: factor
| skim_variable | n_missing | complete_rate | ordered | n_unique | top_counts |
|---|---|---|---|---|---|
| Log_Solubility_Class | 0 | 1 | FALSE | 3 | Low: 427, Mid: 283, Hig: 241 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| FP001 | 0 | 1 | 0.49 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP002 | 0 | 1 | 0.54 | 0.50 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP003 | 0 | 1 | 0.44 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP004 | 0 | 1 | 0.58 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP005 | 0 | 1 | 0.58 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP006 | 0 | 1 | 0.40 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP007 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP008 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP009 | 0 | 1 | 0.28 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP010 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP011 | 0 | 1 | 0.21 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP012 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP013 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP014 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP015 | 0 | 1 | 0.86 | 0.35 | 0.00 | 1.00 | 1.00 | 1.00 | 1.00 | ▁▁▁▁▇ |
| FP016 | 0 | 1 | 0.15 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP017 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP018 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP019 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP020 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP021 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP022 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP023 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP024 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP025 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP026 | 0 | 1 | 0.08 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP027 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP028 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP029 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP030 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP031 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP032 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP033 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP034 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP035 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP036 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP037 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP038 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP039 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP040 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP041 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP042 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP043 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP044 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP045 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP046 | 0 | 1 | 0.32 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP047 | 0 | 1 | 0.27 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP048 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP049 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP050 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP051 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP052 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP053 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP054 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP055 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP056 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP057 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP058 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP059 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP060 | 0 | 1 | 0.48 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP061 | 0 | 1 | 0.45 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP062 | 0 | 1 | 0.44 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP063 | 0 | 1 | 0.43 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP064 | 0 | 1 | 0.42 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP065 | 0 | 1 | 0.59 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP066 | 0 | 1 | 0.61 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP067 | 0 | 1 | 0.38 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP068 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP069 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP070 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP071 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP072 | 0 | 1 | 0.66 | 0.47 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP073 | 0 | 1 | 0.31 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP074 | 0 | 1 | 0.32 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP075 | 0 | 1 | 0.34 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP076 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP077 | 0 | 1 | 0.32 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP078 | 0 | 1 | 0.30 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP079 | 0 | 1 | 0.69 | 0.46 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP080 | 0 | 1 | 0.30 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP081 | 0 | 1 | 0.28 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP082 | 0 | 1 | 0.71 | 0.45 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP083 | 0 | 1 | 0.27 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP084 | 0 | 1 | 0.29 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP085 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP086 | 0 | 1 | 0.27 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP087 | 0 | 1 | 0.73 | 0.45 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP088 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP089 | 0 | 1 | 0.25 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP090 | 0 | 1 | 0.25 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP091 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP092 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP093 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP094 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP095 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP096 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP097 | 0 | 1 | 0.24 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP098 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP099 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP100 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP101 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP102 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP103 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP104 | 0 | 1 | 0.22 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP105 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP106 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP107 | 0 | 1 | 0.21 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP108 | 0 | 1 | 0.21 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP109 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP110 | 0 | 1 | 0.21 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP111 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP112 | 0 | 1 | 0.19 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP113 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP114 | 0 | 1 | 0.16 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP115 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP116 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP117 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP118 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP119 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP120 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP121 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP122 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP123 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP124 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP125 | 0 | 1 | 0.16 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP126 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP127 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP128 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP129 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP130 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP131 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP132 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP133 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP134 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP135 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP136 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP137 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP138 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP139 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP140 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP141 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP142 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP143 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP144 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP145 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP146 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP147 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP148 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP149 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP150 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP151 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP152 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP153 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP155 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP156 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP157 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP158 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP159 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP160 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP161 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP162 | 0 | 1 | 0.50 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP163 | 0 | 1 | 0.48 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP164 | 0 | 1 | 0.63 | 0.48 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP165 | 0 | 1 | 0.35 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP166 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP167 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP168 | 0 | 1 | 0.67 | 0.47 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP169 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP170 | 0 | 1 | 0.18 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP171 | 0 | 1 | 0.17 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP172 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP173 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP174 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP175 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP176 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP177 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP178 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP179 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP180 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP181 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP182 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP183 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP184 | 0 | 1 | 0.08 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP185 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP186 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP187 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP188 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP189 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP190 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP191 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP192 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP193 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP194 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP195 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP196 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP197 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP198 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP201 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP202 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP203 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP204 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP205 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP206 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP207 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP208 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| MolWeight | 0 | 1 | 201.65 | 97.91 | 46.09 | 122.60 | 179.23 | 264.34 | 665.81 | ▇▆▂▁▁ |
| NumAtoms | 0 | 1 | 25.51 | 12.61 | 5.00 | 17.00 | 22.00 | 31.00 | 94.00 | ▇▆▂▁▁ |
| NumNonHAtoms | 0 | 1 | 13.16 | 6.50 | 2.00 | 8.00 | 12.00 | 17.00 | 47.00 | ▇▆▂▁▁ |
| NumBonds | 0 | 1 | 25.91 | 13.48 | 4.00 | 17.00 | 23.00 | 31.50 | 97.00 | ▇▇▂▁▁ |
| NumNonHBonds | 0 | 1 | 13.56 | 7.57 | 1.00 | 8.00 | 12.00 | 18.00 | 50.00 | ▇▇▂▁▁ |
| NumMultBonds | 0 | 1 | 6.15 | 5.17 | 0.00 | 1.00 | 6.00 | 10.00 | 25.00 | ▇▆▃▁▁ |
| NumRotBonds | 0 | 1 | 2.25 | 2.41 | 0.00 | 0.00 | 2.00 | 3.50 | 16.00 | ▇▂▁▁▁ |
| NumDblBonds | 0 | 1 | 1.01 | 1.21 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▂▁▁▁ |
| NumAromaticBonds | 0 | 1 | 5.12 | 5.26 | 0.00 | 0.00 | 6.00 | 6.00 | 25.00 | ▇▆▃▁▁ |
| NumHydrogen | 0 | 1 | 12.35 | 7.32 | 0.00 | 7.00 | 11.00 | 16.00 | 47.00 | ▇▇▂▁▁ |
| NumCarbon | 0 | 1 | 9.89 | 5.29 | 1.00 | 6.00 | 9.00 | 12.00 | 33.00 | ▇▇▃▁▁ |
| NumNitrogen | 0 | 1 | 0.81 | 1.19 | 0.00 | 0.00 | 0.00 | 1.00 | 6.00 | ▇▂▁▁▁ |
| NumOxygen | 0 | 1 | 1.57 | 1.73 | 0.00 | 0.00 | 1.00 | 2.00 | 13.00 | ▇▂▁▁▁ |
| NumSulfer | 0 | 1 | 0.16 | 0.49 | 0.00 | 0.00 | 0.00 | 0.00 | 4.00 | ▇▁▁▁▁ |
| NumChlorine | 0 | 1 | 0.56 | 1.40 | 0.00 | 0.00 | 0.00 | 0.00 | 10.00 | ▇▁▁▁▁ |
| NumHalogen | 0 | 1 | 0.70 | 1.47 | 0.00 | 0.00 | 0.00 | 1.00 | 10.00 | ▇▁▁▁▁ |
| NumRings | 0 | 1 | 1.40 | 1.30 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▃▂▁▁ |
| HydrophilicFactor | 0 | 1 | -0.02 | 1.13 | -0.98 | -0.76 | -0.31 | 0.31 | 13.48 | ▇▁▁▁▁ |
| SurfaceArea1 | 0 | 1 | 36.46 | 35.29 | 0.00 | 9.23 | 29.10 | 53.28 | 331.94 | ▇▂▁▁▁ |
| SurfaceArea2 | 0 | 1 | 40.23 | 38.12 | 0.00 | 10.63 | 33.12 | 60.66 | 331.94 | ▇▂▁▁▁ |
###################################
# Verifying the data dimensions
###################################
dim(DPA_ExcludedLowVariance)## [1] 951 2261.3.3 Collinearity
[A] High correlation > 95% were noted for 2 variable pairs as confirmed using the preprocessing summaries from the caret and lares packages.
[A.1] NumNonHAtoms and NumNonHBonds variables (numeric)
[A.2] NumMultBonds and NumAromaticBonds variables (numeric)
[A.3] NumAtoms and NumBonds variables (numeric)
Code Chunk | Output
##################################
# Loading dataset
##################################
DPA <- Solubility_Train
##################################
# Listing all predictors
##################################
DPA.Predictors <- DPA[,!names(DPA) %in% c("Log_Solubility_Class")]
##################################
# Listing all numeric predictors
##################################
DPA.Predictors.Numeric <- DPA.Predictors[,-(grep("FP", names(DPA.Predictors)))]
##################################
# Visualizing pairwise correlation between predictors
##################################
DPA_CorrelationTest <- cor.mtest(DPA.Predictors.Numeric,
method = "pearson",
conf.level = .95)
corrplot(cor(DPA.Predictors.Numeric,
method = "pearson",
use="pairwise.complete.obs"),
method = "circle",
type = "upper",
order = "original",
tl.col = "black",
tl.cex = 0.75,
tl.srt = 90,
sig.level = 0.05,
p.mat = DPA_CorrelationTest$p,
insig = "blank")
##################################
# Identifying the highly correlated variables
##################################
DPA_Correlation <- cor(DPA.Predictors.Numeric,
method = "pearson",
use="pairwise.complete.obs")
(DPA_HighlyCorrelatedCount <- sum(abs(DPA_Correlation[upper.tri(DPA_Correlation)]) > 0.95))## [1] 3if (DPA_HighlyCorrelatedCount == 0) {
print("No highly correlated predictors noted.")
} else {
print(paste0("High correlation observed for ",
(DPA_HighlyCorrelatedCount),
" pairs of numeric variable(s) with Correlation.Coefficient>0.95."))
(DPA_HighlyCorrelatedPairs <- corr_cross(DPA.Predictors.Numeric,
max_pvalue = 0.05,
top = DPA_HighlyCorrelatedCount,
rm.na = TRUE,
grid = FALSE
))
}## [1] "High correlation observed for 3 pairs of numeric variable(s) with Correlation.Coefficient>0.95."
if (DPA_HighlyCorrelatedCount > 0) {
DPA_HighlyCorrelated <- findCorrelation(DPA_Correlation, cutoff = 0.95)
(DPA_HighlyCorrelatedForRemoval <- length(DPA_HighlyCorrelated))
print(paste0("High correlation can be resolved by removing ",
(DPA_HighlyCorrelatedForRemoval),
" numeric variable(s)."))
for (j in 1:DPA_HighlyCorrelatedForRemoval) {
DPA_HighlyCorrelatedRemovedVariable <- colnames(DPA.Predictors.Numeric)[DPA_HighlyCorrelated[j]]
print(paste0("Variable ",
j,
" for removal: ",
DPA_HighlyCorrelatedRemovedVariable))
}
##################################
# Filtering out columns with high correlation
#################################
DPA_ExcludedHighCorrelation <- DPA[,-DPA_HighlyCorrelated]
##################################
# Gathering descriptive statistics
##################################
(DPA_ExcludedHighCorrelation_Skimmed <- skim(DPA_ExcludedHighCorrelation))
}## [1] "High correlation can be resolved by removing 3 numeric variable(s)."
## [1] "Variable 1 for removal: NumNonHAtoms"
## [1] "Variable 2 for removal: NumBonds"
## [1] "Variable 3 for removal: NumAromaticBonds"| Name | DPA_ExcludedHighCorrelati… |
| Number of rows | 951 |
| Number of columns | 226 |
| _______________________ | |
| Column type frequency: | |
| factor | 1 |
| numeric | 225 |
| ________________________ | |
| Group variables | None |
Variable type: factor
| skim_variable | n_missing | complete_rate | ordered | n_unique | top_counts |
|---|---|---|---|---|---|
| Log_Solubility_Class | 0 | 1 | FALSE | 3 | Low: 427, Mid: 283, Hig: 241 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| FP001 | 0 | 1 | 0.49 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP002 | 0 | 1 | 0.54 | 0.50 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP005 | 0 | 1 | 0.58 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP006 | 0 | 1 | 0.40 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP007 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP008 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP010 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP011 | 0 | 1 | 0.21 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP012 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP013 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP014 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP015 | 0 | 1 | 0.86 | 0.35 | 0.00 | 1.00 | 1.00 | 1.00 | 1.00 | ▁▁▁▁▇ |
| FP016 | 0 | 1 | 0.15 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP017 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP018 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP019 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP020 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP021 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP022 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP023 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP024 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP025 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP026 | 0 | 1 | 0.08 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP027 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP028 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP029 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP030 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP031 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP032 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP033 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP034 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP035 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP036 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP037 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP038 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP039 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP040 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP041 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP042 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP043 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP044 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP045 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP046 | 0 | 1 | 0.32 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP047 | 0 | 1 | 0.27 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP048 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP049 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP050 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP051 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP052 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP053 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP054 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP055 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP056 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP057 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP058 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP059 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP060 | 0 | 1 | 0.48 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP061 | 0 | 1 | 0.45 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP062 | 0 | 1 | 0.44 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP063 | 0 | 1 | 0.43 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP064 | 0 | 1 | 0.42 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP065 | 0 | 1 | 0.59 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP066 | 0 | 1 | 0.61 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP067 | 0 | 1 | 0.38 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP068 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP069 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP070 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP071 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP072 | 0 | 1 | 0.66 | 0.47 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP073 | 0 | 1 | 0.31 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP074 | 0 | 1 | 0.32 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP075 | 0 | 1 | 0.34 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP076 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP077 | 0 | 1 | 0.32 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP078 | 0 | 1 | 0.30 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP079 | 0 | 1 | 0.69 | 0.46 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP080 | 0 | 1 | 0.30 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP081 | 0 | 1 | 0.28 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP082 | 0 | 1 | 0.71 | 0.45 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP083 | 0 | 1 | 0.27 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP084 | 0 | 1 | 0.29 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP085 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP086 | 0 | 1 | 0.27 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP087 | 0 | 1 | 0.73 | 0.45 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP088 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP089 | 0 | 1 | 0.25 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP090 | 0 | 1 | 0.25 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP091 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP092 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP093 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP094 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP095 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP096 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP097 | 0 | 1 | 0.24 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP098 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP099 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP100 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP101 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP102 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP103 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP104 | 0 | 1 | 0.22 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP105 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP106 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP107 | 0 | 1 | 0.21 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP108 | 0 | 1 | 0.21 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP109 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP110 | 0 | 1 | 0.21 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP111 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP112 | 0 | 1 | 0.19 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP113 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP114 | 0 | 1 | 0.16 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP115 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP116 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP117 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP118 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP119 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP120 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP121 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP122 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP123 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP124 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP125 | 0 | 1 | 0.16 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP126 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP127 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP128 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP129 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP130 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP131 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP132 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP133 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP134 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP135 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP136 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP137 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP138 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP139 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP140 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP141 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP142 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP143 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP144 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP145 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP146 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP147 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP148 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP149 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP150 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP151 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP152 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP153 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP154 | 0 | 1 | 0.04 | 0.19 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP155 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP156 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP157 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP158 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP159 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP160 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP161 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP162 | 0 | 1 | 0.50 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP163 | 0 | 1 | 0.48 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP164 | 0 | 1 | 0.63 | 0.48 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP165 | 0 | 1 | 0.35 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP166 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP167 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP168 | 0 | 1 | 0.67 | 0.47 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP169 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP170 | 0 | 1 | 0.18 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP171 | 0 | 1 | 0.17 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP172 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP173 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP174 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP175 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP176 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP177 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP178 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP179 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP180 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP181 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP182 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP183 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP184 | 0 | 1 | 0.08 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP185 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP186 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP187 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP188 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP189 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP190 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP191 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP192 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP193 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP194 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP195 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP196 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP197 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP198 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP199 | 0 | 1 | 0.05 | 0.21 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP200 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP201 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP202 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP203 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP204 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP205 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP206 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP207 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP208 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| MolWeight | 0 | 1 | 201.65 | 97.91 | 46.09 | 122.60 | 179.23 | 264.34 | 665.81 | ▇▆▂▁▁ |
| NumAtoms | 0 | 1 | 25.51 | 12.61 | 5.00 | 17.00 | 22.00 | 31.00 | 94.00 | ▇▆▂▁▁ |
| NumNonHAtoms | 0 | 1 | 13.16 | 6.50 | 2.00 | 8.00 | 12.00 | 17.00 | 47.00 | ▇▆▂▁▁ |
| NumBonds | 0 | 1 | 25.91 | 13.48 | 4.00 | 17.00 | 23.00 | 31.50 | 97.00 | ▇▇▂▁▁ |
| NumNonHBonds | 0 | 1 | 13.56 | 7.57 | 1.00 | 8.00 | 12.00 | 18.00 | 50.00 | ▇▇▂▁▁ |
| NumMultBonds | 0 | 1 | 6.15 | 5.17 | 0.00 | 1.00 | 6.00 | 10.00 | 25.00 | ▇▆▃▁▁ |
| NumRotBonds | 0 | 1 | 2.25 | 2.41 | 0.00 | 0.00 | 2.00 | 3.50 | 16.00 | ▇▂▁▁▁ |
| NumDblBonds | 0 | 1 | 1.01 | 1.21 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▂▁▁▁ |
| NumAromaticBonds | 0 | 1 | 5.12 | 5.26 | 0.00 | 0.00 | 6.00 | 6.00 | 25.00 | ▇▆▃▁▁ |
| NumHydrogen | 0 | 1 | 12.35 | 7.32 | 0.00 | 7.00 | 11.00 | 16.00 | 47.00 | ▇▇▂▁▁ |
| NumCarbon | 0 | 1 | 9.89 | 5.29 | 1.00 | 6.00 | 9.00 | 12.00 | 33.00 | ▇▇▃▁▁ |
| NumNitrogen | 0 | 1 | 0.81 | 1.19 | 0.00 | 0.00 | 0.00 | 1.00 | 6.00 | ▇▂▁▁▁ |
| NumOxygen | 0 | 1 | 1.57 | 1.73 | 0.00 | 0.00 | 1.00 | 2.00 | 13.00 | ▇▂▁▁▁ |
| NumSulfer | 0 | 1 | 0.16 | 0.49 | 0.00 | 0.00 | 0.00 | 0.00 | 4.00 | ▇▁▁▁▁ |
| NumChlorine | 0 | 1 | 0.56 | 1.40 | 0.00 | 0.00 | 0.00 | 0.00 | 10.00 | ▇▁▁▁▁ |
| NumHalogen | 0 | 1 | 0.70 | 1.47 | 0.00 | 0.00 | 0.00 | 1.00 | 10.00 | ▇▁▁▁▁ |
| NumRings | 0 | 1 | 1.40 | 1.30 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▃▂▁▁ |
| HydrophilicFactor | 0 | 1 | -0.02 | 1.13 | -0.98 | -0.76 | -0.31 | 0.31 | 13.48 | ▇▁▁▁▁ |
| SurfaceArea1 | 0 | 1 | 36.46 | 35.29 | 0.00 | 9.23 | 29.10 | 53.28 | 331.94 | ▇▂▁▁▁ |
| SurfaceArea2 | 0 | 1 | 40.23 | 38.12 | 0.00 | 10.63 | 33.12 | 60.66 | 331.94 | ▇▂▁▁▁ |
###################################
# Verifying the data dimensions
###################################
dim(DPA_ExcludedHighCorrelation)## [1] 951 2261.3.4 Linear Dependencies
[A] Linear dependencies noted for 2 subsets of variables using the preprocessing summary from the caret package applying the findLinearCombos method which utilizes the QR decomposition of a matrix to enumerate sets of linear combinations (if they exist).
[B] Subset 1
[B.1] NumNonHBonds variable (numeric)
[B.2] NumAtoms variable (numeric)
[B.3] NumNonHAtoms variable (numeric)
[B.3] NumBonds variable (numeric)
[C] Subset 2
[C.1] NumHydrogen variable (numeric)
[C.2] NumAtoms variable (numeric)
[C.3] NumNonHAtoms variable (numeric)
Code Chunk | Output
##################################
# Loading dataset
##################################
DPA <- Solubility_Train
##################################
# Listing all predictors
##################################
DPA.Predictors <- DPA[,!names(DPA) %in% c("Log_Solubility_Class")]
##################################
# Listing all numeric predictors
##################################
DPA.Predictors.Numeric <- DPA.Predictors[,sapply(DPA.Predictors, is.numeric)]
##################################
# Identifying the linearly dependent variables
##################################
DPA_LinearlyDependent <- findLinearCombos(DPA.Predictors.Numeric)
(DPA_LinearlyDependentCount <- length(DPA_LinearlyDependent$linearCombos))## [1] 2if (DPA_LinearlyDependentCount == 0) {
print("No linearly dependent predictors noted.")
} else {
print(paste0("Linear dependency observed for ",
(DPA_LinearlyDependentCount),
" subset(s) of numeric variable(s)."))
for (i in 1:DPA_LinearlyDependentCount) {
DPA_LinearlyDependentSubset <- colnames(DPA.Predictors.Numeric)[DPA_LinearlyDependent$linearCombos[[i]]]
print(paste0("Linear dependent variable(s) for subset ",
i,
" include: ",
DPA_LinearlyDependentSubset))
}
}## [1] "Linear dependency observed for 2 subset(s) of numeric variable(s)."
## [1] "Linear dependent variable(s) for subset 1 include: NumNonHBonds"
## [2] "Linear dependent variable(s) for subset 1 include: NumAtoms"
## [3] "Linear dependent variable(s) for subset 1 include: NumNonHAtoms"
## [4] "Linear dependent variable(s) for subset 1 include: NumBonds"
## [1] "Linear dependent variable(s) for subset 2 include: NumHydrogen"
## [2] "Linear dependent variable(s) for subset 2 include: NumAtoms"
## [3] "Linear dependent variable(s) for subset 2 include: NumNonHAtoms"##################################
# Identifying the linearly dependent variables for removal
##################################
if (DPA_LinearlyDependentCount > 0) {
DPA_LinearlyDependent <- findLinearCombos(DPA.Predictors.Numeric)
DPA_LinearlyDependentForRemoval <- length(DPA_LinearlyDependent$remove)
print(paste0("Linear dependency can be resolved by removing ",
(DPA_LinearlyDependentForRemoval),
" numeric variable(s)."))
for (j in 1:DPA_LinearlyDependentForRemoval) {
DPA_LinearlyDependentRemovedVariable <- colnames(DPA.Predictors.Numeric)[DPA_LinearlyDependent$remove[j]]
print(paste0("Variable ",
j,
" for removal: ",
DPA_LinearlyDependentRemovedVariable))
}
##################################
# Filtering out columns with linear dependency
#################################
DPA_ExcludedLinearlyDependent <- DPA[,-DPA_LinearlyDependent$remove]
##################################
# Gathering descriptive statistics
##################################
(DPA_ExcludedLinearlyDependent_Skimmed <- skim(DPA_ExcludedLinearlyDependent))
}## [1] "Linear dependency can be resolved by removing 2 numeric variable(s)."
## [1] "Variable 1 for removal: NumNonHBonds"
## [1] "Variable 2 for removal: NumHydrogen"| Name | DPA_ExcludedLinearlyDepen… |
| Number of rows | 951 |
| Number of columns | 227 |
| _______________________ | |
| Column type frequency: | |
| factor | 1 |
| numeric | 226 |
| ________________________ | |
| Group variables | None |
Variable type: factor
| skim_variable | n_missing | complete_rate | ordered | n_unique | top_counts |
|---|---|---|---|---|---|
| Log_Solubility_Class | 0 | 1 | FALSE | 3 | Low: 427, Mid: 283, Hig: 241 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| FP001 | 0 | 1 | 0.49 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP002 | 0 | 1 | 0.54 | 0.50 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP003 | 0 | 1 | 0.44 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP004 | 0 | 1 | 0.58 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP005 | 0 | 1 | 0.58 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP006 | 0 | 1 | 0.40 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP007 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP008 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP009 | 0 | 1 | 0.28 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP010 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP011 | 0 | 1 | 0.21 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP012 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP013 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP014 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP015 | 0 | 1 | 0.86 | 0.35 | 0.00 | 1.00 | 1.00 | 1.00 | 1.00 | ▁▁▁▁▇ |
| FP016 | 0 | 1 | 0.15 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP017 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP018 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP019 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP020 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP021 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP022 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP023 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP024 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP025 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP026 | 0 | 1 | 0.08 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP027 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP028 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP029 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP030 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP031 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP032 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP033 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP034 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP035 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP036 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP037 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP038 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP039 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP040 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP041 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP042 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP043 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP044 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP045 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP046 | 0 | 1 | 0.32 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP047 | 0 | 1 | 0.27 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP048 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP049 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP050 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP051 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP052 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP053 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP054 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP055 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP056 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP057 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP058 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP059 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP060 | 0 | 1 | 0.48 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP061 | 0 | 1 | 0.45 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP062 | 0 | 1 | 0.44 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP063 | 0 | 1 | 0.43 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP064 | 0 | 1 | 0.42 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▆ |
| FP065 | 0 | 1 | 0.59 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▆▁▁▁▇ |
| FP066 | 0 | 1 | 0.61 | 0.49 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP067 | 0 | 1 | 0.38 | 0.49 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP068 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP069 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP070 | 0 | 1 | 0.36 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP071 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP072 | 0 | 1 | 0.66 | 0.47 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP073 | 0 | 1 | 0.31 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP074 | 0 | 1 | 0.32 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP075 | 0 | 1 | 0.34 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP076 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP077 | 0 | 1 | 0.32 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP078 | 0 | 1 | 0.30 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP079 | 0 | 1 | 0.69 | 0.46 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP080 | 0 | 1 | 0.30 | 0.46 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP081 | 0 | 1 | 0.28 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP082 | 0 | 1 | 0.71 | 0.45 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP083 | 0 | 1 | 0.27 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP084 | 0 | 1 | 0.29 | 0.45 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP085 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP086 | 0 | 1 | 0.27 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP087 | 0 | 1 | 0.73 | 0.45 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▃▁▁▁▇ |
| FP088 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP089 | 0 | 1 | 0.25 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP090 | 0 | 1 | 0.25 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP091 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP092 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP093 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP094 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP095 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP096 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP097 | 0 | 1 | 0.24 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP098 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP099 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP100 | 0 | 1 | 0.23 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP101 | 0 | 1 | 0.24 | 0.43 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP102 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP103 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP104 | 0 | 1 | 0.22 | 0.42 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP105 | 0 | 1 | 0.22 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP106 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP107 | 0 | 1 | 0.21 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP108 | 0 | 1 | 0.21 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP109 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP110 | 0 | 1 | 0.21 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP111 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP112 | 0 | 1 | 0.19 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP113 | 0 | 1 | 0.20 | 0.40 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP114 | 0 | 1 | 0.16 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP115 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP116 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP117 | 0 | 1 | 0.18 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP118 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP119 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP120 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP121 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP122 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP123 | 0 | 1 | 0.17 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP124 | 0 | 1 | 0.16 | 0.37 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP125 | 0 | 1 | 0.16 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP126 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP127 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP128 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP129 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP130 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP131 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP132 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP133 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP134 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP135 | 0 | 1 | 0.13 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP136 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP137 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP138 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP139 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP140 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP141 | 0 | 1 | 0.12 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP142 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP143 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP144 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP145 | 0 | 1 | 0.10 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP146 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP147 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP148 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP149 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP150 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP151 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP152 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP153 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP154 | 0 | 1 | 0.04 | 0.19 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP155 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP156 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP157 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP158 | 0 | 1 | 0.05 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP159 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP160 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP161 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP162 | 0 | 1 | 0.50 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP163 | 0 | 1 | 0.48 | 0.50 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▇ |
| FP164 | 0 | 1 | 0.63 | 0.48 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP165 | 0 | 1 | 0.35 | 0.48 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▅ |
| FP166 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP167 | 0 | 1 | 0.33 | 0.47 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP168 | 0 | 1 | 0.67 | 0.47 | 0.00 | 0.00 | 1.00 | 1.00 | 1.00 | ▅▁▁▁▇ |
| FP169 | 0 | 1 | 0.19 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP170 | 0 | 1 | 0.18 | 0.39 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP171 | 0 | 1 | 0.17 | 0.38 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP172 | 0 | 1 | 0.15 | 0.36 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▂ |
| FP173 | 0 | 1 | 0.14 | 0.35 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP174 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP175 | 0 | 1 | 0.13 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP176 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP177 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP178 | 0 | 1 | 0.12 | 0.33 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP179 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP180 | 0 | 1 | 0.11 | 0.31 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP181 | 0 | 1 | 0.09 | 0.29 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP182 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP183 | 0 | 1 | 0.08 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP184 | 0 | 1 | 0.08 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP185 | 0 | 1 | 0.09 | 0.28 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP186 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP187 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP188 | 0 | 1 | 0.07 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP189 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP190 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP191 | 0 | 1 | 0.07 | 0.26 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP192 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP193 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP194 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP195 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP196 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP197 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP198 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP199 | 0 | 1 | 0.05 | 0.21 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP200 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP201 | 0 | 1 | 0.05 | 0.22 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP202 | 0 | 1 | 0.26 | 0.44 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | ▇▁▁▁▃ |
| FP203 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP204 | 0 | 1 | 0.10 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP205 | 0 | 1 | 0.08 | 0.27 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP206 | 0 | 1 | 0.06 | 0.24 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP207 | 0 | 1 | 0.06 | 0.23 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| FP208 | 0 | 1 | 0.11 | 0.32 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | ▇▁▁▁▁ |
| MolWeight | 0 | 1 | 201.65 | 97.91 | 46.09 | 122.60 | 179.23 | 264.34 | 665.81 | ▇▆▂▁▁ |
| NumAtoms | 0 | 1 | 25.51 | 12.61 | 5.00 | 17.00 | 22.00 | 31.00 | 94.00 | ▇▆▂▁▁ |
| NumNonHAtoms | 0 | 1 | 13.16 | 6.50 | 2.00 | 8.00 | 12.00 | 17.00 | 47.00 | ▇▆▂▁▁ |
| NumBonds | 0 | 1 | 25.91 | 13.48 | 4.00 | 17.00 | 23.00 | 31.50 | 97.00 | ▇▇▂▁▁ |
| NumMultBonds | 0 | 1 | 6.15 | 5.17 | 0.00 | 1.00 | 6.00 | 10.00 | 25.00 | ▇▆▃▁▁ |
| NumRotBonds | 0 | 1 | 2.25 | 2.41 | 0.00 | 0.00 | 2.00 | 3.50 | 16.00 | ▇▂▁▁▁ |
| NumDblBonds | 0 | 1 | 1.01 | 1.21 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▂▁▁▁ |
| NumAromaticBonds | 0 | 1 | 5.12 | 5.26 | 0.00 | 0.00 | 6.00 | 6.00 | 25.00 | ▇▆▃▁▁ |
| NumCarbon | 0 | 1 | 9.89 | 5.29 | 1.00 | 6.00 | 9.00 | 12.00 | 33.00 | ▇▇▃▁▁ |
| NumNitrogen | 0 | 1 | 0.81 | 1.19 | 0.00 | 0.00 | 0.00 | 1.00 | 6.00 | ▇▂▁▁▁ |
| NumOxygen | 0 | 1 | 1.57 | 1.73 | 0.00 | 0.00 | 1.00 | 2.00 | 13.00 | ▇▂▁▁▁ |
| NumSulfer | 0 | 1 | 0.16 | 0.49 | 0.00 | 0.00 | 0.00 | 0.00 | 4.00 | ▇▁▁▁▁ |
| NumChlorine | 0 | 1 | 0.56 | 1.40 | 0.00 | 0.00 | 0.00 | 0.00 | 10.00 | ▇▁▁▁▁ |
| NumHalogen | 0 | 1 | 0.70 | 1.47 | 0.00 | 0.00 | 0.00 | 1.00 | 10.00 | ▇▁▁▁▁ |
| NumRings | 0 | 1 | 1.40 | 1.30 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▃▂▁▁ |
| HydrophilicFactor | 0 | 1 | -0.02 | 1.13 | -0.98 | -0.76 | -0.31 | 0.31 | 13.48 | ▇▁▁▁▁ |
| SurfaceArea1 | 0 | 1 | 36.46 | 35.29 | 0.00 | 9.23 | 29.10 | 53.28 | 331.94 | ▇▂▁▁▁ |
| SurfaceArea2 | 0 | 1 | 40.23 | 38.12 | 0.00 | 10.63 | 33.12 | 60.66 | 331.94 | ▇▂▁▁▁ |
###################################
# Verifying the data dimensions
###################################
dim(DPA_ExcludedLinearlyDependent)## [1] 951 2271.3.5 Shape Transformation
[A] A number of numeric variables in the dataset were observed to be right-skewed which required shape transformation for data distribution stability. Considering that all numeric variables were strictly positive values, the BoxCox method from the caret package was used to transform their distributional shapes.
Code Chunk | Output
##################################
# Loading dataset
##################################
DPA <- Solubility_Train
##################################
# Listing all predictors
##################################
DPA.Predictors <- DPA[,!names(DPA) %in% c("Log_Solubility_Class")]
##################################
# Listing all numeric predictors
##################################
DPA.Predictors.Numeric <- DPA.Predictors[,-(grep("FP", names(DPA.Predictors)))]
##################################
# Applying a Box-Cox transformation
##################################
DPA_BoxCox <- preProcess(DPA.Predictors.Numeric, method = c("BoxCox"))
DPA_BoxCoxTransformed <- predict(DPA_BoxCox, DPA.Predictors.Numeric)
##################################
# Gathering descriptive statistics
##################################
(DPA_BoxCoxTransformedSkimmed <- skim(DPA_BoxCoxTransformed))| Name | DPA_BoxCoxTransformed |
| Number of rows | 951 |
| Number of columns | 20 |
| _______________________ | |
| Column type frequency: | |
| numeric | 20 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| MolWeight | 0 | 1 | 5.19 | 0.48 | 3.83 | 4.81 | 5.19 | 5.58 | 6.50 | ▁▆▇▆▁ |
| NumAtoms | 0 | 1 | 3.13 | 0.48 | 1.61 | 2.83 | 3.09 | 3.43 | 4.54 | ▁▃▇▃▁ |
| NumNonHAtoms | 0 | 1 | 2.46 | 0.50 | 0.69 | 2.08 | 2.48 | 2.83 | 3.85 | ▁▃▇▇▁ |
| NumBonds | 0 | 1 | 4.39 | 0.96 | 1.60 | 3.81 | 4.36 | 4.97 | 7.48 | ▁▅▇▃▁ |
| NumNonHBonds | 0 | 1 | 3.21 | 0.95 | 0.00 | 2.58 | 3.22 | 3.91 | 5.93 | ▁▃▇▆▁ |
| NumMultBonds | 0 | 1 | 6.15 | 5.17 | 0.00 | 1.00 | 6.00 | 10.00 | 25.00 | ▇▆▃▁▁ |
| NumRotBonds | 0 | 1 | 2.25 | 2.41 | 0.00 | 0.00 | 2.00 | 3.50 | 16.00 | ▇▂▁▁▁ |
| NumDblBonds | 0 | 1 | 1.01 | 1.21 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▂▁▁▁ |
| NumAromaticBonds | 0 | 1 | 5.12 | 5.26 | 0.00 | 0.00 | 6.00 | 6.00 | 25.00 | ▇▆▃▁▁ |
| NumHydrogen | 0 | 1 | 12.35 | 7.32 | 0.00 | 7.00 | 11.00 | 16.00 | 47.00 | ▇▇▂▁▁ |
| NumCarbon | 0 | 1 | 3.54 | 1.34 | 0.00 | 2.62 | 3.52 | 4.25 | 7.62 | ▂▇▇▃▁ |
| NumNitrogen | 0 | 1 | 0.81 | 1.19 | 0.00 | 0.00 | 0.00 | 1.00 | 6.00 | ▇▂▁▁▁ |
| NumOxygen | 0 | 1 | 1.57 | 1.73 | 0.00 | 0.00 | 1.00 | 2.00 | 13.00 | ▇▂▁▁▁ |
| NumSulfer | 0 | 1 | 0.16 | 0.49 | 0.00 | 0.00 | 0.00 | 0.00 | 4.00 | ▇▁▁▁▁ |
| NumChlorine | 0 | 1 | 0.56 | 1.40 | 0.00 | 0.00 | 0.00 | 0.00 | 10.00 | ▇▁▁▁▁ |
| NumHalogen | 0 | 1 | 0.70 | 1.47 | 0.00 | 0.00 | 0.00 | 1.00 | 10.00 | ▇▁▁▁▁ |
| NumRings | 0 | 1 | 1.40 | 1.30 | 0.00 | 0.00 | 1.00 | 2.00 | 7.00 | ▇▃▂▁▁ |
| HydrophilicFactor | 0 | 1 | -0.02 | 1.13 | -0.98 | -0.76 | -0.31 | 0.31 | 13.48 | ▇▁▁▁▁ |
| SurfaceArea1 | 0 | 1 | 36.46 | 35.29 | 0.00 | 9.23 | 29.10 | 53.28 | 331.94 | ▇▂▁▁▁ |
| SurfaceArea2 | 0 | 1 | 40.23 | 38.12 | 0.00 | 10.63 | 33.12 | 60.66 | 331.94 | ▇▂▁▁▁ |
###################################
# Verifying the data dimensions
###################################
dim(DPA_BoxCoxTransformed)## [1] 951 201.3.6 Centering and Scaling
[A] To maintain numerical stability during modelling, centering and scaling transformations were applied on the transformed numeric variables. The center method from the caret package was implemented which subtracts the average value of a numeric variable to all the values. As a result of centering, the variables had zero mean values. In addition, the scale method, also from the caret package, was applied which performs a center transformation with each value of the variable divided by its standard deviation. Scaling the data coerced the values to have a common standard deviation of one.
Code Chunk | Output
##################################
# Loading dataset
##################################
DPA <- Solubility_Train
##################################
# Listing all predictors
##################################
DPA.Predictors <- DPA[,!names(DPA) %in% c("Log_Solubility_Class")]
##################################
# Listing all numeric predictors
##################################
DPA.Predictors.Numeric <- DPA.Predictors[,-(grep("FP", names(DPA.Predictors)))]
##################################
# Applying a Box-Cox transformation
##################################
DPA_BoxCox <- preProcess(DPA.Predictors.Numeric, method = c("BoxCox"))
DPA_BoxCoxTransformed <- predict(DPA_BoxCox, DPA.Predictors.Numeric)
##################################
# Applying a center and scale data transformation
##################################
DPA.Predictors.Numeric_BoxCoxTransformed_CenteredScaled <- preProcess(DPA_BoxCoxTransformed, method = c("center","scale"))
DPA.Predictors.Numeric_BoxCoxTransformed_CenteredScaledTransformed <- predict(DPA.Predictors.Numeric_BoxCoxTransformed_CenteredScaled, DPA_BoxCoxTransformed)
##################################
# Gathering descriptive statistics
##################################
(DPA.Predictors.Numeric_BoxCoxTransformed_CenteredScaledTransformedSkimmed <- skim(DPA.Predictors.Numeric_BoxCoxTransformed_CenteredScaledTransformed))| Name | DPA.Predictors.Numeric_Bo… |
| Number of rows | 951 |
| Number of columns | 20 |
| _______________________ | |
| Column type frequency: | |
| numeric | 20 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| MolWeight | 0 | 1 | 0 | 1 | -2.84 | -0.80 | -0.01 | 0.80 | 2.72 | ▁▆▇▆▁ |
| NumAtoms | 0 | 1 | 0 | 1 | -3.16 | -0.61 | -0.07 | 0.64 | 2.95 | ▁▃▇▃▁ |
| NumNonHAtoms | 0 | 1 | 0 | 1 | -3.53 | -0.76 | 0.06 | 0.75 | 2.79 | ▁▃▇▇▁ |
| NumBonds | 0 | 1 | 0 | 1 | -2.92 | -0.61 | -0.04 | 0.60 | 3.23 | ▁▅▇▃▁ |
| NumNonHBonds | 0 | 1 | 0 | 1 | -3.38 | -0.67 | 0.01 | 0.74 | 2.86 | ▁▃▇▆▁ |
| NumMultBonds | 0 | 1 | 0 | 1 | -1.19 | -1.00 | -0.03 | 0.74 | 3.65 | ▇▇▃▁▁ |
| NumRotBonds | 0 | 1 | 0 | 1 | -0.93 | -0.93 | -0.10 | 0.52 | 5.71 | ▇▂▁▁▁ |
| NumDblBonds | 0 | 1 | 0 | 1 | -0.83 | -0.83 | -0.01 | 0.82 | 4.95 | ▇▂▁▁▁ |
| NumAromaticBonds | 0 | 1 | 0 | 1 | -0.97 | -0.97 | 0.17 | 0.17 | 3.78 | ▇▆▃▁▁ |
| NumHydrogen | 0 | 1 | 0 | 1 | -1.69 | -0.73 | -0.18 | 0.50 | 4.74 | ▇▇▂▁▁ |
| NumCarbon | 0 | 1 | 0 | 1 | -2.64 | -0.69 | -0.01 | 0.54 | 3.06 | ▂▇▇▃▁ |
| NumNitrogen | 0 | 1 | 0 | 1 | -0.69 | -0.69 | -0.69 | 0.16 | 4.37 | ▇▂▁▁▁ |
| NumOxygen | 0 | 1 | 0 | 1 | -0.91 | -0.91 | -0.33 | 0.25 | 6.61 | ▇▂▁▁▁ |
| NumSulfer | 0 | 1 | 0 | 1 | -0.34 | -0.34 | -0.34 | -0.34 | 7.86 | ▇▁▁▁▁ |
| NumChlorine | 0 | 1 | 0 | 1 | -0.40 | -0.40 | -0.40 | -0.40 | 6.74 | ▇▁▁▁▁ |
| NumHalogen | 0 | 1 | 0 | 1 | -0.47 | -0.47 | -0.47 | 0.20 | 6.32 | ▇▁▁▁▁ |
| NumRings | 0 | 1 | 0 | 1 | -1.08 | -1.08 | -0.31 | 0.46 | 4.31 | ▇▃▂▁▁ |
| HydrophilicFactor | 0 | 1 | 0 | 1 | -0.86 | -0.66 | -0.26 | 0.30 | 11.99 | ▇▁▁▁▁ |
| SurfaceArea1 | 0 | 1 | 0 | 1 | -1.03 | -0.77 | -0.21 | 0.48 | 8.37 | ▇▂▁▁▁ |
| SurfaceArea2 | 0 | 1 | 0 | 1 | -1.06 | -0.78 | -0.19 | 0.54 | 7.65 | ▇▂▁▁▁ |
###################################
# Verifying the data dimensions
###################################
dim(DPA.Predictors.Numeric_BoxCoxTransformed_CenteredScaledTransformed)## [1] 951 201.3.7 Pre-Processed Dataset
[A] 1267 rows (observations)
[A.1] Train Set = 951 observations
[A.2] Test Set = 316 observations
[B] 221 columns (variables)
[B.1] 1/221 response = Class variable (factor)
[B.1.1] Levels = Log_Solubility_Class=Low < Log_Solubility_Class=Mid < Log_Solubility_Class=High
[B.2] 220/221 predictors = All remaining variables (205/220 factor + 15/220 numeric)
[C] Pre-processing actions applied:
[C.1] Centering, scaling and shape transformation applied to improve data quality
[C.2] No outlier treatment applied since the high values noted were contextually valid and sensible
[C.3] 3 predictors removed due to zero or near-zero variance
[C.4] 3 predictors removed due to high correlation
[C.5] 2 predictors removed due to linear dependencies
Code Chunk | Output
##################################
# Creating the pre-modelling
# train set
##################################
Log_Solubility_Class <- DPA$Log_Solubility_Class
PMA.Predictors.Factor <- DPA.Predictors[,(grep("FP", names(DPA.Predictors)))]
PMA.Predictors.Factor <- as.data.frame(lapply(PMA.Predictors.Factor,factor))
PMA.Predictors.Numeric <- DPA.Predictors.Numeric_BoxCoxTransformed_CenteredScaledTransformed
PMA_BoxCoxTransformed_CenteredScaledTransformed <- cbind(Log_Solubility_Class,PMA.Predictors.Factor,PMA.Predictors.Numeric)
##################################
# Filtering out columns noted with data quality issues including
# zero and near-zero variance,
# high correlation and linear dependencies
# to create the pre-modelling dataset
##################################
PMA_BoxCoxTransformed_CenteredScaledTransformed_ExcludedLowVariance_ExcludedLinearlyDependent_ExcludedHighCorrelation <- PMA_BoxCoxTransformed_CenteredScaledTransformed[,!names(PMA_BoxCoxTransformed_CenteredScaledTransformed) %in% c("FP154","FP199","FP200","NumNonHBonds","NumHydrogen","NumNonHAtoms","NumAromaticBonds","NumAtoms")]
PMA_PreModelling_Train <- PMA_BoxCoxTransformed_CenteredScaledTransformed_ExcludedLowVariance_ExcludedLinearlyDependent_ExcludedHighCorrelation
##################################
# Gathering descriptive statistics
##################################
(PMA_PreModelling_Train_Skimmed <- skim(PMA_PreModelling_Train))| Name | PMA_PreModelling_Train |
| Number of rows | 951 |
| Number of columns | 221 |
| _______________________ | |
| Column type frequency: | |
| factor | 206 |
| numeric | 15 |
| ________________________ | |
| Group variables | None |
Variable type: factor
| skim_variable | n_missing | complete_rate | ordered | n_unique | top_counts |
|---|---|---|---|---|---|
| Log_Solubility_Class | 0 | 1 | FALSE | 3 | Low: 427, Mid: 283, Hig: 241 |
| FP001 | 0 | 1 | FALSE | 2 | 0: 482, 1: 469 |
| FP002 | 0 | 1 | FALSE | 2 | 1: 513, 0: 438 |
| FP003 | 0 | 1 | FALSE | 2 | 0: 536, 1: 415 |
| FP004 | 0 | 1 | FALSE | 2 | 1: 556, 0: 395 |
| FP005 | 0 | 1 | FALSE | 2 | 1: 551, 0: 400 |
| FP006 | 0 | 1 | FALSE | 2 | 0: 570, 1: 381 |
| FP007 | 0 | 1 | FALSE | 2 | 0: 605, 1: 346 |
| FP008 | 0 | 1 | FALSE | 2 | 0: 641, 1: 310 |
| FP009 | 0 | 1 | FALSE | 2 | 0: 685, 1: 266 |
| FP010 | 0 | 1 | FALSE | 2 | 0: 781, 1: 170 |
| FP011 | 0 | 1 | FALSE | 2 | 0: 747, 1: 204 |
| FP012 | 0 | 1 | FALSE | 2 | 0: 783, 1: 168 |
| FP013 | 0 | 1 | FALSE | 2 | 0: 793, 1: 158 |
| FP014 | 0 | 1 | FALSE | 2 | 0: 798, 1: 153 |
| FP015 | 0 | 1 | FALSE | 2 | 1: 818, 0: 133 |
| FP016 | 0 | 1 | FALSE | 2 | 0: 812, 1: 139 |
| FP017 | 0 | 1 | FALSE | 2 | 0: 814, 1: 137 |
| FP018 | 0 | 1 | FALSE | 2 | 0: 826, 1: 125 |
| FP019 | 0 | 1 | FALSE | 2 | 0: 835, 1: 116 |
| FP020 | 0 | 1 | FALSE | 2 | 0: 837, 1: 114 |
| FP021 | 0 | 1 | FALSE | 2 | 0: 836, 1: 115 |
| FP022 | 0 | 1 | FALSE | 2 | 0: 852, 1: 99 |
| FP023 | 0 | 1 | FALSE | 2 | 0: 834, 1: 117 |
| FP024 | 0 | 1 | FALSE | 2 | 0: 844, 1: 107 |
| FP025 | 0 | 1 | FALSE | 2 | 0: 841, 1: 110 |
| FP026 | 0 | 1 | FALSE | 2 | 0: 871, 1: 80 |
| FP027 | 0 | 1 | FALSE | 2 | 0: 858, 1: 93 |
| FP028 | 0 | 1 | FALSE | 2 | 0: 850, 1: 101 |
| FP029 | 0 | 1 | FALSE | 2 | 0: 854, 1: 97 |
| FP030 | 0 | 1 | FALSE | 2 | 0: 862, 1: 89 |
| FP031 | 0 | 1 | FALSE | 2 | 0: 866, 1: 85 |
| FP032 | 0 | 1 | FALSE | 2 | 0: 881, 1: 70 |
| FP033 | 0 | 1 | FALSE | 2 | 0: 885, 1: 66 |
| FP034 | 0 | 1 | FALSE | 2 | 0: 875, 1: 76 |
| FP035 | 0 | 1 | FALSE | 2 | 0: 882, 1: 69 |
| FP036 | 0 | 1 | FALSE | 2 | 0: 879, 1: 72 |
| FP037 | 0 | 1 | FALSE | 2 | 0: 884, 1: 67 |
| FP038 | 0 | 1 | FALSE | 2 | 0: 869, 1: 82 |
| FP039 | 0 | 1 | FALSE | 2 | 0: 880, 1: 71 |
| FP040 | 0 | 1 | FALSE | 2 | 0: 886, 1: 65 |
| FP041 | 0 | 1 | FALSE | 2 | 0: 891, 1: 60 |
| FP042 | 0 | 1 | FALSE | 2 | 0: 897, 1: 54 |
| FP043 | 0 | 1 | FALSE | 2 | 0: 888, 1: 63 |
| FP044 | 0 | 1 | FALSE | 2 | 0: 894, 1: 57 |
| FP045 | 0 | 1 | FALSE | 2 | 0: 898, 1: 53 |
| FP046 | 0 | 1 | FALSE | 2 | 0: 651, 1: 300 |
| FP047 | 0 | 1 | FALSE | 2 | 0: 698, 1: 253 |
| FP048 | 0 | 1 | FALSE | 2 | 0: 833, 1: 118 |
| FP049 | 0 | 1 | FALSE | 2 | 0: 835, 1: 116 |
| FP050 | 0 | 1 | FALSE | 2 | 0: 844, 1: 107 |
| FP051 | 0 | 1 | FALSE | 2 | 0: 847, 1: 104 |
| FP052 | 0 | 1 | FALSE | 2 | 0: 864, 1: 87 |
| FP053 | 0 | 1 | FALSE | 2 | 0: 862, 1: 89 |
| FP054 | 0 | 1 | FALSE | 2 | 0: 879, 1: 72 |
| FP055 | 0 | 1 | FALSE | 2 | 0: 900, 1: 51 |
| FP056 | 0 | 1 | FALSE | 2 | 0: 889, 1: 62 |
| FP057 | 0 | 1 | FALSE | 2 | 0: 837, 1: 114 |
| FP058 | 0 | 1 | FALSE | 2 | 0: 843, 1: 108 |
| FP059 | 0 | 1 | FALSE | 2 | 0: 899, 1: 52 |
| FP060 | 0 | 1 | FALSE | 2 | 0: 493, 1: 458 |
| FP061 | 0 | 1 | FALSE | 2 | 0: 526, 1: 425 |
| FP062 | 0 | 1 | FALSE | 2 | 0: 535, 1: 416 |
| FP063 | 0 | 1 | FALSE | 2 | 0: 546, 1: 405 |
| FP064 | 0 | 1 | FALSE | 2 | 0: 555, 1: 396 |
| FP065 | 0 | 1 | FALSE | 2 | 1: 564, 0: 387 |
| FP066 | 0 | 1 | FALSE | 2 | 1: 580, 0: 371 |
| FP067 | 0 | 1 | FALSE | 2 | 0: 590, 1: 361 |
| FP068 | 0 | 1 | FALSE | 2 | 0: 607, 1: 344 |
| FP069 | 0 | 1 | FALSE | 2 | 0: 607, 1: 344 |
| FP070 | 0 | 1 | FALSE | 2 | 0: 613, 1: 338 |
| FP071 | 0 | 1 | FALSE | 2 | 0: 640, 1: 311 |
| FP072 | 0 | 1 | FALSE | 2 | 1: 626, 0: 325 |
| FP073 | 0 | 1 | FALSE | 2 | 0: 656, 1: 295 |
| FP074 | 0 | 1 | FALSE | 2 | 0: 642, 1: 309 |
| FP075 | 0 | 1 | FALSE | 2 | 0: 629, 1: 322 |
| FP076 | 0 | 1 | FALSE | 2 | 0: 639, 1: 312 |
| FP077 | 0 | 1 | FALSE | 2 | 0: 646, 1: 305 |
| FP078 | 0 | 1 | FALSE | 2 | 0: 662, 1: 289 |
| FP079 | 0 | 1 | FALSE | 2 | 1: 656, 0: 295 |
| FP080 | 0 | 1 | FALSE | 2 | 0: 663, 1: 288 |
| FP081 | 0 | 1 | FALSE | 2 | 0: 686, 1: 265 |
| FP082 | 0 | 1 | FALSE | 2 | 1: 679, 0: 272 |
| FP083 | 0 | 1 | FALSE | 2 | 0: 691, 1: 260 |
| FP084 | 0 | 1 | FALSE | 2 | 0: 679, 1: 272 |
| FP085 | 0 | 1 | FALSE | 2 | 0: 708, 1: 243 |
| FP086 | 0 | 1 | FALSE | 2 | 0: 695, 1: 256 |
| FP087 | 0 | 1 | FALSE | 2 | 1: 691, 0: 260 |
| FP088 | 0 | 1 | FALSE | 2 | 0: 701, 1: 250 |
| FP089 | 0 | 1 | FALSE | 2 | 0: 716, 1: 235 |
| FP090 | 0 | 1 | FALSE | 2 | 0: 714, 1: 237 |
| FP091 | 0 | 1 | FALSE | 2 | 0: 737, 1: 214 |
| FP092 | 0 | 1 | FALSE | 2 | 0: 719, 1: 232 |
| FP093 | 0 | 1 | FALSE | 2 | 0: 719, 1: 232 |
| FP094 | 0 | 1 | FALSE | 2 | 0: 731, 1: 220 |
| FP095 | 0 | 1 | FALSE | 2 | 0: 742, 1: 209 |
| FP096 | 0 | 1 | FALSE | 2 | 0: 744, 1: 207 |
| FP097 | 0 | 1 | FALSE | 2 | 0: 727, 1: 224 |
| FP098 | 0 | 1 | FALSE | 2 | 0: 725, 1: 226 |
| FP099 | 0 | 1 | FALSE | 2 | 0: 735, 1: 216 |
| FP100 | 0 | 1 | FALSE | 2 | 0: 731, 1: 220 |
| FP101 | 0 | 1 | FALSE | 2 | 0: 726, 1: 225 |
| FP102 | 0 | 1 | FALSE | 2 | 0: 759, 1: 192 |
| FP103 | 0 | 1 | FALSE | 2 | 0: 743, 1: 208 |
| FP104 | 0 | 1 | FALSE | 2 | 0: 739, 1: 212 |
| FP105 | 0 | 1 | FALSE | 2 | 0: 746, 1: 205 |
| FP106 | 0 | 1 | FALSE | 2 | 0: 769, 1: 182 |
| FP107 | 0 | 1 | FALSE | 2 | 0: 750, 1: 201 |
| FP108 | 0 | 1 | FALSE | 2 | 0: 756, 1: 195 |
| FP109 | 0 | 1 | FALSE | 2 | 0: 783, 1: 168 |
| FP110 | 0 | 1 | FALSE | 2 | 0: 755, 1: 196 |
| FP111 | 0 | 1 | FALSE | 2 | 0: 764, 1: 187 |
| FP112 | 0 | 1 | FALSE | 2 | 0: 766, 1: 185 |
| FP113 | 0 | 1 | FALSE | 2 | 0: 765, 1: 186 |
| FP114 | 0 | 1 | FALSE | 2 | 0: 803, 1: 148 |
| FP115 | 0 | 1 | FALSE | 2 | 0: 781, 1: 170 |
| FP116 | 0 | 1 | FALSE | 2 | 0: 768, 1: 183 |
| FP117 | 0 | 1 | FALSE | 2 | 0: 781, 1: 170 |
| FP118 | 0 | 1 | FALSE | 2 | 0: 768, 1: 183 |
| FP119 | 0 | 1 | FALSE | 2 | 0: 796, 1: 155 |
| FP120 | 0 | 1 | FALSE | 2 | 0: 793, 1: 158 |
| FP121 | 0 | 1 | FALSE | 2 | 0: 818, 1: 133 |
| FP122 | 0 | 1 | FALSE | 2 | 0: 795, 1: 156 |
| FP123 | 0 | 1 | FALSE | 2 | 0: 792, 1: 159 |
| FP124 | 0 | 1 | FALSE | 2 | 0: 797, 1: 154 |
| FP125 | 0 | 1 | FALSE | 2 | 0: 803, 1: 148 |
| FP126 | 0 | 1 | FALSE | 2 | 0: 810, 1: 141 |
| FP127 | 0 | 1 | FALSE | 2 | 0: 818, 1: 133 |
| FP128 | 0 | 1 | FALSE | 2 | 0: 810, 1: 141 |
| FP129 | 0 | 1 | FALSE | 2 | 0: 819, 1: 132 |
| FP130 | 0 | 1 | FALSE | 2 | 0: 851, 1: 100 |
| FP131 | 0 | 1 | FALSE | 2 | 0: 831, 1: 120 |
| FP132 | 0 | 1 | FALSE | 2 | 0: 832, 1: 119 |
| FP133 | 0 | 1 | FALSE | 2 | 0: 831, 1: 120 |
| FP134 | 0 | 1 | FALSE | 2 | 0: 830, 1: 121 |
| FP135 | 0 | 1 | FALSE | 2 | 0: 831, 1: 120 |
| FP136 | 0 | 1 | FALSE | 2 | 0: 836, 1: 115 |
| FP137 | 0 | 1 | FALSE | 2 | 0: 841, 1: 110 |
| FP138 | 0 | 1 | FALSE | 2 | 0: 845, 1: 106 |
| FP139 | 0 | 1 | FALSE | 2 | 0: 873, 1: 78 |
| FP140 | 0 | 1 | FALSE | 2 | 0: 845, 1: 106 |
| FP141 | 0 | 1 | FALSE | 2 | 0: 840, 1: 111 |
| FP142 | 0 | 1 | FALSE | 2 | 0: 847, 1: 104 |
| FP143 | 0 | 1 | FALSE | 2 | 0: 874, 1: 77 |
| FP144 | 0 | 1 | FALSE | 2 | 0: 852, 1: 99 |
| FP145 | 0 | 1 | FALSE | 2 | 0: 852, 1: 99 |
| FP146 | 0 | 1 | FALSE | 2 | 0: 853, 1: 98 |
| FP147 | 0 | 1 | FALSE | 2 | 0: 851, 1: 100 |
| FP148 | 0 | 1 | FALSE | 2 | 0: 868, 1: 83 |
| FP149 | 0 | 1 | FALSE | 2 | 0: 865, 1: 86 |
| FP150 | 0 | 1 | FALSE | 2 | 0: 876, 1: 75 |
| FP151 | 0 | 1 | FALSE | 2 | 0: 898, 1: 53 |
| FP152 | 0 | 1 | FALSE | 2 | 0: 873, 1: 78 |
| FP153 | 0 | 1 | FALSE | 2 | 0: 877, 1: 74 |
| FP155 | 0 | 1 | FALSE | 2 | 0: 885, 1: 66 |
| FP156 | 0 | 1 | FALSE | 2 | 0: 884, 1: 67 |
| FP157 | 0 | 1 | FALSE | 2 | 0: 892, 1: 59 |
| FP158 | 0 | 1 | FALSE | 2 | 0: 900, 1: 51 |
| FP159 | 0 | 1 | FALSE | 2 | 0: 884, 1: 67 |
| FP160 | 0 | 1 | FALSE | 2 | 0: 886, 1: 65 |
| FP161 | 0 | 1 | FALSE | 2 | 0: 888, 1: 63 |
| FP162 | 0 | 1 | FALSE | 2 | 0: 480, 1: 471 |
| FP163 | 0 | 1 | FALSE | 2 | 0: 498, 1: 453 |
| FP164 | 0 | 1 | FALSE | 2 | 1: 597, 0: 354 |
| FP165 | 0 | 1 | FALSE | 2 | 0: 619, 1: 332 |
| FP166 | 0 | 1 | FALSE | 2 | 0: 636, 1: 315 |
| FP167 | 0 | 1 | FALSE | 2 | 0: 639, 1: 312 |
| FP168 | 0 | 1 | FALSE | 2 | 1: 633, 0: 318 |
| FP169 | 0 | 1 | FALSE | 2 | 0: 774, 1: 177 |
| FP170 | 0 | 1 | FALSE | 2 | 0: 776, 1: 175 |
| FP171 | 0 | 1 | FALSE | 2 | 0: 790, 1: 161 |
| FP172 | 0 | 1 | FALSE | 2 | 0: 807, 1: 144 |
| FP173 | 0 | 1 | FALSE | 2 | 0: 816, 1: 135 |
| FP174 | 0 | 1 | FALSE | 2 | 0: 827, 1: 124 |
| FP175 | 0 | 1 | FALSE | 2 | 0: 823, 1: 128 |
| FP176 | 0 | 1 | FALSE | 2 | 0: 835, 1: 116 |
| FP177 | 0 | 1 | FALSE | 2 | 0: 836, 1: 115 |
| FP178 | 0 | 1 | FALSE | 2 | 0: 836, 1: 115 |
| FP179 | 0 | 1 | FALSE | 2 | 0: 858, 1: 93 |
| FP180 | 0 | 1 | FALSE | 2 | 0: 849, 1: 102 |
| FP181 | 0 | 1 | FALSE | 2 | 0: 862, 1: 89 |
| FP182 | 0 | 1 | FALSE | 2 | 0: 857, 1: 94 |
| FP183 | 0 | 1 | FALSE | 2 | 0: 879, 1: 72 |
| FP184 | 0 | 1 | FALSE | 2 | 0: 871, 1: 80 |
| FP185 | 0 | 1 | FALSE | 2 | 0: 870, 1: 81 |
| FP186 | 0 | 1 | FALSE | 2 | 0: 878, 1: 73 |
| FP187 | 0 | 1 | FALSE | 2 | 0: 882, 1: 69 |
| FP188 | 0 | 1 | FALSE | 2 | 0: 886, 1: 65 |
| FP189 | 0 | 1 | FALSE | 2 | 0: 878, 1: 73 |
| FP190 | 0 | 1 | FALSE | 2 | 0: 882, 1: 69 |
| FP191 | 0 | 1 | FALSE | 2 | 0: 884, 1: 67 |
| FP192 | 0 | 1 | FALSE | 2 | 0: 893, 1: 58 |
| FP193 | 0 | 1 | FALSE | 2 | 0: 892, 1: 59 |
| FP194 | 0 | 1 | FALSE | 2 | 0: 895, 1: 56 |
| FP195 | 0 | 1 | FALSE | 2 | 0: 893, 1: 58 |
| FP196 | 0 | 1 | FALSE | 2 | 0: 897, 1: 54 |
| FP197 | 0 | 1 | FALSE | 2 | 0: 901, 1: 50 |
| FP198 | 0 | 1 | FALSE | 2 | 0: 897, 1: 54 |
| FP201 | 0 | 1 | FALSE | 2 | 0: 901, 1: 50 |
| FP202 | 0 | 1 | FALSE | 2 | 0: 706, 1: 245 |
| FP203 | 0 | 1 | FALSE | 2 | 0: 842, 1: 109 |
| FP204 | 0 | 1 | FALSE | 2 | 0: 857, 1: 94 |
| FP205 | 0 | 1 | FALSE | 2 | 0: 877, 1: 74 |
| FP206 | 0 | 1 | FALSE | 2 | 0: 894, 1: 57 |
| FP207 | 0 | 1 | FALSE | 2 | 0: 897, 1: 54 |
| FP208 | 0 | 1 | FALSE | 2 | 0: 844, 1: 107 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| MolWeight | 0 | 1 | 0 | 1 | -2.84 | -0.80 | -0.01 | 0.80 | 2.72 | ▁▆▇▆▁ |
| NumBonds | 0 | 1 | 0 | 1 | -2.92 | -0.61 | -0.04 | 0.60 | 3.23 | ▁▅▇▃▁ |
| NumMultBonds | 0 | 1 | 0 | 1 | -1.19 | -1.00 | -0.03 | 0.74 | 3.65 | ▇▇▃▁▁ |
| NumRotBonds | 0 | 1 | 0 | 1 | -0.93 | -0.93 | -0.10 | 0.52 | 5.71 | ▇▂▁▁▁ |
| NumDblBonds | 0 | 1 | 0 | 1 | -0.83 | -0.83 | -0.01 | 0.82 | 4.95 | ▇▂▁▁▁ |
| NumCarbon | 0 | 1 | 0 | 1 | -2.64 | -0.69 | -0.01 | 0.54 | 3.06 | ▂▇▇▃▁ |
| NumNitrogen | 0 | 1 | 0 | 1 | -0.69 | -0.69 | -0.69 | 0.16 | 4.37 | ▇▂▁▁▁ |
| NumOxygen | 0 | 1 | 0 | 1 | -0.91 | -0.91 | -0.33 | 0.25 | 6.61 | ▇▂▁▁▁ |
| NumSulfer | 0 | 1 | 0 | 1 | -0.34 | -0.34 | -0.34 | -0.34 | 7.86 | ▇▁▁▁▁ |
| NumChlorine | 0 | 1 | 0 | 1 | -0.40 | -0.40 | -0.40 | -0.40 | 6.74 | ▇▁▁▁▁ |
| NumHalogen | 0 | 1 | 0 | 1 | -0.47 | -0.47 | -0.47 | 0.20 | 6.32 | ▇▁▁▁▁ |
| NumRings | 0 | 1 | 0 | 1 | -1.08 | -1.08 | -0.31 | 0.46 | 4.31 | ▇▃▂▁▁ |
| HydrophilicFactor | 0 | 1 | 0 | 1 | -0.86 | -0.66 | -0.26 | 0.30 | 11.99 | ▇▁▁▁▁ |
| SurfaceArea1 | 0 | 1 | 0 | 1 | -1.03 | -0.77 | -0.21 | 0.48 | 8.37 | ▇▂▁▁▁ |
| SurfaceArea2 | 0 | 1 | 0 | 1 | -1.06 | -0.78 | -0.19 | 0.54 | 7.65 | ▇▂▁▁▁ |
###################################
# Verifying the data dimensions
# for the train set
###################################
dim(PMA_PreModelling_Train)## [1] 951 221##################################
# Formulating the test set
##################################
DPA_Test <- Solubility_Test
DPA_Test.Predictors <- DPA_Test[,!names(DPA_Test) %in% c("Log_Solubility_Class")]
DPA_Test.Predictors.Numeric <- DPA_Test.Predictors[,-(grep("FP", names(DPA_Test.Predictors)))]
DPA_Test_BoxCox <- preProcess(DPA_Test.Predictors.Numeric, method = c("BoxCox"))
DPA_Test_BoxCoxTransformed <- predict(DPA_Test_BoxCox, DPA_Test.Predictors.Numeric)
DPA_Test.Predictors.Numeric_BoxCoxTransformed_CenteredScaled <- preProcess(DPA_Test_BoxCoxTransformed, method = c("center","scale"))
DPA_Test.Predictors.Numeric_BoxCoxTransformed_CenteredScaledTransformed <- predict(DPA_Test.Predictors.Numeric_BoxCoxTransformed_CenteredScaled, DPA_Test_BoxCoxTransformed)
##################################
# Creating the pre-modelling
# test set
##################################
Log_Solubility_Class <- DPA_Test$Log_Solubility_Class
PMA_Test.Predictors.Factor <- DPA_Test.Predictors[,(grep("FP", names(DPA_Test.Predictors)))]
PMA_Test.Predictors.Factor <- as.data.frame(lapply(PMA_Test.Predictors.Factor,factor))
PMA_Test.Predictors.Numeric <- DPA_Test.Predictors.Numeric_BoxCoxTransformed_CenteredScaledTransformed
PMA_Test_BoxCoxTransformed_CenteredScaledTransformed <- cbind(Log_Solubility_Class,PMA_Test.Predictors.Factor,PMA_Test.Predictors.Numeric)
PMA_Test_BoxCoxTransformed_CenteredScaledTransformed_ExcludedLowVariance_ExcludedLinearlyDependent_ExcludedHighCorrelation <- PMA_Test_BoxCoxTransformed_CenteredScaledTransformed[,!names(PMA_Test_BoxCoxTransformed_CenteredScaledTransformed) %in% c("FP154","FP199","FP200","NumNonHBonds","NumHydrogen","NumNonHAtoms","NumAromaticBonds","NumAtoms")]
PMA_PreModelling_Test <- PMA_Test_BoxCoxTransformed_CenteredScaledTransformed_ExcludedLowVariance_ExcludedLinearlyDependent_ExcludedHighCorrelation
##################################
# Gathering descriptive statistics
##################################
(PMA_PreModelling_Test_Skimmed <- skim(PMA_PreModelling_Test))| Name | PMA_PreModelling_Test |
| Number of rows | 316 |
| Number of columns | 221 |
| _______________________ | |
| Column type frequency: | |
| factor | 206 |
| numeric | 15 |
| ________________________ | |
| Group variables | None |
Variable type: factor
| skim_variable | n_missing | complete_rate | ordered | n_unique | top_counts |
|---|---|---|---|---|---|
| Log_Solubility_Class | 0 | 1 | FALSE | 3 | Low: 143, Mid: 94, Hig: 79 |
| FP001 | 0 | 1 | FALSE | 2 | 0: 168, 1: 148 |
| FP002 | 0 | 1 | FALSE | 2 | 1: 185, 0: 131 |
| FP003 | 0 | 1 | FALSE | 2 | 0: 176, 1: 140 |
| FP004 | 0 | 1 | FALSE | 2 | 1: 168, 0: 148 |
| FP005 | 0 | 1 | FALSE | 2 | 1: 195, 0: 121 |
| FP006 | 0 | 1 | FALSE | 2 | 0: 205, 1: 111 |
| FP007 | 0 | 1 | FALSE | 2 | 0: 204, 1: 112 |
| FP008 | 0 | 1 | FALSE | 2 | 0: 202, 1: 114 |
| FP009 | 0 | 1 | FALSE | 2 | 0: 233, 1: 83 |
| FP010 | 0 | 1 | FALSE | 2 | 0: 255, 1: 61 |
| FP011 | 0 | 1 | FALSE | 2 | 0: 261, 1: 55 |
| FP012 | 0 | 1 | FALSE | 2 | 0: 263, 1: 53 |
| FP013 | 0 | 1 | FALSE | 2 | 0: 264, 1: 52 |
| FP014 | 0 | 1 | FALSE | 2 | 0: 266, 1: 50 |
| FP015 | 0 | 1 | FALSE | 2 | 1: 262, 0: 54 |
| FP016 | 0 | 1 | FALSE | 2 | 0: 271, 1: 45 |
| FP017 | 0 | 1 | FALSE | 2 | 0: 269, 1: 47 |
| FP018 | 0 | 1 | FALSE | 2 | 0: 289, 1: 27 |
| FP019 | 0 | 1 | FALSE | 2 | 0: 280, 1: 36 |
| FP020 | 0 | 1 | FALSE | 2 | 0: 282, 1: 34 |
| FP021 | 0 | 1 | FALSE | 2 | 0: 282, 1: 34 |
| FP022 | 0 | 1 | FALSE | 2 | 0: 279, 1: 37 |
| FP023 | 0 | 1 | FALSE | 2 | 0: 289, 1: 27 |
| FP024 | 0 | 1 | FALSE | 2 | 0: 285, 1: 31 |
| FP025 | 0 | 1 | FALSE | 2 | 0: 291, 1: 25 |
| FP026 | 0 | 1 | FALSE | 2 | 0: 279, 1: 37 |
| FP027 | 0 | 1 | FALSE | 2 | 0: 291, 1: 25 |
| FP028 | 0 | 1 | FALSE | 2 | 0: 298, 1: 18 |
| FP029 | 0 | 1 | FALSE | 2 | 0: 300, 1: 16 |
| FP030 | 0 | 1 | FALSE | 2 | 0: 290, 1: 26 |
| FP031 | 0 | 1 | FALSE | 2 | 0: 285, 1: 31 |
| FP032 | 0 | 1 | FALSE | 2 | 0: 275, 1: 41 |
| FP033 | 0 | 1 | FALSE | 2 | 0: 278, 1: 38 |
| FP034 | 0 | 1 | FALSE | 2 | 0: 295, 1: 21 |
| FP035 | 0 | 1 | FALSE | 2 | 0: 285, 1: 31 |
| FP036 | 0 | 1 | FALSE | 2 | 0: 297, 1: 19 |
| FP037 | 0 | 1 | FALSE | 2 | 0: 286, 1: 30 |
| FP038 | 0 | 1 | FALSE | 2 | 0: 306, 1: 10 |
| FP039 | 0 | 1 | FALSE | 2 | 0: 296, 1: 20 |
| FP040 | 0 | 1 | FALSE | 2 | 0: 298, 1: 18 |
| FP041 | 0 | 1 | FALSE | 2 | 0: 297, 1: 19 |
| FP042 | 0 | 1 | FALSE | 2 | 0: 297, 1: 19 |
| FP043 | 0 | 1 | FALSE | 2 | 0: 302, 1: 14 |
| FP044 | 0 | 1 | FALSE | 2 | 0: 297, 1: 19 |
| FP045 | 0 | 1 | FALSE | 2 | 0: 296, 1: 20 |
| FP046 | 0 | 1 | FALSE | 2 | 0: 213, 1: 103 |
| FP047 | 0 | 1 | FALSE | 2 | 0: 222, 1: 94 |
| FP048 | 0 | 1 | FALSE | 2 | 0: 280, 1: 36 |
| FP049 | 0 | 1 | FALSE | 2 | 0: 282, 1: 34 |
| FP050 | 0 | 1 | FALSE | 2 | 0: 280, 1: 36 |
| FP051 | 0 | 1 | FALSE | 2 | 0: 298, 1: 18 |
| FP052 | 0 | 1 | FALSE | 2 | 0: 283, 1: 33 |
| FP053 | 0 | 1 | FALSE | 2 | 0: 297, 1: 19 |
| FP054 | 0 | 1 | FALSE | 2 | 0: 285, 1: 31 |
| FP055 | 0 | 1 | FALSE | 2 | 0: 287, 1: 29 |
| FP056 | 0 | 1 | FALSE | 2 | 0: 296, 1: 20 |
| FP057 | 0 | 1 | FALSE | 2 | 0: 277, 1: 39 |
| FP058 | 0 | 1 | FALSE | 2 | 0: 273, 1: 43 |
| FP059 | 0 | 1 | FALSE | 2 | 0: 302, 1: 14 |
| FP060 | 0 | 1 | FALSE | 2 | 0: 173, 1: 143 |
| FP061 | 0 | 1 | FALSE | 2 | 0: 192, 1: 124 |
| FP062 | 0 | 1 | FALSE | 2 | 0: 181, 1: 135 |
| FP063 | 0 | 1 | FALSE | 2 | 0: 203, 1: 113 |
| FP064 | 0 | 1 | FALSE | 2 | 0: 193, 1: 123 |
| FP065 | 0 | 1 | FALSE | 2 | 1: 189, 0: 127 |
| FP066 | 0 | 1 | FALSE | 2 | 1: 195, 0: 121 |
| FP067 | 0 | 1 | FALSE | 2 | 0: 213, 1: 103 |
| FP068 | 0 | 1 | FALSE | 2 | 0: 224, 1: 92 |
| FP069 | 0 | 1 | FALSE | 2 | 0: 198, 1: 118 |
| FP070 | 0 | 1 | FALSE | 2 | 0: 211, 1: 105 |
| FP071 | 0 | 1 | FALSE | 2 | 0: 207, 1: 109 |
| FP072 | 0 | 1 | FALSE | 2 | 1: 204, 0: 112 |
| FP073 | 0 | 1 | FALSE | 2 | 0: 224, 1: 92 |
| FP074 | 0 | 1 | FALSE | 2 | 0: 213, 1: 103 |
| FP075 | 0 | 1 | FALSE | 2 | 0: 235, 1: 81 |
| FP076 | 0 | 1 | FALSE | 2 | 0: 216, 1: 100 |
| FP077 | 0 | 1 | FALSE | 2 | 0: 219, 1: 97 |
| FP078 | 0 | 1 | FALSE | 2 | 0: 218, 1: 98 |
| FP079 | 0 | 1 | FALSE | 2 | 1: 230, 0: 86 |
| FP080 | 0 | 1 | FALSE | 2 | 0: 233, 1: 83 |
| FP081 | 0 | 1 | FALSE | 2 | 0: 225, 1: 91 |
| FP082 | 0 | 1 | FALSE | 2 | 1: 235, 0: 81 |
| FP083 | 0 | 1 | FALSE | 2 | 0: 236, 1: 80 |
| FP084 | 0 | 1 | FALSE | 2 | 0: 245, 1: 71 |
| FP085 | 0 | 1 | FALSE | 2 | 0: 231, 1: 85 |
| FP086 | 0 | 1 | FALSE | 2 | 0: 230, 1: 86 |
| FP087 | 0 | 1 | FALSE | 2 | 1: 241, 0: 75 |
| FP088 | 0 | 1 | FALSE | 2 | 0: 239, 1: 77 |
| FP089 | 0 | 1 | FALSE | 2 | 0: 236, 1: 80 |
| FP090 | 0 | 1 | FALSE | 2 | 0: 244, 1: 72 |
| FP091 | 0 | 1 | FALSE | 2 | 0: 243, 1: 73 |
| FP092 | 0 | 1 | FALSE | 2 | 0: 247, 1: 69 |
| FP093 | 0 | 1 | FALSE | 2 | 0: 248, 1: 68 |
| FP094 | 0 | 1 | FALSE | 2 | 0: 237, 1: 79 |
| FP095 | 0 | 1 | FALSE | 2 | 0: 251, 1: 65 |
| FP096 | 0 | 1 | FALSE | 2 | 0: 257, 1: 59 |
| FP097 | 0 | 1 | FALSE | 2 | 0: 250, 1: 66 |
| FP098 | 0 | 1 | FALSE | 2 | 0: 252, 1: 64 |
| FP099 | 0 | 1 | FALSE | 2 | 0: 249, 1: 67 |
| FP100 | 0 | 1 | FALSE | 2 | 0: 259, 1: 57 |
| FP101 | 0 | 1 | FALSE | 2 | 0: 260, 1: 56 |
| FP102 | 0 | 1 | FALSE | 2 | 0: 270, 1: 46 |
| FP103 | 0 | 1 | FALSE | 2 | 0: 247, 1: 69 |
| FP104 | 0 | 1 | FALSE | 2 | 0: 258, 1: 58 |
| FP105 | 0 | 1 | FALSE | 2 | 0: 248, 1: 68 |
| FP106 | 0 | 1 | FALSE | 2 | 0: 273, 1: 43 |
| FP107 | 0 | 1 | FALSE | 2 | 0: 254, 1: 62 |
| FP108 | 0 | 1 | FALSE | 2 | 0: 259, 1: 57 |
| FP109 | 0 | 1 | FALSE | 2 | 0: 261, 1: 55 |
| FP110 | 0 | 1 | FALSE | 2 | 0: 264, 1: 52 |
| FP111 | 0 | 1 | FALSE | 2 | 0: 259, 1: 57 |
| FP112 | 0 | 1 | FALSE | 2 | 0: 260, 1: 56 |
| FP113 | 0 | 1 | FALSE | 2 | 0: 264, 1: 52 |
| FP114 | 0 | 1 | FALSE | 2 | 0: 260, 1: 56 |
| FP115 | 0 | 1 | FALSE | 2 | 0: 266, 1: 50 |
| FP116 | 0 | 1 | FALSE | 2 | 0: 269, 1: 47 |
| FP117 | 0 | 1 | FALSE | 2 | 0: 262, 1: 54 |
| FP118 | 0 | 1 | FALSE | 2 | 0: 279, 1: 37 |
| FP119 | 0 | 1 | FALSE | 2 | 0: 263, 1: 53 |
| FP120 | 0 | 1 | FALSE | 2 | 0: 267, 1: 49 |
| FP121 | 0 | 1 | FALSE | 2 | 0: 282, 1: 34 |
| FP122 | 0 | 1 | FALSE | 2 | 0: 273, 1: 43 |
| FP123 | 0 | 1 | FALSE | 2 | 0: 270, 1: 46 |
| FP124 | 0 | 1 | FALSE | 2 | 0: 274, 1: 42 |
| FP125 | 0 | 1 | FALSE | 2 | 0: 278, 1: 38 |
| FP126 | 0 | 1 | FALSE | 2 | 0: 280, 1: 36 |
| FP127 | 0 | 1 | FALSE | 2 | 0: 269, 1: 47 |
| FP128 | 0 | 1 | FALSE | 2 | 0: 282, 1: 34 |
| FP129 | 0 | 1 | FALSE | 2 | 0: 272, 1: 44 |
| FP130 | 0 | 1 | FALSE | 2 | 0: 290, 1: 26 |
| FP131 | 0 | 1 | FALSE | 2 | 0: 282, 1: 34 |
| FP132 | 0 | 1 | FALSE | 2 | 0: 276, 1: 40 |
| FP133 | 0 | 1 | FALSE | 2 | 0: 273, 1: 43 |
| FP134 | 0 | 1 | FALSE | 2 | 0: 289, 1: 27 |
| FP135 | 0 | 1 | FALSE | 2 | 0: 296, 1: 20 |
| FP136 | 0 | 1 | FALSE | 2 | 0: 284, 1: 32 |
| FP137 | 0 | 1 | FALSE | 2 | 0: 288, 1: 28 |
| FP138 | 0 | 1 | FALSE | 2 | 0: 290, 1: 26 |
| FP139 | 0 | 1 | FALSE | 2 | 0: 296, 1: 20 |
| FP140 | 0 | 1 | FALSE | 2 | 0: 288, 1: 28 |
| FP141 | 0 | 1 | FALSE | 2 | 0: 294, 1: 22 |
| FP142 | 0 | 1 | FALSE | 2 | 0: 286, 1: 30 |
| FP143 | 0 | 1 | FALSE | 2 | 0: 299, 1: 17 |
| FP144 | 0 | 1 | FALSE | 2 | 0: 287, 1: 29 |
| FP145 | 0 | 1 | FALSE | 2 | 0: 296, 1: 20 |
| FP146 | 0 | 1 | FALSE | 2 | 0: 287, 1: 29 |
| FP147 | 0 | 1 | FALSE | 2 | 0: 294, 1: 22 |
| FP148 | 0 | 1 | FALSE | 2 | 0: 291, 1: 25 |
| FP149 | 0 | 1 | FALSE | 2 | 0: 290, 1: 26 |
| FP150 | 0 | 1 | FALSE | 2 | 0: 295, 1: 21 |
| FP151 | 0 | 1 | FALSE | 2 | 0: 306, 1: 10 |
| FP152 | 0 | 1 | FALSE | 2 | 0: 299, 1: 17 |
| FP153 | 0 | 1 | FALSE | 2 | 0: 305, 1: 11 |
| FP155 | 0 | 1 | FALSE | 2 | 0: 295, 1: 21 |
| FP156 | 0 | 1 | FALSE | 2 | 0: 301, 1: 15 |
| FP157 | 0 | 1 | FALSE | 2 | 0: 298, 1: 18 |
| FP158 | 0 | 1 | FALSE | 2 | 0: 291, 1: 25 |
| FP159 | 0 | 1 | FALSE | 2 | 0: 305, 1: 11 |
| FP160 | 0 | 1 | FALSE | 2 | 0: 305, 1: 11 |
| FP161 | 0 | 1 | FALSE | 2 | 0: 305, 1: 11 |
| FP162 | 0 | 1 | FALSE | 2 | 1: 168, 0: 148 |
| FP163 | 0 | 1 | FALSE | 2 | 0: 173, 1: 143 |
| FP164 | 0 | 1 | FALSE | 2 | 1: 207, 0: 109 |
| FP165 | 0 | 1 | FALSE | 2 | 0: 215, 1: 101 |
| FP166 | 0 | 1 | FALSE | 2 | 0: 209, 1: 107 |
| FP167 | 0 | 1 | FALSE | 2 | 0: 221, 1: 95 |
| FP168 | 0 | 1 | FALSE | 2 | 1: 226, 0: 90 |
| FP169 | 0 | 1 | FALSE | 2 | 0: 257, 1: 59 |
| FP170 | 0 | 1 | FALSE | 2 | 0: 267, 1: 49 |
| FP171 | 0 | 1 | FALSE | 2 | 0: 275, 1: 41 |
| FP172 | 0 | 1 | FALSE | 2 | 0: 269, 1: 47 |
| FP173 | 0 | 1 | FALSE | 2 | 0: 273, 1: 43 |
| FP174 | 0 | 1 | FALSE | 2 | 0: 267, 1: 49 |
| FP175 | 0 | 1 | FALSE | 2 | 0: 274, 1: 42 |
| FP176 | 0 | 1 | FALSE | 2 | 0: 282, 1: 34 |
| FP177 | 0 | 1 | FALSE | 2 | 0: 284, 1: 32 |
| FP178 | 0 | 1 | FALSE | 2 | 0: 282, 1: 34 |
| FP179 | 0 | 1 | FALSE | 2 | 0: 272, 1: 44 |
| FP180 | 0 | 1 | FALSE | 2 | 0: 294, 1: 22 |
| FP181 | 0 | 1 | FALSE | 2 | 0: 283, 1: 33 |
| FP182 | 0 | 1 | FALSE | 2 | 0: 292, 1: 24 |
| FP183 | 0 | 1 | FALSE | 2 | 0: 274, 1: 42 |
| FP184 | 0 | 1 | FALSE | 2 | 0: 286, 1: 30 |
| FP185 | 0 | 1 | FALSE | 2 | 0: 285, 1: 31 |
| FP186 | 0 | 1 | FALSE | 2 | 0: 297, 1: 19 |
| FP187 | 0 | 1 | FALSE | 2 | 0: 295, 1: 21 |
| FP188 | 0 | 1 | FALSE | 2 | 0: 294, 1: 22 |
| FP189 | 0 | 1 | FALSE | 2 | 0: 303, 1: 13 |
| FP190 | 0 | 1 | FALSE | 2 | 0: 299, 1: 17 |
| FP191 | 0 | 1 | FALSE | 2 | 0: 298, 1: 18 |
| FP192 | 0 | 1 | FALSE | 2 | 0: 294, 1: 22 |
| FP193 | 0 | 1 | FALSE | 2 | 0: 294, 1: 22 |
| FP194 | 0 | 1 | FALSE | 2 | 0: 295, 1: 21 |
| FP195 | 0 | 1 | FALSE | 2 | 0: 300, 1: 16 |
| FP196 | 0 | 1 | FALSE | 2 | 0: 294, 1: 22 |
| FP197 | 0 | 1 | FALSE | 2 | 0: 296, 1: 20 |
| FP198 | 0 | 1 | FALSE | 2 | 0: 302, 1: 14 |
| FP201 | 0 | 1 | FALSE | 2 | 0: 303, 1: 13 |
| FP202 | 0 | 1 | FALSE | 2 | 0: 232, 1: 84 |
| FP203 | 0 | 1 | FALSE | 2 | 0: 273, 1: 43 |
| FP204 | 0 | 1 | FALSE | 2 | 0: 286, 1: 30 |
| FP205 | 0 | 1 | FALSE | 2 | 0: 291, 1: 25 |
| FP206 | 0 | 1 | FALSE | 2 | 0: 300, 1: 16 |
| FP207 | 0 | 1 | FALSE | 2 | 0: 302, 1: 14 |
| FP208 | 0 | 1 | FALSE | 2 | 0: 273, 1: 43 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| MolWeight | 0 | 1 | 0 | 1 | -2.46 | -0.78 | -0.06 | 0.81 | 2.18 | ▁▇▇▇▃ |
| NumBonds | 0 | 1 | 0 | 1 | -2.92 | -0.67 | 0.03 | 0.57 | 2.55 | ▁▂▇▃▂ |
| NumMultBonds | 0 | 1 | 0 | 1 | -1.24 | -1.04 | -0.06 | 0.72 | 4.06 | ▇▇▅▁▁ |
| NumRotBonds | 0 | 1 | 0 | 1 | -0.82 | -0.82 | -0.40 | 0.44 | 5.94 | ▇▁▁▁▁ |
| NumDblBonds | 0 | 1 | 0 | 1 | -0.76 | -0.76 | 0.09 | 0.09 | 4.35 | ▇▁▁▁▁ |
| NumCarbon | 0 | 1 | 0 | 1 | -2.71 | -0.70 | -0.21 | 0.56 | 2.23 | ▁▂▇▅▂ |
| NumNitrogen | 0 | 1 | 0 | 1 | -0.63 | -0.63 | -0.63 | 0.26 | 4.71 | ▇▂▁▁▁ |
| NumOxygen | 0 | 1 | 0 | 1 | -0.92 | -0.92 | -0.26 | 0.40 | 5.02 | ▇▃▁▁▁ |
| NumSulfer | 0 | 1 | 0 | 1 | -0.28 | -0.28 | -0.28 | -0.28 | 8.06 | ▇▁▁▁▁ |
| NumChlorine | 0 | 1 | 0 | 1 | -0.40 | -0.40 | -0.40 | -0.40 | 6.02 | ▇▁▁▁▁ |
| NumHalogen | 0 | 1 | 0 | 1 | -0.48 | -0.48 | -0.48 | 0.20 | 5.57 | ▇▁▁▁▁ |
| NumRings | 0 | 1 | 0 | 1 | -1.14 | -0.32 | -0.32 | 0.49 | 3.74 | ▇▃▁▁▁ |
| HydrophilicFactor | 0 | 1 | 0 | 1 | -0.90 | -0.68 | -0.30 | 0.32 | 5.19 | ▇▂▁▁▁ |
| SurfaceArea1 | 0 | 1 | 0 | 1 | -1.04 | -0.75 | -0.21 | 0.53 | 5.37 | ▇▃▁▁▁ |
| SurfaceArea2 | 0 | 1 | 0 | 1 | -1.05 | -0.77 | -0.26 | 0.52 | 5.00 | ▇▃▁▁▁ |
###################################
# Verifying the data dimensions
# for the test set
###################################
dim(PMA_PreModelling_Test)## [1] 316 2211.4 Data Exploration
[A] Numeric variables which demonstrated differential relationships with the Log_Solubility_Class response variable include:
[A.1] MolWeight variable (numeric)
[A.2] NumCarbon variable (numeric)
[A.3] NumChlorine variable (numeric)
[A.4] NumHalogen variable (numeric)
[A.5] NumMultBonds variable (numeric)
[B] Factor variables which demonstrated relatively better differentiation of the Log_Solubility_Class response variable between its 1 and 0 structure levels include:
[B.1] FP207 variable (factor)
[B.2] FP190 variable (factor)
[B.3] FP197 variable (factor)
[B.4] FP196 variable (factor)
[B.5] FP193 variable (factor)
[B.6] FP184 variable (factor)
[B.7] FP172 variable (factor)
[B.8] FP149 variable (factor)
[B.9] FP112 variable (factor)
[B.10] FP107 variable (factor)
[B.11] FP089 variable (factor)
[B.12] FP079 variable (factor)
[B.13] FP076 variable (factor)
[B.14] FP072 variable (factor)
[B.15] FP071 variable (factor)
[B.16] FP070 variable (factor)
[B.17] FP065 variable (factor)
[B.18] FP059 variable (factor)
[B.19] FP054 variable (factor)
[B.20] FP056 variable (factor)
[B.21] FP053 variable (factor)
[B.22] FP049 variable (factor)
[B.23] FP044 variable (factor)
[B.24] FP041 variable (factor)
[B.25] FP039 variable (factor)
[B.26] FP014 variable (factor)
[B.27] FP013 variable (factor)
Code Chunk | Output
##################################
# Loading dataset
##################################
EDA <- PMA_PreModelling_Train
##################################
# Listing all predictors
##################################
EDA.Predictors <- EDA[,!names(EDA) %in% c("Log_Solubility_Class")]
##################################
# Listing all numeric predictors
##################################
EDA.Predictors.Numeric <- EDA.Predictors[,sapply(EDA.Predictors, is.numeric)]
ncol(EDA.Predictors.Numeric)## [1] 15names(EDA.Predictors.Numeric)## [1] "MolWeight" "NumBonds" "NumMultBonds"
## [4] "NumRotBonds" "NumDblBonds" "NumCarbon"
## [7] "NumNitrogen" "NumOxygen" "NumSulfer"
## [10] "NumChlorine" "NumHalogen" "NumRings"
## [13] "HydrophilicFactor" "SurfaceArea1" "SurfaceArea2"##################################
# Listing all factor predictors
##################################
EDA.Predictors.Factor <- EDA.Predictors[,sapply(EDA.Predictors, is.factor)]
ncol(EDA.Predictors.Factor)## [1] 205names(EDA.Predictors.Factor)## [1] "FP001" "FP002" "FP003" "FP004" "FP005" "FP006" "FP007" "FP008" "FP009"
## [10] "FP010" "FP011" "FP012" "FP013" "FP014" "FP015" "FP016" "FP017" "FP018"
## [19] "FP019" "FP020" "FP021" "FP022" "FP023" "FP024" "FP025" "FP026" "FP027"
## [28] "FP028" "FP029" "FP030" "FP031" "FP032" "FP033" "FP034" "FP035" "FP036"
## [37] "FP037" "FP038" "FP039" "FP040" "FP041" "FP042" "FP043" "FP044" "FP045"
## [46] "FP046" "FP047" "FP048" "FP049" "FP050" "FP051" "FP052" "FP053" "FP054"
## [55] "FP055" "FP056" "FP057" "FP058" "FP059" "FP060" "FP061" "FP062" "FP063"
## [64] "FP064" "FP065" "FP066" "FP067" "FP068" "FP069" "FP070" "FP071" "FP072"
## [73] "FP073" "FP074" "FP075" "FP076" "FP077" "FP078" "FP079" "FP080" "FP081"
## [82] "FP082" "FP083" "FP084" "FP085" "FP086" "FP087" "FP088" "FP089" "FP090"
## [91] "FP091" "FP092" "FP093" "FP094" "FP095" "FP096" "FP097" "FP098" "FP099"
## [100] "FP100" "FP101" "FP102" "FP103" "FP104" "FP105" "FP106" "FP107" "FP108"
## [109] "FP109" "FP110" "FP111" "FP112" "FP113" "FP114" "FP115" "FP116" "FP117"
## [118] "FP118" "FP119" "FP120" "FP121" "FP122" "FP123" "FP124" "FP125" "FP126"
## [127] "FP127" "FP128" "FP129" "FP130" "FP131" "FP132" "FP133" "FP134" "FP135"
## [136] "FP136" "FP137" "FP138" "FP139" "FP140" "FP141" "FP142" "FP143" "FP144"
## [145] "FP145" "FP146" "FP147" "FP148" "FP149" "FP150" "FP151" "FP152" "FP153"
## [154] "FP155" "FP156" "FP157" "FP158" "FP159" "FP160" "FP161" "FP162" "FP163"
## [163] "FP164" "FP165" "FP166" "FP167" "FP168" "FP169" "FP170" "FP171" "FP172"
## [172] "FP173" "FP174" "FP175" "FP176" "FP177" "FP178" "FP179" "FP180" "FP181"
## [181] "FP182" "FP183" "FP184" "FP185" "FP186" "FP187" "FP188" "FP189" "FP190"
## [190] "FP191" "FP192" "FP193" "FP194" "FP195" "FP196" "FP197" "FP198" "FP201"
## [199] "FP202" "FP203" "FP204" "FP205" "FP206" "FP207" "FP208"##################################
# Formulating the box plots
##################################
featurePlot(x = EDA.Predictors.Numeric,
y = EDA$Log_Solubility_Class,
plot = "box",
scales = list(x = list(relation="free", rot = 90),
y = list(relation="free")),
adjust = 1.5,
pch = "|")
##################################
# Restructuring the dataset for
# for barchart analysis
##################################
Log_Solubility_Class <- DPA$Log_Solubility_Class
EDA.Bar.Source <- as.data.frame(cbind(Log_Solubility_Class,
EDA.Predictors.Factor))
ncol(EDA.Bar.Source)## [1] 206##################################
# Creating a function to formulate
# the proportions table
##################################
EDA.PropTable.Function <- function(FactorVar) {
EDA.Bar.Source.FactorVar <- EDA.Bar.Source[,c("Log_Solubility_Class",
FactorVar)]
EDA.Bar.Source.FactorVar.Prop <- as.data.frame(prop.table(table(EDA.Bar.Source.FactorVar), 2))
names(EDA.Bar.Source.FactorVar.Prop)[2] <- "Structure"
EDA.Bar.Source.FactorVar.Prop$Variable <- rep(FactorVar,nrow(EDA.Bar.Source.FactorVar.Prop))
return(EDA.Bar.Source.FactorVar.Prop)
}
EDA.Bar.Source.FactorVar.Prop.Group5 <- rbind(EDA.PropTable.Function(names(EDA.Bar.Source)[162]),
EDA.PropTable.Function(names(EDA.Bar.Source)[163]),
EDA.PropTable.Function(names(EDA.Bar.Source)[164]),
EDA.PropTable.Function(names(EDA.Bar.Source)[165]),
EDA.PropTable.Function(names(EDA.Bar.Source)[166]),
EDA.PropTable.Function(names(EDA.Bar.Source)[167]),
EDA.PropTable.Function(names(EDA.Bar.Source)[168]),
EDA.PropTable.Function(names(EDA.Bar.Source)[169]),
EDA.PropTable.Function(names(EDA.Bar.Source)[170]),
EDA.PropTable.Function(names(EDA.Bar.Source)[171]),
EDA.PropTable.Function(names(EDA.Bar.Source)[172]),
EDA.PropTable.Function(names(EDA.Bar.Source)[173]),
EDA.PropTable.Function(names(EDA.Bar.Source)[174]),
EDA.PropTable.Function(names(EDA.Bar.Source)[175]),
EDA.PropTable.Function(names(EDA.Bar.Source)[176]),
EDA.PropTable.Function(names(EDA.Bar.Source)[177]),
EDA.PropTable.Function(names(EDA.Bar.Source)[178]),
EDA.PropTable.Function(names(EDA.Bar.Source)[179]),
EDA.PropTable.Function(names(EDA.Bar.Source)[180]),
EDA.PropTable.Function(names(EDA.Bar.Source)[181]),
EDA.PropTable.Function(names(EDA.Bar.Source)[182]),
EDA.PropTable.Function(names(EDA.Bar.Source)[183]),
EDA.PropTable.Function(names(EDA.Bar.Source)[184]),
EDA.PropTable.Function(names(EDA.Bar.Source)[185]),
EDA.PropTable.Function(names(EDA.Bar.Source)[186]),
EDA.PropTable.Function(names(EDA.Bar.Source)[187]),
EDA.PropTable.Function(names(EDA.Bar.Source)[188]),
EDA.PropTable.Function(names(EDA.Bar.Source)[189]),
EDA.PropTable.Function(names(EDA.Bar.Source)[190]),
EDA.PropTable.Function(names(EDA.Bar.Source)[191]),
EDA.PropTable.Function(names(EDA.Bar.Source)[192]),
EDA.PropTable.Function(names(EDA.Bar.Source)[193]),
EDA.PropTable.Function(names(EDA.Bar.Source)[194]),
EDA.PropTable.Function(names(EDA.Bar.Source)[195]),
EDA.PropTable.Function(names(EDA.Bar.Source)[196]),
EDA.PropTable.Function(names(EDA.Bar.Source)[197]),
EDA.PropTable.Function(names(EDA.Bar.Source)[198]),
EDA.PropTable.Function(names(EDA.Bar.Source)[199]),
EDA.PropTable.Function(names(EDA.Bar.Source)[200]),
EDA.PropTable.Function(names(EDA.Bar.Source)[201]),
EDA.PropTable.Function(names(EDA.Bar.Source)[202]),
EDA.PropTable.Function(names(EDA.Bar.Source)[203]),
EDA.PropTable.Function(names(EDA.Bar.Source)[204]),
EDA.PropTable.Function(names(EDA.Bar.Source)[205]),
EDA.PropTable.Function(names(EDA.Bar.Source)[206]))
(EDA.Barchart.FactorVar <- barchart(EDA.Bar.Source.FactorVar.Prop.Group5[,3] ~
EDA.Bar.Source.FactorVar.Prop.Group5[,2] | EDA.Bar.Source.FactorVar.Prop.Group5[,4],
data=EDA.Bar.Source.FactorVar.Prop.Group5,
groups = EDA.Bar.Source.FactorVar.Prop.Group5[,1],
stack=TRUE,
ylab = "Proportion",
xlab = "Structure",
auto.key = list(adj = 1),
layout=(c(9,5))))
EDA.Bar.Source.FactorVar.Prop.Group4 <- rbind(EDA.PropTable.Function(names(EDA.Bar.Source)[122]),
EDA.PropTable.Function(names(EDA.Bar.Source)[123]),
EDA.PropTable.Function(names(EDA.Bar.Source)[124]),
EDA.PropTable.Function(names(EDA.Bar.Source)[125]),
EDA.PropTable.Function(names(EDA.Bar.Source)[126]),
EDA.PropTable.Function(names(EDA.Bar.Source)[127]),
EDA.PropTable.Function(names(EDA.Bar.Source)[128]),
EDA.PropTable.Function(names(EDA.Bar.Source)[129]),
EDA.PropTable.Function(names(EDA.Bar.Source)[130]),
EDA.PropTable.Function(names(EDA.Bar.Source)[131]),
EDA.PropTable.Function(names(EDA.Bar.Source)[132]),
EDA.PropTable.Function(names(EDA.Bar.Source)[133]),
EDA.PropTable.Function(names(EDA.Bar.Source)[134]),
EDA.PropTable.Function(names(EDA.Bar.Source)[135]),
EDA.PropTable.Function(names(EDA.Bar.Source)[136]),
EDA.PropTable.Function(names(EDA.Bar.Source)[137]),
EDA.PropTable.Function(names(EDA.Bar.Source)[138]),
EDA.PropTable.Function(names(EDA.Bar.Source)[139]),
EDA.PropTable.Function(names(EDA.Bar.Source)[140]),
EDA.PropTable.Function(names(EDA.Bar.Source)[141]),
EDA.PropTable.Function(names(EDA.Bar.Source)[142]),
EDA.PropTable.Function(names(EDA.Bar.Source)[143]),
EDA.PropTable.Function(names(EDA.Bar.Source)[144]),
EDA.PropTable.Function(names(EDA.Bar.Source)[145]),
EDA.PropTable.Function(names(EDA.Bar.Source)[146]),
EDA.PropTable.Function(names(EDA.Bar.Source)[147]),
EDA.PropTable.Function(names(EDA.Bar.Source)[148]),
EDA.PropTable.Function(names(EDA.Bar.Source)[149]),
EDA.PropTable.Function(names(EDA.Bar.Source)[150]),
EDA.PropTable.Function(names(EDA.Bar.Source)[151]),
EDA.PropTable.Function(names(EDA.Bar.Source)[152]),
EDA.PropTable.Function(names(EDA.Bar.Source)[153]),
EDA.PropTable.Function(names(EDA.Bar.Source)[154]),
EDA.PropTable.Function(names(EDA.Bar.Source)[155]),
EDA.PropTable.Function(names(EDA.Bar.Source)[156]),
EDA.PropTable.Function(names(EDA.Bar.Source)[157]),
EDA.PropTable.Function(names(EDA.Bar.Source)[158]),
EDA.PropTable.Function(names(EDA.Bar.Source)[159]),
EDA.PropTable.Function(names(EDA.Bar.Source)[160]),
EDA.PropTable.Function(names(EDA.Bar.Source)[161]))
(EDA.Barchart.FactorVar <- barchart(EDA.Bar.Source.FactorVar.Prop.Group4[,3] ~
EDA.Bar.Source.FactorVar.Prop.Group4[,2] | EDA.Bar.Source.FactorVar.Prop.Group4[,4],
data=EDA.Bar.Source.FactorVar.Prop.Group4,
groups = EDA.Bar.Source.FactorVar.Prop.Group4[,1],
stack=TRUE,
ylab = "Proportion",
xlab = "Structure",
auto.key = list(adj = 1),
layout=(c(9,5))))
EDA.Bar.Source.FactorVar.Prop.Group3 <- rbind(EDA.PropTable.Function(names(EDA.Bar.Source)[82]),
EDA.PropTable.Function(names(EDA.Bar.Source)[83]),
EDA.PropTable.Function(names(EDA.Bar.Source)[84]),
EDA.PropTable.Function(names(EDA.Bar.Source)[85]),
EDA.PropTable.Function(names(EDA.Bar.Source)[86]),
EDA.PropTable.Function(names(EDA.Bar.Source)[87]),
EDA.PropTable.Function(names(EDA.Bar.Source)[88]),
EDA.PropTable.Function(names(EDA.Bar.Source)[89]),
EDA.PropTable.Function(names(EDA.Bar.Source)[90]),
EDA.PropTable.Function(names(EDA.Bar.Source)[91]),
EDA.PropTable.Function(names(EDA.Bar.Source)[92]),
EDA.PropTable.Function(names(EDA.Bar.Source)[93]),
EDA.PropTable.Function(names(EDA.Bar.Source)[94]),
EDA.PropTable.Function(names(EDA.Bar.Source)[95]),
EDA.PropTable.Function(names(EDA.Bar.Source)[96]),
EDA.PropTable.Function(names(EDA.Bar.Source)[97]),
EDA.PropTable.Function(names(EDA.Bar.Source)[98]),
EDA.PropTable.Function(names(EDA.Bar.Source)[99]),
EDA.PropTable.Function(names(EDA.Bar.Source)[100]),
EDA.PropTable.Function(names(EDA.Bar.Source)[101]),
EDA.PropTable.Function(names(EDA.Bar.Source)[102]),
EDA.PropTable.Function(names(EDA.Bar.Source)[103]),
EDA.PropTable.Function(names(EDA.Bar.Source)[104]),
EDA.PropTable.Function(names(EDA.Bar.Source)[105]),
EDA.PropTable.Function(names(EDA.Bar.Source)[106]),
EDA.PropTable.Function(names(EDA.Bar.Source)[107]),
EDA.PropTable.Function(names(EDA.Bar.Source)[108]),
EDA.PropTable.Function(names(EDA.Bar.Source)[109]),
EDA.PropTable.Function(names(EDA.Bar.Source)[110]),
EDA.PropTable.Function(names(EDA.Bar.Source)[111]),
EDA.PropTable.Function(names(EDA.Bar.Source)[112]),
EDA.PropTable.Function(names(EDA.Bar.Source)[113]),
EDA.PropTable.Function(names(EDA.Bar.Source)[114]),
EDA.PropTable.Function(names(EDA.Bar.Source)[115]),
EDA.PropTable.Function(names(EDA.Bar.Source)[116]),
EDA.PropTable.Function(names(EDA.Bar.Source)[117]),
EDA.PropTable.Function(names(EDA.Bar.Source)[118]),
EDA.PropTable.Function(names(EDA.Bar.Source)[119]),
EDA.PropTable.Function(names(EDA.Bar.Source)[120]),
EDA.PropTable.Function(names(EDA.Bar.Source)[121]))
(EDA.Barchart.FactorVar <- barchart(EDA.Bar.Source.FactorVar.Prop.Group3[,3] ~
EDA.Bar.Source.FactorVar.Prop.Group3[,2] | EDA.Bar.Source.FactorVar.Prop.Group3[,4],
data=EDA.Bar.Source.FactorVar.Prop.Group3,
groups = EDA.Bar.Source.FactorVar.Prop.Group3[,1],
stack=TRUE,
ylab = "Proportion",
xlab = "Structure",
auto.key = list(adj = 1),
layout=(c(9,5))))
EDA.Bar.Source.FactorVar.Prop.Group2 <- rbind(EDA.PropTable.Function(names(EDA.Bar.Source)[42]),
EDA.PropTable.Function(names(EDA.Bar.Source)[43]),
EDA.PropTable.Function(names(EDA.Bar.Source)[44]),
EDA.PropTable.Function(names(EDA.Bar.Source)[45]),
EDA.PropTable.Function(names(EDA.Bar.Source)[46]),
EDA.PropTable.Function(names(EDA.Bar.Source)[47]),
EDA.PropTable.Function(names(EDA.Bar.Source)[48]),
EDA.PropTable.Function(names(EDA.Bar.Source)[49]),
EDA.PropTable.Function(names(EDA.Bar.Source)[50]),
EDA.PropTable.Function(names(EDA.Bar.Source)[51]),
EDA.PropTable.Function(names(EDA.Bar.Source)[52]),
EDA.PropTable.Function(names(EDA.Bar.Source)[53]),
EDA.PropTable.Function(names(EDA.Bar.Source)[54]),
EDA.PropTable.Function(names(EDA.Bar.Source)[55]),
EDA.PropTable.Function(names(EDA.Bar.Source)[56]),
EDA.PropTable.Function(names(EDA.Bar.Source)[57]),
EDA.PropTable.Function(names(EDA.Bar.Source)[58]),
EDA.PropTable.Function(names(EDA.Bar.Source)[59]),
EDA.PropTable.Function(names(EDA.Bar.Source)[60]),
EDA.PropTable.Function(names(EDA.Bar.Source)[61]),
EDA.PropTable.Function(names(EDA.Bar.Source)[62]),
EDA.PropTable.Function(names(EDA.Bar.Source)[63]),
EDA.PropTable.Function(names(EDA.Bar.Source)[64]),
EDA.PropTable.Function(names(EDA.Bar.Source)[65]),
EDA.PropTable.Function(names(EDA.Bar.Source)[66]),
EDA.PropTable.Function(names(EDA.Bar.Source)[67]),
EDA.PropTable.Function(names(EDA.Bar.Source)[68]),
EDA.PropTable.Function(names(EDA.Bar.Source)[69]),
EDA.PropTable.Function(names(EDA.Bar.Source)[70]),
EDA.PropTable.Function(names(EDA.Bar.Source)[71]),
EDA.PropTable.Function(names(EDA.Bar.Source)[72]),
EDA.PropTable.Function(names(EDA.Bar.Source)[73]),
EDA.PropTable.Function(names(EDA.Bar.Source)[74]),
EDA.PropTable.Function(names(EDA.Bar.Source)[75]),
EDA.PropTable.Function(names(EDA.Bar.Source)[76]),
EDA.PropTable.Function(names(EDA.Bar.Source)[77]),
EDA.PropTable.Function(names(EDA.Bar.Source)[78]),
EDA.PropTable.Function(names(EDA.Bar.Source)[79]),
EDA.PropTable.Function(names(EDA.Bar.Source)[80]),
EDA.PropTable.Function(names(EDA.Bar.Source)[81]))
(EDA.Barchart.FactorVar <- barchart(EDA.Bar.Source.FactorVar.Prop.Group2[,3] ~
EDA.Bar.Source.FactorVar.Prop.Group2[,2] | EDA.Bar.Source.FactorVar.Prop.Group2[,4],
data=EDA.Bar.Source.FactorVar.Prop.Group2,
groups = EDA.Bar.Source.FactorVar.Prop.Group2[,1],
stack=TRUE,
ylab = "Proportion",
xlab = "Structure",
auto.key = list(adj = 1),
layout=(c(9,5))))
EDA.Bar.Source.FactorVar.Prop.Group1 <- rbind(EDA.PropTable.Function(names(EDA.Bar.Source)[2]),
EDA.PropTable.Function(names(EDA.Bar.Source)[3]),
EDA.PropTable.Function(names(EDA.Bar.Source)[4]),
EDA.PropTable.Function(names(EDA.Bar.Source)[5]),
EDA.PropTable.Function(names(EDA.Bar.Source)[6]),
EDA.PropTable.Function(names(EDA.Bar.Source)[7]),
EDA.PropTable.Function(names(EDA.Bar.Source)[8]),
EDA.PropTable.Function(names(EDA.Bar.Source)[9]),
EDA.PropTable.Function(names(EDA.Bar.Source)[10]),
EDA.PropTable.Function(names(EDA.Bar.Source)[11]),
EDA.PropTable.Function(names(EDA.Bar.Source)[12]),
EDA.PropTable.Function(names(EDA.Bar.Source)[13]),
EDA.PropTable.Function(names(EDA.Bar.Source)[14]),
EDA.PropTable.Function(names(EDA.Bar.Source)[15]),
EDA.PropTable.Function(names(EDA.Bar.Source)[16]),
EDA.PropTable.Function(names(EDA.Bar.Source)[17]),
EDA.PropTable.Function(names(EDA.Bar.Source)[18]),
EDA.PropTable.Function(names(EDA.Bar.Source)[19]),
EDA.PropTable.Function(names(EDA.Bar.Source)[20]),
EDA.PropTable.Function(names(EDA.Bar.Source)[21]),
EDA.PropTable.Function(names(EDA.Bar.Source)[22]),
EDA.PropTable.Function(names(EDA.Bar.Source)[23]),
EDA.PropTable.Function(names(EDA.Bar.Source)[24]),
EDA.PropTable.Function(names(EDA.Bar.Source)[25]),
EDA.PropTable.Function(names(EDA.Bar.Source)[26]),
EDA.PropTable.Function(names(EDA.Bar.Source)[27]),
EDA.PropTable.Function(names(EDA.Bar.Source)[28]),
EDA.PropTable.Function(names(EDA.Bar.Source)[29]),
EDA.PropTable.Function(names(EDA.Bar.Source)[30]),
EDA.PropTable.Function(names(EDA.Bar.Source)[31]),
EDA.PropTable.Function(names(EDA.Bar.Source)[32]),
EDA.PropTable.Function(names(EDA.Bar.Source)[33]),
EDA.PropTable.Function(names(EDA.Bar.Source)[34]),
EDA.PropTable.Function(names(EDA.Bar.Source)[35]),
EDA.PropTable.Function(names(EDA.Bar.Source)[36]),
EDA.PropTable.Function(names(EDA.Bar.Source)[37]),
EDA.PropTable.Function(names(EDA.Bar.Source)[38]),
EDA.PropTable.Function(names(EDA.Bar.Source)[39]),
EDA.PropTable.Function(names(EDA.Bar.Source)[40]),
EDA.PropTable.Function(names(EDA.Bar.Source)[41]))
(EDA.Barchart.FactorVar <- barchart(EDA.Bar.Source.FactorVar.Prop.Group1[,3] ~
EDA.Bar.Source.FactorVar.Prop.Group1[,2] | EDA.Bar.Source.FactorVar.Prop.Group1[,4],
data=EDA.Bar.Source.FactorVar.Prop.Group1,
groups = EDA.Bar.Source.FactorVar.Prop.Group1[,1],
stack=TRUE,
ylab = "Proportion",
xlab = "Structure",
auto.key = list(adj = 1),
layout=(c(9,5))))
1.5 Predictive Model Development
1.5.1 Penalized Multinomial Regression (PMR)
Penalized Multinomial Regression fits multinomial log-linear models via neural networks. The algorithm is structured as a neural network with a single output layer consisting of multiple neurons, each representing a different class of the response variable. The output layer applies a softmax function as an activation function ensuring that the output values of the neurons representing the different categories sum up to one and can be interpreted as probabilities for each category. During training, the model learns a set of weights for each feature, as well as a bias term for each class in the output layer. The weights and bias terms are estimated using maximum likelihood. The learned weights and biases are applied to new data to make predictions.
[A] The penalized multinomial regression model from the nnet package was implemented through the caret package.
[B] The model contains 1 hyperparameter:
[B.1] decay = decay made to vary across a range of 5 default values
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves decay=0.1000
[C.2] Accuracy = 0.74338
[D] The model allows for ranking of predictors in terms of variable importance. The top-performing predictors in the model are as follows:
[D.1] MolWeight variable (numeric)
[D.2] FP063 (Structure=1) variable (factor)
[D.3] FP072 (Structure=1) variable (factor)
[D.4] FP159 (Structure=1) variable (factor)
[D.5] NumBonds variable (numeric)
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.76582
Code Chunk | Output
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_PMR <- as.data.frame(lapply(PMA_PreModelling_Train[,!names(PMA_PreModelling_Train) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Train_PMR$Log_Solubility_Class <- PMA_PreModelling_Train$Log_Solubility_Class
dim(PMA_PreModelling_Train_PMR)## [1] 951 221PMA_PreModelling_Test_PMR <- as.data.frame(lapply(PMA_PreModelling_Test[,!names(PMA_PreModelling_Test) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Test_PMR$Log_Solubility_Class <- PMA_PreModelling_Test$Log_Solubility_Class
dim(PMA_PreModelling_Test_PMR)## [1] 316 221##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_PMR$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
# used a range of default values
##################################
# Running the penalized multinomial regression model
# by setting the caret method to 'multinom'
##################################
set.seed(12345678)
PMR_Tune <- train(x = PMA_PreModelling_Train_PMR[,!names(PMA_PreModelling_Train_PMR) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_PMR$Log_Solubility_Class,
method = "multinom",
metric = "Accuracy",
preProc = c("center", "scale"),
tuneLength = 5,
trControl = KFold_Control)## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 505.883620
## iter 20 value 413.328456
## iter 30 value 358.647309
## iter 40 value 276.942588
## iter 50 value 221.746726
## iter 60 value 179.497085
## iter 70 value 121.420246
## iter 80 value 68.224963
## iter 90 value 26.570867
## iter 100 value 1.361644
## final value 1.361644
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 506.746454
## iter 20 value 416.572349
## iter 30 value 368.019847
## iter 40 value 291.322544
## iter 50 value 242.920526
## iter 60 value 215.615404
## iter 70 value 187.705888
## iter 80 value 158.438328
## iter 90 value 146.387217
## iter 100 value 139.035184
## final value 139.035184
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 505.970185
## iter 20 value 413.658170
## iter 30 value 359.624222
## iter 40 value 278.602815
## iter 50 value 224.530872
## iter 60 value 184.560341
## iter 70 value 136.674128
## iter 80 value 97.203549
## iter 90 value 81.013772
## iter 100 value 73.501426
## final value 73.501426
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 505.892279
## iter 20 value 413.361482
## iter 30 value 358.745320
## iter 40 value 277.109441
## iter 50 value 222.032433
## iter 60 value 180.034498
## iter 70 value 123.230139
## iter 80 value 72.293945
## iter 90 value 37.565945
## iter 100 value 25.817226
## final value 25.817226
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 505.884486
## iter 20 value 413.331759
## iter 30 value 358.657113
## iter 40 value 276.959281
## iter 50 value 221.775372
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## iter 90 value 5.319592
## iter 100 value 0.208084
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## initial value 940.412119
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## initial value 940.412119
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## stopped after 100 iterations
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## initial value 939.313507
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## initial value 939.313507
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## initial value 939.313507
## iter 10 value 522.907910
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## iter 70 value 138.021234
## iter 80 value 95.567319
## iter 90 value 78.352582
## iter 100 value 69.717679
## final value 69.717679
## stopped after 100 iterations
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## initial value 939.313507
## iter 10 value 522.807927
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## iter 50 value 222.239299
## iter 60 value 190.755151
## iter 70 value 124.050815
## iter 80 value 73.127712
## iter 90 value 36.809189
## iter 100 value 22.707720
## final value 22.707720
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 939.313507
## iter 10 value 522.797924
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## iter 70 value 121.873508
## iter 80 value 70.053815
## iter 90 value 24.994855
## iter 100 value 5.364738
## final value 5.364738
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 941.510731
## iter 10 value 508.454131
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## iter 30 value 353.438933
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## iter 70 value 115.565276
## iter 80 value 64.779114
## iter 90 value 17.969744
## iter 100 value 0.509584
## final value 0.509584
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 941.510731
## iter 10 value 509.485577
## iter 20 value 414.713898
## iter 30 value 364.588020
## iter 40 value 288.436159
## iter 50 value 241.345497
## iter 60 value 211.074621
## iter 70 value 181.198458
## iter 80 value 148.310519
## iter 90 value 135.430431
## iter 100 value 127.489563
## final value 127.489563
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 941.510731
## iter 10 value 508.557636
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## iter 30 value 354.548933
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## iter 70 value 122.312319
## iter 80 value 88.922239
## iter 90 value 69.659789
## iter 100 value 60.856064
## final value 60.856064
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 941.510731
## iter 10 value 508.464485
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## iter 60 value 185.884623
## iter 70 value 116.356270
## iter 80 value 67.674482
## iter 90 value 40.816455
## iter 100 value 20.138752
## final value 20.138752
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 941.510731
## iter 10 value 508.455167
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## iter 70 value 115.651011
## iter 80 value 65.078380
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## iter 100 value 4.843812
## final value 4.843812
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 501.929673
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## iter 40 value 263.017974
## iter 50 value 214.026640
## iter 60 value 179.031009
## iter 70 value 109.310217
## iter 80 value 58.258791
## iter 90 value 10.650380
## iter 100 value 0.572691
## final value 0.572691
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 502.978004
## iter 20 value 402.556229
## iter 30 value 348.734827
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## iter 50 value 233.986688
## iter 60 value 207.637438
## iter 70 value 177.165135
## iter 80 value 148.356094
## iter 90 value 136.758366
## iter 100 value 129.304895
## final value 129.304895
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 502.034882
## iter 20 value 399.340649
## iter 30 value 341.746131
## iter 40 value 264.599231
## iter 50 value 216.525158
## iter 60 value 183.129042
## iter 70 value 130.043506
## iter 80 value 87.982971
## iter 90 value 73.456633
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## final value 65.284530
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 501.940198
## iter 20 value 399.013575
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## iter 70 value 117.229688
## iter 80 value 63.650219
## iter 90 value 32.240778
## iter 100 value 22.762218
## final value 22.762218
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 501.930726
## iter 20 value 398.980811
## iter 30 value 340.936085
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## iter 60 value 179.074160
## iter 70 value 109.511109
## iter 80 value 58.694358
## iter 90 value 13.790210
## iter 100 value 5.572783
## final value 5.572783
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 939.313507
## iter 10 value 501.143336
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## iter 40 value 273.363698
## iter 50 value 216.786593
## iter 60 value 184.952734
## iter 70 value 116.338314
## iter 80 value 65.508686
## iter 90 value 24.954043
## iter 100 value 0.886655
## final value 0.886655
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 939.313507
## iter 10 value 502.089109
## iter 20 value 409.637376
## iter 30 value 361.938201
## iter 40 value 288.239185
## iter 50 value 239.094867
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## iter 70 value 187.673883
## iter 80 value 155.270855
## iter 90 value 143.900974
## iter 100 value 135.552363
## final value 135.552363
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 939.313507
## iter 10 value 501.238227
## iter 20 value 406.765728
## iter 30 value 355.894792
## iter 40 value 275.064751
## iter 50 value 219.616912
## iter 60 value 182.713184
## iter 70 value 133.767237
## iter 80 value 91.769542
## iter 90 value 76.867664
## iter 100 value 68.634698
## final value 68.634698
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 939.313507
## iter 10 value 501.152828
## iter 20 value 406.473881
## iter 30 value 355.258944
## iter 40 value 273.536289
## iter 50 value 217.077587
## iter 60 value 185.485013
## iter 70 value 118.142170
## iter 80 value 69.057876
## iter 90 value 44.053015
## iter 100 value 23.361684
## final value 23.361684
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 939.313507
## iter 10 value 501.144285
## iter 20 value 406.444648
## iter 30 value 355.195023
## iter 40 value 273.380982
## iter 50 value 216.815775
## iter 60 value 185.006190
## iter 70 value 116.503392
## iter 80 value 65.878970
## iter 90 value 26.680294
## iter 100 value 6.099040
## final value 6.099040
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 492.217387
## iter 20 value 404.808601
## iter 30 value 360.648980
## iter 40 value 274.658084
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## iter 60 value 187.402881
## iter 70 value 123.087338
## iter 80 value 65.799108
## iter 90 value 12.475121
## iter 100 value 0.498507
## final value 0.498507
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 493.018780
## iter 20 value 407.651745
## iter 30 value 372.450194
## iter 40 value 288.450825
## iter 50 value 241.296720
## iter 60 value 214.537918
## iter 70 value 190.744045
## iter 80 value 152.806967
## iter 90 value 140.282122
## iter 100 value 131.530285
## final value 131.530285
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 492.297748
## iter 20 value 405.096975
## iter 30 value 361.399822
## iter 40 value 276.328799
## iter 50 value 224.090944
## iter 60 value 191.600687
## iter 70 value 137.583703
## iter 80 value 91.867051
## iter 90 value 75.063815
## iter 100 value 66.373491
## final value 66.373491
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 492.225426
## iter 20 value 404.837480
## iter 30 value 360.724225
## iter 40 value 274.827562
## iter 50 value 221.788046
## iter 60 value 187.843571
## iter 70 value 124.772970
## iter 80 value 69.346265
## iter 90 value 32.297133
## iter 100 value 22.593491
## final value 22.593491
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 492.218191
## iter 20 value 404.811489
## iter 30 value 360.656506
## iter 40 value 274.675056
## iter 50 value 221.550885
## iter 60 value 187.447174
## iter 70 value 123.258754
## iter 80 value 66.168405
## iter 90 value 15.026037
## iter 100 value 5.450970
## final value 5.450970
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 488.821630
## iter 20 value 400.158597
## iter 30 value 350.103123
## iter 40 value 275.252711
## iter 50 value 224.997182
## iter 60 value 186.854839
## iter 70 value 121.841376
## iter 80 value 71.333767
## iter 90 value 19.982876
## iter 100 value 0.680711
## final value 0.680711
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 489.684845
## iter 20 value 403.197612
## iter 30 value 356.977030
## iter 40 value 289.617342
## iter 50 value 245.377539
## iter 60 value 219.977990
## iter 70 value 190.792575
## iter 80 value 157.196733
## iter 90 value 145.541524
## iter 100 value 136.762372
## final value 136.762372
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 488.908204
## iter 20 value 400.467079
## iter 30 value 350.825329
## iter 40 value 276.906424
## iter 50 value 227.650783
## iter 60 value 191.424036
## iter 70 value 135.319933
## iter 80 value 97.238759
## iter 90 value 79.820233
## iter 100 value 71.290124
## final value 71.290124
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 488.830290
## iter 20 value 400.189492
## iter 30 value 350.175716
## iter 40 value 275.420626
## iter 50 value 225.269787
## iter 60 value 187.335303
## iter 70 value 123.233398
## iter 80 value 74.838626
## iter 90 value 39.168010
## iter 100 value 25.676625
## final value 25.676625
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 940.412119
## iter 10 value 488.822496
## iter 20 value 400.161687
## iter 30 value 350.110386
## iter 40 value 275.269528
## iter 50 value 225.024515
## iter 60 value 186.903141
## iter 70 value 121.984216
## iter 80 value 71.698819
## iter 90 value 22.648685
## iter 100 value 6.547673
## final value 6.547673
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 941.510731
## iter 10 value 521.286567
## iter 20 value 419.076477
## iter 30 value 355.170629
## iter 40 value 277.875625
## iter 50 value 227.435062
## iter 60 value 190.707427
## iter 70 value 127.428587
## iter 80 value 76.789155
## iter 90 value 33.394188
## iter 100 value 2.120937
## final value 2.120937
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 941.510731
## iter 10 value 522.308471
## iter 20 value 422.591737
## iter 30 value 363.814063
## iter 40 value 292.230872
## iter 50 value 248.249647
## iter 60 value 225.200512
## iter 70 value 191.196016
## iter 80 value 165.297831
## iter 90 value 151.493510
## iter 100 value 143.133939
## final value 143.133939
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 941.510731
## iter 10 value 521.389129
## iter 20 value 419.433696
## iter 30 value 356.070721
## iter 40 value 279.499633
## iter 50 value 230.044768
## iter 60 value 195.383504
## iter 70 value 140.441947
## iter 80 value 102.745390
## iter 90 value 83.305148
## iter 100 value 74.694684
## final value 74.694684
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 941.510731
## iter 10 value 521.296827
## iter 20 value 419.112257
## iter 30 value 355.261004
## iter 40 value 278.040165
## iter 50 value 227.702928
## iter 60 value 191.198932
## iter 70 value 128.900240
## iter 80 value 80.168467
## iter 90 value 44.922117
## iter 100 value 25.985200
## final value 25.985200
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 941.510731
## iter 10 value 521.287593
## iter 20 value 419.080056
## iter 30 value 355.179670
## iter 40 value 277.892101
## iter 50 value 227.461920
## iter 60 value 190.756837
## iter 70 value 127.578471
## iter 80 value 77.140360
## iter 90 value 34.827183
## iter 100 value 7.456146
## final value 7.456146
## stopped after 100 iterations
## # weights: 666 (442 variable)
## initial value 1044.780287
## iter 10 value 591.615430
## iter 20 value 469.910574
## iter 30 value 411.926966
## iter 40 value 327.688646
## iter 50 value 276.245078
## iter 60 value 249.640241
## iter 70 value 227.809290
## iter 80 value 191.001082
## iter 90 value 173.047854
## iter 100 value 162.821782
## final value 162.821782
## stopped after 100 iterations##################################
# Reportingting the cross-validation results
# for the train set
##################################
PMR_Tune## Penalized Multinomial Regression
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## Pre-processing: centered (220), scaled (220)
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## decay logLoss AUC prAUC Accuracy Kappa Mean_F1
## 0e+00 6.268653 0.8333238 0.4536161 0.6835610 0.5140285 0.6706793
## 1e-04 5.487383 0.8348603 0.5004770 0.6877387 0.5198066 0.6741649
## 1e-03 3.879741 0.8385638 0.6098625 0.6950744 0.5309883 0.6811589
## 1e-02 2.164788 0.8527698 0.6956716 0.7118960 0.5546841 0.6976960
## 1e-01 1.028097 0.8840758 0.7446643 0.7433879 0.6034366 0.7292788
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.6742287 0.8417692 0.6707438 0.8393936
## 0.6768690 0.8436688 0.6749554 0.8415973
## 0.6841549 0.8474496 0.6810874 0.8453742
## 0.6979662 0.8546371 0.6987544 0.8538125
## 0.7298753 0.8712734 0.7325479 0.8705616
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.6707438 0.6742287 0.2278537 0.7579989
## 0.6749554 0.6768690 0.2292462 0.7602689
## 0.6810874 0.6841549 0.2316915 0.7658022
## 0.6987544 0.6979662 0.2372987 0.7763016
## 0.7325479 0.7298753 0.2477960 0.8005744
##
## Accuracy was used to select the optimal model using the largest value.
## The final value used for the model was decay = 0.1.PMR_Tune$finalModel## Call:
## nnet::multinom(formula = .outcome ~ ., data = dat, decay = param$decay)
##
## Coefficients:
## (Intercept) FP001 FP002 FP003 FP004 FP005 FP006
## Mid 0.7702862 0.387247 -0.08392134 -0.2068101 -1.830839 -1.308756 0.6863685
## High -2.9224515 1.420950 -1.13231633 1.0323685 -1.872285 -1.192009 -0.3291985
## FP007 FP008 FP009 FP010 FP011 FP012
## Mid -0.3442218 0.07348782 -1.141147 0.4793638 0.0192878 1.4249260
## High -1.1966302 -0.24356866 -1.183417 0.1619986 0.1026934 -0.1141841
## FP013 FP014 FP015 FP016 FP017 FP018
## Mid -0.87156436 -0.8627798 -0.4939584 0.3222238 -0.95075937 -0.7666128
## High -0.07512187 -1.3345855 -0.1376469 0.4533557 -0.08419407 -1.3269259
## FP019 FP020 FP021 FP022 FP023 FP024
## Mid 1.2861265 -0.07260037 0.7386469 -0.4603497 -0.50936115 0.06489086
## High 0.3239464 0.13444672 0.9359778 -0.3007523 0.08821953 -1.19667058
## FP025 FP026 FP027 FP028 FP029 FP030
## Mid -0.18595219 -0.9682133 -0.76743001 -0.2283272 1.155501 -0.09440084
## High -0.09277032 0.5519762 0.04782863 -0.6150805 -0.817543 -0.19363888
## FP031 FP032 FP033 FP034 FP035 FP036 FP037
## Mid 0.2043519 -0.3239928 -0.2998948 0.3517654 -1.0315493 0.1812509 0.6755704
## High 1.7565966 -1.0673350 -0.2366944 -0.6478395 -0.9004425 1.1611353 1.8950471
## FP038 FP039 FP040 FP041 FP042 FP043
## Mid -0.2216016 -0.0706278 -0.07973857 0.9444687 0.9801262 -0.5783072
## High 0.5247800 -0.4041910 0.27647855 -1.4018870 0.4757096 0.1388797
## FP044 FP045 FP046 FP047 FP048 FP049 FP050
## Mid 0.2905172 0.5003461 0.4289552 0.1956553 -0.03288215 0.1313204 -0.7209036
## High 1.5469966 0.5081891 0.3308734 -1.1120280 0.23746535 0.3224293 -0.6020936
## FP051 FP052 FP053 FP054 FP055 FP056
## Mid 0.4053661 0.2938679 1.128636 -0.2656152 -0.3029370 0.4400948
## High -0.5729887 0.6140839 0.374147 -0.7519996 -0.2920189 -1.0492325
## FP057 FP058 FP059 FP060 FP061 FP062 FP063
## Mid -0.403170642 0.5171627 0.1412360 0.4206273 -0.5244561 0.9615365 2.987642
## High 0.001902966 -0.3595172 -0.8636609 0.3368837 -0.7389476 1.2344888 2.672510
## FP064 FP065 FP066 FP067 FP068 FP069
## Mid 0.06433782 1.091457 0.02104293 -0.38733209 -2.144903 0.3400739
## High -0.34613530 0.832384 -0.66983552 0.04653057 1.784919 -0.6669396
## FP070 FP071 FP072 FP073 FP074 FP075 FP076
## Mid 0.3050364 0.06511125 2.316753 -0.3343082 -0.001637847 1.444371 0.9854032
## High 0.3145152 0.43246145 2.805560 0.5203168 0.648286759 1.833744 0.1342224
## FP077 FP078 FP079 FP080 FP081 FP082
## Mid 0.1750215 -0.5312592 -0.4096345 1.5980629 -0.6842064 0.3845965
## High -0.3078430 -1.3787583 -0.8548013 -0.3773864 -1.8892356 -0.2637251
## FP083 FP084 FP085 FP086 FP087 FP088
## Mid -0.4486936 -0.3565204 0.08971201 -0.2881948 -0.05802898 1.0174955
## High -2.9175479 0.5610060 -1.66242110 0.6611248 -0.32998948 0.7176691
## FP089 FP090 FP091 FP092 FP093 FP094 FP095
## Mid -0.7951702 0.2283722 1.713320 1.933052 0.7479896 0.02050178 -1.0366739
## High -0.6465050 -0.6977186 1.010577 -1.937962 0.7301366 -0.47931258 -0.6788353
## FP096 FP097 FP098 FP099 FP100 FP101
## Mid 0.2857435 -0.5144927 0.245868 0.5284689 0.02237789 -0.05640296
## High 0.3125885 -0.8006670 -1.181972 -0.8920963 0.55813777 -0.15348042
## FP102 FP103 FP104 FP105 FP106 FP107
## Mid -1.7373996 0.4491732 -1.447670 -0.5525368 -0.249729873 -0.4036078
## High 0.3858069 0.5011706 -2.635027 -0.7725175 0.001740566 -0.9096954
## FP108 FP109 FP110 FP111 FP112 FP113 FP114
## Mid -1.1407408 0.1663905 -0.4385522 -0.9104599 -1.048569 0.1991461 -1.264080
## High 0.8125672 0.7851773 -0.5094087 -1.7169448 1.605809 0.7741149 -2.312443
## FP115 FP116 FP117 FP118 FP119 FP120 FP121
## Mid 0.4544520 1.5299058 0.4995241 -0.7274274 1.27883 -1.7535204 0.8199299
## High 0.5684876 -0.2530857 0.1910838 0.4281759 2.30713 0.1667666 -1.0936131
## FP122 FP123 FP124 FP125 FP126 FP127
## Mid 0.9766721 -0.8912633 -0.4464019 0.8678230 -0.8477609 0.7767033
## High 1.3540896 -1.7860194 1.6381951 0.3824767 -1.3287580 -0.4767430
## FP128 FP129 FP130 FP131 FP132 FP133
## Mid -0.09607944 0.6653038 0.2882053 0.9669156 -0.6981534 0.1544506
## High -0.68602176 0.9339282 0.1102145 1.7452320 -0.6625415 -0.2076645
## FP134 FP135 FP136 FP137 FP138 FP139
## Mid -0.33605474 0.5891155 -2.101535 0.4966107 -1.5309557 0.3673071
## High 0.02854853 1.0787335 1.246948 -1.0326168 0.2761916 -0.7913198
## FP140 FP141 FP142 FP143 FP144 FP145
## Mid 1.739704937 -2.2101801 -0.04835435 0.9877672 0.7522101 -0.3695825
## High -0.009863372 -0.7915654 0.56401524 0.5739642 0.4158787 -1.3881376
## FP146 FP147 FP148 FP149 FP150 FP151 FP152
## Mid -0.3529394 0.5681435 -0.4534573 0.3818418 -0.5439020 -0.7842198 1.0437007
## High 1.1306548 0.4560444 -0.5404217 -0.7123495 0.3410997 0.3708683 0.3964055
## FP153 FP155 FP156 FP157 FP158 FP159 FP160
## Mid -0.2217946 -1.1192872 -1.5614879 -1.5877514 -1.2051472 3.233232 -0.476313
## High 0.4689081 0.3261405 0.1907534 -0.1474891 -0.1902042 1.689629 -1.291519
## FP161 FP162 FP163 FP164 FP165 FP166 FP167
## Mid 0.4217388 -0.5694841 0.4623746 1.122994 0.1091634 0.1250613 -1.213595
## High 0.8250906 0.2641386 1.5015764 1.953777 -1.1010819 -0.1057227 -1.145418
## FP168 FP169 FP170 FP171 FP172 FP173 FP174
## Mid 0.7361837 -0.2747340 0.2763340 1.1457456 -0.2451987 0.1283694 -1.563702
## High 0.6127858 -0.2735982 0.5148641 0.5552398 -0.3743099 0.6830350 -1.351538
## FP175 FP176 FP177 FP178 FP179 FP180
## Mid -0.04063002 -0.6428712 0.3148494 -0.3371144 0.8376987 0.6959440
## High 1.16455022 0.7098259 -0.1740625 -0.9153921 0.2492426 -0.2914802
## FP181 FP182 FP183 FP184 FP185 FP186
## Mid 0.3223045 -0.8096873 -0.08861724 0.9089379 0.7510516 0.1135708
## High -0.9167732 -0.1299087 -0.34243073 0.9982696 0.4894935 -1.0577079
## FP187 FP188 FP189 FP190 FP191 FP192 FP193
## Mid -0.6890491 0.2878383 -0.02618061 0.1416122 -0.1282181 0.8457766 0.2384319
## High 0.3843625 0.5303369 0.23909401 0.5542136 0.2742643 1.0899632 0.9086864
## FP194 FP195 FP196 FP197 FP198 FP201
## Mid 0.1611417 -0.05072066 -1.2628212 -1.2426343 -0.36393309 -0.4367053
## High 0.7662758 -0.51170939 -0.2938505 0.2440656 0.08879696 -0.2120910
## FP202 FP203 FP204 FP205 FP206 FP207
## Mid -0.3494017 0.3831490 0.67174246 -0.4106869 -0.0963502 -0.2403326
## High 1.0076553 -0.4048149 -0.06073232 -0.3103634 -0.1330361 -0.2323437
## FP208 MolWeight NumBonds NumMultBonds NumRotBonds NumDblBonds
## Mid -0.2492231 -3.726498 -2.124305 -2.2835259 -1.14839 2.209437
## High 0.3378366 -5.655681 -2.111696 -0.9108377 -2.23907 -1.609858
## NumCarbon NumNitrogen NumOxygen NumSulfer NumChlorine NumHalogen
## Mid -0.3663732 0.7680388 -0.1071704 -0.6095681 -0.6983195 -0.74261052
## High -3.6450066 -0.1176069 3.4248677 -0.9895045 0.6590478 0.01551646
## NumRings HydrophilicFactor SurfaceArea1 SurfaceArea2
## Mid -0.3988221 1.981722 0.2966302 -0.1267327
## High 0.6023396 1.764594 1.2304715 0.3980592
##
## Residual Deviance: 325.6436
## AIC: 1209.644PMR_Tune$results## decay logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 0e+00 6.268653 0.8333238 0.4536161 0.6835610 0.5140285 0.6706793
## 2 1e-04 5.487383 0.8348603 0.5004770 0.6877387 0.5198066 0.6741649
## 3 1e-03 3.879741 0.8385638 0.6098625 0.6950744 0.5309883 0.6811589
## 4 1e-02 2.164788 0.8527698 0.6956716 0.7118960 0.5546841 0.6976960
## 5 1e-01 1.028097 0.8840758 0.7446643 0.7433879 0.6034366 0.7292788
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.6742287 0.8417692 0.6707438 0.8393936
## 2 0.6768690 0.8436688 0.6749554 0.8415973
## 3 0.6841549 0.8474496 0.6810874 0.8453742
## 4 0.6979662 0.8546371 0.6987544 0.8538125
## 5 0.7298753 0.8712734 0.7325479 0.8705616
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.6707438 0.6742287 0.2278537 0.7579989
## 2 0.6749554 0.6768690 0.2292462 0.7602689
## 3 0.6810874 0.6841549 0.2316915 0.7658022
## 4 0.6987544 0.6979662 0.2372987 0.7763016
## 5 0.7325479 0.7298753 0.2477960 0.8005744
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 1.0045558 0.03088745 0.03932687 0.03461454 0.05276605 0.03157092
## 2 0.7902989 0.03076925 0.03165771 0.03879316 0.05921707 0.03706947
## 3 0.6570727 0.03128892 0.03633868 0.03892950 0.05951409 0.03829579
## 4 0.4276198 0.03028311 0.04816400 0.03799363 0.05893747 0.03638139
## 5 0.2209345 0.02857309 0.04603667 0.03643856 0.05693879 0.03717359
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.03455499 0.01811754 0.02986873
## 2 0.04012566 0.01982767 0.03529035
## 3 0.04121621 0.01971138 0.03651634
## 4 0.03827321 0.02020328 0.03476195
## 5 0.04114348 0.01913026 0.03351310
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.01934190 0.02986873 0.03455499 0.01153818
## 2 0.02124061 0.03529035 0.04012566 0.01293105
## 3 0.02092513 0.03651634 0.04121621 0.01297650
## 4 0.02086006 0.03476195 0.03827321 0.01266454
## 5 0.01925731 0.03351310 0.04114348 0.01214619
## Mean_Balanced_AccuracySD
## 1 0.02583835
## 2 0.02958166
## 3 0.03008787
## 4 0.02895948
## 5 0.02993183(PMR_Train_Accuracy <- PMR_Tune$results[PMR_Tune$results$decay==PMR_Tune$bestTune$decay,
c("Accuracy")])## [1] 0.7433879##################################
# Identifying and plotting the
# best model predictors
##################################
PMR_VarImp <- varImp(PMR_Tune, scale = TRUE)
plot(PMR_VarImp,
top=25,
scales=list(y=list(cex = .95)),
main="Ranked Variable Importance : Penalized Multinomial Regression",
xlab="Scaled Variable Importance Metrics",
ylab="Predictors",
cex=2,
origin=0,
alpha=0.45)
##################################
# Independently evaluating the model
# on the test set
##################################
PMR_Test <- data.frame(PMR_Observed = PMA_PreModelling_Test_PMR$Log_Solubility_Class,
PMR_Predicted = predict(PMR_Tune,
PMA_PreModelling_Test_PMR[,!names(PMA_PreModelling_Test_PMR) %in% c("Log_Solubility_Class")],
type = "raw"))
PMR_Test## PMR_Observed PMR_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Mid
## 13 High High
## 14 High High
## 15 High Mid
## 16 High High
## 17 High High
## 18 High High
## 19 High High
## 20 High High
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High High
## 27 High Mid
## 28 High High
## 29 High High
## 30 High High
## 31 High Mid
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High High
## 43 High Mid
## 44 High High
## 45 High Mid
## 46 High High
## 47 High High
## 48 High High
## 49 High High
## 50 High High
## 51 High High
## 52 High Mid
## 53 High Mid
## 54 High High
## 55 High Mid
## 56 High High
## 57 High Mid
## 58 Mid Mid
## 59 Mid Mid
## 60 Mid Low
## 61 Mid Mid
## 62 Mid Mid
## 63 Mid High
## 64 Mid High
## 65 Mid Mid
## 66 Mid Mid
## 67 Mid Low
## 68 Mid High
## 69 Mid High
## 70 Mid Mid
## 71 Mid Mid
## 72 Mid Mid
## 73 Mid Mid
## 74 Mid Mid
## 75 Mid Mid
## 76 Mid Mid
## 77 Mid Low
## 78 Mid Mid
## 79 Mid Mid
## 80 Mid Mid
## 81 Mid Mid
## 82 Mid High
## 83 Mid Mid
## 84 Mid Mid
## 85 Mid Mid
## 86 Mid High
## 87 Mid Low
## 88 Mid Mid
## 89 Mid Mid
## 90 Mid Mid
## 91 Mid High
## 92 Mid Mid
## 93 Mid Low
## 94 Mid Mid
## 95 Mid Mid
## 96 Mid Mid
## 97 Mid High
## 98 Mid Mid
## 99 Mid High
## 100 Mid Mid
## 101 Mid High
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid Mid
## 105 Mid Low
## 106 Mid Mid
## 107 Mid Mid
## 108 Mid Mid
## 109 Mid Low
## 110 Mid Low
## 111 Mid Mid
## 112 Mid Low
## 113 Mid Mid
## 114 Mid Low
## 115 Mid Mid
## 116 Mid Low
## 117 Mid Low
## 118 Mid Low
## 119 Low Mid
## 120 Low Low
## 121 Low Mid
## 122 Low Mid
## 123 Low Low
## 124 Low Low
## 125 Low High
## 126 Low Mid
## 127 Low Low
## 128 Low Mid
## 129 Low Low
## 130 Low Mid
## 131 Low Low
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low Low
## 136 Low Low
## 137 Low Mid
## 138 Low Low
## 139 Low Mid
## 140 Low Mid
## 141 Low Mid
## 142 Low Low
## 143 Low Low
## 144 Low Mid
## 145 Low Mid
## 146 Low Low
## 147 Low High
## 148 Low Low
## 149 Low Low
## 150 Low Low
## 151 Low High
## 152 Low Low
## 153 Low Low
## 154 Low Low
## 155 Low Mid
## 156 Low Mid
## 157 Low Low
## 158 Low Low
## 159 Low Low
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Mid
## 183 Low Low
## 184 Low Low
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Mid
## 226 High High
## 227 High High
## 228 High Mid
## 229 High High
## 230 High Mid
## 231 High Mid
## 232 High High
## 233 High High
## 234 High Mid
## 235 High High
## 236 High Mid
## 237 High Mid
## 238 Mid Mid
## 239 Mid Mid
## 240 Mid Mid
## 241 Mid High
## 242 Mid Mid
## 243 Mid Mid
## 244 Mid Low
## 245 Mid Mid
## 246 Mid Mid
## 247 Mid Mid
## 248 Mid High
## 249 Mid High
## 250 Mid Mid
## 251 Mid Mid
## 252 Mid Mid
## 253 Mid Mid
## 254 Mid Low
## 255 Mid Low
## 256 Mid Mid
## 257 Mid Mid
## 258 Mid Mid
## 259 Mid Low
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid Mid
## 263 Mid Mid
## 264 Mid Mid
## 265 Mid High
## 266 Mid Mid
## 267 Mid Low
## 268 Mid Mid
## 269 Low Mid
## 270 Low High
## 271 Low Low
## 272 Low Low
## 273 Low Low
## 274 Low Low
## 275 Low Low
## 276 Low Low
## 277 Low Low
## 278 Low Mid
## 279 Low Low
## 280 Low Low
## 281 Low Low
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Low
## 287 Low Low
## 288 Low Mid
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(PMR_Test_Accuracy <- Accuracy(y_pred = PMR_Test$PMR_Predicted,
y_true = PMR_Test$PMR_Observed))## [1] 0.76582281.5.2 Linear Discriminant Analysis (LDA)
Linear Discriminant Analysis finds a linear combination of features that best separates the classes in a data set by projecting the data onto a lower-dimensional space that maximizes the separation between the classes. The algorithm searches for a set of linear discriminants that maximize the ratio of between-class variance to within-class variance by evaluating directions in the feature space that best separate the different classes of data. LDA assumes that the data has a Gaussian distribution and that the covariance matrices of the different classes are equal, in addition to the data being linearly separable by the presence of a linear decision boundary can accurately classify the different classes.
[A] The linear discriminant analysis model from the MASS package was implemented through the caret package.
[B] The model does not contain any hyperparameter.
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration is fixed due to the absence of a hyperparameter
[C.2] Accuracy = 0.72865
[D] The model does not allow for ranking of predictors in terms of variable importance.
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.76899
Code Chunk | Output
##################################
# Transforming factor predictors
# as required by the nature of the model
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_LDA <- as.data.frame(lapply(PMA_PreModelling_Train[,!names(PMA_PreModelling_Train) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Train_LDA$Log_Solubility_Class <- PMA_PreModelling_Train$Log_Solubility_Class
dim(PMA_PreModelling_Train_LDA)## [1] 951 221PMA_PreModelling_Test_LDA <- as.data.frame(lapply(PMA_PreModelling_Test[,!names(PMA_PreModelling_Test) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Test_LDA$Log_Solubility_Class <- PMA_PreModelling_Test$Log_Solubility_Class
dim(PMA_PreModelling_Test_LDA)## [1] 316 221##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_LDA$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
# No hyperparameter tuning process conducted
##################################
# Running the linear discriminant analysis model
# by setting the caret method to 'lda'
##################################
set.seed(12345678)
LDA_Tune <- train(x = PMA_PreModelling_Train_LDA[,!names(PMA_PreModelling_Train_LDA) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_LDA$Log_Solubility_Class,
method = "lda",
preProc = c("center","scale"),
metric = "Accuracy",
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
LDA_Tune## Linear Discriminant Analysis
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## Pre-processing: centered (220), scaled (220)
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results:
##
## logLoss AUC prAUC Accuracy Kappa Mean_F1
## 0.8551144 0.8843082 0.7482794 0.7286501 0.5808144 0.7213929
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.7189133 0.8624052 0.7282928 0.8609278
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.7282928 0.7189133 0.2428834 0.7906592LDA_Tune$finalModel## Call:
## lda(x, y)
##
## Prior probabilities of groups:
## Low Mid High
## 0.4490011 0.2975815 0.2534175
##
## Group means:
## FP001 FP002 FP003 FP004 FP005 FP006
## Low -0.04954059 0.28017515 0.007856301 -0.06481098 0.27311405 -0.16273792
## Mid 0.10902901 0.01658496 -0.003534440 0.06840558 0.02169575 0.06934358
## High -0.04025467 -0.51588520 -0.009769270 0.03450419 -0.50937592 0.20690812
## FP007 FP008 FP009 FP010 FP011 FP012
## Low 0.0323329262 0.14386418 0.31583843 -0.09365294 -0.14025459 -0.02106485
## Mid 0.0002701702 0.08852866 -0.09565208 0.08674774 -0.07491005 -0.07402484
## High -0.0576042226 -0.35885318 -0.44727581 0.06406720 0.33646577 0.12424779
## FP013 FP014 FP015 FP016 FP017 FP018
## Low 0.3525294 0.3395685 -0.1976220 0.030404859 0.1365611 0.13768398
## Mid -0.1899409 -0.1781120 0.1382642 -0.053623483 -0.1183642 0.06064874
## High -0.4015634 -0.3924898 0.1877834 0.009097804 -0.1029648 -0.31516454
## FP019 FP020 FP021 FP022 FP023 FP024
## Low -0.007754077 -0.04457870 0.05287346 -0.003457511 0.11021758 -0.01513399
## Mid 0.005185959 0.04431530 0.07342152 0.133448185 -0.03028879 0.01295101
## High 0.007648815 0.02694553 -0.17989733 -0.150578751 -0.15971444 0.01160613
## FP025 FP026 FP027 FP028 FP029 FP030
## Low -0.046766898 0.06813605 -0.10840914 -0.03304107 0.02665863 -0.05594394
## Mid 0.069193318 -0.01026187 0.13465289 -0.12673102 0.16494312 -0.10288598
## High 0.001608949 -0.10867214 0.03395823 0.20735856 -0.24092173 0.21993690
## FP031 FP032 FP033 FP034 FP035 FP036
## Low 0.03146379 -0.07556463 -0.06110273 0.05072117 0.1716135 -0.12678018
## Mid -0.02840347 0.06991333 0.06058579 0.08314469 -0.1161756 0.11447091
## High -0.02239359 0.05178683 0.03711653 -0.18750160 -0.1676401 0.09020693
## FP037 FP038 FP039 FP040 FP041 FP042
## Low 0.07241315 -0.048516283 0.17918499 -0.08519871 0.15461568 -0.03283123
## Mid -0.05434673 0.007528016 -0.06890764 0.03718920 -0.05599678 0.13628659
## High -0.06448253 0.077120433 -0.23656070 0.10728344 -0.20819007 -0.10186792
## FP043 FP044 FP045 FP046 FP047 FP048
## Low 0.06317712 0.2702580 0.11430896 0.192916006 0.1027778 0.03562711
## Mid -0.02481643 -0.1928574 -0.04267312 -0.009685825 0.1095910 0.04162326
## High -0.08279493 -0.2523714 -0.15242087 -0.330431726 -0.3107898 -0.11200065
## FP049 FP050 FP051 FP052 FP053 FP054
## Low 0.2711896 0.08856849 0.11478038 -0.03298863 0.21730247 0.16521618
## Mid -0.1351073 0.01295101 0.05716494 0.14835698 -0.09075999 -0.08579001
## High -0.3218366 -0.17213228 -0.27049336 -0.11576299 -0.27843601 -0.19198646
## FP055 FP056 FP057 FP058 FP059 FP060
## Low -0.06129149 0.17220255 0.04189625 0.01112416 0.15084744 -0.134177171
## Mid 0.05993805 -0.07796857 0.06606136 0.06524187 -0.02290085 -0.009134416
## High 0.03821161 -0.21354930 -0.15180523 -0.09632143 -0.24037725 0.248459302
## FP061 FP062 FP063 FP064 FP065 FP066
## Low -0.01330222 -0.06975983 -0.08447482 -0.046553448 0.36098458 -0.002018379
## Mid 0.06057852 0.09401921 0.08199070 0.008294273 -0.04914397 0.010156404
## High -0.04756711 0.01319507 0.05339162 0.072742916 -0.58187830 -0.008350268
## FP067 FP068 FP069 FP070 FP071 FP072
## Low -0.03901753 -0.03145129 0.04161918 0.3288123 0.28619909 -0.25699328
## Mid 0.10605653 0.06344564 -0.02475532 -0.1371141 -0.09446362 0.07977886
## High -0.05540876 -0.01877766 -0.04467068 -0.4215750 -0.39615687 0.36165441
## FP073 FP074 FP075 FP076 FP077 FP078
## Low -0.13892731 -0.0486850322 -0.07210725 0.4980956 0.07048212 0.02157141
## Mid -0.01364004 0.0003568214 0.08342687 -0.2395438 -0.01333500 0.09981503
## High 0.26216635 0.0858403664 0.02979250 -0.6012279 -0.10922017 -0.15543006
## FP079 FP080 FP081 FP082 FP083 FP084
## Low 0.34639244 -0.05762649 0.07838924 0.33734517 -0.14043143 -0.031742701
## Mid -0.04743907 -0.03615189 -0.05403156 -0.07078979 0.18723275 0.039528547
## High -0.55802620 0.14455393 -0.07544098 -0.51457625 0.02895168 0.009823878
## FP085 FP086 FP087 FP088 FP089 FP090
## Low 0.30532425 0.10584011 0.30323360 -0.10767772 0.4204845 0.10598961
## Mid -0.08350289 -0.08106582 -0.02083049 -0.02724107 -0.2368909 -0.01246604
## High -0.44291344 -0.09233236 -0.51280382 0.22277016 -0.4668330 -0.17315218
## FP091 FP092 FP093 FP094 FP095 FP096
## Low 0.005121802 0.3533487 0.16804052 0.001219888 -0.04432336 0.05137200
## Mid 0.070343012 -0.1154491 -0.07433153 0.029581833 -0.01871684 0.03766248
## High -0.091676689 -0.4904889 -0.21044596 -0.036898552 0.10051013 -0.13524617
## FP097 FP098 FP099 FP100 FP101 FP102
## Low 0.2946914 -0.05760012 0.17327514 -0.07094028 -0.0331847631 0.13290193
## Mid -0.1136762 0.05597914 -0.02762812 0.12170912 0.0502275852 -0.01878986
## High -0.3886426 0.03632014 -0.27456317 -0.01722898 -0.0001847002 -0.21340910
## FP103 FP104 FP105 FP106 FP107 FP108
## Low 0.12235122 0.1057947 0.16481555 0.09092851 0.27949701 -0.00321884
## Mid -0.01620674 0.0247158 -0.06874443 0.04345375 -0.08489414 0.02599436
## High -0.19774881 -0.2164685 -0.21129280 -0.21213230 -0.39551943 -0.02482140
## FP109 FP110 FP111 FP112 FP113 FP114
## Low 0.10168435 -0.06946341 0.02377356 0.3898869 -0.07974936 0.06165111
## Mid 0.06488128 0.08446396 0.11864596 -0.2145986 -0.01202162 0.08727404
## High -0.25635112 0.02389036 -0.18144447 -0.4387979 0.15541533 -0.21171609
## FP115 FP116 FP117 FP118 FP119 FP120
## Low 0.02852821 -0.03068122 0.107945953 -0.05443201 -0.0227835 -0.05623436
## Mid 0.05909508 0.02277903 -0.005427792 -0.08472895 0.1422317 -0.07607813
## High -0.11993963 0.02761169 -0.184883224 0.19593677 -0.1266515 0.18897172
## FP121 FP122 FP123 FP124 FP125 FP126
## Low 0.11663727 0.006041735 0.15436685 -0.03269777 -0.02874788 -0.002036287
## Mid -0.04661987 -0.023105838 -0.05030893 0.03041381 0.02881816 0.099790899
## High -0.15191157 0.016427930 -0.21442829 0.02221924 0.01709464 -0.113573984
## FP127 FP128 FP129 FP130 FP131 FP132
## Low -0.06557830 -0.06131717 0.12681663 0.069437772 0.007894091 -0.12331459
## Mid 0.15703423 0.07991423 -0.05394273 0.002784506 0.088174009 0.11301506
## High -0.06821058 0.01479959 -0.16134817 -0.126298523 -0.117527061 0.08577622
## FP133 FP134 FP135 FP136 FP137 FP138
## Low -0.020302268 0.10305010 0.007894091 -0.011738754 0.09228709 0.07739663
## Mid -0.007549145 0.06351145 -0.039456863 0.008428781 -0.03019007 -0.09587982
## High 0.044836002 -0.25716237 0.032346536 0.010900842 -0.12806140 -0.02454097
## FP139 FP140 FP141 FP142 FP143 FP144
## Low 0.03393326 -0.05648327 0.12510155 0.03227952 0.04656681 -0.08010303
## Mid 0.06163448 0.10612273 0.05464945 -0.07863154 0.03995693 -0.09784255
## High -0.13249817 -0.02454097 -0.28582637 0.03514262 -0.12942671 0.25681924
## FP145 FP146 FP147 FP148 FP149
## Low -0.049444825 0.20785792 -0.022129579 -0.035388064 0.2479928
## Mid -0.005326253 -0.09482594 -0.008728821 0.003763156 -0.1304328
## High 0.093860041 -0.25692776 0.049458866 0.058281038 -0.2862260
## FP150 FP151 FP152 FP153 FP155 FP156
## Low -0.0145471113 -0.01833621 0.05952448 0.07666591 0.18757927 0.08155977
## Mid 0.0220318460 0.11128036 0.08737641 -0.02664544 -0.09228155 0.04225839
## High -0.0000970785 -0.09818581 -0.20806837 -0.10454642 -0.22398619 -0.19412924
## FP157 FP158 FP159 FP160 FP161 FP162
## Low 0.01464155 -0.07168155 0.07241315 0.00755913 -0.17210420 0.25056091
## Mid -0.05208092 0.05993805 0.09746131 0.17714538 -0.02481643 0.03418225
## High 0.03521559 0.05662054 -0.24274675 -0.22141034 0.33407280 -0.48407919
## FP163 FP164 FP165 FP166 FP167 FP168
## Low -0.072162232 0.309635895 -0.03470786 0.1669255 -0.0403232212 0.33629878
## Mid 0.114524513 -0.004793811 0.08300102 -0.0130429 0.0613393521 -0.01024898
## High -0.006627237 -0.542978749 -0.03597109 -0.2804401 -0.0005851502 -0.58381377
## FP169 FP170 FP171 FP172 FP173 FP174
## Low 0.3279270 0.1173360 -0.09542927 0.3613895 0.1501297 0.07871463
## Mid -0.1785070 -0.0644986 0.01967689 -0.2152948 -0.0928301 0.01153595
## High -0.3713998 -0.1321550 0.14597401 -0.3874892 -0.1569894 -0.15301170
## FP175 FP176 FP177 FP178 FP179 FP180
## Low 0.01047863 -0.0006016742 0.02415692 0.124664813 0.06495599 -0.05898743
## Mid 0.05080472 0.0051859590 0.08425364 -0.002403342 0.01575326 0.06444741
## High -0.07822452 -0.0050236991 -0.14173770 -0.218056969 -0.13358665 0.02883409
## FP181 FP182 FP183 FP184 FP185 FP186
## Low 0.20122916 -0.03298749 -0.06484156 0.2620897 0.14784168 -0.024417623
## Mid -0.05438204 -0.01150993 0.06106800 -0.1502220 -0.06457773 0.030201904
## High -0.29267524 0.07196253 0.04317470 -0.2879647 -0.18611163 0.007797453
## FP187 FP188 FP189 FP190 FP191 FP192
## Low 0.009194087 -0.07592293 0.08109314 0.2167300 -0.0190530545 0.08761784
## Mid -0.061716927 0.03718920 -0.02286417 -0.1161756 0.0008561968 -0.04810687
## High 0.056182636 0.09084875 -0.11683075 -0.2475768 0.0327524921 -0.09874928
## FP193 FP194 FP195 FP196 FP197 FP198
## Low 0.2572220 -0.02131844 -0.14712681 0.2099093 0.1945447 -0.08340218
## Mid -0.1692053 0.12505136 0.14374642 -0.1231442 -0.1721513 -0.10788352
## High -0.2570485 -0.10907288 0.09187929 -0.2273091 -0.1425386 0.27445547
## FP201 FP202 FP203 FP204 FP205 FP206
## Low -0.06764568 0.155187968 0.007780434 0.10033971 0.1640452 0.10262214
## Mid 0.04938574 -0.007328423 0.061681308 0.02399042 -0.0530136 0.01544173
## High 0.06186115 -0.266354020 -0.086215999 -0.20595163 -0.2284002 -0.19995711
## FP207 FP208 MolWeight NumBonds NumMultBonds NumRotBonds
## Low 0.2099093 0.01449529 0.6447051 0.5260887 0.4454402 0.2155584
## Mid -0.1231442 0.05765667 -0.2055106 -0.2189291 -0.1400358 -0.0940740
## High -0.2273091 -0.09338725 -0.9009527 -0.6750329 -0.6247835 -0.2714543
## NumDblBonds NumCarbon NumNitrogen NumOxygen NumSulfer NumChlorine
## Low 0.07217700 0.6263249 -0.02976857 -0.034068396 0.11971764 0.3118792
## Mid 0.07068664 -0.2418994 0.09225615 -0.005066866 0.02589293 -0.1802282
## High -0.21088755 -0.8256564 -0.05559051 0.066311736 -0.24251923 -0.3409454
## NumHalogen NumRings HydrophilicFactor SurfaceArea1 SurfaceArea2
## Low 0.3385013 0.4841073 -0.24599149 -0.09225436 -0.04168274
## Mid -0.1813798 -0.2058863 0.04475775 0.05481524 0.04393220
## High -0.3867617 -0.6159668 0.38328598 0.09908671 0.02226439
##
## Coefficients of linear discriminants:
## LD1 LD2
## FP001 0.1855954975 0.2782018361
## FP002 -0.6135782677 -0.4869325572
## FP003 -0.1171296765 0.2016916568
## FP004 -0.3276237359 0.3723988172
## FP005 -0.2936812786 0.2790433472
## FP006 -0.1580868991 -0.2175967131
## FP007 -0.0024671682 -0.0531052007
## FP008 -0.0114845200 0.0486234793
## FP009 -0.7674538872 0.2480820903
## FP010 0.1154366294 -0.0432426384
## FP011 0.3240619951 -0.0116202499
## FP012 0.0605046035 -0.3412027772
## FP013 0.1884122341 0.2680885013
## FP014 -0.0462969588 0.0444996102
## FP015 -0.0282440198 0.1238226602
## FP016 0.0172486696 0.3033577070
## FP017 -0.0599993551 0.3802235691
## FP018 -0.2954880803 0.0525242137
## FP019 -0.0386691077 0.3187903994
## FP020 -0.1324525118 0.2354473790
## FP021 0.6284314259 -0.0210429906
## FP022 -0.1352122296 0.5295282694
## FP023 -0.1032436318 -0.0584782787
## FP024 -0.2204170676 -0.4382696029
## FP025 0.1372341200 -0.1474673058
## FP026 -0.1014806293 0.5139002537
## FP027 -0.0164945482 -0.0120253131
## FP028 0.0537229491 0.1577667611
## FP029 -0.1085851472 -0.4843880547
## FP030 -0.2624947116 -0.0926482262
## FP031 0.1500340973 0.1492848152
## FP032 -0.9195073885 0.0524921754
## FP033 0.4167652293 0.0301834284
## FP034 -0.1470831193 -0.4414241905
## FP035 -0.1031841333 0.2568278829
## FP036 0.0634733352 0.1734969095
## FP037 0.3485126869 0.0247010530
## FP038 0.0836556589 0.4071005230
## FP039 -0.0670826698 -0.2989192842
## FP040 0.1544857350 0.1037763013
## FP041 -0.1669929848 -0.1325106453
## FP042 0.4963774935 -1.1426948713
## FP043 -0.0221607335 0.3203933546
## FP044 0.3380786213 0.0427068101
## FP045 0.0827810467 -0.0329890878
## FP046 -0.2172569895 -0.4220620843
## FP047 -0.1718454009 -0.1607422030
## FP048 0.1461852427 0.2231997653
## FP049 -0.0176447529 0.0503995557
## FP050 -0.0931434874 0.1582041425
## FP051 0.0354933501 -0.2253910655
## FP052 0.0722163792 -0.2519097665
## FP053 0.0646839936 -0.3813563879
## FP054 -0.1323716151 -0.0691674024
## FP055 -0.0145772704 -0.0537440907
## FP056 -0.0829152405 0.0639150900
## FP057 0.0072998013 0.0276230491
## FP058 -0.2555640653 -1.5465719028
## FP059 -0.0496023904 -0.0516000115
## FP060 -0.0431722435 0.0677726623
## FP061 -0.0421944083 0.1879922798
## FP062 0.1911762556 -0.5138627958
## FP063 0.6170638075 -0.9438104915
## FP064 -0.0485679931 -0.2176115295
## FP065 0.2361246228 -0.0047075831
## FP066 0.2009884350 -0.0228432500
## FP067 -0.1848843296 0.1433143283
## FP068 0.2085167329 1.4370826730
## FP069 -0.0248422548 -0.2317096768
## FP070 0.1570116877 -0.1629412731
## FP071 0.1037472958 -0.0148156577
## FP072 0.9050845121 -0.4236605345
## FP073 -0.2472336591 0.1211136762
## FP074 0.0373990499 0.2345652156
## FP075 0.1627371376 0.1477369498
## FP076 -0.0900720530 -0.1772856585
## FP077 0.0825293086 -0.0626189573
## FP078 -0.3701972749 -0.0990982962
## FP079 0.0188915630 0.0813004368
## FP080 0.2367191350 -0.5356534951
## FP081 -0.1840646236 -0.1404042285
## FP082 0.0468484495 -0.1146665204
## FP083 -0.3268201299 -0.4028308542
## FP084 -0.1157856537 0.1816453336
## FP085 -0.4212018704 -0.1274480979
## FP086 0.1642584339 0.2062438606
## FP087 -0.2524432340 -0.0049795450
## FP088 0.1121031520 -0.1602929235
## FP089 -0.2718104483 0.1483257871
## FP090 -0.2332962895 -0.4034552206
## FP091 0.1835121283 -0.2996565065
## FP092 -0.1535174799 -1.2205602917
## FP093 0.1672121947 0.0544042666
## FP094 -0.0996185276 -0.0098894580
## FP095 -0.1414176215 0.4405669739
## FP096 0.0379191486 -0.0775166100
## FP097 -0.1618644555 0.0201784623
## FP098 0.0226275766 -0.2730961547
## FP099 -0.0330526481 -0.4996072094
## FP100 -0.0818768698 0.0261769809
## FP101 0.1724492218 0.1212551959
## FP102 -0.2353082012 0.3259076883
## FP103 -0.0053374563 -0.0230736405
## FP104 -0.3607892425 0.2197319343
## FP105 -0.0415106954 0.0777261527
## FP106 -0.1217208654 -0.0771176930
## FP107 -0.3038114911 -0.0147591123
## FP108 0.0767082077 0.3257432271
## FP109 0.3143162185 -0.1124442829
## FP110 -0.0822873456 0.6478144230
## FP111 -0.2441480479 -0.1939900091
## FP112 0.0885632775 0.7417263121
## FP113 0.0710511228 -0.0809268393
## FP114 -0.1023952832 0.1268063683
## FP115 0.0112473204 0.1233280683
## FP116 0.2770757404 -0.4403297692
## FP117 -0.1414265453 -0.2245772609
## FP118 0.0351017221 0.3271422127
## FP119 0.4823680409 -0.2265144752
## FP120 -0.2891043456 0.2153201378
## FP121 0.0604346998 -0.1780081694
## FP122 0.1466950066 -0.1662303538
## FP123 -0.1714631887 0.1224106829
## FP124 0.0572465164 0.2722374249
## FP125 0.0346221414 -0.1065088159
## FP126 -0.3052339685 0.1098611152
## FP127 -0.0546286185 -0.2124155884
## FP128 0.1186249305 -0.4714523999
## FP129 0.3429476397 -0.2287883429
## FP130 0.4350766274 0.1935100544
## FP131 0.1564367716 -0.3379911071
## FP132 -0.0554198107 -0.2642284074
## FP133 -0.0670602326 -0.2737920071
## FP134 -0.1138548201 -0.4255466088
## FP135 -0.0669922590 -0.0022719779
## FP136 -0.0704817851 0.5719667023
## FP137 -0.2273694282 -0.6811418848
## FP138 -0.0817266666 0.2407017835
## FP139 -0.6599087522 -0.4113917131
## FP140 0.3390361543 -0.3797609179
## FP141 -0.0157110418 0.8069698276
## FP142 0.0431823975 0.1581515595
## FP143 0.1912175717 -0.1589449467
## FP144 0.3429089023 0.4151530844
## FP145 -0.1327208994 -0.1566070750
## FP146 0.0261105424 0.3403575374
## FP147 0.0104200914 -0.2086773032
## FP148 -0.0297838977 0.0689044781
## FP149 -0.0836497227 -0.2472384587
## FP150 0.0770093157 -0.0579850055
## FP151 0.1896081228 0.3455125650
## FP152 0.0005548397 -0.0359204233
## FP153 0.0984136286 0.0572128331
## FP155 0.1386220303 -0.0596584384
## FP156 -0.2514664026 0.2890610365
## FP157 -0.1302727624 0.4084761545
## FP158 0.0854522628 0.2447924860
## FP159 0.2376086442 -0.3112956132
## FP160 0.0436486408 -0.3469338103
## FP161 0.0205020373 0.0458705176
## FP162 0.1478637597 0.1048445505
## FP163 -0.0209691151 0.5435913789
## FP164 0.6441035785 -0.0313349222
## FP165 -0.0606278508 -0.4344078523
## FP166 0.2679453479 0.3599876048
## FP167 -0.3708844139 0.0824426887
## FP168 -0.1062666415 -0.0753494208
## FP169 0.0021683192 0.1907321006
## FP170 0.0666590446 -0.2347615002
## FP171 0.1073628753 -0.2795321095
## FP172 0.1591663885 0.2416815793
## FP173 -0.0142068490 0.1558127331
## FP174 -0.0925937893 -0.0857224759
## FP175 0.0019426630 -0.0965043186
## FP176 0.0231708518 0.2232212267
## FP177 0.0155403650 -0.4574333046
## FP178 -0.0528423508 -0.1767720167
## FP179 0.1010153212 -0.4442764045
## FP180 -0.0198855626 -0.3545312903
## FP181 -0.1320664614 0.1880009963
## FP182 -0.0194297745 0.3387766786
## FP183 0.4956198693 -0.0520044682
## FP184 0.1669138567 -0.1447819271
## FP185 0.1012688500 -0.1857517411
## FP186 -0.0716929025 -0.2672587281
## FP187 -0.0864040983 0.6815932105
## FP188 0.0411310049 0.1027911502
## FP189 -0.0968876840 0.0521920066
## FP190 -0.0354150309 0.0746942187
## FP191 0.0799792683 0.0507282204
## FP192 0.1491260446 -0.0308715870
## FP193 0.0530831063 0.0570077188
## FP194 -0.3101909882 0.8111375836
## FP195 0.0290554102 -0.1295186830
## FP196 -0.1251573633 0.2522715907
## FP197 -0.1679138546 0.3592871293
## FP198 0.1095925029 0.0614155060
## FP201 -0.0714239011 -0.0965672142
## FP202 0.2117368015 0.0009925958
## FP203 0.0900593816 0.4340255873
## FP204 -0.2861469330 -0.2622159232
## FP205 -0.0034706009 -0.0166735602
## FP206 0.0027292033 0.0075908940
## FP207 0.0972664077 0.0504006067
## FP208 0.1102711753 0.9489645462
## MolWeight -1.2293465238 -0.1713579830
## NumBonds -0.9800961412 0.5929706982
## NumMultBonds 0.0656262346 0.7927019690
## NumRotBonds -0.0824006362 0.5731691511
## NumDblBonds -0.4805687676 -0.4069509523
## NumCarbon 0.2036708080 -0.9808406987
## NumNitrogen 0.9513847851 0.1426724194
## NumOxygen 1.7462489612 0.4590333732
## NumSulfer 0.7164459644 -0.0449795204
## NumChlorine -0.1185379390 -0.1437736943
## NumHalogen 0.4085575775 0.3652486383
## NumRings 0.1069141579 0.4794606940
## HydrophilicFactor 0.0544416087 0.3018207102
## SurfaceArea1 1.1023992923 -0.2493095291
## SurfaceArea2 -2.2289539407 -0.4627203779
##
## Proportion of trace:
## LD1 LD2
## 0.8843 0.1157LDA_Tune$results## parameter logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 none 0.8551144 0.8843082 0.7482794 0.7286501 0.5808144 0.7213929
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.7189133 0.8624052 0.7282928 0.8609278
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.7282928 0.7189133 0.2428834 0.7906592
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 0.1984679 0.02870558 0.04579126 0.04137414 0.0633381 0.04217894
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.04339287 0.02070353 0.03963661
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.02123518 0.03963661 0.04339287 0.01379138
## Mean_Balanced_AccuracySD
## 1 0.03194615(LDA_Train_Accuracy <- LDA_Tune$results$Accuracy)## [1] 0.7286501##################################
# Identifying and plotting the
# best model predictors
##################################
# model does not support variable importance measurement
##################################
# Independently evaluating the model
# on the test set
##################################
LDA_Test <- data.frame(LDA_Observed = PMA_PreModelling_Test_LDA$Log_Solubility_Class,
LDA_Predicted = predict(LDA_Tune,
PMA_PreModelling_Test_LDA[,!names(PMA_PreModelling_Test_LDA) %in% c("Log_Solubility_Class")],
type = "raw"))
LDA_Test## LDA_Observed LDA_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High Mid
## 11 High Mid
## 12 High High
## 13 High High
## 14 High High
## 15 High High
## 16 High High
## 17 High High
## 18 High High
## 19 High High
## 20 High High
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High Mid
## 27 High High
## 28 High High
## 29 High High
## 30 High High
## 31 High Mid
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High High
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High High
## 50 High High
## 51 High High
## 52 High Mid
## 53 High Mid
## 54 High High
## 55 High High
## 56 High Mid
## 57 High High
## 58 Mid Mid
## 59 Mid Mid
## 60 Mid Mid
## 61 Mid Mid
## 62 Mid Mid
## 63 Mid High
## 64 Mid High
## 65 Mid Mid
## 66 Mid Mid
## 67 Mid Low
## 68 Mid Mid
## 69 Mid Mid
## 70 Mid Mid
## 71 Mid Mid
## 72 Mid Mid
## 73 Mid Mid
## 74 Mid Mid
## 75 Mid Mid
## 76 Mid Mid
## 77 Mid Mid
## 78 Mid Mid
## 79 Mid High
## 80 Mid Mid
## 81 Mid Mid
## 82 Mid High
## 83 Mid Low
## 84 Mid Mid
## 85 Mid Mid
## 86 Mid High
## 87 Mid Low
## 88 Mid Mid
## 89 Mid Mid
## 90 Mid Mid
## 91 Mid Mid
## 92 Mid Mid
## 93 Mid Mid
## 94 Mid Mid
## 95 Mid High
## 96 Mid Mid
## 97 Mid Mid
## 98 Mid Low
## 99 Mid Mid
## 100 Mid Mid
## 101 Mid Mid
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid Mid
## 105 Mid Low
## 106 Mid Mid
## 107 Mid Low
## 108 Mid Mid
## 109 Mid Low
## 110 Mid Low
## 111 Mid Mid
## 112 Mid Low
## 113 Mid Mid
## 114 Mid Low
## 115 Mid Mid
## 116 Mid Low
## 117 Mid Low
## 118 Mid Low
## 119 Low High
## 120 Low Low
## 121 Low Mid
## 122 Low Mid
## 123 Low Low
## 124 Low Mid
## 125 Low Low
## 126 Low Mid
## 127 Low Low
## 128 Low Low
## 129 Low Low
## 130 Low Mid
## 131 Low Low
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low Low
## 136 Low Mid
## 137 Low Mid
## 138 Low Low
## 139 Low Low
## 140 Low Mid
## 141 Low Mid
## 142 Low Low
## 143 Low Low
## 144 Low Mid
## 145 Low Mid
## 146 Low Low
## 147 Low Mid
## 148 Low Low
## 149 Low Low
## 150 Low Low
## 151 Low High
## 152 Low Mid
## 153 Low Mid
## 154 Low Low
## 155 Low Mid
## 156 Low High
## 157 Low Low
## 158 Low Low
## 159 Low Low
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Mid
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Low
## 183 Low Low
## 184 Low Low
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Low
## 226 High Mid
## 227 High High
## 228 High Mid
## 229 High High
## 230 High Mid
## 231 High Mid
## 232 High High
## 233 High High
## 234 High Mid
## 235 High High
## 236 High Mid
## 237 High Low
## 238 Mid Mid
## 239 Mid Mid
## 240 Mid Mid
## 241 Mid High
## 242 Mid Mid
## 243 Mid Mid
## 244 Mid Low
## 245 Mid Mid
## 246 Mid High
## 247 Mid Mid
## 248 Mid High
## 249 Mid High
## 250 Mid Mid
## 251 Mid Mid
## 252 Mid Mid
## 253 Mid Mid
## 254 Mid Low
## 255 Mid Low
## 256 Mid Mid
## 257 Mid Mid
## 258 Mid Mid
## 259 Mid Low
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid Mid
## 263 Mid Mid
## 264 Mid Mid
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Mid
## 268 Mid Mid
## 269 Low Mid
## 270 Low Low
## 271 Low Low
## 272 Low Low
## 273 Low Low
## 274 Low Low
## 275 Low Mid
## 276 Low Low
## 277 Low Low
## 278 Low Mid
## 279 Low Low
## 280 Low Low
## 281 Low Mid
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Mid
## 287 Low Low
## 288 Low Mid
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Mid
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Mid
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(LDA_Test_Accuracy <- Accuracy(y_pred = LDA_Test$LDA_Predicted,
y_true = LDA_Test$LDA_Observed))## [1] 0.76898731.5.3 Flexible Discriminant Analysis (FDA)
Flexible Discriminant Analysis, as a flexible extension of the linear discriminant analysis, uses optimal scoring to transform the response variable so that the data are in a better form for linear separation, and multiple adaptive regression splines to generate the discriminant surface. The algorithm is useful to model multivariate non-normality or non-linear relationships among variables within each group, allowing for a more accurate classification.
[A] The flexible discriminant analysis model from the earth and mda packages was implemented through the caret package.
[B] The model contains 2 hyperparameters:
[B.1] degree = product degree held constant at a value of 1
[B.2] nprune = number of terms made to vary across a range of values equal to 2 to 25
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves degree=1 and nprune=24
[C.2] Accuracy = 0.77500
[D] The model allows for ranking of predictors in terms of variable importance. The top-performing predictors in the model are as follows:
[D.1] MolWeight variable (numeric)
[D.2] HydrophilicFactor variable (numeric)
[D.3] SurfaceArea1 variable (numeric)
[D.4] FP204 (Structure=1) variable (factor)
[D.5] NumCarbon variable (numeric)
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.81962
Code Chunk | Output
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_FDA <- PMA_PreModelling_Train
PMA_PreModelling_Test_FDA <- PMA_PreModelling_Test
##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_FDA$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
FDA_Grid = expand.grid(degree = 1, nprune = 2:25)
##################################
# Running the flexible discriminant analysis model
# by setting the caret method to 'fda'
##################################
set.seed(12345678)
FDA_Tune <- train(x = PMA_PreModelling_Train_FDA[,!names(PMA_PreModelling_Train_FDA) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_FDA$Log_Solubility_Class,
method = "fda",
tuneGrid = FDA_Grid,
metric = "Accuracy",
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
FDA_Tune## Flexible Discriminant Analysis
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## No pre-processing
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## nprune logLoss AUC prAUC Accuracy Kappa Mean_F1
## 2 0.8231674 0.7965561 0.5553061 0.6351043 0.4301200 0.5975246
## 3 0.7048935 0.8433419 0.6347325 0.6698659 0.4850944 0.6391000
## 4 0.7039261 0.8559477 0.6675228 0.6981777 0.5308492 0.6761924
## 5 0.6657453 0.8678639 0.6943039 0.7182449 0.5620472 0.7014765
## 6 0.6527154 0.8721968 0.7303171 0.7182897 0.5638379 0.7024859
## 7 0.6324543 0.8802720 0.7420987 0.7256033 0.5729966 0.7099495
## 8 0.6156190 0.8852227 0.7471687 0.7351108 0.5881128 0.7195323
## 9 0.6036074 0.8897191 0.7534468 0.7277081 0.5761439 0.7131058
## 10 0.6023570 0.8913971 0.7608133 0.7329160 0.5849738 0.7199232
## 11 0.5928148 0.8948063 0.7662466 0.7382120 0.5932174 0.7240861
## 12 0.5886990 0.8964073 0.7732466 0.7308770 0.5828844 0.7203730
## 13 0.5937795 0.8952767 0.7690962 0.7298129 0.5810350 0.7184383
## 14 0.5992033 0.8955594 0.7692143 0.7423789 0.6005398 0.7319930
## 15 0.5843155 0.8993043 0.7719396 0.7497588 0.6118688 0.7388684
## 16 0.5786303 0.9028603 0.7756432 0.7540027 0.6189236 0.7439697
## 17 0.5708834 0.9060282 0.7819558 0.7613492 0.6294769 0.7504120
## 18 0.5781048 0.9058731 0.7800163 0.7550114 0.6193362 0.7425458
## 19 0.5809513 0.9070770 0.7842156 0.7539145 0.6178167 0.7421605
## 20 0.5828684 0.9070090 0.7876738 0.7665575 0.6373921 0.7575890
## 21 0.5723533 0.9097906 0.7892280 0.7676213 0.6394573 0.7584545
## 22 0.5686360 0.9114876 0.7938885 0.7718430 0.6458808 0.7617706
## 23 0.5676345 0.9127939 0.7965501 0.7697599 0.6428760 0.7591612
## 24 0.5628087 0.9136705 0.7967707 0.7750012 0.6510476 0.7639327
## 25 0.5647450 0.9128715 0.7937452 0.7728623 0.6475719 0.7622231
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.6121828 0.8117167 0.6043844 0.8221574
## 0.6442423 0.8317477 0.6419145 0.8374190
## 0.6760749 0.8468186 0.6806733 0.8490027
## 0.6972497 0.8568982 0.7121769 0.8579751
## 0.7000232 0.8581181 0.7098042 0.8576606
## 0.7055748 0.8598443 0.7216178 0.8617824
## 0.7153845 0.8653480 0.7312753 0.8666201
## 0.7091029 0.8609402 0.7243510 0.8624097
## 0.7157034 0.8639859 0.7329490 0.8648790
## 0.7196614 0.8668516 0.7381707 0.8680859
## 0.7160762 0.8633970 0.7337476 0.8629162
## 0.7140920 0.8628846 0.7323319 0.8627332
## 0.7277614 0.8691651 0.7450806 0.8691250
## 0.7344479 0.8730607 0.7537232 0.8733708
## 0.7396066 0.8756035 0.7595685 0.8755244
## 0.7462604 0.8784979 0.7650799 0.8799218
## 0.7384812 0.8751818 0.7550229 0.8766116
## 0.7380207 0.8746363 0.7560109 0.8759758
## 0.7526477 0.8805864 0.7721710 0.8816612
## 0.7540366 0.8815574 0.7725000 0.8824380
## 0.7582074 0.8835884 0.7744291 0.8848934
## 0.7558491 0.8828200 0.7715304 0.8839638
## 0.7605330 0.8857127 0.7773752 0.8868103
## 0.7577368 0.8845098 0.7767343 0.8855541
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.6043844 0.6121828 0.2117014 0.7119498
## 0.6419145 0.6442423 0.2232886 0.7379950
## 0.6806733 0.6760749 0.2327259 0.7614468
## 0.7121769 0.6972497 0.2394150 0.7770740
## 0.7098042 0.7000232 0.2394299 0.7790706
## 0.7216178 0.7055748 0.2418678 0.7827096
## 0.7312753 0.7153845 0.2450369 0.7903663
## 0.7243510 0.7091029 0.2425694 0.7850215
## 0.7329490 0.7157034 0.2443053 0.7898446
## 0.7381707 0.7196614 0.2460707 0.7932565
## 0.7337476 0.7160762 0.2436257 0.7897366
## 0.7323319 0.7140920 0.2432710 0.7884883
## 0.7450806 0.7277614 0.2474596 0.7984632
## 0.7537232 0.7344479 0.2499196 0.8037543
## 0.7595685 0.7396066 0.2513342 0.8076050
## 0.7650799 0.7462604 0.2537831 0.8123791
## 0.7550229 0.7384812 0.2516705 0.8068315
## 0.7560109 0.7380207 0.2513048 0.8063285
## 0.7721710 0.7526477 0.2555192 0.8166171
## 0.7725000 0.7540366 0.2558738 0.8177970
## 0.7744291 0.7582074 0.2572810 0.8208979
## 0.7715304 0.7558491 0.2565866 0.8193345
## 0.7773752 0.7605330 0.2583337 0.8231229
## 0.7767343 0.7577368 0.2576208 0.8211233
##
## Tuning parameter 'degree' was held constant at a value of 1
## Accuracy was used to select the optimal model using the largest value.
## The final values used for the model were degree = 1 and nprune = 24.FDA_Tune$finalModel## Call:
## mda::fda(formula = .outcome ~ ., data = dat, weights = wts, method = earth::earth,
## degree = param$degree, nprune = param$nprune)
##
## Dimension: 2
##
## Percent Between-Group Variance Explained:
## v1 v2
## 87.5 100.0
##
## Training Misclassification Error: 0.18297 ( N = 951 )FDA_Tune$results## degree nprune logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 1 2 0.8231674 0.7965561 0.5553061 0.6351043 0.4301200 0.5975246
## 2 1 3 0.7048935 0.8433419 0.6347325 0.6698659 0.4850944 0.6391000
## 3 1 4 0.7039261 0.8559477 0.6675228 0.6981777 0.5308492 0.6761924
## 4 1 5 0.6657453 0.8678639 0.6943039 0.7182449 0.5620472 0.7014765
## 5 1 6 0.6527154 0.8721968 0.7303171 0.7182897 0.5638379 0.7024859
## 6 1 7 0.6324543 0.8802720 0.7420987 0.7256033 0.5729966 0.7099495
## 7 1 8 0.6156190 0.8852227 0.7471687 0.7351108 0.5881128 0.7195323
## 8 1 9 0.6036074 0.8897191 0.7534468 0.7277081 0.5761439 0.7131058
## 9 1 10 0.6023570 0.8913971 0.7608133 0.7329160 0.5849738 0.7199232
## 10 1 11 0.5928148 0.8948063 0.7662466 0.7382120 0.5932174 0.7240861
## 11 1 12 0.5886990 0.8964073 0.7732466 0.7308770 0.5828844 0.7203730
## 12 1 13 0.5937795 0.8952767 0.7690962 0.7298129 0.5810350 0.7184383
## 13 1 14 0.5992033 0.8955594 0.7692143 0.7423789 0.6005398 0.7319930
## 14 1 15 0.5843155 0.8993043 0.7719396 0.7497588 0.6118688 0.7388684
## 15 1 16 0.5786303 0.9028603 0.7756432 0.7540027 0.6189236 0.7439697
## 16 1 17 0.5708834 0.9060282 0.7819558 0.7613492 0.6294769 0.7504120
## 17 1 18 0.5781048 0.9058731 0.7800163 0.7550114 0.6193362 0.7425458
## 18 1 19 0.5809513 0.9070770 0.7842156 0.7539145 0.6178167 0.7421605
## 19 1 20 0.5828684 0.9070090 0.7876738 0.7665575 0.6373921 0.7575890
## 20 1 21 0.5723533 0.9097906 0.7892280 0.7676213 0.6394573 0.7584545
## 21 1 22 0.5686360 0.9114876 0.7938885 0.7718430 0.6458808 0.7617706
## 22 1 23 0.5676345 0.9127939 0.7965501 0.7697599 0.6428760 0.7591612
## 23 1 24 0.5628087 0.9136705 0.7967707 0.7750012 0.6510476 0.7639327
## 24 1 25 0.5647450 0.9128715 0.7937452 0.7728623 0.6475719 0.7622231
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.6121828 0.8117167 0.6043844 0.8221574
## 2 0.6442423 0.8317477 0.6419145 0.8374190
## 3 0.6760749 0.8468186 0.6806733 0.8490027
## 4 0.6972497 0.8568982 0.7121769 0.8579751
## 5 0.7000232 0.8581181 0.7098042 0.8576606
## 6 0.7055748 0.8598443 0.7216178 0.8617824
## 7 0.7153845 0.8653480 0.7312753 0.8666201
## 8 0.7091029 0.8609402 0.7243510 0.8624097
## 9 0.7157034 0.8639859 0.7329490 0.8648790
## 10 0.7196614 0.8668516 0.7381707 0.8680859
## 11 0.7160762 0.8633970 0.7337476 0.8629162
## 12 0.7140920 0.8628846 0.7323319 0.8627332
## 13 0.7277614 0.8691651 0.7450806 0.8691250
## 14 0.7344479 0.8730607 0.7537232 0.8733708
## 15 0.7396066 0.8756035 0.7595685 0.8755244
## 16 0.7462604 0.8784979 0.7650799 0.8799218
## 17 0.7384812 0.8751818 0.7550229 0.8766116
## 18 0.7380207 0.8746363 0.7560109 0.8759758
## 19 0.7526477 0.8805864 0.7721710 0.8816612
## 20 0.7540366 0.8815574 0.7725000 0.8824380
## 21 0.7582074 0.8835884 0.7744291 0.8848934
## 22 0.7558491 0.8828200 0.7715304 0.8839638
## 23 0.7605330 0.8857127 0.7773752 0.8868103
## 24 0.7577368 0.8845098 0.7767343 0.8855541
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.6043844 0.6121828 0.2117014 0.7119498
## 2 0.6419145 0.6442423 0.2232886 0.7379950
## 3 0.6806733 0.6760749 0.2327259 0.7614468
## 4 0.7121769 0.6972497 0.2394150 0.7770740
## 5 0.7098042 0.7000232 0.2394299 0.7790706
## 6 0.7216178 0.7055748 0.2418678 0.7827096
## 7 0.7312753 0.7153845 0.2450369 0.7903663
## 8 0.7243510 0.7091029 0.2425694 0.7850215
## 9 0.7329490 0.7157034 0.2443053 0.7898446
## 10 0.7381707 0.7196614 0.2460707 0.7932565
## 11 0.7337476 0.7160762 0.2436257 0.7897366
## 12 0.7323319 0.7140920 0.2432710 0.7884883
## 13 0.7450806 0.7277614 0.2474596 0.7984632
## 14 0.7537232 0.7344479 0.2499196 0.8037543
## 15 0.7595685 0.7396066 0.2513342 0.8076050
## 16 0.7650799 0.7462604 0.2537831 0.8123791
## 17 0.7550229 0.7384812 0.2516705 0.8068315
## 18 0.7560109 0.7380207 0.2513048 0.8063285
## 19 0.7721710 0.7526477 0.2555192 0.8166171
## 20 0.7725000 0.7540366 0.2558738 0.8177970
## 21 0.7744291 0.7582074 0.2572810 0.8208979
## 22 0.7715304 0.7558491 0.2565866 0.8193345
## 23 0.7773752 0.7605330 0.2583337 0.8231229
## 24 0.7767343 0.7577368 0.2576208 0.8211233
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 0.09948687 0.04087009 0.03619624 0.03963242 0.06041235 0.04265308
## 2 0.07228017 0.02889036 0.06017162 0.03947035 0.06352563 0.04335516
## 3 0.11038894 0.03671996 0.06862930 0.04024586 0.06243504 0.04835711
## 4 0.09839783 0.02938232 0.05920073 0.04694960 0.07182258 0.05358417
## 5 0.08870837 0.02655585 0.04142467 0.04777716 0.07255334 0.05197150
## 6 0.08238747 0.02336353 0.03835266 0.03650564 0.05553718 0.04337315
## 7 0.08266054 0.02320992 0.04006196 0.03992764 0.06208000 0.04615102
## 8 0.07381815 0.02017468 0.03568617 0.03341162 0.05414991 0.04061509
## 9 0.07772130 0.02183655 0.03979534 0.03596252 0.05665629 0.04070263
## 10 0.09035717 0.02634528 0.05022428 0.03965763 0.06075621 0.04066830
## 11 0.10159460 0.02678698 0.04830454 0.04191946 0.06470356 0.04544607
## 12 0.09202283 0.02490803 0.04357916 0.04263748 0.06613300 0.04552389
## 13 0.10058720 0.02558479 0.04532034 0.04183650 0.06487482 0.04406681
## 14 0.09376399 0.02445959 0.04264515 0.04302226 0.06674575 0.04326361
## 15 0.09316035 0.02497500 0.04284854 0.05250267 0.08130657 0.05268271
## 16 0.09393848 0.02488505 0.04311412 0.05161431 0.07995923 0.05322248
## 17 0.09703986 0.02473156 0.04230966 0.04644660 0.07202234 0.05052868
## 18 0.09559186 0.02277604 0.03965171 0.04992044 0.07725553 0.05444959
## 19 0.09312121 0.02264733 0.03868544 0.04267094 0.06622318 0.04233906
## 20 0.08971567 0.02008386 0.03526441 0.03609107 0.05534650 0.03378561
## 21 0.08664476 0.01971627 0.03431745 0.03138547 0.04762940 0.03031535
## 22 0.09144519 0.01985911 0.03244006 0.03465673 0.05208536 0.03425770
## 23 0.09620443 0.02116479 0.03516026 0.03470007 0.05222981 0.03495379
## 24 0.09509037 0.02049175 0.03525880 0.03965186 0.06002964 0.03848172
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.04475433 0.01926660 0.04367160
## 2 0.04662095 0.02113372 0.04224597
## 3 0.04971564 0.01891130 0.05076823
## 4 0.05512604 0.02236497 0.05166574
## 5 0.05318712 0.02308890 0.05263360
## 6 0.04274462 0.01682433 0.04556430
## 7 0.04831790 0.01974605 0.04522588
## 8 0.04360315 0.01839926 0.03782123
## 9 0.04402350 0.01902869 0.03612402
## 10 0.04319868 0.01995639 0.03978912
## 11 0.04707342 0.02124146 0.04356573
## 12 0.04651388 0.02218031 0.04668381
## 13 0.04542620 0.02172764 0.04411720
## 14 0.04439086 0.02295166 0.04523679
## 15 0.05442588 0.02756405 0.05227698
## 16 0.05393760 0.02689334 0.05467782
## 17 0.04958206 0.02427961 0.05207827
## 18 0.05368056 0.02572243 0.05687184
## 19 0.04433031 0.02249381 0.04093264
## 20 0.03668609 0.01882653 0.03075766
## 21 0.03158621 0.01607152 0.03196202
## 22 0.03476541 0.01702988 0.03542179
## 23 0.03548338 0.01683543 0.03547790
## 24 0.03963436 0.01958777 0.03827923
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.02145219 0.04367160 0.04475433 0.01321081
## 2 0.02112615 0.04224597 0.04662095 0.01315678
## 3 0.01969298 0.05076823 0.04971564 0.01341529
## 4 0.02296701 0.05166574 0.05512604 0.01564987
## 5 0.02419160 0.05263360 0.05318712 0.01592572
## 6 0.01780218 0.04556430 0.04274462 0.01216855
## 7 0.01998599 0.04522588 0.04831790 0.01330921
## 8 0.01585955 0.03782123 0.04360315 0.01113721
## 9 0.01844127 0.03612402 0.04402350 0.01198751
## 10 0.02154928 0.03978912 0.04319868 0.01321921
## 11 0.02122751 0.04356573 0.04707342 0.01397315
## 12 0.02201389 0.04668381 0.04651388 0.01421249
## 13 0.02159015 0.04411720 0.04542620 0.01394550
## 14 0.02304081 0.04523679 0.04439086 0.01434075
## 15 0.02817419 0.05227698 0.05442588 0.01750089
## 16 0.02765826 0.05467782 0.05393760 0.01720477
## 17 0.02388479 0.05207827 0.04958206 0.01548220
## 18 0.02575125 0.05687184 0.05368056 0.01664015
## 19 0.02308966 0.04093264 0.04433031 0.01422365
## 20 0.02032225 0.03075766 0.03668609 0.01203036
## 21 0.01802909 0.03196202 0.03158621 0.01046182
## 22 0.01913991 0.03542179 0.03476541 0.01155224
## 23 0.01877573 0.03547790 0.03548338 0.01156669
## 24 0.02169021 0.03827923 0.03963436 0.01321729
## Mean_Balanced_AccuracySD
## 1 0.03172452
## 2 0.03367686
## 3 0.03411836
## 4 0.03852057
## 5 0.03779744
## 6 0.02945849
## 7 0.03355106
## 8 0.03055172
## 9 0.03098711
## 10 0.03112161
## 11 0.03383014
## 12 0.03399820
## 13 0.03334019
## 14 0.03335832
## 15 0.04072363
## 16 0.04010936
## 17 0.03653263
## 18 0.03931677
## 19 0.03309588
## 20 0.02737749
## 21 0.02336610
## 22 0.02557241
## 23 0.02586424
## 24 0.02933889(FDA_Train_Accuracy <- FDA_Tune$results[FDA_Tune$results$degree==FDA_Tune$bestTune$degree &
FDA_Tune$results$nprune==FDA_Tune$bestTune$nprune,
c("Accuracy")])## [1] 0.7750012##################################
# Identifying and plotting the
# best model predictors
##################################
FDA_VarImp <- varImp(FDA_Tune, scale = TRUE)
plot(FDA_VarImp,
top=25,
scales=list(y=list(cex = .95)),
main="Ranked Variable Importance : Flexible Discriminant Analysis",
xlab="Scaled Variable Importance Metrics",
ylab="Predictors",
cex=2,
origin=0,
alpha=0.45)
##################################
# Independently evaluating the model
# on the test set
##################################
FDA_Test <- data.frame(FDA_Observed = PMA_PreModelling_Test_FDA$Log_Solubility_Class,
FDA_Predicted = predict(FDA_Tune,
PMA_PreModelling_Test_FDA[,!names(PMA_PreModelling_Test_FDA) %in% c("Log_Solubility_Class")],
type = "raw"))
FDA_Test## FDA_Observed FDA_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Mid
## 13 High High
## 14 High High
## 15 High High
## 16 High High
## 17 High High
## 18 High High
## 19 High High
## 20 High Mid
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High High
## 27 High High
## 28 High High
## 29 High Low
## 30 High High
## 31 High Low
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High Mid
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High Mid
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High High
## 50 High Mid
## 51 High High
## 52 High Mid
## 53 High High
## 54 High High
## 55 High Mid
## 56 High High
## 57 High Mid
## 58 Mid Mid
## 59 Mid Mid
## 60 Mid Mid
## 61 Mid Mid
## 62 Mid High
## 63 Mid High
## 64 Mid High
## 65 Mid High
## 66 Mid Low
## 67 Mid Mid
## 68 Mid Mid
## 69 Mid High
## 70 Mid Mid
## 71 Mid Mid
## 72 Mid Low
## 73 Mid Mid
## 74 Mid Low
## 75 Mid High
## 76 Mid Mid
## 77 Mid Mid
## 78 Mid Mid
## 79 Mid Mid
## 80 Mid Mid
## 81 Mid Mid
## 82 Mid High
## 83 Mid Mid
## 84 Mid Mid
## 85 Mid Mid
## 86 Mid High
## 87 Mid Low
## 88 Mid Mid
## 89 Mid Mid
## 90 Mid Mid
## 91 Mid Mid
## 92 Mid Mid
## 93 Mid Mid
## 94 Mid Mid
## 95 Mid Mid
## 96 Mid Mid
## 97 Mid Low
## 98 Mid Low
## 99 Mid Mid
## 100 Mid Mid
## 101 Mid Mid
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid Mid
## 105 Mid Low
## 106 Mid Mid
## 107 Mid Mid
## 108 Mid Mid
## 109 Mid Low
## 110 Mid Low
## 111 Mid Mid
## 112 Mid Mid
## 113 Mid Mid
## 114 Mid Mid
## 115 Mid Low
## 116 Mid Low
## 117 Mid Low
## 118 Mid Mid
## 119 Low Low
## 120 Low Low
## 121 Low Low
## 122 Low Mid
## 123 Low Low
## 124 Low Low
## 125 Low Low
## 126 Low Low
## 127 Low Low
## 128 Low Low
## 129 Low Mid
## 130 Low Low
## 131 Low Low
## 132 Low Low
## 133 Low Mid
## 134 Low Low
## 135 Low Low
## 136 Low Low
## 137 Low Low
## 138 Low Low
## 139 Low Low
## 140 Low Mid
## 141 Low Low
## 142 Low Mid
## 143 Low Low
## 144 Low Mid
## 145 Low Mid
## 146 Low Mid
## 147 Low Low
## 148 Low Low
## 149 Low Low
## 150 Low Low
## 151 Low Mid
## 152 Low Low
## 153 Low Low
## 154 Low Low
## 155 Low Low
## 156 Low Low
## 157 Low Low
## 158 Low Low
## 159 Low Low
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Low
## 183 Low Low
## 184 Low Low
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Mid
## 226 High High
## 227 High High
## 228 High Mid
## 229 High High
## 230 High Mid
## 231 High High
## 232 High High
## 233 High High
## 234 High High
## 235 High High
## 236 High High
## 237 High Low
## 238 Mid Mid
## 239 Mid High
## 240 Mid Mid
## 241 Mid High
## 242 Mid High
## 243 Mid High
## 244 Mid Mid
## 245 Mid Mid
## 246 Mid High
## 247 Mid Mid
## 248 Mid Mid
## 249 Mid Mid
## 250 Mid Mid
## 251 Mid Mid
## 252 Mid Mid
## 253 Mid Mid
## 254 Mid Low
## 255 Mid Mid
## 256 Mid High
## 257 Mid Mid
## 258 Mid Mid
## 259 Mid Mid
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid Mid
## 263 Mid Mid
## 264 Mid Mid
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Mid
## 268 Mid Mid
## 269 Low Low
## 270 Low Low
## 271 Low Low
## 272 Low Low
## 273 Low Low
## 274 Low Low
## 275 Low Mid
## 276 Low Low
## 277 Low Low
## 278 Low Mid
## 279 Low Low
## 280 Low Low
## 281 Low Low
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Low
## 287 Low Low
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Mid
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(FDA_Test_Accuracy <- Accuracy(y_pred = FDA_Test$FDA_Predicted,
y_true = FDA_Test$FDA_Observed))## [1] 0.81962031.5.4 Mixture Discriminant Analysis (MDA)
Mixture Discriminant Analysis, as an improvement to the restrictions of the linear discriminant analysis towards having all classes coming from a single normal (or Gaussian) distribution, applies the assumption that each class is a Gaussian mixture of sub-classes. The algorithm treats each data point as having the probability of belonging to each class. Equality of covariance matrix among classes, is still assumed.
[A] The mixture discriminant analysis model from the mda package was implemented through the caret package.
[B] The model contains 1 hyperparameter:
[B.1] subclasses = number of subclasses per class made to vary across a range of values equal to 1 to 8
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves subclasses=6
[C.2] Accuracy = 0.74344
[D] The model does not allow for ranking of predictors in terms of variable importance.
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.71519
Code Chunk | Output
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_MDA <- PMA_PreModelling_Train
PMA_PreModelling_Test_MDA <- PMA_PreModelling_Test
##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_MDA$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
MDA_Grid = expand.grid(subclasses = 1:8)
##################################
# Running the mixture discriminant analysis model
# by setting the caret method to 'mda'
##################################
set.seed(12345678)
MDA_Tune <- train(x = PMA_PreModelling_Train_MDA[,!names(PMA_PreModelling_Train_MDA) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_MDA$Log_Solubility_Class,
method = "mda",
tuneGrid = MDA_Grid,
tries = 40,
metric = "Accuracy",
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
MDA_Tune## Mixture Discriminant Analysis
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## No pre-processing
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## subclasses logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 0.8703527 0.8840328 0.7491824 0.7249985 0.5752189 0.7180853
## 2 1.4314632 0.8688693 0.7189988 0.7131707 0.5589285 0.7045055
## 3 2.0595434 0.8581014 0.7049035 0.6922689 0.5285097 0.6838840
## 4 2.2740159 0.8712859 0.6974792 0.7330198 0.5892480 0.7238572
## 5 2.5720199 0.8718619 0.6727550 0.7290305 0.5846168 0.7234769
## 6 2.9189561 0.8744312 0.6661658 0.7434488 0.6057253 0.7364177
## 7 3.2109649 0.8701668 0.6325790 0.7342656 0.5902093 0.7273326
## 8 3.6063295 0.8606245 0.5902870 0.7330467 0.5900236 0.7283174
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.7155190 0.8603738 0.7258070 0.8590583
## 0.7042850 0.8563475 0.7085791 0.8534143
## 0.6845145 0.8473993 0.6928273 0.8429228
## 0.7254459 0.8664294 0.7303821 0.8641301
## 0.7256188 0.8648123 0.7283093 0.8610513
## 0.7372350 0.8719875 0.7437723 0.8692227
## 0.7262013 0.8658409 0.7335805 0.8638550
## 0.7294932 0.8662003 0.7331427 0.8628440
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.7258070 0.7155190 0.2416662 0.7879464
## 0.7085791 0.7042850 0.2377236 0.7803162
## 0.6928273 0.6845145 0.2307563 0.7659569
## 0.7303821 0.7254459 0.2443399 0.7959376
## 0.7283093 0.7256188 0.2430102 0.7952155
## 0.7437723 0.7372350 0.2478163 0.8046113
## 0.7335805 0.7262013 0.2447552 0.7960211
## 0.7331427 0.7294932 0.2443489 0.7978467
##
## Accuracy was used to select the optimal model using the largest value.
## The final value used for the model was subclasses = 6.MDA_Tune$finalModel## Call:
## mda::mda(formula = as.formula(".outcome ~ ."), data = dat, subclasses = param$subclasses,
## tries = 40)
##
## Dimension: 17
##
## Percent Between-Group Variance Explained:
## v1 v2 v3 v4 v5 v6 v7 v8 v9 v10 v11
## 21.25 39.53 57.04 67.48 73.69 79.66 83.48 86.71 89.26 91.61 93.63
## v12 v13 v14 v15 v16 v17
## 95.30 96.79 97.86 98.87 99.50 100.00
##
## Degrees of Freedom (per dimension): 221
##
## Training Misclassification Error: 0.08517 ( N = 951 )
##
## Deviance: 904.276MDA_Tune$results## subclasses logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 1 0.8703527 0.8840328 0.7491824 0.7249985 0.5752189 0.7180853
## 2 2 1.4314632 0.8688693 0.7189988 0.7131707 0.5589285 0.7045055
## 3 3 2.0595434 0.8581014 0.7049035 0.6922689 0.5285097 0.6838840
## 4 4 2.2740159 0.8712859 0.6974792 0.7330198 0.5892480 0.7238572
## 5 5 2.5720199 0.8718619 0.6727550 0.7290305 0.5846168 0.7234769
## 6 6 2.9189561 0.8744312 0.6661658 0.7434488 0.6057253 0.7364177
## 7 7 3.2109649 0.8701668 0.6325790 0.7342656 0.5902093 0.7273326
## 8 8 3.6063295 0.8606245 0.5902870 0.7330467 0.5900236 0.7283174
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.7155190 0.8603738 0.7258070 0.8590583
## 2 0.7042850 0.8563475 0.7085791 0.8534143
## 3 0.6845145 0.8473993 0.6928273 0.8429228
## 4 0.7254459 0.8664294 0.7303821 0.8641301
## 5 0.7256188 0.8648123 0.7283093 0.8610513
## 6 0.7372350 0.8719875 0.7437723 0.8692227
## 7 0.7262013 0.8658409 0.7335805 0.8638550
## 8 0.7294932 0.8662003 0.7331427 0.8628440
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.7258070 0.7155190 0.2416662 0.7879464
## 2 0.7085791 0.7042850 0.2377236 0.7803162
## 3 0.6928273 0.6845145 0.2307563 0.7659569
## 4 0.7303821 0.7254459 0.2443399 0.7959376
## 5 0.7283093 0.7256188 0.2430102 0.7952155
## 6 0.7437723 0.7372350 0.2478163 0.8046113
## 7 0.7335805 0.7262013 0.2447552 0.7960211
## 8 0.7331427 0.7294932 0.2443489 0.7978467
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 0.2071882 0.02875117 0.04309919 0.04137979 0.06333215 0.03946820
## 2 0.3031995 0.02569702 0.04607195 0.03314219 0.05009314 0.03172107
## 3 0.3833903 0.02648458 0.04207273 0.04967806 0.07782410 0.04602288
## 4 0.4099364 0.02745111 0.04275287 0.03689183 0.05853830 0.03567472
## 5 0.5258283 0.02788445 0.03678231 0.04295809 0.06628696 0.04188057
## 6 0.7907319 0.03087419 0.05538568 0.02603226 0.04139184 0.02669914
## 7 0.6162988 0.02612881 0.04023668 0.03507430 0.05490946 0.03490828
## 8 0.7329378 0.02489811 0.03503678 0.03913776 0.06115327 0.03924767
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.04168410 0.02121073 0.03527376
## 2 0.03331193 0.01674276 0.02872397
## 3 0.05136633 0.02717656 0.04153757
## 4 0.03985896 0.02055470 0.03246725
## 5 0.04219136 0.02314163 0.04314999
## 6 0.03134817 0.01454689 0.02343827
## 7 0.03842495 0.01814152 0.03074948
## 8 0.03972675 0.02131902 0.04015380
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.02177393 0.03527376 0.04168410 0.013793262
## 2 0.01754450 0.02872397 0.03331193 0.011047397
## 3 0.02726463 0.04153757 0.05136633 0.016559352
## 4 0.01988305 0.03246725 0.03985896 0.012297278
## 5 0.02244001 0.04314999 0.04219136 0.014319365
## 6 0.01422668 0.02343827 0.03134817 0.008677421
## 7 0.01868891 0.03074948 0.03842495 0.011691433
## 8 0.02032141 0.04015380 0.03972675 0.013045919
## Mean_Balanced_AccuracySD
## 1 0.03141383
## 2 0.02476206
## 3 0.03919795
## 4 0.03012209
## 5 0.03255895
## 6 0.02255665
## 7 0.02820524
## 8 0.03047643(MDA_Train_Accuracy <- MDA_Tune$results[MDA_Tune$results$subclasses==MDA_Tune$bestTune$subclasses,
c("Accuracy")])## [1] 0.7434488##################################
# Identifying and plotting the
# best model predictors
##################################
# model does not support variable importance measurement
##################################
# Independently evaluating the model
# on the test set
##################################
MDA_Test <- data.frame(MDA_Observed = PMA_PreModelling_Test_MDA$Log_Solubility_Class,
MDA_Predicted = predict(MDA_Tune,
PMA_PreModelling_Test_MDA[,!names(PMA_PreModelling_Test_MDA) %in% c("Log_Solubility_Class")],
type = "raw"))
MDA_Test## MDA_Observed MDA_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Mid
## 13 High High
## 14 High High
## 15 High Mid
## 16 High High
## 17 High Mid
## 18 High High
## 19 High High
## 20 High High
## 21 High High
## 22 High Mid
## 23 High High
## 24 High Mid
## 25 High High
## 26 High Mid
## 27 High Mid
## 28 High High
## 29 High Mid
## 30 High Mid
## 31 High Mid
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High Mid
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## 313 Mid Mid
## 314 High Mid
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(MDA_Test_Accuracy <- Accuracy(y_pred = MDA_Test$MDA_Predicted,
y_true = MDA_Test$MDA_Observed))## [1] 0.71518991.5.5 Naive Bayes (NB)
Naive Bayes Classifier categorizes instances by applying Bayes Theorem in determining posterior probabilities as conditioned by the likelihood of features, and prior probabilities pertaining to both events and features. The algorithm naively assumes independence between features and assigns the same weight (degree of significance) to all given features. The class conditional probabilities and the prior probabilities are calculated to yield the posterior probability, and operates by returning the class, which has the maximum posterior probability out of a group of classes.
[A] The naive bayes model from the klaR package was implemented through the caret package.
[B] The model contains 3 hyperparameters:
[B.1] fL = laplace correction held constant at a value of 2
[B.2] adjust = bandwidth adjustment held constant at a value of FALSE
[B.3] usekernel = distribution type made to vary across a range of levels equal to TRUE and FALSE
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves fL=2, adjust=FALSE and usekernel=FALSE
[C.2] Accuracy = 0.64346
[D] The model does not allow for ranking of predictors in terms of variable importance.
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.65506
Code Chunk | Output
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_NB <- PMA_PreModelling_Train
PMA_PreModelling_Test_NB <- PMA_PreModelling_Test
##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_NB$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
NB_Grid = data.frame(usekernel = c(TRUE, FALSE), fL = 2, adjust = FALSE)
##################################
# Running the naive bayes model
# by setting the caret method to 'nb'
##################################
set.seed(12345678)
NB_Tune <- train(x = PMA_PreModelling_Train_NB[,!names(PMA_PreModelling_Train_NB) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_NB$Log_Solubility_Class,
method = "nb",
tuneGrid = NB_Grid,
metric = "Accuracy",
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
NB_Tune## Naive Bayes
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## No pre-processing
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## usekernel logLoss AUC prAUC Accuracy Kappa Mean_F1
## FALSE 3.224027 0.8205606 0.6408077 0.6434612 0.4593777 0.6286132
## TRUE NaN NaN NaN NaN NaN NaN
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.6398324 0.8254896 0.632263 0.8219493
## NaN NaN NaN NaN
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.632263 0.6398324 0.2144871 0.732661
## NaN NaN NaN NaN
##
## Tuning parameter 'fL' was held constant at a value of 2
## Tuning
## parameter 'adjust' was held constant at a value of FALSE
## Accuracy was used to select the optimal model using the largest value.
## The final values used for the model were fL = 2, usekernel = FALSE and adjust
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## High 0.5183673 0.4816327
##
## $tables$FP083
## var
## grouping 0 1
## Low 0.7865429 0.2134571
## Mid 0.6411150 0.3588850
## High 0.7102041 0.2897959
##
## $tables$FP084
## var
## grouping 0 1
## Low 0.7262181 0.2737819
## Mid 0.6933798 0.3066202
## High 0.7061224 0.2938776
##
## $tables$FP085
## var
## grouping 0 1
## Low 0.61020882 0.38979118
## Mid 0.77700348 0.22299652
## High 0.93061224 0.06938776
##
## $tables$FP086
## var
## grouping 0 1
## Low 0.6821346 0.3178654
## Mid 0.7630662 0.2369338
## High 0.7673469 0.2326531
##
## $tables$FP087
## var
## grouping 0 1
## Low 0.1415313 0.8584687
## Mid 0.2857143 0.7142857
## High 0.5020408 0.4979592
##
## $tables$FP088
## var
## grouping 0 1
## Low 0.7819026 0.2180974
## Mid 0.7456446 0.2543554
## High 0.6367347 0.3632653
##
## $tables$FP089
## var
## grouping 0 1
## Low 0.57076566 0.42923434
## Mid 0.85017422 0.14982578
## High 0.94693878 0.05306122
##
## $tables$FP090
## var
## grouping 0 1
## Low 0.7030162 0.2969838
## Mid 0.7526132 0.2473868
## High 0.8204082 0.1795918
##
## $tables$FP091
## var
## grouping 0 1
## Low 0.7703016 0.2296984
## Mid 0.7421603 0.2578397
## High 0.8081633 0.1918367
##
## $tables$FP092
## var
## grouping 0 1
## Low 0.60324826 0.39675174
## Mid 0.80139373 0.19860627
## High 0.95918367 0.04081633
##
## $tables$FP093
## var
## grouping 0 1
## Low 0.6821346 0.3178654
## Mid 0.7839721 0.2160279
## High 0.8408163 0.1591837
##
## $tables$FP094
## var
## grouping 0 1
## Low 0.7656613 0.2343387
## Mid 0.7526132 0.2473868
## High 0.7795918 0.2204082
##
## $tables$FP095
## var
## grouping 0 1
## Low 0.7958237 0.2041763
## Mid 0.7839721 0.2160279
## High 0.7346939 0.2653061
##
## $tables$FP096
## var
## grouping 0 1
## Low 0.7587007 0.2412993
## Mid 0.7630662 0.2369338
## High 0.8326531 0.1673469
##
## $tables$FP097
## var
## grouping 0 1
## Low 0.63805104 0.36194896
## Mid 0.80836237 0.19163763
## High 0.92244898 0.07755102
##
## $tables$FP098
## var
## grouping 0 1
## Low 0.7842227 0.2157773
## Mid 0.7351916 0.2648084
## High 0.7428571 0.2571429
##
## $tables$FP099
## var
## grouping 0 1
## Low 0.6983759 0.3016241
## Mid 0.7804878 0.2195122
## High 0.8816327 0.1183673
##
## $tables$FP100
## var
## grouping 0 1
## Low 0.7958237 0.2041763
## Mid 0.7142857 0.2857143
## High 0.7714286 0.2285714
##
## $tables$FP101
## var
## grouping 0 1
## Low 0.7749420 0.2250580
## Mid 0.7386760 0.2613240
## High 0.7591837 0.2408163
##
## $tables$FP102
## var
## grouping 0 1
## Low 0.7424594 0.2575406
## Mid 0.8013937 0.1986063
## High 0.8775510 0.1224490
##
## $tables$FP103
## var
## grouping 0 1
## Low 0.7285383 0.2714617
## Mid 0.7839721 0.2160279
## High 0.8571429 0.1428571
##
## $tables$FP104
## var
## grouping 0 1
## Low 0.7308585 0.2691415
## Mid 0.7630662 0.2369338
## High 0.8612245 0.1387755
##
## $tables$FP105
## var
## grouping 0 1
## Low 0.7146172 0.2853828
## Mid 0.8083624 0.1916376
## High 0.8653061 0.1346939
##
## $tables$FP106
## var
## grouping 0 1
## Low 0.7703016 0.2296984
## Mid 0.7874564 0.2125436
## High 0.8857143 0.1142857
##
## $tables$FP107
## var
## grouping 0 1
## Low 0.67285383 0.32714617
## Mid 0.81881533 0.18118467
## High 0.94285714 0.05714286
##
## $tables$FP108
## var
## grouping 0 1
## Low 0.7935035 0.2064965
## Mid 0.7804878 0.2195122
## High 0.8000000 0.2000000
##
## $tables$FP109
## var
## grouping 0 1
## Low 0.78190255 0.21809745
## Mid 0.79442509 0.20557491
## High 0.91428571 0.08571429
##
## $tables$FP110
## var
## grouping 0 1
## Low 0.8190255 0.1809745
## Mid 0.7560976 0.2439024
## High 0.7795918 0.2204082
##
## $tables$FP111
## var
## grouping 0 1
## Low 0.7911833 0.2088167
## Mid 0.7526132 0.2473868
## High 0.8693878 0.1306122
##
## $tables$FP112
## var
## grouping 0 1
## Low 0.64965197 0.35034803
## Mid 0.88501742 0.11498258
## High 0.97142857 0.02857143
##
## $tables$FP113
## var
## grouping 0 1
## Low 0.8329466 0.1670534
## Mid 0.8048780 0.1951220
## High 0.7387755 0.2612245
##
## $tables$FP114
## var
## grouping 0 1
## Low 0.81902552 0.18097448
## Mid 0.80836237 0.19163763
## High 0.91428571 0.08571429
##
## $tables$FP115
## var
## grouping 0 1
## Low 0.8074246 0.1925754
## Mid 0.7944251 0.2055749
## High 0.8612245 0.1387755
##
## $tables$FP116
## var
## grouping 0 1
## Low 0.8167053 0.1832947
## Mid 0.7944251 0.2055749
## High 0.7918367 0.2081633
##
## $tables$FP117
## var
## grouping 0 1
## Low 0.7772622 0.2227378
## Mid 0.8188153 0.1811847
## High 0.8857143 0.1142857
##
## $tables$FP118
## var
## grouping 0 1
## Low 0.8259861 0.1740139
## Mid 0.8362369 0.1637631
## High 0.7265306 0.2734694
##
## $tables$FP119
## var
## grouping 0 1
## Low 0.8422274 0.1577726
## Mid 0.7804878 0.2195122
## High 0.8775510 0.1224490
##
## $tables$FP120
## var
## grouping 0 1
## Low 0.8515081 0.1484919
## Mid 0.8571429 0.1428571
## High 0.7591837 0.2408163
##
## $tables$FP121
## var
## grouping 0 1
## Low 0.81670534 0.18329466
## Mid 0.87108014 0.12891986
## High 0.90612245 0.09387755
##
## $tables$FP122
## var
## grouping 0 1
## Low 0.8306265 0.1693735
## Mid 0.8397213 0.1602787
## High 0.8244898 0.1755102
##
## $tables$FP123
## var
## grouping 0 1
## Low 0.77262181 0.22737819
## Mid 0.84668990 0.15331010
## High 0.90612245 0.09387755
##
## $tables$FP124
## var
## grouping 0 1
## Low 0.8468677 0.1531323
## Mid 0.8222997 0.1777003
## High 0.8244898 0.1755102
##
## $tables$FP125
## var
## grouping 0 1
## Low 0.8515081 0.1484919
## Mid 0.8292683 0.1707317
## High 0.8326531 0.1673469
##
## $tables$FP126
## var
## grouping 0 1
## Low 0.8491879 0.1508121
## Mid 0.8118467 0.1881533
## High 0.8857143 0.1142857
##
## $tables$FP127
## var
## grouping 0 1
## Low 0.8793503 0.1206497
## Mid 0.8013937 0.1986063
## High 0.8775510 0.1224490
##
## $tables$FP128
## var
## grouping 0 1
## Low 0.8700696 0.1299304
## Mid 0.8188153 0.1811847
## High 0.8408163 0.1591837
##
## $tables$FP129
## var
## grouping 0 1
## Low 0.81438515 0.18561485
## Mid 0.87456446 0.12543554
## High 0.91020408 0.08979592
##
## $tables$FP130
## var
## grouping 0 1
## Low 0.87006961 0.12993039
## Mid 0.88850174 0.11149826
## High 0.92653061 0.07346939
##
## $tables$FP131
## var
## grouping 0 1
## Low 0.86774942 0.13225058
## Mid 0.83972125 0.16027875
## High 0.90612245 0.09387755
##
## $tables$FP132
## var
## grouping 0 1
## Low 0.91183295 0.08816705
## Mid 0.83275261 0.16724739
## High 0.84081633 0.15918367
##
## $tables$FP133
## var
## grouping 0 1
## Low 0.8770302 0.1229698
## Mid 0.8710801 0.1289199
## High 0.8530612 0.1469388
##
## $tables$FP134
## var
## grouping 0 1
## Low 0.83526682 0.16473318
## Mid 0.84668990 0.15331010
## High 0.95102041 0.04897959
##
## $tables$FP135
## var
## grouping 0 1
## Low 0.8677494 0.1322506
## Mid 0.8815331 0.1184669
## High 0.8571429 0.1428571
##
## $tables$FP136
## var
## grouping 0 1
## Low 0.8793503 0.1206497
## Mid 0.8710801 0.1289199
## High 0.8693878 0.1306122
##
## $tables$FP137
## var
## grouping 0 1
## Low 0.85150812 0.14849188
## Mid 0.88850174 0.11149826
## High 0.91836735 0.08163265
##
## $tables$FP138
## var
## grouping 0 1
## Low 0.86078886 0.13921114
## Mid 0.91289199 0.08710801
## High 0.88979592 0.11020408
##
## $tables$FP139
## var
## grouping 0 1
## Low 0.90487239 0.09512761
## Mid 0.89547038 0.10452962
## High 0.94693878 0.05306122
##
## $tables$FP140
## var
## grouping 0 1
## Low 0.9025522 0.0974478
## Mid 0.8501742 0.1498258
## High 0.8897959 0.1102041
##
## $tables$FP141
## var
## grouping 0 1
## Low 0.83990719 0.16009281
## Mid 0.86062718 0.13937282
## High 0.96734694 0.03265306
##
## $tables$FP142
## var
## grouping 0 1
## Low 0.87703016 0.12296984
## Mid 0.90940767 0.09059233
## High 0.87346939 0.12653061
##
## $tables$FP143
## var
## grouping 0 1
## Low 0.90255220 0.09744780
## Mid 0.90243902 0.09756098
## High 0.94693878 0.05306122
##
## $tables$FP144
## var
## grouping 0 1
## Low 0.91647332 0.08352668
## Mid 0.91986063 0.08013937
## High 0.81224490 0.18775510
##
## $tables$FP145
## var
## grouping 0 1
## Low 0.90719258 0.09280742
## Mid 0.89198606 0.10801394
## High 0.86122449 0.13877551
##
## $tables$FP146
## var
## grouping 0 1
## Low 0.83062645 0.16937355
## Mid 0.91986063 0.08013937
## High 0.96734694 0.03265306
##
## $tables$FP147
## var
## grouping 0 1
## Low 0.8979118 0.1020882
## Mid 0.8919861 0.1080139
## High 0.8734694 0.1265306
##
## $tables$FP148
## var
## grouping 0 1
## Low 0.91879350 0.08120650
## Mid 0.90592334 0.09407666
## High 0.88979592 0.11020408
##
## $tables$FP149
## var
## grouping 0 1
## Low 0.83526682 0.16473318
## Mid 0.94076655 0.05923345
## High 0.98367347 0.01632653
##
## $tables$FP150
## var
## grouping 0 1
## Low 0.92111369 0.07888631
## Mid 0.90940767 0.09059233
## High 0.91428571 0.08571429
##
## $tables$FP151
## var
## grouping 0 1
## Low 0.94431555 0.05568445
## Mid 0.91289199 0.08710801
## High 0.95918367 0.04081633
##
## $tables$FP152
## var
## grouping 0 1
## Low 0.89791183 0.10208817
## Mid 0.88850174 0.11149826
## High 0.96734694 0.03265306
##
## $tables$FP153
## var
## grouping 0 1
## Low 0.89791183 0.10208817
## Mid 0.92334495 0.07665505
## High 0.94285714 0.05714286
##
## $tables$FP155
## var
## grouping 0 1
## Low 0.87935035 0.12064965
## Mid 0.94773519 0.05226481
## High 0.97959184 0.02040816
##
## $tables$FP156
## var
## grouping 0 1
## Low 0.90487239 0.09512761
## Mid 0.91289199 0.08710801
## High 0.97142857 0.02857143
##
## $tables$FP157
## var
## grouping 0 1
## Low 0.93039443 0.06960557
## Mid 0.94425087 0.05574913
## High 0.92244898 0.07755102
##
## $tables$FP158
## var
## grouping 0 1
## Low 0.95823666 0.04176334
## Mid 0.92682927 0.07317073
## High 0.92653061 0.07346939
##
## $tables$FP159
## var
## grouping 0 1
## Low 0.90719258 0.09280742
## Mid 0.89895470 0.10104530
## High 0.98367347 0.01632653
##
## $tables$FP160
## var
## grouping 0 1
## Low 0.92575406 0.07424594
## Mid 0.88153310 0.11846690
## High 0.97959184 0.02040816
##
## $tables$FP161
## var
## grouping 0 1
## Low 0.97215777 0.02784223
## Mid 0.93379791 0.06620209
## High 0.84489796 0.15510204
##
## $tables$FP162
## var
## grouping 0 1
## Low 0.3805104 0.6194896
## Mid 0.4878049 0.5121951
## High 0.7428571 0.2571429
##
## $tables$FP163
## var
## grouping 0 1
## Low 0.5591647 0.4408353
## Mid 0.4668990 0.5331010
## High 0.5265306 0.4734694
##
## $tables$FP164
## var
## grouping 0 1
## Low 0.2250580 0.7749420
## Mid 0.3763066 0.6236934
## High 0.6326531 0.3673469
##
## $tables$FP165
## var
## grouping 0 1
## Low 0.6658933 0.3341067
## Mid 0.6097561 0.3902439
## High 0.6653061 0.3346939
##
## $tables$FP166
## var
## grouping 0 1
## Low 0.5893271 0.4106729
## Mid 0.6724739 0.3275261
## High 0.7959184 0.2040816
##
## $tables$FP167
## var
## grouping 0 1
## Low 0.6890951 0.3109049
## Mid 0.6411150 0.3588850
## High 0.6693878 0.3306122
##
## $tables$FP168
## var
## grouping 0 1
## Low 0.1786543 0.8213457
## Mid 0.3414634 0.6585366
## High 0.6081633 0.3918367
##
## $tables$FP169
## var
## grouping 0 1
## Low 0.68445476 0.31554524
## Mid 0.87804878 0.12195122
## High 0.95102041 0.04897959
##
## $tables$FP170
## var
## grouping 0 1
## Low 0.7679814 0.2320186
## Mid 0.8362369 0.1637631
## High 0.8612245 0.1387755
##
## $tables$FP171
## var
## grouping 0 1
## Low 0.8631090 0.1368910
## Mid 0.8188153 0.1811847
## High 0.7714286 0.2285714
##
## $tables$FP172
## var
## grouping 0 1
## Low 0.71693735 0.28306265
## Mid 0.91986063 0.08013937
## High 0.97959184 0.02040816
##
## $tables$FP173
## var
## grouping 0 1
## Low 0.80278422 0.19721578
## Mid 0.88501742 0.11498258
## High 0.90612245 0.09387755
##
## $tables$FP174
## var
## grouping 0 1
## Low 0.83990719 0.16009281
## Mid 0.86062718 0.13937282
## High 0.91428571 0.08571429
##
## $tables$FP175
## var
## grouping 0 1
## Low 0.8584687 0.1415313
## Mid 0.8432056 0.1567944
## High 0.8857143 0.1142857
##
## $tables$FP176
## var
## grouping 0 1
## Low 0.8747100 0.1252900
## Mid 0.8710801 0.1289199
## High 0.8734694 0.1265306
##
## $tables$FP177
## var
## grouping 0 1
## Low 0.86774942 0.13225058
## Mid 0.84668990 0.15331010
## High 0.91836735 0.08163265
##
## $tables$FP178
## var
## grouping 0 1
## Low 0.83526682 0.16473318
## Mid 0.87456446 0.12543554
## High 0.94285714 0.05714286
##
## $tables$FP179
## var
## grouping 0 1
## Low 0.87935035 0.12064965
## Mid 0.89198606 0.10801394
## High 0.93469388 0.06530612
##
## $tables$FP180
## var
## grouping 0 1
## Low 0.90719258 0.09280742
## Mid 0.86759582 0.13240418
## High 0.87755102 0.12244898
##
## $tables$FP181
## var
## grouping 0 1
## Low 0.84454756 0.15545244
## Mid 0.91637631 0.08362369
## High 0.98367347 0.01632653
##
## $tables$FP182
## var
## grouping 0 1
## Low 0.90719258 0.09280742
## Mid 0.89895470 0.10104530
## High 0.87346939 0.12653061
##
## $tables$FP183
## var
## grouping 0 1
## Low 0.93735499 0.06264501
## Mid 0.90243902 0.09756098
## High 0.90612245 0.09387755
##
## $tables$FP184
## var
## grouping 0 1
## Low 0.83990719 0.16009281
## Mid 0.95121951 0.04878049
## High 0.98775510 0.01224490
##
## $tables$FP185
## var
## grouping 0 1
## Low 0.87006961 0.12993039
## Mid 0.92682927 0.07317073
## High 0.95918367 0.04081633
##
## $tables$FP186
## var
## grouping 0 1
## Low 0.92575406 0.07424594
## Mid 0.90940767 0.09059233
## High 0.91428571 0.08571429
##
## $tables$FP187
## var
## grouping 0 1
## Low 0.92111369 0.07888631
## Mid 0.93728223 0.06271777
## High 0.90612245 0.09387755
##
## $tables$FP188
## var
## grouping 0 1
## Low 0.94663573 0.05336427
## Mid 0.91637631 0.08362369
## High 0.90204082 0.09795918
##
## $tables$FP189
## var
## grouping 0 1
## Low 0.89791183 0.10208817
## Mid 0.92334495 0.07665505
## High 0.94693878 0.05306122
##
## $tables$FP190
## var
## grouping 0 1
## Low 0.86774942 0.13225058
## Mid 0.95121951 0.04878049
## High 0.98367347 0.01632653
##
## $tables$FP191
## var
## grouping 0 1
## Low 0.93039443 0.06960557
## Mid 0.92334495 0.07665505
## High 0.91428571 0.08571429
##
## $tables$FP192
## var
## grouping 0 1
## Low 0.91415313 0.08584687
## Mid 0.94425087 0.05574913
## High 0.95510204 0.04489796
##
## $tables$FP193
## var
## grouping 0 1
## Low 0.872389791 0.127610209
## Mid 0.972125436 0.027874564
## High 0.991836735 0.008163265
##
## $tables$FP194
## var
## grouping 0 1
## Low 0.94199536 0.05800464
## Mid 0.90592334 0.09407666
## High 0.95918367 0.04081633
##
## $tables$FP195
## var
## grouping 0 1
## Low 0.96983759 0.03016241
## Mid 0.89895470 0.10104530
## High 0.91020408 0.08979592
##
## $tables$FP196
## var
## grouping 0 1
## Low 0.89095128 0.10904872
## Mid 0.96515679 0.03484321
## High 0.98775510 0.01224490
##
## $tables$FP197
## var
## grouping 0 1
## Low 0.90023202 0.09976798
## Mid 0.97909408 0.02090592
## High 0.97142857 0.02857143
##
## $tables$FP198
## var
## grouping 0 1
## Low 0.95823666 0.04176334
## Mid 0.96167247 0.03832753
## High 0.87346939 0.12653061
##
## $tables$FP201
## var
## grouping 0 1
## Low 0.95823666 0.04176334
## Mid 0.93031359 0.06968641
## High 0.92653061 0.07346939
##
## $tables$FP202
## var
## grouping 0 1
## Low 0.6728538 0.3271462
## Mid 0.7421603 0.2578397
## High 0.8530612 0.1469388
##
## $tables$FP203
## var
## grouping 0 1
## Low 0.87935035 0.12064965
## Mid 0.86062718 0.13937282
## High 0.90612245 0.09387755
##
## $tables$FP204
## var
## grouping 0 1
## Low 0.86774942 0.13225058
## Mid 0.88850174 0.11149826
## High 0.95510204 0.04489796
##
## $tables$FP205
## var
## grouping 0 1
## Low 0.87470998 0.12529002
## Mid 0.93031359 0.06968641
## High 0.97551020 0.02448980
##
## $tables$FP206
## var
## grouping 0 1
## Low 0.91183295 0.08816705
## Mid 0.93031359 0.06968641
## High 0.97959184 0.02040816
##
## $tables$FP207
## var
## grouping 0 1
## Low 0.89095128 0.10904872
## Mid 0.96515679 0.03484321
## High 0.98775510 0.01224490
##
## $tables$FP208
## var
## grouping 0 1
## Low 0.87935035 0.12064965
## Mid 0.86411150 0.13588850
## High 0.91020408 0.08979592
##
## $tables$MolWeight
## [,1] [,2]
## Low 0.6447051 0.8127549
## Mid -0.2055106 0.7535493
## High -0.9009527 0.7170859
##
## $tables$NumBonds
## [,1] [,2]
## Low 0.5260887 0.9212852
## Mid -0.2189291 0.8689442
## High -0.6750329 0.7470400
##
## $tables$NumMultBonds
## [,1] [,2]
## Low 0.4454402 1.0735331
## Mid -0.1400358 0.8162199
## High -0.6247835 0.6014728
##
## $tables$NumRotBonds
## [,1] [,2]
## Low 0.2155584 1.1862560
## Mid -0.0940740 0.8218105
## High -0.2714543 0.7070257
##
## $tables$NumDblBonds
## [,1] [,2]
## Low 0.07217700 1.1166156
## Mid 0.07068664 0.9635389
## High -0.21088755 0.7710460
##
## $tables$NumCarbon
## [,1] [,2]
## Low 0.6263249 0.8520677
## Mid -0.2418994 0.8045988
## High -0.8256564 0.6763829
##
## $tables$NumNitrogen
## [,1] [,2]
## Low -0.02976857 1.0250998
## Mid 0.09225615 1.0510022
## High -0.05559051 0.8834496
##
## $tables$NumOxygen
## [,1] [,2]
## Low -0.034068396 1.0954990
## Mid -0.005066866 0.8544102
## High 0.066311736 0.9817552
##
## $tables$NumSulfer
## [,1] [,2]
## Low 0.11971764 1.2230290
## Mid 0.02589293 0.9222710
## High -0.24251923 0.4674415
##
## $tables$NumChlorine
## [,1] [,2]
## Low 0.3118792 1.3422891
## Mid -0.1802282 0.5542606
## High -0.3409454 0.2668185
##
## $tables$NumHalogen
## [,1] [,2]
## Low 0.3385013 1.3025157
## Mid -0.1813798 0.6177592
## High -0.3867617 0.3250965
##
## $tables$NumRings
## [,1] [,2]
## Low 0.4841073 1.0815485
## Mid -0.2058863 0.8005849
## High -0.6159668 0.5300818
##
## $tables$HydrophilicFactor
## [,1] [,2]
## Low -0.24599149 0.7233875
## Mid 0.04475775 0.8785500
## High 0.38328598 1.3656601
##
## $tables$SurfaceArea1
## [,1] [,2]
## Low -0.09225436 1.0302674
## Mid 0.05481524 0.9389079
## High 0.09908671 1.0049351
##
## $tables$SurfaceArea2
## [,1] [,2]
## Low -0.04168274 1.0668148
## Mid 0.04393220 0.9456058
## High 0.02226439 0.9389898
##
##
## $levels
## [1] "Low" "Mid" "High"
##
## $call
## NaiveBayes.default(x = x, grouping = y, usekernel = FALSE, fL = param$fL)
##
## $x
## FP001 FP002 FP003 FP004 FP005 FP006 FP007 FP008 FP009 FP010 FP011 FP012
## X661 0 1 0 0 1 0 0 1 0 0 0 0
## X662 0 1 0 1 1 1 1 1 0 0 1 0
## X663 1 1 1 1 1 0 0 1 0 1 0 0
## X665 0 0 1 0 0 0 1 0 0 0 0 0
## X668 0 0 1 1 1 1 0 0 1 0 0 0
## X669 1 0 1 1 0 0 0 0 1 0 0 1
## X670 0 1 0 1 1 0 0 1 1 0 0 0
## X671 1 0 1 1 0 0 1 0 0 0 0 1
## X672 1 0 1 1 0 1 1 0 1 0 1 0
## X673 1 1 1 1 1 1 1 0 0 0 0 0
## X674 1 1 1 1 1 0 0 1 0 0 0 0
## X676 1 0 1 1 0 1 1 0 0 0 1 0
## X677 0 1 0 0 1 0 0 1 0 0 0 0
## X678 0 1 0 0 1 0 0 0 1 0 0 0
## X679 0 1 1 0 1 0 1 1 0 0 0 0
## X682 1 1 1 1 1 0 0 1 0 1 0 0
## X683 1 0 1 1 1 1 1 1 0 0 0 0
## X684 0 1 0 1 1 1 1 0 1 0 1 0
## X685 1 0 1 1 0 1 1 0 0 0 1 0
## X686 0 1 1 0 1 0 0 1 0 0 0 0
## X688 1 1 0 1 1 1 0 1 1 0 1 1
## X689 0 1 0 1 1 0 1 1 0 0 0 0
## X690 1 1 1 1 1 0 1 1 1 0 0 1
## X691 1 0 0 1 0 1 0 0 1 0 0 0
## X692 1 1 1 1 1 1 0 1 0 0 0 1
## X693 1 1 0 1 1 1 1 1 0 0 0 0
## X695 0 1 1 1 1 0 0 0 0 0 0 0
## X696 0 1 0 0 1 1 0 0 0 0 0 0
## X698 1 1 1 1 1 1 0 1 0 0 0 0
## X699 0 1 0 0 1 0 0 1 1 0 0 0
## X700 0 0 1 0 0 0 1 0 0 0 0 0
## X702 0 0 1 0 0 0 1 0 0 0 0 0
## X703 0 0 1 0 0 0 1 0 0 0 0 0
## X704 0 1 0 0 1 0 0 1 0 0 0 0
## X706 1 1 1 1 1 0 0 1 0 0 0 0
## X708 0 1 0 0 1 0 0 0 0 0 0 0
## X709 0 0 1 0 0 0 1 0 0 0 0 0
## X711 1 0 1 1 0 1 1 0 0 1 1 0
## X712 0 1 1 0 1 0 1 1 0 1 0 0
## X713 1 1 0 1 1 1 0 1 1 1 0 0
## X714 1 0 1 1 0 1 1 0 0 0 1 1
## X715 1 1 0 1 1 1 0 0 1 0 0 1
## X717 0 1 0 0 1 0 0 0 1 0 0 0
## X718 0 1 0 1 1 0 1 0 1 0 0 0
## X721 0 0 1 0 1 1 0 0 1 0 0 0
## X722 1 1 0 1 1 0 0 1 1 0 0 0
## X723 0 0 1 0 0 0 1 0 0 0 0 0
## X724 0 1 0 1 1 0 0 0 0 0 0 0
## X726 0 1 0 1 1 0 0 0 1 1 0 0
## X728 1 1 1 1 1 0 0 1 1 1 0 0
## X729 0 1 0 0 1 0 0 0 1 0 0 0
## X731 0 0 1 0 0 0 1 0 0 0 0 0
## X732 0 1 0 0 1 0 0 0 1 0 0 0
## X733 0 0 1 0 1 1 0 0 1 0 0 0
## X734 0 1 0 0 1 0 0 0 1 0 0 0
## X735 1 0 1 1 0 1 1 0 0 0 1 0
## X736 1 1 1 1 1 1 1 1 0 0 0 1
## X737 1 1 0 1 1 0 0 0 0 0 0 0
## X739 1 1 1 1 1 0 1 1 1 0 0 1
## X740 1 1 0 1 1 0 0 1 1 1 0 0
## X741 1 0 1 1 0 0 1 0 0 1 0 0
## X742 1 0 1 1 0 0 1 0 0 0 0 1
## X743 0 1 0 0 1 0 0 0 1 0 0 0
## X744 0 1 0 0 1 0 0 1 0 0 0 0
## X746 1 1 1 1 1 0 0 1 0 0 0 1
## X747 0 0 1 0 0 1 1 0 0 0 1 0
## X749 1 1 1 1 1 0 1 0 1 0 0 1
## X752 1 0 1 1 0 1 1 0 1 0 1 1
## X753 0 0 1 0 0 0 1 0 0 0 0 0
## X754 0 1 0 1 1 0 1 0 0 0 0 0
## X755 0 1 0 0 1 0 0 1 0 0 0 0
## X757 0 0 1 0 0 0 1 0 1 0 0 0
## X758 0 1 0 1 1 0 0 1 0 0 0 0
## X759 1 0 1 1 0 0 0 0 0 0 0 0
## X760 0 1 0 0 1 0 0 0 1 0 0 0
## X761 1 0 1 1 0 1 1 0 1 0 1 1
## X762 0 1 0 0 1 0 0 1 0 0 0 0
## X763 0 1 0 0 1 1 0 0 1 0 0 0
## X764 0 1 0 0 1 0 0 1 0 0 0 0
## X765 1 1 1 1 1 1 0 1 1 0 1 1
## X767 1 0 1 1 0 0 1 0 1 0 0 1
## X768 0 1 0 0 1 0 0 0 0 0 0 0
## X770 0 1 0 1 1 0 1 0 1 0 0 0
## X771 1 1 0 1 1 1 0 1 1 0 0 0
## X772 0 1 0 0 1 0 0 0 1 0 0 0
## X773 0 0 1 0 0 0 1 0 0 0 0 0
## X774 0 0 1 0 0 0 1 0 1 0 0 0
## X775 1 1 0 1 1 0 1 1 0 1 0 0
## X776 1 1 0 1 1 1 1 1 1 0 0 0
## X777 1 0 1 1 0 0 1 0 0 0 0 1
## X778 1 0 1 1 0 1 1 0 0 1 1 0
## X779 0 1 0 0 1 1 0 0 0 0 0 0
## X780 0 0 0 0 0 0 0 0 1 0 0 0
## X781 1 0 1 1 0 0 1 0 0 0 0 1
## X782 1 1 0 1 1 0 0 1 0 0 0 0
## X784 1 1 0 1 1 1 0 1 1 1 1 0
## X786 0 0 1 0 0 0 1 0 0 0 0 0
## X787 0 1 0 0 1 0 0 0 1 0 0 0
## X788 1 0 1 1 0 0 1 0 0 0 0 0
## X789 0 1 0 0 1 0 0 0 1 0 0 0
## X791 0 1 0 0 1 0 0 0 1 0 0 0
## X792 0 1 0 1 1 0 1 1 1 0 0 0
## X794 1 0 1 1 0 0 1 0 0 1 0 0
## X798 0 1 0 0 1 0 0 0 0 0 0 0
## X799 1 0 0 1 0 0 1 0 1 0 0 0
## X800 0 0 1 1 0 1 1 0 0 0 1 1
## X804 0 1 0 1 1 0 0 1 0 0 0 0
## X805 1 0 1 1 0 1 1 0 0 0 1 1
## X807 1 0 1 1 0 0 0 0 0 0 0 1
## X808 1 1 0 1 1 0 0 1 0 1 0 0
## X809 1 1 1 1 1 0 1 1 0 0 0 1
## X810 0 0 0 0 0 0 1 0 1 0 0 0
## X813 1 0 1 1 0 0 1 0 0 1 0 0
## X814 1 1 1 1 1 0 0 0 1 0 0 1
## X818 0 1 0 0 1 0 0 0 1 0 0 0
## X819 1 1 0 1 1 1 0 1 1 0 0 0
## X820 0 0 1 0 0 1 1 0 0 0 1 0
## X821 0 1 0 0 1 0 0 0 1 0 0 0
## X822 0 1 0 0 1 0 0 0 0 0 0 0
## X823 0 1 0 0 1 1 0 0 0 0 0 0
## X827 0 0 0 1 0 0 1 0 1 0 0 1
## X828 0 1 0 0 1 0 0 0 1 0 0 0
## X829 1 1 1 1 1 0 0 1 1 0 0 1
## X831 0 1 0 0 1 0 0 1 1 0 0 0
## X832 0 1 0 0 1 0 0 0 1 0 0 0
## X833 0 1 0 0 1 0 0 0 1 0 0 0
## X834 0 1 0 0 1 0 0 1 1 0 0 0
## X835 0 1 0 0 1 0 0 0 1 0 0 0
## X836 0 1 0 0 1 0 0 0 1 0 0 0
## X839 0 1 0 0 1 0 0 1 0 0 0 0
## X840 0 1 0 0 1 0 0 0 0 0 0 0
## X841 0 1 0 0 1 0 0 0 1 0 0 0
## X842 0 1 1 0 1 0 0 1 0 0 0 0
## X843 0 1 0 0 1 0 0 1 1 0 0 0
## X846 0 1 0 0 1 0 0 0 0 0 0 0
## X848 0 1 0 0 1 0 0 0 1 0 0 0
## X849 0 1 0 0 1 0 0 0 1 0 0 0
## X851 0 0 1 1 0 1 1 0 0 0 1 1
## X854 0 1 0 0 1 0 0 0 1 0 0 0
## X855 0 1 0 0 1 0 0 0 0 0 0 0
## X856 0 1 0 0 1 0 0 0 1 0 0 0
## X857 0 1 0 0 1 0 0 0 1 0 0 0
## X858 0 1 0 0 1 0 0 0 1 0 0 0
## X859 0 1 0 0 1 0 0 0 1 0 0 0
## X860 0 1 0 0 1 0 0 0 1 0 0 0
## X862 0 1 0 0 1 0 0 0 1 0 0 0
## X863 0 1 0 0 1 0 0 0 1 0 0 0
## X864 0 1 0 0 1 0 0 1 0 0 0 0
## X865 0 1 0 0 1 0 0 0 0 0 0 0
## X866 0 1 0 0 1 0 0 0 1 0 0 0
## X867 0 1 0 0 1 0 0 0 0 0 0 0
## X869 0 1 0 0 1 0 0 1 1 0 0 0
## X870 0 1 0 0 1 0 0 0 1 0 0 0
## X871 0 1 0 0 1 0 0 0 1 0 0 0
## X872 0 1 0 0 1 0 0 0 1 0 0 0
## X873 0 1 0 0 1 0 0 0 0 0 0 0
## X875 0 1 0 0 1 0 0 0 1 0 0 0
## X876 0 1 0 0 1 0 0 0 1 0 0 0
## X877 0 0 0 0 1 0 0 0 1 0 0 0
## X1190 0 1 0 1 1 0 0 0 0 0 0 0
## X1191 0 0 1 0 0 0 1 0 1 0 0 0
## X1192 1 0 1 1 0 1 1 0 0 0 1 0
## X1193 0 1 0 0 1 0 0 1 0 0 0 0
## X1194 1 0 1 1 0 1 1 0 0 0 1 1
## X1195 0 1 0 0 1 0 0 0 1 0 0 0
## X1197 0 1 1 0 1 0 1 1 0 0 0 0
## X1198 0 1 0 0 1 0 0 0 1 0 0 0
## X1199 0 0 1 1 1 1 0 0 0 0 0 0
## X1200 1 0 1 1 0 0 0 0 0 0 0 1
## X1201 1 1 0 1 1 0 0 1 0 0 0 1
## X1202 1 0 1 1 0 1 1 0 1 0 1 1
## X1203 0 0 0 0 0 0 1 0 0 0 0 0
## X1204 1 1 0 1 1 1 0 1 0 1 0 0
## X1205 1 1 0 1 1 1 0 1 1 1 0 0
## X1206 0 0 0 0 0 0 0 0 1 0 0 0
## X1207 0 1 1 1 1 0 0 0 0 0 0 0
## X1208 1 0 1 1 0 0 1 0 0 0 0 1
## X1209 0 0 0 0 1 0 0 0 1 1 0 0
## X1210 1 0 1 1 0 1 1 0 0 1 1 0
## X1212 0 1 1 0 1 1 1 1 0 1 1 0
## X1213 0 1 0 1 1 0 1 0 0 0 0 0
## X1215 1 0 1 1 0 1 1 0 1 0 1 1
## X1216 0 1 0 0 1 0 0 0 0 0 0 0
## X1217 0 1 0 0 1 1 0 1 1 0 1 0
## X1219 0 1 1 0 1 0 1 1 0 1 0 0
## X1220 1 1 0 1 1 1 1 1 1 0 1 0
## X1221 0 0 1 0 0 0 1 0 1 0 0 0
## X1222 0 1 0 0 1 0 1 1 0 0 0 0
## X1226 0 1 0 1 1 0 1 1 1 0 0 0
## X1228 1 1 0 1 1 0 0 1 0 0 0 1
## X1229 1 0 1 1 0 1 1 0 0 0 1 1
## X1230 1 1 0 1 1 0 0 1 0 0 0 1
## X1231 0 1 0 0 1 0 0 1 0 0 0 0
## X1233 1 0 1 1 0 1 1 0 0 0 1 0
## X1234 0 1 0 0 1 0 0 1 0 0 0 0
## X1236 1 0 1 1 0 0 1 0 0 0 0 1
## X1237 1 1 0 1 1 0 0 0 1 0 0 1
## X1239 1 0 1 1 0 0 0 0 1 0 0 1
## X1242 0 0 0 0 0 0 0 0 1 0 0 0
## X1244 0 1 0 0 1 0 0 0 1 0 0 0
## X1245 0 1 1 0 1 0 1 1 0 0 0 0
## X1246 1 1 1 1 1 0 1 1 0 1 0 0
## X1247 1 1 1 1 1 0 0 1 0 0 0 1
## X1249 1 1 1 1 1 0 0 1 1 0 0 1
## X1250 0 0 0 0 0 1 0 0 1 0 1 0
## X1251 0 0 0 0 1 0 0 1 1 0 0 0
## X1253 1 1 1 1 1 0 0 0 1 0 0 1
## X1254 0 1 0 0 1 0 0 0 1 0 0 0
## X1255 0 1 0 0 1 0 0 1 0 0 0 0
## X1256 0 1 0 0 1 0 1 1 0 0 0 0
## X1257 0 1 0 0 1 0 0 0 1 0 0 0
## X1259 0 0 0 1 0 0 1 0 1 0 0 1
## X1260 0 1 0 0 1 0 0 0 1 0 0 0
## X1262 1 1 1 1 1 0 0 1 1 0 0 1
## X1264 0 0 0 0 0 0 0 0 1 0 0 0
## X1265 0 1 0 0 1 0 0 0 1 0 0 0
## X1266 0 1 0 0 1 0 0 1 1 0 0 0
## X1267 1 1 0 1 1 0 0 1 0 1 0 0
## X1268 1 0 1 1 0 0 1 0 0 1 0 0
## X1273 0 1 0 0 1 0 0 0 1 0 0 0
## X1274 0 0 1 0 0 1 1 0 0 0 1 0
## X1275 0 0 0 0 0 0 1 0 1 0 0 0
## X1276 0 1 0 0 1 0 0 0 0 0 0 0
## X1277 0 1 0 0 1 0 0 0 1 0 0 0
## X1278 0 1 0 0 1 0 0 1 0 0 0 0
## X1279 0 1 0 0 1 0 0 0 0 0 0 0
## X1281 0 1 0 0 1 0 0 0 1 0 0 0
## X1282 0 1 0 0 1 0 0 0 1 0 0 0
## X1283 0 1 0 0 1 0 0 0 0 0 0 0
## X1284 0 1 0 0 1 0 0 0 0 0 0 0
## X1285 0 1 0 0 1 0 0 0 1 0 0 0
## X1288 0 1 0 0 1 0 0 0 1 0 0 0
## X1299 1 1 0 1 1 1 0 1 0 0 0 0
## X1301 1 0 1 1 0 1 1 0 0 0 1 0
## X1302 0 0 0 0 0 0 0 0 1 0 0 0
## X1307 1 1 1 1 1 0 0 0 1 0 0 1
## X1309 0 1 0 0 1 0 0 1 1 0 0 0
## X1310 0 0 0 0 0 0 1 0 1 0 0 0
## X447 1 1 0 1 1 0 0 0 1 1 0 0
## X448 1 1 0 1 1 1 1 1 1 1 1 0
## X451 0 0 1 0 0 0 1 0 0 0 0 0
## X452 0 1 0 0 1 0 0 1 1 0 0 0
## X453 0 1 0 0 1 0 0 0 0 1 0 0
## X454 1 1 0 1 1 1 0 1 0 0 0 0
## X455 1 1 1 1 1 0 0 1 1 1 0 0
## X456 1 1 1 1 1 1 1 0 0 0 0 1
## X458 1 1 0 1 1 1 0 1 0 0 0 0
## X459 1 0 1 1 0 0 1 0 0 0 0 0
## X460 0 0 0 0 0 0 1 0 0 0 0 0
## X461 1 1 0 1 1 0 0 1 1 1 0 0
## X462 0 1 1 0 1 0 0 0 0 0 0 0
## X463 0 1 0 1 1 1 0 1 0 0 0 0
## X464 0 0 0 0 0 0 0 0 1 0 0 0
## X465 0 1 0 1 1 1 1 1 0 0 1 0
## X466 1 1 0 1 1 0 0 0 1 1 0 0
## X468 1 0 1 1 0 1 1 0 0 0 1 1
## X471 1 1 1 1 1 1 1 1 0 0 0 0
## X472 0 0 1 0 0 0 1 0 1 0 0 0
## X473 0 0 0 0 0 0 1 0 0 0 0 0
## X476 1 1 0 1 1 0 0 1 0 1 0 0
## X477 1 1 1 1 1 1 0 1 0 0 0 0
## X478 0 0 0 0 0 0 1 0 0 0 0 0
## X479 0 0 1 0 0 0 1 0 0 0 0 0
## X480 0 1 0 0 1 0 0 0 0 0 0 0
## X482 0 0 1 0 0 0 0 0 1 0 0 0
## X483 0 0 1 0 0 0 0 0 1 0 0 0
## X484 0 1 0 0 1 1 0 0 0 0 0 0
## X486 1 0 1 1 0 0 1 0 0 0 0 1
## X487 1 1 1 1 1 0 0 1 0 0 0 1
## X488 1 1 1 1 1 0 1 1 0 1 0 1
## X489 1 1 0 1 1 0 0 1 1 1 0 0
## X490 1 1 1 1 1 0 0 1 1 0 0 1
## X491 0 0 1 0 0 0 1 0 1 0 0 0
## X492 1 0 1 1 0 1 1 0 0 0 0 0
## X493 1 0 1 1 0 0 1 0 0 1 0 0
## X494 1 0 0 1 1 1 0 0 1 1 0 0
## X495 0 1 0 1 1 1 1 1 0 0 1 0
## X496 1 0 0 1 1 1 0 0 0 0 0 0
## X497 0 1 0 0 1 0 0 0 0 0 0 0
## X498 0 1 0 0 1 0 0 1 1 1 0 0
## X499 0 1 0 0 1 0 0 1 0 0 0 0
## X501 1 1 0 1 1 0 0 0 1 0 0 0
## X502 0 1 0 0 1 0 0 1 0 0 0 0
## X503 0 1 1 1 1 1 1 1 0 0 1 0
## X505 1 1 1 1 1 1 0 0 1 0 0 0
## X506 1 1 0 1 1 1 0 1 0 0 0 0
## X507 0 1 0 1 1 1 0 1 0 0 0 0
## X508 1 1 0 1 1 1 0 1 1 1 1 0
## X509 1 1 1 1 1 1 0 1 0 1 1 0
## X510 1 1 0 1 1 1 0 0 1 0 1 0
## X513 0 0 1 0 0 0 1 0 1 0 0 0
## X514 1 1 0 1 1 1 0 1 0 0 0 0
## X515 0 1 0 0 1 0 0 0 0 1 0 0
## X516 0 1 0 1 1 0 0 1 0 0 0 0
## X518 1 1 1 1 1 1 0 0 0 0 0 0
## X521 1 1 0 1 1 1 0 1 0 0 0 0
## X523 1 1 1 1 1 0 0 1 0 0 0 1
## X524 1 1 1 1 1 1 1 0 1 0 0 0
## X525 1 0 1 1 0 1 1 0 0 0 0 0
## X526 0 0 1 0 0 1 1 0 0 0 1 0
## X530 0 1 1 1 1 0 0 0 0 0 0 0
## X531 1 1 1 1 1 1 0 1 0 1 0 0
## X532 0 0 1 1 1 1 0 0 0 0 0 0
## X533 1 1 0 1 1 1 0 1 1 0 1 0
## X534 1 1 1 1 1 1 1 1 0 0 0 0
## X535 0 1 0 0 1 0 0 0 1 0 0 0
## X536 0 1 0 0 1 1 1 1 0 0 1 0
## X538 1 1 0 1 1 0 0 1 0 1 0 0
## X539 0 1 0 0 1 1 1 1 0 0 1 0
## X542 1 0 1 1 0 1 1 0 0 0 1 0
## X543 0 0 1 0 0 0 1 0 1 0 0 0
## X544 1 1 1 1 1 1 1 1 0 1 1 0
## X545 0 0 1 0 0 0 1 0 0 0 0 0
## X546 0 0 0 0 0 0 0 0 1 0 0 0
## X548 0 1 1 1 1 0 0 1 0 0 0 0
## X549 0 1 0 0 1 0 0 0 1 0 0 0
## X551 0 0 0 0 0 0 0 0 1 0 0 0
## X552 1 1 0 1 1 0 0 1 0 0 0 1
## X553 1 1 1 1 1 1 0 0 0 0 0 1
## X554 0 0 1 0 1 1 0 0 1 0 0 0
## X556 1 1 0 1 1 0 0 1 0 1 0 0
## X557 1 1 1 1 1 1 0 1 1 0 0 0
## X558 0 1 0 1 1 0 0 0 0 0 0 0
## X559 0 0 1 0 0 0 1 0 0 0 0 0
## X560 0 1 0 0 1 0 0 1 0 0 0 0
## X561 0 1 0 0 1 0 0 0 1 0 0 0
## X562 0 1 1 0 1 0 0 1 0 0 0 0
## X563 1 1 0 1 1 0 0 1 0 1 0 0
## X565 0 0 1 0 0 0 1 0 0 0 0 0
## X566 0 1 0 0 1 1 0 0 1 0 0 0
## X567 1 1 1 1 1 1 0 1 1 0 0 0
## X568 1 1 1 1 1 1 0 0 1 0 0 0
## X569 1 1 1 1 1 0 0 1 1 0 0 1
## X571 1 1 0 1 1 1 0 1 1 0 0 1
## X572 1 1 1 1 1 1 1 1 0 0 0 1
## X574 0 0 1 0 0 0 1 0 0 0 0 0
## X576 1 1 0 1 1 1 0 1 0 0 0 0
## X577 1 1 0 1 1 1 0 0 0 0 0 0
## X579 1 1 0 1 1 1 0 1 0 0 0 0
## X580 1 1 0 1 1 0 0 1 1 1 0 0
## X582 1 0 1 1 0 0 1 0 0 0 0 0
## X583 0 1 0 0 1 0 0 1 0 0 0 0
## X584 1 1 0 1 1 0 1 1 0 0 0 1
## X586 1 1 1 1 1 0 0 1 0 0 0 1
## X587 0 1 0 0 1 0 0 0 0 0 0 0
## X588 1 0 1 1 0 1 1 0 0 0 0 0
## X589 1 0 1 1 0 1 1 0 0 1 1 0
## X591 0 1 0 1 1 1 1 1 0 0 1 0
## X592 0 1 1 0 1 0 1 1 0 0 0 0
## X593 0 1 0 0 1 1 0 1 1 0 1 0
## X594 1 0 1 1 0 0 1 0 0 0 0 1
## X595 1 0 1 1 0 0 0 0 1 0 0 1
## X596 1 1 1 1 1 1 1 1 0 0 0 0
## X597 0 1 0 1 1 0 1 1 0 0 0 0
## X598 1 0 0 1 0 0 1 0 0 1 0 0
## X599 0 1 0 0 1 0 0 1 0 0 0 0
## X600 1 1 1 1 1 0 0 1 0 0 0 1
## X603 1 0 1 1 0 0 1 0 0 1 0 0
## X604 1 0 1 1 0 1 1 0 0 0 0 0
## X605 1 0 1 1 0 0 1 0 0 0 0 0
## X606 1 1 1 1 1 0 1 1 0 0 0 1
## X608 0 1 0 0 1 0 0 0 1 0 0 0
## X609 1 1 0 1 1 1 0 1 0 0 0 0
## X611 0 0 0 0 0 0 1 0 0 0 0 0
## X612 1 1 0 1 1 1 0 0 1 0 0 0
## X613 0 1 0 0 1 0 0 1 1 0 0 0
## X614 0 1 0 0 1 0 0 1 1 0 0 0
## X616 0 0 1 0 0 0 1 0 0 0 0 0
## X617 1 1 1 1 1 0 0 0 0 0 0 0
## X619 1 1 0 1 1 1 0 1 1 0 1 0
## X620 0 1 0 0 1 0 0 0 1 0 0 0
## X621 1 1 0 1 1 1 0 1 0 1 0 0
## X622 0 1 0 0 1 0 0 0 0 0 0 0
## X623 1 1 0 1 1 1 0 1 1 0 1 0
## X625 1 1 1 1 1 0 0 0 1 0 0 0
## X628 1 0 1 1 0 1 1 0 1 0 1 0
## X629 1 0 1 1 0 1 1 0 0 1 1 0
## X630 0 1 0 1 1 1 1 1 0 0 0 0
## X631 0 0 1 0 0 0 1 0 0 0 0 0
## X632 0 0 0 0 0 0 0 0 1 0 0 0
## X633 1 1 0 1 1 0 1 0 1 1 0 0
## X635 1 1 0 1 1 1 1 1 0 0 0 0
## X636 1 0 1 1 0 1 1 0 1 0 1 0
## X637 1 0 1 1 0 0 1 0 0 0 0 0
## X638 1 1 1 1 1 0 0 1 0 1 0 0
## X639 1 1 0 1 1 1 0 1 0 0 0 0
## X641 1 1 1 1 1 0 1 0 0 1 0 0
## X648 1 1 0 1 1 1 0 1 1 1 1 0
## X650 1 1 1 1 1 1 0 0 0 0 1 0
## X651 1 1 1 1 1 0 1 0 0 0 0 0
## X653 1 0 1 1 0 1 1 0 0 1 1 0
## X654 1 1 1 1 1 0 1 1 0 0 0 1
## X655 0 1 1 0 1 0 1 1 0 0 0 0
## X656 0 1 0 0 1 0 0 0 1 0 0 0
## X657 1 1 1 1 1 1 1 1 0 0 0 1
## X1082 0 0 1 0 0 0 1 0 1 0 0 0
## X1083 0 1 0 0 1 1 0 1 0 0 1 0
## X1084 0 0 1 0 0 1 1 0 0 0 1 0
## X1086 0 1 0 0 1 0 0 0 1 0 0 0
## X1088 1 1 0 1 1 1 0 0 1 0 0 0
## X1089 0 1 1 0 1 1 1 1 0 0 1 0
## X1090 1 1 0 1 1 1 0 1 0 1 1 0
## X1091 0 1 1 0 1 0 1 1 0 1 0 0
## X1092 1 0 1 1 0 0 1 0 0 0 0 0
## X1093 1 0 1 1 0 0 0 0 1 0 0 0
## X1094 1 1 0 1 1 0 0 1 0 1 0 0
## X1095 1 1 0 1 1 1 0 1 0 0 0 0
## X1097 0 0 1 0 0 0 1 0 1 0 0 0
## X1098 1 0 1 1 0 1 1 0 0 0 0 0
## X1101 1 1 0 1 1 1 0 1 1 0 1 0
## X1103 1 1 0 1 1 1 1 1 0 1 1 0
## X1104 1 1 0 1 1 1 0 1 0 0 0 0
## X1105 1 0 0 1 1 1 0 0 0 0 0 0
## X1106 0 0 1 0 0 1 1 0 0 0 1 0
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## X865 0 0 0 0 0 0 1 0 0 1 0 0
## X866 0 0 0 0 0 0 0 0 0 0 0 0
## X867 0 0 0 0 0 0 1 0 0 1 0 0
## X869 0 0 0 0 0 0 1 1 0 1 0 0
## X870 0 0 0 0 0 0 0 0 0 0 0 0
## X871 0 0 0 0 0 0 0 0 0 1 0 0
## X872 0 0 0 0 0 0 0 0 0 0 0 0
## X873 0 0 0 0 0 0 0 0 0 1 0 0
## X875 0 0 0 0 0 0 0 0 0 0 0 0
## X876 0 0 0 0 0 0 0 0 0 0 0 0
## X877 0 0 0 0 0 0 0 0 0 0 0 0
## X1190 0 0 0 0 0 0 1 1 0 0 0 0
## X1191 0 0 0 0 0 0 0 0 1 0 1 0
## X1192 0 0 1 1 0 0 0 0 0 0 0 0
## X1193 0 0 0 0 0 0 0 0 0 0 0 0
## X1194 0 0 1 1 0 0 0 0 0 0 0 0
## X1195 0 0 0 0 0 0 0 0 0 1 0 0
## X1197 0 0 0 0 0 0 1 1 1 0 0 0
## X1198 0 0 0 0 0 0 0 0 0 0 0 0
## X1199 0 0 0 0 0 0 0 0 0 0 0 0
## X1200 0 0 0 0 0 0 0 0 0 0 0 0
## X1201 0 0 0 1 0 0 0 0 0 0 0 0
## X1202 0 0 1 1 0 0 0 0 0 0 0 0
## X1203 0 0 0 0 0 0 0 0 0 0 0 0
## X1204 0 0 0 0 0 1 1 0 0 0 0 0
## X1205 0 0 0 0 0 1 0 0 0 1 0 0
## X1206 0 0 0 0 0 0 0 0 0 0 0 0
## X1207 0 0 0 0 0 0 1 0 0 0 0 0
## X1208 0 0 1 1 0 0 0 0 0 0 0 0
## X1209 0 0 0 0 0 0 0 0 0 0 0 0
## X1210 0 0 1 0 0 0 0 0 0 0 0 0
## X1212 0 0 1 1 0 0 0 0 0 0 0 0
## X1213 0 0 0 0 0 0 1 0 0 0 0 0
## X1215 0 0 1 1 1 0 0 0 0 0 0 0
## X1216 0 0 0 0 0 0 1 0 0 0 0 0
## X1217 0 0 0 0 0 0 1 0 0 0 0 1
## X1219 0 0 0 0 0 0 0 0 0 0 0 0
## X1220 0 0 0 0 0 0 0 0 0 0 0 1
## X1221 0 0 0 0 0 0 0 0 1 0 1 0
## X1222 0 0 0 1 0 0 1 0 0 0 0 0
## X1226 0 0 0 0 0 0 1 0 0 0 0 0
## X1228 0 0 0 0 0 0 0 0 0 0 0 0
## X1229 0 0 1 1 0 0 0 0 0 0 0 0
## X1230 0 0 0 0 0 0 1 1 0 0 0 0
## X1231 0 0 0 0 0 0 1 1 0 0 0 0
## X1233 0 0 1 0 0 0 0 0 0 0 0 0
## X1234 0 0 0 0 0 0 1 0 0 0 0 0
## X1236 0 0 1 1 0 0 0 0 0 0 0 0
## X1237 0 0 0 0 0 0 0 0 0 0 0 0
## X1239 0 0 0 0 0 0 0 0 0 0 0 0
## X1242 0 0 0 0 0 0 0 0 0 0 0 0
## X1244 0 0 0 0 0 0 1 1 0 0 0 1
## X1245 0 0 0 0 0 0 1 1 1 0 1 0
## X1246 0 0 1 1 0 0 0 0 0 0 0 0
## X1247 0 0 1 0 0 0 1 1 0 1 0 0
## X1249 0 0 0 0 0 0 0 0 0 0 0 0
## X1250 0 0 0 0 0 0 0 0 0 0 0 0
## X1251 0 0 0 0 0 0 0 0 0 0 0 0
## X1253 0 0 0 0 0 0 0 0 0 0 0 1
## X1254 0 0 0 0 0 0 0 0 0 1 0 0
## X1255 0 0 0 0 0 0 1 0 0 0 0 0
## X1256 0 0 0 1 0 0 0 0 0 0 0 0
## X1257 0 0 0 0 0 0 1 0 0 0 0 1
## X1259 0 0 0 0 0 0 0 0 0 0 0 0
## X1260 0 0 0 0 0 0 0 0 0 0 0 1
## X1262 0 0 1 0 0 0 1 1 0 1 0 0
## X1264 0 0 0 0 0 0 0 0 0 0 0 0
## X1265 0 0 0 0 0 0 0 0 0 0 0 1
## X1266 0 0 0 0 0 0 1 0 0 0 0 1
## X1267 0 0 0 0 0 0 0 0 0 1 0 0
## X1268 0 0 0 0 0 0 0 0 1 0 1 0
## X1273 0 0 0 0 0 0 1 1 0 0 0 0
## X1274 0 0 0 0 1 0 0 0 1 0 1 0
## X1275 0 0 0 0 0 0 0 0 0 0 0 0
## X1276 0 0 0 0 0 0 1 0 0 1 0 0
## X1277 0 0 0 0 0 0 0 0 0 0 0 1
## X1278 0 0 0 0 0 0 1 0 0 0 0 0
## X1279 0 0 0 0 0 0 1 0 0 0 0 0
## X1281 0 0 0 0 0 0 0 0 0 0 0 0
## X1282 0 0 0 0 0 0 0 0 0 1 0 0
## X1283 0 0 0 0 0 0 1 0 0 1 0 0
## X1284 0 0 0 0 0 0 1 0 0 0 0 0
## X1285 0 0 0 0 0 0 0 0 0 0 0 0
## X1288 0 0 0 0 0 0 0 0 0 0 0 0
## X1299 0 1 0 0 0 0 1 1 0 0 0 0
## X1301 0 0 1 1 0 0 0 0 0 0 0 0
## X1302 0 0 0 0 0 0 0 0 0 0 0 0
## X1307 0 0 0 0 0 0 0 0 0 0 0 0
## X1309 0 0 0 0 0 0 0 0 0 0 0 1
## X1310 0 0 0 0 0 0 0 0 0 0 0 0
## X447 0 0 0 0 0 0 0 0 0 0 0 1
## X448 0 0 0 0 0 0 0 0 0 0 0 0
## X451 0 0 0 0 0 0 0 0 0 0 0 0
## X452 0 0 0 0 0 0 0 0 0 0 0 0
## X453 0 0 0 0 0 1 0 0 0 1 0 0
## X454 1 0 0 0 0 0 0 0 0 0 0 0
## X455 0 0 0 0 0 0 0 0 0 0 0 1
## X456 0 0 0 1 0 0 1 1 0 0 0 0
## X458 1 0 0 0 0 1 0 0 0 0 0 0
## X459 0 0 0 0 0 0 0 0 1 0 1 0
## X460 0 0 0 0 0 0 0 0 0 0 0 0
## X461 0 0 0 0 0 0 0 0 0 1 0 0
## X462 0 0 0 0 0 0 0 0 0 0 0 0
## X463 0 1 0 0 0 0 1 1 0 0 0 0
## X464 0 0 0 0 0 0 0 0 0 0 0 0
## X465 0 0 0 0 0 0 0 0 0 0 0 0
## X466 0 0 0 0 0 0 0 0 0 1 0 0
## X468 0 0 0 0 0 0 0 0 1 0 1 0
## X471 1 0 0 0 0 0 0 0 0 0 0 0
## X472 0 0 0 0 0 0 0 0 0 0 0 0
## X473 0 0 0 0 0 0 0 0 0 0 0 0
## X476 0 0 0 0 0 0 1 0 0 1 0 0
## X477 0 1 0 0 0 0 1 0 0 0 0 0
## X478 0 0 0 0 0 0 0 0 0 0 0 0
## X479 0 0 0 0 0 0 0 0 0 0 0 0
## X480 0 0 0 0 0 1 0 0 0 0 0 0
## X482 0 0 0 0 0 0 0 0 0 0 0 0
## X483 0 0 0 0 0 0 0 0 0 0 0 0
## X484 1 0 0 0 0 0 0 0 0 0 0 0
## X486 0 0 0 0 0 0 0 0 1 0 1 0
## X487 0 0 0 0 0 0 0 0 0 0 0 0
## X488 0 0 0 0 0 0 0 0 1 0 0 0
## X489 0 0 0 0 0 0 1 0 0 0 0 0
## X490 0 0 0 0 0 0 0 0 0 1 0 0
## X491 0 0 0 0 0 0 0 0 1 0 1 0
## X492 0 1 1 1 0 0 0 0 0 0 0 0
## X493 0 0 0 0 0 0 0 0 1 0 1 0
## X494 1 0 0 0 0 0 0 0 0 0 0 0
## X495 0 0 0 0 0 1 0 0 0 0 0 0
## X496 0 1 0 0 0 1 0 0 0 0 0 0
## X497 0 0 0 0 0 1 1 0 0 0 0 0
## X498 0 0 0 0 0 0 0 0 0 0 0 0
## X499 0 0 0 0 0 0 1 0 0 0 0 0
## X501 0 0 0 0 0 0 0 0 0 0 0 0
## X502 0 0 0 0 0 0 0 0 0 1 0 0
## X503 0 0 0 0 0 0 1 0 0 0 0 0
## X505 0 0 0 0 0 0 0 0 0 0 0 1
## X506 1 0 0 0 0 1 0 0 0 0 0 0
## X507 1 0 0 0 0 1 0 0 0 0 0 0
## X508 0 0 0 0 0 0 0 0 0 0 0 0
## X509 0 0 0 0 0 0 0 0 0 1 0 0
## X510 1 0 0 0 0 0 1 1 0 0 0 0
## X513 0 0 0 0 0 0 0 0 0 0 0 0
## X514 1 0 0 0 0 0 0 0 0 0 0 0
## X515 0 0 0 0 0 0 0 0 0 1 0 0
## X516 0 0 0 0 0 0 0 0 0 0 0 0
## X518 0 0 0 0 0 0 0 0 0 1 0 0
## X521 1 0 0 0 0 0 0 0 0 0 0 0
## X523 0 0 0 0 0 0 1 1 0 0 0 0
## X524 0 0 0 0 0 0 0 0 0 0 0 0
## X525 0 1 0 1 0 0 0 0 0 0 0 0
## X526 0 0 0 0 1 0 0 0 1 0 1 0
## X530 0 0 0 0 0 0 1 1 0 0 0 0
## X531 0 0 0 0 0 0 0 0 0 0 0 0
## X532 0 0 0 0 0 0 0 0 0 0 0 0
## X533 0 1 0 0 0 0 0 0 0 0 0 0
## X534 0 0 0 0 0 0 1 1 1 0 0 0
## X535 0 0 0 0 0 0 1 0 0 0 0 0
## X536 0 0 0 0 0 1 1 0 0 0 0 0
## X538 0 0 0 0 0 0 0 0 0 0 0 0
## X539 0 0 0 0 0 1 1 0 0 0 0 0
## X542 0 0 1 1 1 0 0 0 0 0 0 0
## X543 0 0 0 0 0 0 0 0 1 0 1 0
## X544 0 0 1 0 0 0 0 0 0 1 0 0
## X545 0 0 0 0 0 0 0 0 1 0 0 0
## X546 0 0 0 0 0 0 0 0 0 0 0 0
## X548 0 0 0 0 0 0 0 0 0 0 0 0
## X549 0 0 0 0 0 0 0 0 0 0 0 0
## X551 0 0 0 0 0 0 0 0 0 0 0 0
## X552 0 0 0 1 0 0 0 0 0 0 0 0
## X553 0 0 0 0 0 0 1 1 0 0 0 0
## X554 0 0 0 0 0 0 0 0 0 0 0 0
## X556 0 0 0 0 0 0 1 1 0 0 0 0
## X557 1 0 0 0 0 0 0 0 0 0 0 0
## X558 0 0 0 0 0 0 1 0 0 0 0 0
## X559 0 0 0 0 0 0 0 0 1 0 0 0
## X560 0 0 0 0 0 0 0 0 0 1 0 0
## X561 0 0 0 0 0 0 0 0 0 1 0 0
## X562 0 0 0 0 0 0 1 0 0 0 0 0
## X563 0 0 0 0 0 0 1 1 0 0 0 0
## X565 0 0 0 0 0 0 0 0 1 0 0 0
## X566 1 0 0 0 0 0 0 0 0 0 0 0
## X567 0 0 0 0 0 0 0 0 0 0 0 0
## X568 0 0 0 0 0 0 0 0 0 0 0 0
## X569 0 0 0 0 0 0 0 0 0 1 0 0
## X571 1 0 0 0 0 0 0 0 0 0 0 0
## X572 1 0 0 0 0 0 0 0 1 0 1 0
## X574 0 0 0 1 0 0 0 0 0 0 0 0
## X576 1 0 0 0 0 0 0 0 0 0 0 0
## X577 0 0 0 0 0 0 1 0 0 1 0 0
## X579 0 0 0 0 0 0 1 1 0 0 0 0
## X580 0 0 0 0 0 0 0 0 0 0 0 0
## X582 0 0 0 0 0 0 0 0 1 0 1 0
## X583 0 0 0 0 0 0 0 0 0 0 0 0
## X584 0 0 0 0 0 0 1 0 0 0 0 0
## X586 0 0 0 0 0 0 1 0 0 0 0 0
## X587 0 0 0 0 0 1 1 0 0 0 0 0
## X588 0 1 0 0 0 0 0 0 0 0 0 0
## X589 0 0 1 0 0 0 0 0 0 0 0 0
## X591 0 0 0 0 0 1 0 0 0 0 0 0
## X592 0 0 0 0 0 0 1 1 0 0 0 0
## X593 0 0 0 0 0 0 1 0 0 0 0 0
## X594 0 0 0 0 0 0 0 0 1 0 1 0
## X595 0 0 0 0 0 0 0 0 0 0 0 0
## X596 0 0 0 0 0 0 0 0 1 0 0 0
## X597 0 0 0 0 0 0 1 0 0 0 0 0
## X598 0 0 0 0 0 0 0 0 0 0 0 0
## X599 0 0 0 0 0 0 0 0 0 0 0 0
## X600 0 0 1 0 0 0 0 0 0 0 0 0
## X603 0 0 0 0 0 0 0 0 1 0 1 0
## X604 0 1 0 0 0 0 0 0 0 0 0 0
## X605 0 0 1 1 0 0 0 0 0 0 0 0
## X606 0 0 0 0 0 0 1 1 1 0 0 0
## X608 0 0 0 0 0 0 1 0 0 0 0 0
## X609 1 0 0 0 0 1 0 0 0 0 0 0
## X611 0 0 0 0 0 0 0 0 0 0 0 0
## X612 0 0 0 0 0 0 0 0 0 0 0 0
## X613 0 0 0 0 0 0 0 0 0 1 0 0
## X614 0 0 0 0 0 0 1 0 0 0 0 0
## X616 0 0 0 0 0 0 0 0 0 0 0 0
## X617 0 0 0 0 0 0 1 0 0 1 0 0
## X619 0 1 0 0 0 0 1 1 0 0 0 0
## X620 0 0 0 0 0 0 0 0 0 0 0 1
## X621 0 0 0 0 0 0 1 1 0 0 0 0
## X622 0 0 0 0 0 0 1 0 0 0 0 0
## X623 0 1 0 0 0 0 1 0 0 0 0 1
## X625 0 0 0 0 0 0 0 0 0 0 0 1
## X628 0 0 1 1 1 0 0 0 0 0 0 0
## X629 0 0 1 0 0 0 0 0 0 0 0 0
## X630 0 0 0 1 0 0 1 0 0 0 0 0
## X631 0 0 0 0 0 0 0 0 1 0 1 0
## X632 0 0 0 0 0 0 0 0 0 0 0 0
## X633 0 0 0 0 0 0 0 0 0 0 0 1
## X635 0 0 0 0 0 0 0 0 0 0 0 0
## X636 0 0 1 1 1 0 0 0 0 0 0 0
## X637 0 0 1 1 0 0 0 0 0 0 0 0
## X638 0 0 0 0 0 0 1 1 0 1 0 0
## X639 1 0 0 0 0 1 0 0 0 0 0 0
## X641 0 0 0 0 0 0 1 1 1 0 0 0
## X648 0 0 0 0 0 0 0 0 0 1 0 0
## X650 0 0 0 0 0 0 0 0 0 0 0 0
## X651 0 0 0 0 0 0 1 1 1 0 0 0
## X653 0 0 1 0 0 0 0 0 0 0 0 0
## X654 0 0 0 0 0 0 0 0 1 0 0 0
## X655 0 0 0 0 0 0 1 1 0 0 0 0
## X656 0 0 0 0 0 0 1 0 0 1 0 0
## X657 1 0 0 0 0 0 0 0 1 0 1 0
## X1082 0 0 0 0 0 0 0 0 0 0 0 0
## X1083 0 0 0 0 0 0 1 1 0 0 0 0
## X1084 0 0 0 0 0 0 0 0 0 0 0 0
## X1086 0 0 0 0 0 0 1 1 0 0 0 0
## X1088 0 0 0 0 0 0 0 0 0 0 0 1
## X1089 0 0 0 0 0 0 1 0 0 0 0 0
## X1090 0 0 0 0 0 0 0 0 0 0 0 0
## X1091 0 0 0 0 0 0 0 0 1 0 1 0
## X1092 0 0 0 0 0 0 0 0 1 0 0 0
## X1093 0 0 1 0 0 0 0 0 0 0 0 0
## X1094 0 0 0 0 0 0 0 0 0 0 0 0
## X1095 0 1 0 0 0 0 1 0 0 0 0 0
## X1097 0 0 0 0 0 0 0 0 0 0 0 0
## X1098 0 1 0 0 0 0 0 0 0 0 0 0
## X1101 0 1 0 0 0 0 0 0 0 0 0 0
## X1103 0 0 0 0 0 0 0 0 0 0 0 0
## X1104 1 0 0 0 0 1 1 0 0 0 0 0
## X1105 0 1 0 0 0 1 0 0 0 0 0 0
## X1106 0 0 0 0 0 0 0 0 1 0 1 0
## X1108 0 0 0 0 0 0 0 0 0 0 0 0
## X1110 0 0 0 0 0 0 1 1 0 0 0 0
## X1112 1 0 0 0 0 1 0 0 0 0 0 0
## X1113 0 0 0 0 0 0 0 0 0 0 0 0
## X1115 0 0 0 0 0 0 1 1 0 0 0 0
## X1116 0 0 0 0 0 0 0 0 0 0 0 1
## X1117 0 0 0 0 0 0 1 0 0 0 0 0
## X1119 0 0 0 0 0 0 0 0 0 0 0 0
## X1120 0 0 1 1 1 0 0 0 0 0 0 0
## X1121 0 1 0 0 0 1 0 0 0 0 0 0
## X1122 0 0 1 0 1 0 0 0 0 0 0 0
## X1124 0 0 0 0 0 0 1 0 0 0 0 0
## X1125 0 0 0 0 0 0 0 0 0 0 0 0
## X1126 0 0 0 0 0 0 0 0 0 1 0 0
## X1127 0 0 0 1 0 0 1 0 0 0 0 0
## X1128 0 0 0 0 0 0 0 0 0 0 0 0
## X1129 0 0 0 0 0 0 0 0 0 0 0 1
## X1130 0 0 0 0 0 0 0 0 0 0 0 0
## X1131 0 0 0 0 0 0 0 0 0 0 0 0
## X1133 1 0 0 0 0 0 1 1 0 0 0 0
## X1135 0 0 0 0 0 0 0 0 1 0 1 0
## X1136 0 0 0 0 0 0 0 0 0 0 0 0
## X1138 0 0 0 0 0 0 0 0 0 0 0 0
## X1139 0 0 1 1 1 0 0 0 0 0 0 0
## X1141 0 0 0 0 0 0 0 0 0 0 0 0
## X1142 0 0 0 0 0 0 0 0 0 0 0 1
## X1143 0 0 0 0 0 0 1 1 0 0 0 0
## X1144 0 0 0 0 0 0 0 0 0 0 0 0
## X1145 0 1 0 0 0 0 0 0 0 0 0 0
## X1146 0 0 0 0 0 0 0 0 1 0 1 0
## X1147 0 0 0 0 0 0 0 0 1 0 0 0
## X1149 0 0 0 0 0 0 0 0 0 1 0 0
## X1150 0 0 0 0 0 0 0 0 1 0 1 0
## X1151 0 0 0 0 0 0 0 0 0 0 0 0
## X1152 0 0 0 0 0 0 0 0 0 0 0 0
## X1153 0 0 0 0 0 0 0 0 0 0 0 0
## X1156 0 0 0 0 0 0 0 0 1 0 1 0
## X1158 0 0 0 0 0 0 0 0 0 0 0 0
## X1159 0 0 0 0 0 0 0 0 0 0 0 0
## X1160 0 0 0 0 0 0 1 0 0 0 0 0
## FP208 MolWeight NumBonds NumMultBonds NumRotBonds NumDblBonds
## X661 0 0.304017769 0.49840233 1.90489650 -0.9347280 -0.831341597
## X662 0 1.474751336 1.69828720 1.32482715 0.7260405 -0.831341597
## X663 0 0.284237960 0.69697444 0.16468846 0.7260405 -0.005212173
## X665 0 -0.579130036 0.20728011 -0.80209379 -0.5195359 0.820917251
## X668 0 0.508214019 0.56629095 -0.02866799 1.1412327 -0.831341597
## X669 0 0.846130172 0.56629095 -0.80209379 1.1412327 0.820917251
## X670 0 1.343679568 0.99793817 2.29160940 -0.5195359 -0.005212173
## X671 0 0.223329553 0.94039386 -0.99545024 3.2171934 -0.005212173
## X672 0 1.536294032 1.99292450 -0.41538089 -0.5195359 2.473176098
## X673 1 0.531725024 0.99793817 0.16468846 -0.1043438 -0.005212173
## X674 0 0.513009822 0.63244961 0.55140136 -0.1043438 1.647046674
## X676 0 0.981923863 1.69828720 -0.80209379 -0.9347280 0.820917251
## X677 0 -0.294344540 0.12893412 0.93811425 -0.9347280 -0.831341597
## X678 0 -0.211043577 -0.40240913 0.93811425 -0.9347280 -0.831341597
## X679 1 -0.403319666 0.28325136 -0.02866799 -0.1043438 -0.831341597
## X682 0 0.513009822 0.63244961 1.13147070 0.3108484 -0.005212173
## X683 0 1.174798750 1.36999732 0.35804491 2.3868091 0.820917251
## X684 0 1.683069116 1.87027471 1.13147070 1.5564248 -0.831341597
## X685 0 0.996447520 1.78555525 -0.99545024 -0.9347280 -0.005212173
## X686 0 -0.294344540 0.12893412 0.93811425 -0.5195359 -0.831341597
## X688 0 0.880198541 0.63244961 1.32482715 -0.1043438 -0.005212173
## X689 0 0.923239370 1.46773946 1.13147070 0.7260405 -0.831341597
## X690 0 1.144391553 1.46773946 0.16468846 2.3868091 -0.005212173
## X691 0 1.836745684 0.88159159 -0.80209379 0.7260405 0.820917251
## X692 1 1.649573481 1.46773946 0.55140136 3.2171934 1.647046674
## X693 0 1.038577746 1.16359252 0.55140136 0.3108484 1.647046674
## X695 0 1.252510849 1.56220886 1.13147070 1.1412327 -0.831341597
## X696 0 0.158871193 0.28325136 1.90489650 -0.9347280 -0.831341597
## X698 0 0.792852769 1.31981693 0.16468846 0.7260405 -0.005212173
## X699 0 -0.094205025 -1.09071695 0.16468846 -0.9347280 -0.831341597
## X700 0 -0.771172819 0.04803954 -0.99545024 1.1412327 -0.831341597
## X702 0 -1.218301524 -0.12219740 -1.18880668 -0.1043438 -0.831341597
## X703 0 -0.982753213 0.04803954 -1.18880668 -0.9347280 -0.831341597
## X704 0 -0.294344540 0.12893412 0.93811425 -0.9347280 -0.831341597
## X706 0 0.636103875 0.82146772 0.55140136 0.3108484 1.647046674
## X708 1 -0.321429192 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X709 0 -0.982753213 0.04803954 -1.18880668 -0.9347280 -0.831341597
## X711 0 1.706734262 2.47286768 -0.99545024 0.7260405 -0.005212173
## X712 0 0.831678296 1.16359252 1.32482715 0.7260405 -0.005212173
## X713 0 0.929168040 0.56629095 1.32482715 0.3108484 -0.005212173
## X714 0 1.675379106 2.11068236 -0.22202444 0.7260405 3.299305521
## X715 0 0.750468797 0.12893412 0.35804491 0.3108484 -0.005212173
## X717 0 0.291891037 -0.40240913 0.93811425 -0.9347280 -0.831341597
## X718 0 1.522316745 1.69828720 1.13147070 0.7260405 -0.831341597
## X721 0 0.508214019 0.56629095 -0.02866799 0.7260405 -0.831341597
## X722 1 1.257699471 1.10948462 1.71154005 -0.1043438 1.647046674
## X723 0 -0.982753213 -0.03559810 -0.99545024 1.1412327 -0.005212173
## X724 1 0.026037466 0.12893412 1.32482715 -0.1043438 -0.005212173
## X726 0 0.989629709 0.12893412 1.13147070 -0.1043438 -0.831341597
## X728 1 0.635848282 0.63244961 1.32482715 0.3108484 -0.005212173
## X729 0 1.163654675 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X731 0 -1.218301524 -0.12219740 -1.18880668 0.7260405 -0.831341597
## X732 1 0.098097256 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X733 0 0.237099891 0.12893412 -0.02866799 0.7260405 -0.831341597
## X734 0 0.378611406 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X735 0 1.052782459 1.65364219 -0.60873734 -0.9347280 0.820917251
## X736 0 0.558425111 0.99793817 0.16468846 2.3868091 -0.005212173
## X737 0 0.060245711 -0.21200528 1.32482715 -0.5195359 0.820917251
## X739 0 1.400858350 1.26871571 0.55140136 0.3108484 1.647046674
## X740 0 1.430265786 1.26871571 2.29160940 0.7260405 0.820917251
## X741 0 0.223329553 0.94039386 -0.99545024 3.2171934 -0.005212173
## X742 0 0.072232210 0.75995351 -0.99545024 2.8020012 -0.005212173
## X743 0 0.378611406 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X744 0 -0.321429192 0.04803954 0.93811425 -0.9347280 -0.831341597
## X746 0 0.907820092 1.21665476 0.35804491 2.3868091 0.820917251
## X747 0 0.072790642 0.99793817 -1.18880668 3.2171934 -0.831341597
## X749 0 1.889098307 2.07194628 1.32482715 2.3868091 -0.005212173
## X752 0 2.027107324 2.54041376 -0.22202444 1.9716169 3.299305521
## X753 0 -0.982753213 0.04803954 -1.18880668 -0.1043438 -0.831341597
## X754 0 1.135094949 1.46773946 1.13147070 -0.1043438 -0.831341597
## X755 0 -0.294344540 0.12893412 0.93811425 -0.9347280 -0.831341597
## X757 0 0.475066868 -0.12219740 -1.18880668 0.7260405 -0.831341597
## X758 0 0.201609653 0.49840233 1.13147070 -0.1043438 -0.831341597
## X759 0 1.039771029 0.82146772 -0.80209379 1.9716169 0.820917251
## X760 1 0.098097256 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X761 0 1.834687162 2.22396656 -0.22202444 0.7260405 3.299305521
## X762 0 -0.165345469 0.12893412 1.13147070 -0.9347280 -0.831341597
## X763 0 0.710001130 0.28325136 1.13147070 -0.5195359 -0.831341597
## X764 0 -0.115366351 0.35700394 0.93811425 -0.9347280 -0.831341597
## X765 0 1.803708352 1.05428349 1.32482715 1.1412327 -0.005212173
## X767 0 1.677549637 1.95260717 -0.02866799 0.3108484 4.125434945
## X768 0 -0.152986644 0.04803954 1.71154005 -0.9347280 -0.831341597
## X770 0 1.190653352 1.21665476 1.13147070 0.7260405 -0.831341597
## X771 0 1.188302449 0.20728011 0.74475780 -0.5195359 2.473176098
## X772 0 1.163654675 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X773 0 -0.737607576 0.20728011 -0.99545024 1.5564248 -0.005212173
## X774 0 0.147051515 0.12893412 -1.18880668 1.1412327 -0.831341597
## X775 1 0.719516934 0.75995351 1.51818360 1.1412327 0.820917251
## X776 0 2.101817743 2.14892180 1.90489650 2.3868091 2.473176098
## X777 0 1.162199568 1.26871571 -0.99545024 4.0475776 -0.005212173
## X778 0 1.978779123 2.70310385 -0.80209379 1.5564248 0.820917251
## X779 0 0.148236508 0.35700394 1.90489650 -0.9347280 -0.831341597
## X780 0 0.865295430 -1.37754378 -0.80209379 -0.9347280 0.820917251
## X781 0 1.135296034 1.82822307 -0.60873734 3.6323855 1.647046674
## X782 0 0.303418106 0.20728011 1.51818360 -0.9347280 0.820917251
## X784 0 2.675894881 0.88159159 1.32482715 1.1412327 -0.005212173
## X786 0 -0.945628244 0.12893412 -1.18880668 1.1412327 -0.831341597
## X787 1 0.447081835 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X788 0 1.327364381 2.03269881 -0.41538089 -0.5195359 2.473176098
## X789 0 0.447081835 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X791 0 0.447081835 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X792 0 1.398910560 1.36999732 1.13147070 0.7260405 -0.831341597
## X794 0 0.496130384 1.26871571 -0.99545024 4.0475776 -0.005212173
## X798 0 0.735984417 0.82146772 3.06503519 -0.5195359 -0.831341597
## X799 0 1.378795179 0.35700394 -0.60873734 -0.1043438 1.647046674
## X800 0 1.108515489 1.82822307 -1.18880668 -0.9347280 -0.831341597
## X804 0 1.017548306 1.41929339 1.51818360 0.7260405 0.820917251
## X805 0 1.956176482 2.60651481 -0.41538089 1.5564248 2.473176098
## X807 0 1.580162693 1.10948462 -0.80209379 4.0475776 0.820917251
## X808 1 1.380821445 1.46773946 2.48496584 1.1412327 1.647046674
## X809 1 1.147725526 1.31981693 1.51818360 2.8020012 0.820917251
## X810 0 1.317009930 0.04803954 -0.80209379 -0.9347280 0.820917251
## X813 0 0.953373701 1.82822307 -0.99545024 5.7083462 -0.005212173
## X814 0 1.355892859 1.16359252 0.35804491 0.7260405 0.820917251
## X818 0 0.745867382 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X819 0 1.136435150 0.56629095 1.51818360 -0.1043438 0.820917251
## X820 0 0.364681635 1.31981693 -1.18880668 4.0475776 -0.831341597
## X821 1 0.745867382 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X822 0 0.242973688 0.42867850 2.48496584 -0.9347280 -0.831341597
## X823 0 0.627652706 0.82146772 2.87167874 -0.9347280 -0.831341597
## X827 0 1.560421390 0.56629095 -0.99545024 -0.9347280 -0.005212173
## X828 0 0.745867382 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X829 0 1.630165630 1.16359252 0.55140136 1.9716169 1.647046674
## X831 0 1.184902006 0.28325136 1.32482715 -0.1043438 -0.005212173
## X832 1 0.447081835 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X833 0 1.007095938 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X834 0 1.198080407 0.42867850 1.13147070 -0.1043438 -0.831341597
## X835 0 0.447081835 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X836 0 1.007095938 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X839 0 0.382560531 0.63244961 2.09825295 -0.9347280 -0.831341597
## X840 0 0.495036672 0.69697444 2.87167874 -0.9347280 -0.831341597
## X841 0 1.007095938 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X842 0 0.284137074 0.63244961 1.90489650 -0.5195359 -0.831341597
## X843 0 1.184902006 0.28325136 1.32482715 -0.1043438 -0.005212173
## X846 1 0.513371322 0.75995351 2.29160940 -0.1043438 -0.831341597
## X848 0 1.239163633 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X849 0 1.007095938 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X851 0 1.737322938 2.63904482 -0.99545024 -0.9347280 -0.005212173
## X854 0 1.007095938 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X855 0 0.823597252 0.99793817 3.64510454 -0.9347280 -0.831341597
## X856 0 1.447932035 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X857 0 1.239163633 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X858 0 1.447932035 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X859 0 1.447932035 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X860 0 1.007095938 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X862 1 1.239163633 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X863 0 1.637655670 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X864 0 0.831600743 1.16359252 2.87167874 -0.9347280 -0.831341597
## X865 0 0.703248097 0.88159159 3.45174809 -0.9347280 -0.831341597
## X866 0 1.447932035 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X867 0 0.703248097 0.88159159 3.45174809 -0.9347280 -0.831341597
## X869 1 1.552263693 1.46773946 3.25839164 0.7260405 -0.831341597
## X870 0 1.447932035 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X871 0 1.447932035 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X872 0 1.447932035 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X873 0 0.703248097 0.88159159 3.45174809 -0.9347280 -0.831341597
## X875 0 1.811520606 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X876 0 1.811520606 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X877 0 2.120939599 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1190 1 -0.115977627 0.04803954 1.13147070 -0.1043438 -0.831341597
## X1191 0 -0.603559640 -0.12219740 -1.18880668 0.7260405 -0.831341597
## X1192 0 1.080766715 1.82822307 -0.80209379 -0.9347280 0.820917251
## X1193 0 -0.403319666 0.28325136 -0.02866799 -0.9347280 -0.831341597
## X1194 0 1.675379106 2.11068236 -0.22202444 0.7260405 3.299305521
## X1195 0 0.016880687 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X1197 1 -0.610215946 0.04803954 -0.02866799 0.3108484 -0.831341597
## X1198 0 0.563194962 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X1199 0 0.611250316 0.82146772 -0.02866799 1.1412327 -0.831341597
## X1200 0 0.769013180 0.42867850 -0.99545024 2.3868091 -0.005212173
## X1201 0 1.574200229 1.74225056 1.32482715 0.3108484 -0.005212173
## X1202 0 2.035474501 2.33314222 -0.02866799 1.5564248 4.125434945
## X1203 0 -0.982753213 0.04803954 -1.18880668 -0.9347280 -0.831341597
## X1204 0 1.270551909 0.99793817 1.90489650 -0.1043438 2.473176098
## X1205 0 0.936481465 0.49840233 1.32482715 0.3108484 -0.005212173
## X1206 0 0.476723028 -1.70965649 -0.80209379 -0.5195359 0.820917251
## X1207 0 0.952788440 1.21665476 1.13147070 0.3108484 -0.831341597
## X1208 0 1.747037108 2.22396656 -0.41538089 -0.1043438 2.473176098
## X1209 0 0.815641020 -1.09071695 -0.02866799 -0.9347280 -0.831341597
## X1210 0 1.623602913 2.43853015 -0.99545024 0.7260405 -0.005212173
## X1212 0 1.038647958 1.56220886 0.16468846 -0.9347280 -0.831341597
## X1213 0 0.952788440 1.21665476 1.13147070 0.7260405 -0.831341597
## X1215 0 1.834687162 2.26079827 -0.41538089 -0.1043438 2.473176098
## X1216 0 0.049093577 -0.03559810 1.71154005 -0.9347280 -0.831341597
## X1217 0 1.269483899 0.88159159 2.29160940 0.3108484 -0.831341597
## X1219 0 0.847285078 1.26871571 1.13147070 1.1412327 -0.831341597
## X1220 0 1.532919242 1.65364219 1.32482715 1.5564248 -0.005212173
## X1221 0 -0.009904078 -0.12219740 -1.18880668 0.7260405 -0.831341597
## X1222 0 0.900780208 1.41929339 1.32482715 0.3108484 -0.005212173
## X1226 0 1.701175131 1.82822307 1.13147070 0.7260405 -0.831341597
## X1228 0 0.907670555 0.56629095 0.16468846 1.1412327 -0.005212173
## X1229 0 1.882368345 2.43853015 -0.22202444 1.1412327 3.299305521
## X1230 1 0.448387506 0.35700394 1.51818360 -0.5195359 0.820917251
## X1231 1 0.026494249 0.42867850 1.13147070 0.3108484 -0.831341597
## X1233 0 1.175127549 1.95260717 -0.80209379 -0.5195359 0.820917251
## X1234 0 -0.294344540 0.12893412 0.93811425 -0.9347280 -0.831341597
## X1236 0 1.327058775 1.87027471 -0.41538089 -0.1043438 1.647046674
## X1237 0 1.214275611 -0.03559810 0.16468846 0.7260405 -0.005212173
## X1239 0 1.095780590 0.56629095 -0.80209379 1.1412327 0.820917251
## X1242 0 0.771569118 -1.70965649 -0.80209379 -0.5195359 0.820917251
## X1244 1 0.098097256 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1245 1 -0.215143211 0.49840233 -0.02866799 1.1412327 -0.831341597
## X1246 0 0.815953602 1.16359252 1.13147070 -0.9347280 -0.005212173
## X1247 1 1.387244764 1.78555525 1.51818360 1.9716169 0.820917251
## X1249 0 1.459034034 1.05428349 0.55140136 1.5564248 1.647046674
## X1250 0 1.413034907 0.12893412 -0.80209379 -0.9347280 0.820917251
## X1251 0 0.812356063 -0.96037479 0.35804491 -0.9347280 -0.831341597
## X1253 0 1.341677499 0.75995351 0.16468846 2.3868091 -0.005212173
## X1254 0 0.447081835 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1255 0 0.137547205 0.42867850 1.90489650 -0.9347280 -0.831341597
## X1256 0 0.304417449 0.82146772 0.93811425 -0.9347280 -0.831341597
## X1257 0 0.745867382 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1259 0 1.560421390 0.56629095 -0.99545024 -0.9347280 -0.005212173
## X1260 0 0.745867382 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1262 1 1.616540792 1.51536781 1.51818360 1.9716169 0.820917251
## X1264 0 1.518473204 0.04803954 -0.80209379 -0.9347280 0.820917251
## X1265 0 1.007095938 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1266 0 1.410804929 0.42867850 1.13147070 -0.1043438 -0.831341597
## X1267 0 1.745837809 1.69828720 2.48496584 1.5564248 -0.005212173
## X1268 0 0.737283220 1.56220886 -0.99545024 4.8779619 -0.005212173
## X1273 1 1.007095938 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1274 0 0.620626671 1.60829128 -1.18880668 4.8779619 -0.831341597
## X1275 0 1.471104074 0.42867850 -0.80209379 -0.9347280 0.820917251
## X1276 0 0.703248097 0.88159159 3.45174809 -0.9347280 -0.831341597
## X1277 0 1.239163633 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1278 0 0.382560531 0.63244961 2.09825295 -0.9347280 -0.831341597
## X1279 0 0.495036672 0.69697444 2.87167874 -0.9347280 -0.831341597
## X1281 0 1.447932035 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1282 0 1.447932035 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1283 0 0.703248097 0.88159159 3.45174809 -0.9347280 -0.831341597
## X1284 0 0.495036672 0.69697444 2.87167874 -0.9347280 -0.831341597
## X1285 0 1.447932035 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1288 0 1.971974745 -0.03559810 1.13147070 -0.5195359 -0.831341597
## X1299 1 0.703000619 0.69697444 1.51818360 -0.1043438 0.820917251
## X1301 0 0.981923863 1.69828720 -0.80209379 -0.9347280 0.820917251
## X1302 0 0.998810596 -0.50369472 -1.18880668 -0.9347280 -0.831341597
## X1307 0 1.387897880 0.42867850 0.16468846 1.5564248 -0.005212173
## X1309 0 1.410804929 0.42867850 1.13147070 -0.1043438 -0.831341597
## X1310 0 1.712430972 0.20728011 -0.99545024 -0.9347280 -0.005212173
## X447 0 0.427774521 -0.40240913 0.16468846 0.3108484 -0.005212173
## X448 0 1.975155875 1.87027471 0.93811425 -0.1043438 3.299305521
## X451 0 -1.960986946 -0.96037479 -0.99545024 -0.5195359 -0.005212173
## X452 0 -0.455773295 -0.83728034 -0.02866799 -0.9347280 -0.831341597
## X453 0 -0.447297107 -0.40240913 0.93811425 -0.9347280 -0.831341597
## X454 0 1.024063318 0.82146772 1.51818360 0.7260405 0.820917251
## X455 0 0.366815837 0.12893412 0.16468846 0.3108484 -0.005212173
## X456 1 0.392161232 0.63244961 0.35804491 -0.1043438 0.820917251
## X458 0 0.922422855 0.63244961 1.51818360 0.7260405 0.820917251
## X459 0 -0.489295914 0.28325136 -0.99545024 1.5564248 -0.005212173
## X460 0 -1.632068261 -0.72058540 -0.99545024 -0.9347280 -0.005212173
## X461 0 -0.289953121 -0.83728034 0.16468846 -0.5195359 -0.005212173
## X462 0 -0.983309595 -0.83728034 -0.22202444 -0.5195359 -0.831341597
## X463 1 0.808360205 1.16359252 1.32482715 1.1412327 -0.005212173
## X464 0 0.243179485 -2.10721958 -1.18880668 -0.9347280 -0.831341597
## X465 0 0.736065616 0.94039386 1.13147070 0.7260405 -0.831341597
## X466 0 0.630729830 -0.12219740 0.35804491 -0.1043438 0.820917251
## X468 0 -0.254497849 0.28325136 -0.99545024 1.9716169 -0.005212173
## X471 0 -0.390166117 -0.12219740 0.16468846 -0.1043438 -0.005212173
## X472 0 -1.089862985 -0.72058540 -1.18880668 -0.1043438 -0.831341597
## X473 0 -1.960986946 -0.83728034 -1.18880668 -0.9347280 -0.831341597
## X476 0 0.071003132 0.12893412 1.13147070 -0.1043438 -0.005212173
## X477 0 0.601744921 0.42867850 0.55140136 -0.5195359 1.647046674
## X478 0 -1.632068261 -0.83728034 -0.80209379 0.3108484 0.820917251
## X479 0 -1.960986946 -0.96037479 -0.99545024 -0.1043438 -0.005212173
## X480 0 0.002838576 0.04803954 1.90489650 -0.9347280 -0.831341597
## X482 0 -0.507220812 -0.72058540 -1.18880668 -0.5195359 -0.831341597
## X483 0 -0.725281754 -1.09071695 -1.18880668 -0.5195359 -0.831341597
## X484 0 0.048980624 0.28325136 1.13147070 -0.5195359 -0.831341597
## X486 0 -0.267476312 0.35700394 -0.99545024 1.9716169 -0.005212173
## X487 0 0.808360205 1.21665476 0.16468846 2.8020012 -0.005212173
## X488 0 0.158871193 0.35700394 0.16468846 1.1412327 -0.005212173
## X489 0 0.667472628 -0.83728034 0.16468846 -0.5195359 -0.005212173
## X490 0 0.948173754 1.16359252 0.16468846 1.1412327 -0.005212173
## X491 0 -1.089862985 -0.72058540 -1.18880668 -0.1043438 -0.831341597
## X492 0 0.566721151 0.75995351 -0.41538089 -0.5195359 2.473176098
## X493 0 -0.267476312 0.35700394 -0.99545024 1.9716169 -0.005212173
## X494 0 0.611681349 -0.72058540 0.16468846 -0.5195359 -0.005212173
## X495 0 1.226628531 1.65364219 1.13147070 0.7260405 -0.005212173
## X496 0 -0.190792410 -0.72058540 0.35804491 -0.9347280 0.820917251
## X497 0 -0.008626296 0.12893412 1.90489650 -0.9347280 -0.831341597
## X498 0 -0.289288562 -0.40240913 -0.02866799 -0.9347280 -0.831341597
## X499 0 -1.098274791 -0.50369472 -0.02866799 -0.9347280 -0.831341597
## X501 0 0.774201646 -0.03559810 0.35804491 -0.5195359 0.820917251
## X502 0 -1.098274791 -0.50369472 -0.02866799 -0.9347280 -0.831341597
## X503 0 1.239546173 1.82822307 -0.02866799 -0.5195359 -0.831341597
## X505 0 -0.123326972 -0.40240913 0.16468846 -0.5195359 -0.005212173
## X506 0 0.800109202 0.56629095 1.51818360 0.3108484 0.820917251
## X507 0 0.995515874 1.10948462 1.13147070 1.1412327 -0.831341597
## X508 0 1.827201901 0.04803954 0.16468846 0.3108484 -0.005212173
## X509 0 1.881712881 1.99292450 0.93811425 -0.1043438 3.299305521
## X510 1 0.433604324 0.04803954 0.55140136 -0.5195359 1.647046674
## X513 0 -0.364519110 -0.72058540 -1.18880668 -0.5195359 -0.831341597
## X514 0 0.823597252 0.63244961 1.32482715 0.3108484 0.820917251
## X515 0 -0.242509175 -0.21200528 0.93811425 -0.9347280 -0.831341597
## X516 0 -0.404021657 -0.03559810 0.16468846 0.3108484 -0.005212173
## X518 0 0.915283282 1.16359252 0.35804491 0.7260405 0.820917251
## X521 0 1.134223355 0.88159159 1.51818360 1.1412327 0.820917251
## X523 1 -0.043759055 0.12893412 0.35804491 0.7260405 0.820917251
## X524 0 0.399810034 -0.12219740 0.16468846 -0.1043438 -0.005212173
## X525 0 0.686767950 0.94039386 -0.41538089 -0.1043438 2.473176098
## X526 0 -0.459952245 0.42867850 -1.18880668 1.9716169 -0.831341597
## X530 1 -0.389468783 0.20728011 -0.02866799 0.3108484 -0.831341597
## X531 0 0.430503397 0.82146772 0.16468846 0.7260405 -0.005212173
## X532 0 0.486632405 0.63244961 -0.02866799 1.1412327 -0.831341597
## X533 0 1.033797758 0.04803954 0.93811425 -0.5195359 3.299305521
## X534 1 0.736309194 0.69697444 0.55140136 1.1412327 1.647046674
## X535 0 -0.421224013 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X536 0 1.024487502 1.46773946 1.13147070 0.3108484 -0.005212173
## X538 0 1.079045894 0.75995351 1.51818360 -0.5195359 0.820917251
## X539 0 1.024487502 1.46773946 1.13147070 0.3108484 -0.005212173
## X542 0 1.445796891 1.91172984 -0.41538089 -0.1043438 2.473176098
## X543 0 -0.832540404 -0.40240913 -1.18880668 0.3108484 -0.831341597
## X544 0 1.881712881 1.99292450 0.93811425 -0.1043438 3.299305521
## X545 0 0.061817968 1.05428349 -1.18880668 2.8020012 -0.831341597
## X546 0 -0.107436062 -2.10721958 -1.18880668 -0.9347280 -0.831341597
## X548 0 -0.404021657 -0.03559810 0.16468846 -0.1043438 -0.005212173
## X549 0 0.436794393 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X551 0 1.271995992 -2.92387959 -1.18880668 -0.9347280 -0.831341597
## X552 0 1.731140385 1.91172984 1.32482715 0.7260405 -0.005212173
## X553 1 0.558159799 0.49840233 0.35804491 -0.1043438 0.820917251
## X554 0 0.605379378 0.42867850 0.16468846 0.7260405 -0.831341597
## X556 1 0.362642398 0.28325136 1.32482715 0.3108484 -0.005212173
## X557 0 1.062383808 1.21665476 0.16468846 1.9716169 -0.005212173
## X558 0 -0.152364404 -0.72058540 0.74475780 -0.9347280 -0.831341597
## X559 0 -1.901900752 -0.72058540 -1.18880668 -0.1043438 -0.831341597
## X560 0 -0.839972199 -0.21200528 -0.02866799 -0.9347280 -0.831341597
## X561 0 0.128651681 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X562 0 -0.839972199 -0.21200528 -0.02866799 -0.5195359 -0.831341597
## X563 1 0.343414497 0.42867850 1.32482715 0.3108484 -0.005212173
## X565 0 -1.581515202 -0.60958681 -0.99545024 0.3108484 -0.005212173
## X566 0 -0.218737027 -0.96037479 -0.02866799 -0.9347280 -0.831341597
## X567 0 1.133955099 0.69697444 0.55140136 0.3108484 1.647046674
## X568 0 0.774201646 -0.40240913 0.16468846 -0.5195359 -0.005212173
## X569 0 0.842661605 0.99793817 0.16468846 1.1412327 -0.005212173
## X571 0 0.418526237 -0.30530231 0.16468846 -0.1043438 -0.005212173
## X572 0 0.687183627 1.10948462 0.16468846 2.8020012 -0.005212173
## X574 0 -1.303931995 -0.40240913 -0.99545024 -0.9347280 -0.005212173
## X576 0 0.922422855 0.63244961 1.51818360 0.7260405 0.820917251
## X577 0 0.232450944 0.28325136 1.13147070 -0.1043438 -0.005212173
## X579 1 0.232450944 0.28325136 1.13147070 -0.1043438 -0.005212173
## X580 0 1.609081003 -0.72058540 0.16468846 -0.5195359 -0.005212173
## X582 0 -0.293545411 0.49840233 -0.99545024 1.9716169 -0.005212173
## X583 0 -0.839972199 -0.21200528 -0.02866799 -0.9347280 -0.831341597
## X584 0 1.289745203 1.74225056 0.35804491 -0.9347280 0.820917251
## X586 0 1.058701570 0.75995351 0.55140136 1.1412327 1.647046674
## X587 0 -0.008626296 0.12893412 1.90489650 -0.9347280 -0.831341597
## X588 0 0.619596479 0.75995351 -0.60873734 0.7260405 1.647046674
## X589 0 1.706734262 2.47286768 -0.99545024 0.7260405 -0.005212173
## X591 0 1.226628531 1.65364219 1.13147070 0.7260405 -0.005212173
## X592 1 -0.839972199 -0.21200528 -0.02866799 -0.1043438 -0.831341597
## X593 0 1.072631922 0.94039386 2.09825295 0.7260405 -0.831341597
## X594 0 -0.267476312 0.35700394 -0.99545024 1.9716169 -0.005212173
## X595 0 0.453788004 0.12893412 -0.80209379 1.1412327 0.820917251
## X596 0 0.847208104 0.88159159 0.55140136 1.1412327 1.647046674
## X597 0 0.915506765 1.31981693 1.32482715 0.3108484 -0.005212173
## X598 0 0.049545329 0.63244961 -0.80209379 2.8020012 0.820917251
## X599 0 -0.839972199 -0.21200528 -0.02866799 -0.9347280 -0.831341597
## X600 0 0.966789467 0.99793817 0.35804491 0.7260405 0.820917251
## X603 0 -0.090698960 0.56629095 -0.99545024 2.3868091 -0.005212173
## X604 0 0.720253413 0.82146772 -0.41538089 1.1412327 2.473176098
## X605 0 1.066475255 1.56220886 -0.41538089 -0.9347280 2.473176098
## X606 1 -0.020037904 0.28325136 0.16468846 1.1412327 -0.005212173
## X608 0 0.563194962 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X609 0 0.686601657 0.35700394 1.51818360 0.3108484 0.820917251
## X611 0 -1.260676413 -0.21200528 -1.18880668 -0.9347280 -0.831341597
## X612 0 0.676599640 0.12893412 0.16468846 -0.1043438 -0.005212173
## X613 0 -0.105975307 -0.83728034 -0.02866799 -0.9347280 -0.831341597
## X614 0 -0.732339628 -0.83728034 -0.02866799 -0.9347280 -0.831341597
## X616 0 -1.532160955 -0.40240913 -1.18880668 -0.5195359 -0.831341597
## X617 0 0.854891424 1.21665476 1.13147070 1.1412327 -0.005212173
## X619 1 1.771027243 1.26871571 1.90489650 0.3108484 2.473176098
## X620 0 0.016880687 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X621 1 0.353099452 0.35700394 1.32482715 -0.1043438 -0.005212173
## X622 0 -0.706360421 -0.40240913 0.93811425 -0.9347280 -0.831341597
## X623 0 1.205416250 0.69697444 1.51818360 -0.5195359 0.820917251
## X625 0 1.019887558 0.94039386 1.13147070 1.1412327 -0.005212173
## X628 0 1.622913686 2.03269881 -0.41538089 -0.1043438 2.473176098
## X629 0 1.623602913 2.43853015 -0.99545024 0.7260405 -0.005212173
## X630 0 0.816422389 1.31981693 1.13147070 0.7260405 -0.831341597
## X631 0 -1.020552429 -0.21200528 -0.99545024 0.7260405 -0.831341597
## X632 0 0.570417230 -2.10721958 -1.18880668 -0.9347280 -0.831341597
## X633 0 0.676516088 0.12893412 0.16468846 1.1412327 -0.005212173
## X635 0 1.141453232 1.26871571 0.55140136 0.3108484 1.647046674
## X636 0 1.633333725 1.95260717 -0.41538089 -0.1043438 2.473176098
## X637 0 0.967298146 1.60829128 -0.60873734 -0.9347280 1.647046674
## X638 1 0.719516934 0.75995351 1.51818360 0.7260405 0.820917251
## X639 0 0.686601657 0.35700394 1.51818360 0.3108484 0.820917251
## X641 1 1.226307769 1.41929339 1.51818360 1.1412327 0.820917251
## X648 0 1.412917599 1.05428349 1.71154005 0.3108484 1.647046674
## X650 0 0.752403196 0.28325136 1.13147070 0.3108484 0.820917251
## X651 1 1.121037974 1.36999732 1.51818360 1.1412327 0.820917251
## X653 0 1.623602913 2.43853015 -0.99545024 0.7260405 -0.005212173
## X654 0 1.017548306 1.51536781 0.16468846 3.6323855 -0.005212173
## X655 1 -0.610215946 0.04803954 -0.02866799 -0.1043438 -0.831341597
## X656 0 -0.211043577 -0.40240913 0.93811425 -0.9347280 -0.831341597
## X657 0 0.430503397 0.82146772 0.16468846 1.9716169 -0.005212173
## X1082 0 -1.089862985 -0.72058540 -1.18880668 -0.5195359 -0.831341597
## X1083 1 0.201609653 0.49840233 1.13147070 0.3108484 -0.831341597
## X1084 0 -0.293545411 0.56629095 -1.18880668 -0.5195359 -0.831341597
## X1086 1 -0.284112271 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X1088 0 0.366912794 0.12893412 0.16468846 -0.1043438 -0.005212173
## X1089 0 0.094121874 0.56629095 0.74475780 0.3108484 -0.831341597
## X1090 0 0.014240641 0.04803954 0.16468846 0.3108484 -0.005212173
## X1091 0 0.159406860 0.63244961 -0.02866799 1.1412327 -0.831341597
## X1092 0 -0.489295914 0.28325136 -0.99545024 1.5564248 -0.005212173
## X1093 0 0.188446950 -0.60958681 -0.80209379 -0.9347280 0.820917251
## X1094 0 -0.580658068 -0.50369472 0.16468846 -0.5195359 -0.005212173
## X1095 0 -0.419242736 -0.60958681 0.35804491 -0.9347280 0.820917251
## X1097 0 -1.089862985 -0.72058540 -1.18880668 -0.1043438 -0.831341597
## X1098 0 0.784301940 1.05428349 -0.41538089 -0.1043438 2.473176098
## X1101 0 1.559218908 0.42867850 0.74475780 -0.5195359 2.473176098
## X1103 0 1.065435819 0.94039386 0.74475780 -0.9347280 2.473176098
## X1104 0 0.678353466 0.42867850 1.51818360 0.3108484 0.820917251
## X1105 0 -0.190792410 -0.72058540 0.35804491 -0.9347280 0.820917251
## X1106 0 -0.688575293 0.28325136 -1.18880668 1.5564248 -0.831341597
## X1108 0 -1.098274791 -0.50369472 -0.02866799 -0.9347280 -0.831341597
## X1110 1 0.260904394 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X1112 0 0.800109202 0.56629095 1.51818360 0.3108484 0.820917251
## X1113 0 0.495127837 0.75995351 1.13147070 -0.1043438 -0.831341597
## X1115 1 0.343414497 0.42867850 1.32482715 0.3108484 -0.005212173
## X1116 0 0.184958063 0.20728011 0.16468846 -0.1043438 -0.005212173
## X1117 0 -0.362866384 -0.30530231 0.16468846 -0.1043438 -0.005212173
## X1119 0 0.729152370 -0.40240913 0.16468846 0.3108484 -0.005212173
## X1120 0 1.457427050 1.99292450 -0.60873734 -0.1043438 1.647046674
## X1121 0 1.086675495 1.16359252 0.55140136 0.3108484 1.647046674
## X1122 0 1.525264217 2.03269881 -0.41538089 -0.1043438 2.473176098
## X1124 0 -0.092028152 -0.12219740 0.55140136 -0.9347280 1.647046674
## X1125 0 0.083816857 -2.10721958 -1.18880668 -0.9347280 -0.831341597
## X1126 0 -0.421224013 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X1127 0 -0.875243942 -0.30530231 -0.02866799 -0.9347280 -0.831341597
## X1128 0 0.361087352 -0.40240913 0.16468846 -0.5195359 -0.005212173
## X1129 0 -0.732339628 -0.83728034 -0.02866799 -0.9347280 -0.831341597
## X1130 0 0.594543822 -0.50369472 0.16468846 -0.1043438 -0.005212173
## X1131 0 -1.581515202 -0.50369472 -1.18880668 -0.9347280 -0.831341597
## X1133 1 0.813999190 0.04803954 0.55140136 -0.5195359 1.647046674
## X1135 0 -0.489295914 0.28325136 -0.99545024 1.9716169 -0.005212173
## X1136 0 -0.105975307 -0.83728034 -0.02866799 -0.9347280 -0.831341597
## X1138 0 2.722777775 3.22789945 0.16468846 0.3108484 4.951564368
## X1139 0 1.445796891 1.91172984 -0.41538089 -0.1043438 2.473176098
## X1141 0 -1.581515202 -0.60958681 -0.99545024 -0.1043438 -0.005212173
## X1142 0 -0.421224013 -1.22934392 -0.02866799 -0.9347280 -0.831341597
## X1143 1 1.213307444 1.31981693 1.71154005 1.1412327 1.647046674
## X1144 0 0.959436086 1.31981693 0.16468846 -0.9347280 -0.005212173
## X1145 0 0.991282387 0.56629095 0.55140136 -0.1043438 1.647046674
## X1146 0 -0.078774283 0.49840233 -0.99545024 2.3868091 -0.005212173
## X1147 0 0.254569455 0.69697444 -0.99545024 1.9716169 -0.005212173
## X1149 0 0.357292051 0.20728011 0.16468846 0.3108484 -0.005212173
## X1150 0 -0.090698960 0.56629095 -0.99545024 2.3868091 -0.005212173
## X1151 0 0.373978500 0.82146772 -0.99545024 0.7260405 -0.005212173
## X1152 0 0.959436086 1.21665476 0.55140136 0.3108484 1.647046674
## X1153 0 2.401813942 -1.53694587 -0.22202444 -0.9347280 -0.831341597
## X1156 0 0.072232210 0.75995351 -0.99545024 2.8020012 -0.005212173
## X1158 0 0.980480348 0.82146772 1.32482715 -0.5195359 -0.005212173
## X1159 0 0.381694291 0.20728011 1.13147070 -0.5195359 0.820917251
## X1160 0 1.705409579 1.56220886 2.09825295 1.1412327 3.299305521
## NumCarbon NumNitrogen NumOxygen NumSulfer NumChlorine NumHalogen
## X661 0.85821946 1.0008314 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X662 1.80408084 1.8438701 -0.3320280 1.7123815 -0.3972472 -0.4741055
## X663 0.70131917 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X665 0.18177643 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X668 -0.01199386 3.5299475 -0.9103405 -0.3360145 0.3168966 0.2049221
## X669 0.18177643 0.1577927 -0.3320280 1.7123815 1.0310404 0.8839497
## X670 1.29203392 2.6869088 -0.9103405 -0.3360145 1.0310404 0.8839497
## X671 0.53699786 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X672 1.92274051 -0.6852460 1.4029096 -0.3360145 -0.3972472 0.2049221
## X673 0.85821946 1.0008314 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X674 0.85821946 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X676 1.55615914 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X677 0.53699786 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X678 0.18177643 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X679 0.36423857 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X682 0.85821946 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X683 0.70131917 2.6869088 0.8245970 1.7123815 -0.3972472 -0.4741055
## X684 1.80408084 1.8438701 -0.3320280 1.7123815 0.3168966 0.2049221
## X685 1.55615914 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X686 0.53699786 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X688 1.00853037 -0.6852460 0.8245970 -0.3360145 0.3168966 0.2049221
## X689 1.55615914 1.0008314 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X690 1.29203392 0.1577927 0.2462845 -0.3360145 0.3168966 0.2049221
## X691 0.18177643 2.6869088 0.2462845 -0.3360145 3.8876154 3.6000599
## X692 0.85821946 0.1577927 1.4029096 5.8091734 -0.3972472 -0.4741055
## X693 0.85821946 1.0008314 0.8245970 1.7123815 -0.3972472 -0.4741055
## X695 1.55615914 1.0008314 -0.3320280 1.7123815 -0.3972472 -0.4741055
## X696 0.70131917 1.0008314 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X698 1.15294194 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X699 -0.44251753 0.1577927 -0.9103405 -0.3360145 1.0310404 0.8839497
## X700 -0.01199386 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X702 -0.44251753 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X703 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X704 0.53699786 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X706 1.00853037 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X708 0.53699786 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X709 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X711 2.15069776 -0.6852460 1.9812221 -0.3360145 -0.3972472 -0.4741055
## X712 1.42629884 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X713 0.85821946 0.1577927 0.2462845 -0.3360145 -0.3972472 1.5629772
## X714 2.03820634 -0.6852460 2.5595346 -0.3360145 -0.3972472 -0.4741055
## X715 0.36423857 0.1577927 0.2462845 -0.3360145 1.0310404 0.8839497
## X717 0.18177643 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.2049221
## X718 1.68198027 1.8438701 -0.9103405 1.7123815 0.3168966 0.2049221
## X721 -0.01199386 3.5299475 -0.9103405 -0.3360145 0.3168966 0.2049221
## X722 1.55615914 0.1577927 -0.3320280 -0.3360145 -0.3972472 1.5629772
## X723 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X724 0.53699786 1.0008314 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X726 0.53699786 -0.6852460 0.2462845 -0.3360145 1.7451841 1.5629772
## X728 1.00853037 -0.6852460 0.2462845 -0.3360145 -0.3972472 0.2049221
## X729 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 1.5629772
## X731 -0.44251753 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X732 0.53699786 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X733 -0.44251753 3.5299475 -0.9103405 -0.3360145 0.3168966 0.2049221
## X734 -0.68595798 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X735 1.68198027 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X736 0.85821946 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X737 0.36423857 0.1577927 -0.9103405 1.7123815 -0.3972472 -0.4741055
## X739 1.29203392 -0.6852460 2.5595346 -0.3360145 0.3168966 0.2049221
## X740 1.55615914 0.1577927 1.4029096 -0.3360145 0.3168966 0.2049221
## X741 0.53699786 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X742 0.36423857 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X743 -0.68595798 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X744 0.53699786 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X746 1.15294194 -0.6852460 1.4029096 -0.3360145 -0.3972472 -0.4741055
## X747 0.53699786 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X749 2.03820634 1.8438701 0.2462845 1.7123815 0.3168966 0.2049221
## X752 2.47218708 -0.6852460 2.5595346 -0.3360145 -0.3972472 0.2049221
## X753 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X754 1.55615914 1.0008314 -0.9103405 1.7123815 -0.3972472 -0.4741055
## X755 0.53699786 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X757 -0.44251753 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.2049221
## X758 0.85821946 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X759 0.18177643 1.0008314 -0.9103405 7.8575693 -0.3972472 -0.4741055
## X760 0.53699786 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X761 2.15069776 -0.6852460 2.5595346 -0.3360145 -0.3972472 0.2049221
## X762 0.70131917 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X763 0.53699786 1.0008314 -0.9103405 -0.3360145 1.0310404 0.8839497
## X764 0.70131917 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X765 1.29203392 -0.6852460 0.8245970 -0.3360145 -0.3972472 0.8839497
## X767 2.03820634 -0.6852460 1.4029096 -0.3360145 0.3168966 0.2049221
## X768 0.53699786 0.1577927 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X770 1.29203392 1.0008314 -0.9103405 1.7123815 0.3168966 0.2049221
## X771 0.53699786 0.1577927 0.8245970 -0.3360145 1.7451841 1.5629772
## X772 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 1.5629772
## X773 -0.01199386 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X774 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.2049221
## X775 1.15294194 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X776 2.03820634 1.8438701 1.9812221 1.7123815 0.3168966 0.2049221
## X777 0.53699786 -0.6852460 -0.3320280 5.8091734 -0.3972472 -0.4741055
## X778 2.36752103 0.1577927 2.5595346 -0.3360145 -0.3972472 -0.4741055
## X779 0.85821946 0.1577927 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X780 -0.95516548 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X781 1.55615914 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X782 0.85821946 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X784 1.00853037 0.1577927 1.4029096 -0.3360145 -0.3972472 1.5629772
## X786 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X787 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X788 2.03820634 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X789 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X791 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X792 1.42629884 1.0008314 -0.9103405 1.7123815 -0.3972472 1.5629772
## X794 0.85821946 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X798 1.42629884 1.0008314 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X799 0.18177643 0.1577927 0.2462845 1.7123815 2.4593279 2.2420048
## X800 1.55615914 -0.6852460 -0.3320280 1.7123815 -0.3972472 -0.4741055
## X804 1.55615914 1.8438701 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X805 2.47218708 -0.6852460 2.5595346 -0.3360145 -0.3972472 -0.4741055
## X807 -0.01199386 -0.6852460 1.4029096 7.8575693 -0.3972472 -0.4741055
## X808 1.80408084 0.1577927 1.4029096 -0.3360145 -0.3972472 -0.4741055
## X809 1.55615914 -0.6852460 1.4029096 -0.3360145 -0.3972472 -0.4741055
## X810 0.18177643 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X813 1.42629884 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X814 1.00853037 1.0008314 0.8245970 -0.3360145 1.0310404 0.8839497
## X818 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.7451841 1.5629772
## X819 0.85821946 1.0008314 0.2462845 -0.3360145 0.3168966 1.5629772
## X820 0.85821946 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X821 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.7451841 1.5629772
## X822 1.15294194 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X823 1.42629884 0.1577927 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X827 0.53699786 -0.6852460 -0.3320280 -0.3360145 3.8876154 3.6000599
## X828 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.7451841 1.5629772
## X829 0.85821946 0.1577927 1.4029096 3.7607774 0.3168966 0.2049221
## X831 0.85821946 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X832 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X833 0.53699786 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X834 0.85821946 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X835 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X836 0.53699786 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X839 1.29203392 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X840 1.42629884 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X841 0.53699786 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X842 1.15294194 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X843 0.85821946 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X846 1.42629884 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X848 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.1734717 2.9210324
## X849 0.53699786 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X851 2.47218708 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X854 0.53699786 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X855 1.68198027 0.1577927 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X856 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X857 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.1734717 2.9210324
## X858 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X859 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X860 0.53699786 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X862 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.1734717 2.9210324
## X863 0.53699786 -0.6852460 -0.9103405 -0.3360145 4.6017592 4.2790875
## X864 1.80408084 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X865 1.68198027 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X866 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X867 1.68198027 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X869 1.92274051 1.8438701 -0.9103405 -0.3360145 -0.3972472 1.5629772
## X870 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X871 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X872 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X873 1.68198027 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X875 0.53699786 -0.6852460 -0.9103405 -0.3360145 5.3159030 4.9581151
## X876 0.53699786 -0.6852460 -0.9103405 -0.3360145 5.3159030 4.9581151
## X877 0.53699786 -0.6852460 -0.9103405 -0.3360145 6.7441905 6.3161702
## X1190 0.53699786 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X1191 -0.44251753 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X1192 1.68198027 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1193 0.36423857 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1194 2.03820634 -0.6852460 2.5595346 -0.3360145 -0.3972472 -0.4741055
## X1195 -0.68595798 -0.6852460 -0.9103405 -0.3360145 1.7451841 1.5629772
## X1197 0.18177643 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1198 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.8839497
## X1199 0.18177643 3.5299475 -0.9103405 1.7123815 -0.3972472 -0.4741055
## X1200 -0.44251753 -0.6852460 0.2462845 5.8091734 -0.3972472 -0.4741055
## X1201 1.80408084 0.1577927 2.5595346 -0.3360145 -0.3972472 -0.4741055
## X1202 2.26041072 -0.6852460 3.7161597 -0.3360145 -0.3972472 0.2049221
## X1203 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1204 1.00853037 1.8438701 1.4029096 1.7123815 -0.3972472 -0.4741055
## X1205 0.70131917 1.0008314 0.2462845 -0.3360145 -0.3972472 1.5629772
## X1206 -1.25901822 -0.6852460 -0.9103405 -0.3360145 3.1734717 2.9210324
## X1207 1.29203392 1.0008314 -0.9103405 1.7123815 -0.3972472 -0.4741055
## X1208 2.15069776 -0.6852460 1.4029096 1.7123815 -0.3972472 -0.4741055
## X1209 -0.68595798 -0.6852460 -0.3320280 -0.3360145 3.1734717 2.9210324
## X1210 2.15069776 -0.6852460 1.4029096 -0.3360145 -0.3972472 -0.4741055
## X1212 1.68198027 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1213 1.29203392 1.0008314 -0.9103405 1.7123815 -0.3972472 -0.4741055
## X1215 2.15069776 -0.6852460 2.5595346 -0.3360145 -0.3972472 0.2049221
## X1216 0.53699786 -0.6852460 -0.9103405 1.7123815 -0.3972472 -0.4741055
## X1217 1.29203392 1.0008314 -0.3320280 -0.3360145 1.0310404 0.8839497
## X1219 1.42629884 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1220 1.80408084 0.1577927 0.2462845 -0.3360145 0.3168966 0.8839497
## X1221 -0.44251753 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.2049221
## X1222 1.68198027 0.1577927 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1226 1.80408084 1.8438701 -0.9103405 1.7123815 -0.3972472 1.5629772
## X1228 0.18177643 -0.6852460 0.8245970 3.7607774 -0.3972472 -0.4741055
## X1229 2.36752103 -0.6852460 2.5595346 -0.3360145 -0.3972472 -0.4741055
## X1230 0.85821946 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1231 0.85821946 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1233 1.80408084 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1234 0.53699786 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1236 1.92274051 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X1237 -0.44251753 0.1577927 0.8245970 1.7123815 1.7451841 1.5629772
## X1239 0.18177643 0.1577927 -0.3320280 1.7123815 1.7451841 1.5629772
## X1242 -1.25901822 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X1244 0.53699786 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X1245 0.53699786 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1246 1.42629884 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1247 2.03820634 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X1249 0.85821946 -0.6852460 1.9812221 1.7123815 0.3168966 0.2049221
## X1250 0.18177643 -0.6852460 -0.3320280 -0.3360145 3.8876154 3.6000599
## X1251 -0.21915966 1.0008314 -0.9103405 -0.3360145 2.4593279 2.2420048
## X1253 0.36423857 -0.6852460 0.2462845 5.8091734 0.3168966 0.2049221
## X1254 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X1255 1.00853037 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1256 1.15294194 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1257 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.7451841 1.5629772
## X1259 0.53699786 -0.6852460 -0.3320280 -0.3360145 3.8876154 3.6000599
## X1260 0.53699786 -0.6852460 -0.9103405 -0.3360145 1.7451841 1.5629772
## X1262 1.80408084 -0.6852460 0.8245970 -0.3360145 1.0310404 0.8839497
## X1264 0.18177643 -0.6852460 -0.9103405 -0.3360145 4.6017592 4.2790875
## X1265 0.53699786 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X1266 0.85821946 -0.6852460 -0.9103405 -0.3360145 3.1734717 2.9210324
## X1267 1.80408084 -0.6852460 3.1378471 -0.3360145 -0.3972472 -0.4741055
## X1268 1.15294194 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1273 0.53699786 -0.6852460 -0.9103405 -0.3360145 2.4593279 2.2420048
## X1274 1.15294194 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X1275 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X1276 1.68198027 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1277 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.1734717 2.9210324
## X1278 1.29203392 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1279 1.42629884 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1281 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X1282 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X1283 1.68198027 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1284 1.42629884 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1285 0.53699786 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X1288 0.53699786 -0.6852460 -0.9103405 -0.3360145 6.0300467 5.6371426
## X1299 1.00853037 1.0008314 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1301 1.55615914 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1302 -0.68595798 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X1307 -0.01199386 0.1577927 0.8245970 1.7123815 1.7451841 1.5629772
## X1309 0.85821946 -0.6852460 -0.9103405 -0.3360145 3.1734717 2.9210324
## X1310 0.18177643 -0.6852460 -0.9103405 -0.3360145 5.3159030 4.9581151
## X447 -0.21915966 -0.6852460 0.8245970 -0.3360145 1.0310404 0.8839497
## X448 1.80408084 1.0008314 3.7161597 -0.3360145 0.3168966 0.2049221
## X451 -0.95516548 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X452 -0.44251753 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.8839497
## X453 -0.01199386 0.1577927 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X454 0.53699786 2.6869088 0.8245970 1.7123815 -0.3972472 -0.4741055
## X455 0.18177643 -0.6852460 0.8245970 -0.3360145 0.3168966 0.2049221
## X456 0.70131917 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X458 0.36423857 2.6869088 0.8245970 1.7123815 -0.3972472 -0.4741055
## X459 -0.01199386 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X460 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X461 -0.44251753 -0.6852460 0.2462845 -0.3360145 0.3168966 0.2049221
## X462 -0.68595798 -0.6852460 -0.9103405 1.7123815 -0.3972472 -0.4741055
## X463 1.29203392 1.8438701 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X464 -2.04708364 -0.6852460 -0.9103405 -0.3360145 3.1734717 2.9210324
## X465 1.00853037 1.0008314 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X466 -0.01199386 0.1577927 0.8245970 1.7123815 0.3168966 0.2049221
## X468 -0.21915966 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X471 -0.01199386 0.1577927 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X472 -0.95516548 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X473 -0.95516548 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X476 0.53699786 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X477 0.18177643 1.0008314 0.8245970 1.7123815 -0.3972472 -0.4741055
## X478 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X479 -0.95516548 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X480 0.53699786 1.0008314 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X482 -0.95516548 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X483 -1.25901822 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X484 0.53699786 1.0008314 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X486 -0.01199386 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X487 1.00853037 0.1577927 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X488 0.36423857 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X489 -0.44251753 -0.6852460 0.2462845 -0.3360145 -0.3972472 0.2049221
## X490 1.00853037 0.1577927 0.2462845 -0.3360145 0.3168966 0.2049221
## X491 -0.95516548 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X492 0.53699786 1.0008314 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X493 -0.01199386 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X494 -0.68595798 1.0008314 0.2462845 -0.3360145 1.7451841 1.5629772
## X495 1.68198027 1.0008314 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X496 -0.68595798 2.6869088 -0.9103405 1.7123815 -0.3972472 -0.4741055
## X497 0.70131917 0.1577927 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X498 -0.21915966 -0.6852460 -0.3320280 -0.3360145 0.3168966 0.2049221
## X499 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X501 -0.01199386 1.0008314 0.8245970 -0.3360145 1.0310404 0.8839497
## X502 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X503 1.68198027 1.0008314 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X505 -0.21915966 0.1577927 -0.3320280 -0.3360145 0.3168966 0.2049221
## X506 0.36423857 2.6869088 0.2462845 1.7123815 -0.3972472 -0.4741055
## X507 0.85821946 2.6869088 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X508 -0.01199386 0.1577927 0.8245970 -0.3360145 -0.3972472 0.8839497
## X509 1.92274051 1.0008314 3.7161597 -0.3360145 -0.3972472 -0.4741055
## X510 0.18177643 1.8438701 -0.3320280 -0.3360145 0.3168966 0.2049221
## X513 -0.95516548 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.2049221
## X514 0.36423857 1.8438701 0.8245970 1.7123815 -0.3972472 -0.4741055
## X515 0.18177643 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X516 0.18177643 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X518 0.85821946 1.8438701 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X521 0.53699786 2.6869088 1.4029096 1.7123815 -0.3972472 -0.4741055
## X523 0.36423857 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X524 -0.01199386 0.1577927 -0.3320280 -0.3360145 1.0310404 0.8839497
## X525 0.70131917 1.0008314 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X526 -0.01199386 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X530 0.18177643 0.1577927 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X531 0.70131917 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X532 -0.01199386 3.5299475 -0.9103405 1.7123815 -0.3972472 -0.4741055
## X533 -0.44251753 1.8438701 1.4029096 3.7607774 0.3168966 0.2049221
## X534 0.36423857 1.0008314 0.8245970 1.7123815 -0.3972472 -0.4741055
## X535 -0.68595798 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X536 1.55615914 1.0008314 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X538 1.00853037 -0.6852460 3.1378471 -0.3360145 -0.3972472 -0.4741055
## X539 1.55615914 1.0008314 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X542 1.80408084 -0.6852460 1.9812221 -0.3360145 -0.3972472 -0.4741055
## X543 -0.68595798 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X544 1.92274051 1.0008314 3.7161597 -0.3360145 -0.3972472 -0.4741055
## X545 0.53699786 0.1577927 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X546 -2.04708364 -0.6852460 -0.9103405 -0.3360145 1.0310404 3.6000599
## X548 0.18177643 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X549 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.8839497
## X551 -2.64432555 -0.6852460 -0.9103405 -0.3360145 -0.3972472 2.2420048
## X552 1.92274051 0.1577927 3.1378471 -0.3360145 -0.3972472 -0.4741055
## X553 0.53699786 0.1577927 0.2462845 1.7123815 -0.3972472 -0.4741055
## X554 -0.01199386 4.3729862 -0.9103405 -0.3360145 0.3168966 0.2049221
## X556 0.70131917 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X557 0.85821946 1.8438701 0.2462845 -0.3360145 0.3168966 0.2049221
## X558 -0.44251753 0.1577927 -0.9103405 3.7607774 -0.3972472 -0.4741055
## X559 -0.95516548 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X560 -0.01199386 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X561 -0.68595798 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.8839497
## X562 -0.01199386 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X563 0.85821946 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X565 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X566 -0.68595798 0.1577927 -0.9103405 -0.3360145 1.0310404 0.8839497
## X567 0.36423857 1.0008314 0.8245970 1.7123815 -0.3972472 1.5629772
## X568 -0.21915966 0.1577927 -0.3320280 -0.3360145 -0.3972472 0.2049221
## X569 0.85821946 0.1577927 0.2462845 -0.3360145 0.3168966 0.2049221
## X571 -0.21915966 0.1577927 0.2462845 -0.3360145 1.0310404 0.8839497
## X572 0.85821946 1.0008314 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X574 -0.44251753 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X576 0.36423857 2.6869088 0.8245970 1.7123815 -0.3972472 -0.4741055
## X577 0.53699786 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X579 0.53699786 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X580 -0.44251753 -0.6852460 0.8245970 -0.3360145 -0.3972472 0.8839497
## X582 0.18177643 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X583 -0.01199386 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X584 1.80408084 1.0008314 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X586 0.53699786 0.1577927 1.4029096 1.7123815 -0.3972472 -0.4741055
## X587 0.70131917 0.1577927 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X588 0.36423857 1.0008314 0.2462845 1.7123815 -0.3972472 -0.4741055
## X589 2.15069776 -0.6852460 1.9812221 -0.3360145 -0.3972472 -0.4741055
## X591 1.68198027 1.0008314 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X592 -0.01199386 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X593 1.15294194 1.8438701 -0.3320280 -0.3360145 -0.3972472 0.8839497
## X594 -0.01199386 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X595 -0.21915966 0.1577927 -0.9103405 3.7607774 0.3168966 0.2049221
## X596 0.53699786 1.0008314 0.8245970 1.7123815 -0.3972472 -0.4741055
## X597 1.55615914 0.1577927 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X598 0.36423857 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X599 -0.01199386 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X600 0.70131917 -0.6852460 1.9812221 1.7123815 -0.3972472 -0.4741055
## X603 0.18177643 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X604 0.53699786 1.0008314 0.2462845 1.7123815 -0.3972472 -0.4741055
## X605 1.55615914 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X606 0.36423857 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X608 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.8839497
## X609 0.18177643 2.6869088 0.2462845 1.7123815 -0.3972472 -0.4741055
## X611 -0.44251753 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X612 -0.01199386 1.0008314 0.2462845 -0.3360145 1.0310404 0.8839497
## X613 -0.44251753 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.2049221
## X614 -0.44251753 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X616 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X617 1.29203392 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X619 1.00853037 1.8438701 1.4029096 3.7607774 -0.3972472 1.5629772
## X620 -0.68595798 -0.6852460 -0.9103405 -0.3360145 1.7451841 1.5629772
## X621 0.70131917 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X622 0.18177643 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X623 1.00853037 1.0008314 0.2462845 -0.3360145 1.0310404 0.8839497
## X625 0.85821946 1.8438701 0.2462845 -0.3360145 0.3168966 0.2049221
## X628 1.92274051 -0.6852460 1.9812221 -0.3360145 -0.3972472 0.2049221
## X629 2.15069776 -0.6852460 1.4029096 -0.3360145 -0.3972472 -0.4741055
## X630 1.42629884 1.0008314 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X631 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X632 -2.04708364 -0.6852460 -0.9103405 -0.3360145 3.8876154 3.6000599
## X633 0.18177643 -0.6852460 0.8245970 -0.3360145 1.0310404 0.8839497
## X635 0.85821946 1.8438701 0.8245970 1.7123815 -0.3972472 -0.4741055
## X636 1.80408084 -0.6852460 2.5595346 -0.3360145 -0.3972472 0.2049221
## X637 1.55615914 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X638 1.15294194 -0.6852460 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X639 0.18177643 2.6869088 0.2462845 1.7123815 -0.3972472 -0.4741055
## X641 1.55615914 1.0008314 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X648 1.00853037 1.0008314 1.4029096 1.7123815 0.3168966 0.2049221
## X650 -0.01199386 1.0008314 0.8245970 3.7607774 -0.3972472 -0.4741055
## X651 1.55615914 1.0008314 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X653 2.15069776 -0.6852460 1.4029096 -0.3360145 -0.3972472 -0.4741055
## X654 1.29203392 0.1577927 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X655 0.18177643 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X656 0.18177643 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X657 0.70131917 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1082 -0.95516548 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X1083 0.85821946 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X1084 0.18177643 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X1086 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.2049221
## X1088 -0.01199386 1.0008314 0.2462845 -0.3360145 0.3168966 0.2049221
## X1089 0.53699786 1.0008314 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1090 -0.01199386 0.1577927 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X1091 0.53699786 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1092 -0.01199386 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X1093 -0.95516548 1.0008314 0.2462845 -0.3360145 1.0310404 0.8839497
## X1094 -0.21915966 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1095 -0.21915966 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1097 -0.95516548 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X1098 0.85821946 1.0008314 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X1101 -0.21915966 1.8438701 1.4029096 3.7607774 1.7451841 1.5629772
## X1103 1.15294194 -0.6852460 2.5595346 -0.3360145 -0.3972472 -0.4741055
## X1104 0.36423857 1.8438701 0.2462845 1.7123815 -0.3972472 -0.4741055
## X1105 -0.68595798 2.6869088 -0.9103405 1.7123815 -0.3972472 -0.4741055
## X1106 -0.21915966 0.1577927 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1108 -0.21915966 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1110 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.2049221
## X1112 0.36423857 2.6869088 0.2462845 1.7123815 -0.3972472 -0.4741055
## X1113 1.00853037 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1115 0.85821946 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1116 0.18177643 1.0008314 -0.9103405 -0.3360145 0.3168966 0.2049221
## X1117 -0.21915966 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1119 -0.21915966 -0.6852460 0.8245970 -0.3360145 1.7451841 1.5629772
## X1120 1.80408084 -0.6852460 1.9812221 -0.3360145 -0.3972472 -0.4741055
## X1121 0.85821946 3.5299475 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X1122 1.92274051 -0.6852460 1.9812221 -0.3360145 -0.3972472 -0.4741055
## X1124 0.36423857 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1125 -2.04708364 -0.6852460 -0.9103405 -0.3360145 1.7451841 3.6000599
## X1126 -0.68595798 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X1127 -0.01199386 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1128 -0.21915966 0.1577927 -0.3320280 -0.3360145 -0.3972472 0.2049221
## X1129 -0.44251753 -0.6852460 -0.9103405 -0.3360145 0.3168966 0.2049221
## X1130 -0.21915966 -0.6852460 0.2462845 -0.3360145 1.7451841 1.5629772
## X1131 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1133 0.18177643 1.8438701 -0.3320280 -0.3360145 -0.3972472 0.2049221
## X1135 -0.01199386 -0.6852460 -0.3320280 -0.3360145 -0.3972472 -0.4741055
## X1136 -0.44251753 -0.6852460 -0.9103405 -0.3360145 -0.3972472 0.2049221
## X1138 3.05604172 0.1577927 6.6077223 -0.3360145 -0.3972472 -0.4741055
## X1139 1.80408084 -0.6852460 1.9812221 -0.3360145 -0.3972472 -0.4741055
## X1141 -0.68595798 -0.6852460 -0.9103405 -0.3360145 -0.3972472 -0.4741055
## X1142 -0.68595798 -0.6852460 -0.9103405 -0.3360145 1.0310404 0.8839497
## X1143 1.55615914 1.0008314 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X1144 1.29203392 0.1577927 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X1145 0.18177643 1.8438701 0.8245970 1.7123815 0.3168966 0.2049221
## X1146 -0.01199386 0.1577927 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1147 0.18177643 0.1577927 -0.3320280 1.7123815 -0.3972472 -0.4741055
## X1149 0.18177643 0.1577927 0.2462845 -0.3360145 0.3168966 0.2049221
## X1150 0.18177643 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1151 0.36423857 0.1577927 -0.3320280 1.7123815 -0.3972472 -0.4741055
## X1152 1.29203392 0.1577927 0.8245970 -0.3360145 -0.3972472 -0.4741055
## X1153 -1.25901822 0.1577927 -0.9103405 -0.3360145 -0.3972472 2.2420048
## X1156 0.36423857 -0.6852460 0.2462845 -0.3360145 -0.3972472 -0.4741055
## X1158 1.00853037 -0.6852460 2.5595346 -0.3360145 -0.3972472 -0.4741055
## X1159 0.53699786 -0.6852460 1.4029096 -0.3360145 -0.3972472 -0.4741055
## X1160 1.92274051 -0.6852460 3.7161597 -0.3360145 -0.3972472 -0.4741055
## NumRings HydrophilicFactor SurfaceArea1 SurfaceArea2
## X661 1.2306033 -0.741919037 -0.302617991 -0.379138448
## X662 2.0005400 -0.310306393 0.445784255 1.054350614
## X663 -0.3092700 -0.274782719 0.023833878 -0.076964725
## X665 -0.3092700 -0.834280591 -1.033167401 -1.055357076
## X668 -0.3092700 -0.042990743 0.495375467 0.359508432
## X669 -1.0792067 -0.559860206 -0.457625954 0.141009550
## X670 2.0005400 -0.629131371 0.187343191 0.074384441
## X671 -1.0792067 -0.723269108 -0.287882317 -0.365498662
## X672 2.0005400 0.190577416 1.080835157 0.901427627
## X673 0.4606666 0.331784022 0.132367790 0.023497546
## X674 0.4606666 -0.698402536 0.418013175 0.287899555
## X676 2.0005400 -0.365368089 0.023833878 -0.076964725
## X677 0.4606666 -0.842273418 -1.033167401 -1.055357076
## X678 0.4606666 -0.760568966 -1.033167401 -1.055357076
## X679 -0.3092700 -0.838721050 -1.033167401 -1.055357076
## X682 0.4606666 -0.260573249 0.285392103 0.165141479
## X683 -0.3092700 -0.115814276 1.359112705 1.378820142
## X684 2.0005400 -0.288992189 -0.136558273 0.515316758
## X685 2.0005400 -0.365368089 0.023833878 -0.076964725
## X686 0.4606666 -0.842273418 -1.033167401 -1.055357076
## X688 1.2306033 -0.249028055 0.285392103 0.165141479
## X689 1.2306033 -0.773002252 -0.849538224 -0.885384357
## X690 -0.3092700 -0.689521618 -0.196067728 -0.280512302
## X691 -0.3092700 0.566240273 0.799723825 0.641222476
## X692 -0.3092700 -0.119366643 0.798306933 2.622401413
## X693 0.4606666 0.382405258 1.099821507 1.138812367
## X695 1.2306033 -0.705507271 -0.540089056 0.141796461
## X696 1.2306033 0.343329216 0.069457794 -0.034733848
## X698 -0.3092700 -0.295208832 0.053021849 -0.049947456
## X699 -0.3092700 -0.578510135 -0.359010285 -0.431336861
## X700 -1.0792067 -0.828952040 -1.033167401 -1.055357076
## X702 -1.0792067 -0.812966386 -1.033167401 -1.055357076
## X703 -0.3092700 -0.821847305 -1.033167401 -1.055357076
## X704 0.4606666 -0.842273418 -1.033167401 -1.055357076
## X706 0.4606666 -0.708171547 0.084476847 -0.020831759
## X708 0.4606666 -0.842273418 -1.033167401 -1.055357076
## X709 -0.3092700 -0.821847305 -1.033167401 -1.055357076
## X711 2.0005400 1.404598989 1.743657139 1.514955700
## X712 0.4606666 0.207451161 0.113381439 0.005923206
## X713 0.4606666 0.382405258 0.364738044 0.238586482
## X714 2.0005400 0.190577416 1.826120241 1.591286041
## X715 -0.3092700 -0.130911837 0.053021849 -0.049947456
## X717 0.4606666 -0.760568966 -1.033167401 -1.055357076
## X718 2.0005400 -0.683304975 -0.709832693 -0.015323383
## X721 -0.3092700 0.574233100 0.744465045 0.590073278
## X722 1.2306033 -0.676200240 -0.409735011 -0.478289201
## X723 -1.0792067 -0.821847305 -1.033167401 -1.055357076
## X724 0.4606666 -0.723269108 -0.332656097 -0.406942628
## X726 0.4606666 -0.157554593 -0.198334755 -0.282610731
## X728 0.4606666 -0.278335086 0.023833878 -0.076964725
## X729 -0.3092700 -0.546538828 -1.033167401 -1.055357076
## X731 -1.0792067 -0.812966386 -1.033167401 -1.055357076
## X732 0.4606666 -0.778330804 -1.033167401 -1.055357076
## X733 -0.3092700 0.687908858 0.744465045 0.590073278
## X734 -0.3092700 -0.493253316 -1.033167401 -1.055357076
## X735 2.0005400 -0.376025191 0.023833878 -0.076964725
## X736 -0.3092700 0.331784022 0.449468173 0.317015252
## X737 0.4606666 -0.711723914 -0.682911749 0.110582335
## X739 1.2306033 -0.602488615 0.980519218 0.808572160
## X740 1.2306033 -0.263237525 0.908824493 0.742209354
## X741 -1.0792067 -0.252580422 0.023833878 -0.076964725
## X742 -1.0792067 -0.711723914 -0.287882317 -0.365498662
## X743 -0.3092700 -0.493253316 -1.033167401 -1.055357076
## X744 1.2306033 -0.842273418 -1.033167401 -1.055357076
## X746 -0.3092700 -0.680640699 0.457402767 0.324359752
## X747 -1.0792067 -0.294320740 -0.459892981 -0.524716935
## X749 2.0005400 -0.655774127 0.035452391 0.674535031
## X752 2.0005400 0.148837099 1.826120241 1.591286041
## X753 -0.3092700 -0.821847305 -1.033167401 -1.055357076
## X754 2.0005400 -0.737478578 -0.801647282 -0.100309743
## X755 0.4606666 -0.842273418 -1.033167401 -1.055357076
## X757 -1.0792067 -0.717052465 -1.033167401 -1.055357076
## X758 0.4606666 -0.791652182 -0.771609176 -0.813250873
## X759 -1.0792067 -0.525224623 -0.849538224 2.125336130
## X760 0.4606666 -0.778330804 -1.033167401 -1.055357076
## X761 2.0005400 0.189689324 1.826120241 1.591286041
## X762 1.2306033 -0.844937693 -1.033167401 -1.055357076
## X763 0.4606666 1.916139901 0.441533579 0.309670752
## X764 0.4606666 -0.844937693 -1.033167401 -1.055357076
## X765 0.4606666 -0.257020882 0.285392103 0.165141479
## X767 2.0005400 -0.703731087 0.679571401 0.530005758
## X768 1.2306033 -0.294320740 -0.585712972 -0.641179724
## X770 1.2306033 -0.689521618 -0.801647282 -0.100309743
## X771 0.4606666 -0.111373817 0.758917341 0.603450761
## X772 -0.3092700 -0.546538828 -1.033167401 -1.055357076
## X773 -1.0792067 -0.828952040 -1.033167401 -1.055357076
## X774 -1.0792067 -0.734814302 -1.033167401 -1.055357076
## X775 0.4606666 -0.295208832 0.507560737 0.370787486
## X776 1.2306033 0.810465534 2.186010757 2.144221987
## X777 -1.0792067 -0.596271972 -0.549440542 1.640599114
## X778 2.0005400 2.044025128 2.568288163 2.278259116
## X779 1.2306033 0.285603245 -0.295816911 -0.372843162
## X780 -0.3092700 -0.371584732 -1.033167401 -1.055357076
## X781 -1.0792067 -0.737478578 -0.026324091 -0.123392458
## X782 1.2306033 -0.741919037 -0.065713683 -0.159852656
## X784 0.4606666 1.712766865 1.596017014 1.378295535
## X786 -1.0792067 -0.821847305 -1.033167401 -1.055357076
## X787 0.4606666 -0.723269108 -1.033167401 -1.055357076
## X788 2.0005400 -0.788987906 -0.065713683 -0.159852656
## X789 0.4606666 -0.723269108 -1.033167401 -1.055357076
## X791 0.4606666 -0.723269108 -1.033167401 -1.055357076
## X792 1.2306033 -0.638900382 -0.801647282 -0.100309743
## X794 -1.0792067 -0.294320740 0.023833878 -0.076964725
## X798 2.0005400 -0.768561793 -0.302617991 -0.379138448
## X799 0.4606666 -0.465722469 0.026100905 0.588761760
## X800 2.7704767 -0.365368089 -0.459892981 0.138911121
## X804 0.4606666 -0.737478578 -0.240841509 -0.321956268
## X805 2.0005400 0.135515721 1.826120241 1.591286041
## X807 -1.0792067 -0.395563212 0.013065500 3.438427849
## X808 1.2306033 -0.310306393 0.908824493 0.742209354
## X809 0.4606666 -0.705507271 0.457402767 0.324359752
## X810 1.2306033 -0.525224623 -1.033167401 -1.055357076
## X813 -1.0792067 -0.353822894 0.023833878 -0.076964725
## X814 0.4606666 -0.578510135 0.589457083 0.446593220
## X818 0.4606666 -0.675312148 -1.033167401 -1.055357076
## X819 0.4606666 0.395726636 0.616094648 0.471249757
## X820 -1.0792067 -0.332508690 -0.459892981 -0.524716935
## X821 0.4606666 -0.675312148 -1.033167401 -1.055357076
## X822 2.0005400 -0.851154336 -1.033167401 -1.055357076
## X823 2.0005400 0.183472681 -0.295816911 -0.372843162
## X827 2.7704767 -0.533217450 -0.678094317 -0.726690691
## X828 0.4606666 -0.675312148 -1.033167401 -1.055357076
## X829 0.4606666 -0.515455613 0.597108298 2.216355472
## X831 0.4606666 -0.659326494 -1.033167401 -1.055357076
## X832 0.4606666 -0.723269108 -1.033167401 -1.055357076
## X833 0.4606666 -0.633571830 -1.033167401 -1.055357076
## X834 0.4606666 -0.659326494 -1.033167401 -1.055357076
## X835 0.4606666 -0.723269108 -1.033167401 -1.055357076
## X836 0.4606666 -0.633571830 -1.033167401 -1.055357076
## X839 2.0005400 -0.852042428 -1.033167401 -1.055357076
## X840 2.0005400 -0.853818612 -1.033167401 -1.055357076
## X841 0.4606666 -0.633571830 -1.033167401 -1.055357076
## X842 1.2306033 -0.851154336 -1.033167401 -1.055357076
## X843 0.4606666 -0.659326494 -1.033167401 -1.055357076
## X846 1.2306033 -0.853818612 -1.033167401 -1.055357076
## X848 0.4606666 -0.596271972 -1.033167401 -1.055357076
## X849 0.4606666 -0.633571830 -1.033167401 -1.055357076
## X851 3.5404134 -0.408884590 0.063223470 -0.040504527
## X854 0.4606666 -0.633571830 -1.033167401 -1.055357076
## X855 2.7704767 -0.407108406 -0.585712972 -0.641179724
## X856 0.4606666 -0.562524482 -1.033167401 -1.055357076
## X857 0.4606666 -0.596271972 -1.033167401 -1.055357076
## X858 0.4606666 -0.562524482 -1.033167401 -1.055357076
## X859 0.4606666 -0.562524482 -1.033167401 -1.055357076
## X860 0.4606666 -0.633571830 -1.033167401 -1.055357076
## X862 0.4606666 -0.596271972 -1.033167401 -1.055357076
## X863 0.4606666 -0.533217450 -1.033167401 -1.055357076
## X864 2.7704767 -0.856482887 -1.033167401 -1.055357076
## X865 2.7704767 -0.855594796 -1.033167401 -1.055357076
## X866 0.4606666 -0.562524482 -1.033167401 -1.055357076
## X867 2.7704767 -0.855594796 -1.033167401 -1.055357076
## X869 2.0005400 -0.672647872 -0.162912460 -0.249822784
## X870 0.4606666 -0.562524482 -1.033167401 -1.055357076
## X871 0.4606666 -0.562524482 -1.033167401 -1.055357076
## X872 0.4606666 -0.562524482 -1.033167401 -1.055357076
## X873 2.7704767 -0.855594796 -1.033167401 -1.055357076
## X875 0.4606666 -0.505686603 -1.033167401 -1.055357076
## X876 0.4606666 -0.505686603 -1.033167401 -1.055357076
## X877 0.4606666 -0.459505826 -1.033167401 -1.055357076
## X1190 0.4606666 -0.778330804 -0.771609176 -0.813250873
## X1191 -1.0792067 -0.717052465 -1.033167401 -1.055357076
## X1192 2.0005400 -0.376025191 0.023833878 -0.076964725
## X1193 -0.3092700 -0.838721050 -1.033167401 -1.055357076
## X1194 2.0005400 -0.311194485 1.736572680 1.508398110
## X1195 -0.3092700 -0.546538828 -1.033167401 -1.055357076
## X1197 -0.3092700 -0.834280591 -1.033167401 -1.055357076
## X1198 -0.3092700 -0.612257626 -1.033167401 -1.055357076
## X1199 -0.3092700 0.527164231 0.744465045 1.253701335
## X1200 -1.0792067 -0.446184448 -0.510050950 1.855163443
## X1201 2.7704767 -0.640676565 0.850165173 0.687912513
## X1202 2.0005400 0.201234518 2.571405325 2.281144456
## X1203 -0.3092700 -0.821847305 -1.033167401 -1.055357076
## X1204 1.2306033 0.379740982 1.789281054 1.776996976
## X1205 0.4606666 0.425921759 0.730012749 0.576695796
## X1206 -1.0792067 -0.358263354 -1.033167401 -1.055357076
## X1207 1.2306033 -0.724157200 -0.801647282 -0.100309743
## X1208 2.7704767 -0.709059639 0.679571401 1.193633815
## X1209 -0.3092700 0.088446852 -0.459892981 -0.524716935
## X1210 2.0005400 0.738530094 1.170382718 0.984315558
## X1212 2.0005400 0.168375119 0.113381439 0.005923206
## X1213 1.2306033 -0.724157200 -0.801647282 -0.100309743
## X1215 2.7704767 0.189689324 1.603951608 1.385640035
## X1216 1.2306033 -0.778330804 -1.033167401 -0.314611768
## X1217 1.2306033 -0.257020882 0.270656429 0.151501693
## X1219 0.4606666 0.207451161 0.113381439 0.005923206
## X1220 1.2306033 -0.310306393 0.115648466 0.008021635
## X1221 -1.0792067 -0.717052465 -1.033167401 -1.055357076
## X1222 1.2306033 -0.814742570 -0.941352813 -0.970370717
## X1226 2.0005400 -0.640676565 -0.709832693 -0.015323383
## X1228 -0.3092700 -0.525224623 -0.248492725 1.433641590
## X1229 2.0005400 0.147949007 1.826120241 1.591286041
## X1230 1.2306033 -0.698402536 0.188193326 0.075171351
## X1231 0.4606666 -0.847601969 -1.033167401 -1.055357076
## X1233 2.0005400 -0.385794201 0.023833878 -0.076964725
## X1234 0.4606666 -0.842273418 -1.033167401 -1.055357076
## X1236 2.0005400 -0.753464232 0.195844542 0.082253548
## X1237 -0.3092700 -0.361815721 0.116781980 1.108122848
## X1239 -1.0792067 -0.525224623 -0.457625954 0.141009550
## X1242 -1.0792067 -0.322739679 -1.033167401 -1.055357076
## X1244 0.4606666 -0.778330804 -1.033167401 -1.055357076
## X1245 -0.3092700 -0.842273418 -1.033167401 -1.055357076
## X1246 2.0005400 -0.353822894 0.023833878 -0.076964725
## X1247 1.2306033 -0.757904691 -0.026324091 -0.123392458
## X1249 0.4606666 -0.538546001 0.607593298 1.562432648
## X1250 1.2306033 -0.055424029 -0.459892981 -0.524716935
## X1251 -0.3092700 -0.476379571 0.315146831 0.192683355
## X1253 -0.3092700 -0.514567521 -0.510050950 1.855163443
## X1254 0.4606666 -0.723269108 -1.033167401 -1.055357076
## X1255 1.2306033 -0.849378152 -1.033167401 -1.055357076
## X1256 2.0005400 -0.851154336 -1.033167401 -1.055357076
## X1257 0.4606666 -0.675312148 -1.033167401 -1.055357076
## X1259 2.7704767 -0.533217450 -0.678094317 -0.726690691
## X1260 0.4606666 -0.675312148 -1.033167401 -1.055357076
## X1262 1.2306033 -0.690409709 -0.026324091 -0.123392458
## X1264 1.2306033 -0.494141408 -1.033167401 -1.055357076
## X1265 0.4606666 -0.633571830 -1.033167401 -1.055357076
## X1266 0.4606666 -0.624690912 -1.033167401 -1.055357076
## X1267 1.2306033 0.840660658 1.955057394 1.967953982
## X1268 -1.0792067 -0.327180139 0.023833878 -0.076964725
## X1273 0.4606666 -0.633571830 -1.033167401 -1.055357076
## X1274 -1.0792067 -0.362703813 -0.459892981 -0.524716935
## X1275 2.0005400 -0.562524482 -1.033167401 -1.055357076
## X1276 2.7704767 -0.855594796 -1.033167401 -1.055357076
## X1277 0.4606666 -0.596271972 -1.033167401 -1.055357076
## X1278 2.0005400 -0.852042428 -1.033167401 -1.055357076
## X1279 2.0005400 -0.853818612 -1.033167401 -1.055357076
## X1281 0.4606666 -0.562524482 -1.033167401 -1.055357076
## X1282 0.4606666 -0.562524482 -1.033167401 -1.055357076
## X1283 2.7704767 -0.855594796 -1.033167401 -1.055357076
## X1284 2.0005400 -0.853818612 -1.033167401 -1.055357076
## X1285 0.4606666 -0.562524482 -1.033167401 -1.055357076
## X1288 0.4606666 -0.481708122 -1.033167401 -1.055357076
## X1299 1.2306033 0.321126919 0.616094648 0.471249757
## X1301 2.0005400 -0.365368089 0.023833878 -0.076964725
## X1302 -0.3092700 -0.411548865 -1.033167401 -1.055357076
## X1307 -0.3092700 -0.417765508 0.116781980 1.108122848
## X1309 0.4606666 -0.624690912 -1.033167401 -1.055357076
## X1310 1.2306033 -0.465722469 -1.033167401 -1.055357076
## X447 -0.3092700 -0.028781274 0.285392103 0.165141479
## X448 2.0005400 3.680778427 4.113550354 3.708600536
## X451 -1.0792067 -0.779218896 -1.033167401 -1.055357076
## X452 -0.3092700 -0.640676565 -1.033167401 -1.055357076
## X453 0.4606666 -0.164659328 -0.094618276 -0.186607621
## X454 0.4606666 1.129290512 2.004648607 1.976347696
## X455 -0.3092700 -0.129135654 0.285392103 0.165141479
## X456 0.4606666 -0.240147136 0.053021849 -0.049947456
## X458 0.4606666 1.175471289 2.004648607 1.976347696
## X459 -1.0792067 -0.749023772 -0.549440542 -0.607604866
## X460 -0.3092700 -0.799645008 -1.033167401 -1.055357076
## X461 -0.3092700 -0.039438376 0.023833878 -0.076964725
## X462 -0.3092700 -0.693962077 -1.033167401 -0.314611768
## X463 1.2306033 -0.310306393 -0.250192995 -0.330612286
## X464 -1.0792067 -0.218832932 -1.033167401 -1.055357076
## X465 1.2306033 -0.249028055 0.532214654 0.393607897
## X466 0.4606666 -0.042990743 0.647266268 1.240848459
## X468 -1.0792067 0.604428223 0.449468173 0.317015252
## X471 -0.3092700 0.527164231 0.187909948 0.074909048
## X472 -1.0792067 -0.662878862 -1.033167401 -1.055357076
## X473 -0.3092700 -0.779218896 -1.033167401 -1.055357076
## X476 0.4606666 -0.252580422 0.023833878 -0.076964725
## X477 0.4606666 -0.076738234 0.850731929 0.908247520
## X478 -1.0792067 -0.799645008 -1.033167401 -1.055357076
## X479 -1.0792067 -0.779218896 -1.033167401 -1.055357076
## X480 1.2306033 -0.723269108 -0.302617991 -0.379138448
## X482 -1.0792067 -0.574957768 -1.033167401 -1.055357076
## X483 -1.0792067 -0.527000807 -1.033167401 -1.055357076
## X484 0.4606666 1.948111208 0.441533579 0.309670752
## X486 -1.0792067 -0.683304975 -0.287882317 -0.365498662
## X487 -0.3092700 -0.670871689 0.065490497 -0.038406098
## X488 -0.3092700 -0.190413992 0.285392103 0.165141479
## X489 -0.3092700 -0.039438376 0.023833878 -0.076964725
## X490 -0.3092700 -0.670871689 -0.196067728 -0.280512302
## X491 -1.0792067 -0.662878862 -1.033167401 -1.055357076
## X492 0.4606666 -0.157554593 0.850731929 0.688437121
## X493 -1.0792067 -0.164659328 0.023833878 -0.076964725
## X494 -0.3092700 1.517386655 1.126459073 0.943658503
## X495 2.0005400 -0.321851587 0.258754538 0.140484943
## X496 0.4606666 0.068908831 0.510111142 1.214880405
## X497 1.2306033 -0.785435539 -0.667892696 -0.717247762
## X498 -0.3092700 -0.124695194 -0.459892981 -0.524716935
## X499 -0.3092700 -0.821847305 -1.033167401 -1.055357076
## X501 0.4606666 -0.470162928 0.586056542 0.443445577
## X502 -0.3092700 -0.821847305 -1.033167401 -1.055357076
## X503 3.5404134 0.208339253 0.297010616 0.175895926
## X505 -0.3092700 -0.087395336 -0.208536376 -0.292053660
## X506 0.4606666 1.178135565 1.743090382 1.734241492
## X507 0.4606666 1.766052376 1.956757664 1.712207992
## X508 -0.3092700 2.105303467 1.334458788 1.136189331
## X509 2.0005400 3.653247579 4.113550354 3.708600536
## X510 0.4606666 0.516507129 0.692890184 0.542334027
## X513 -1.0792067 -0.662878862 -1.033167401 -1.055357076
## X514 0.4606666 1.178135565 1.750174841 1.740799082
## X515 0.4606666 0.470326352 0.113381439 0.005923206
## X516 -0.3092700 -0.760568966 -0.771609176 -0.813250873
## X518 -0.3092700 0.382405258 0.969467462 0.798342320
## X521 0.4606666 1.128402420 2.266206832 2.218453900
## X523 -0.3092700 -0.711723914 -0.287882317 -0.365498662
## X524 -0.3092700 -0.094500071 -0.208536376 -0.292053660
## X525 0.4606666 0.399279003 1.099821507 0.919001967
## X526 -1.0792067 -0.209952013 -0.459892981 -0.524716935
## X530 -0.3092700 -0.760568966 -0.941352813 -0.970370717
## X531 -0.3092700 0.364643421 0.364738044 0.238586482
## X532 -0.3092700 0.574233100 0.744465045 1.253701335
## X533 0.4606666 1.385060968 2.330250342 2.497544909
## X534 -0.3092700 0.485423914 1.099821507 1.138812367
## X535 -0.3092700 -0.612257626 -1.033167401 -1.055357076
## X536 2.0005400 -0.336061057 -0.002803688 -0.101621261
## X538 1.2306033 2.486294875 2.689290722 2.390262745
## X539 2.0005400 -0.336061057 -0.002803688 -0.101621261
## X542 2.0005400 0.207451161 1.564562016 1.349179838
## X543 -1.0792067 -0.693962077 -1.033167401 -1.055357076
## X544 2.0005400 3.653247579 4.113550354 3.708600536
## X545 -1.0792067 -0.778330804 -0.941352813 -0.970370717
## X546 -1.0792067 -0.192190176 -1.033167401 -1.055357076
## X548 -0.3092700 -0.760568966 -0.771609176 -0.813250873
## X549 -0.3092700 -0.612257626 -1.033167401 -1.055357076
## X551 -1.0792067 -0.141568940 -1.033167401 -1.055357076
## X552 2.7704767 -0.626467096 1.111723398 0.930018717
## X553 0.4606666 -0.185085441 0.053021849 0.613680600
## X554 -0.3092700 0.581337835 1.418622161 1.214093494
## X556 0.4606666 -0.240147136 0.285392103 0.165141479
## X557 -0.3092700 1.041369418 0.882186927 0.717552818
## X558 0.4606666 -0.039438376 -0.667892696 1.041235435
## X559 -1.0792067 -0.779218896 -1.033167401 -1.055357076
## X560 -0.3092700 -0.828952040 -1.033167401 -1.055357076
## X561 -0.3092700 -0.612257626 -1.033167401 -1.055357076
## X562 -0.3092700 -0.828952040 -1.033167401 -1.055357076
## X563 0.4606666 -0.294320740 0.023833878 -0.076964725
## X565 -1.0792067 -0.799645008 -1.033167401 -1.055357076
## X566 -0.3092700 0.766949033 -0.295816911 -0.372843162
## X567 -0.3092700 0.512954761 1.099821507 1.138812367
## X568 -0.3092700 -0.087395336 -0.208536376 -0.292053660
## X569 -0.3092700 -0.659326494 -0.196067728 -0.280512302
## X571 -0.3092700 0.621301968 0.449468173 0.317015252
## X572 -0.3092700 1.032488500 0.790372339 0.632566458
## X574 -0.3092700 -0.812966386 -1.033167401 -1.055357076
## X576 0.4606666 1.175471289 2.004648607 1.976347696
## X577 0.4606666 -0.217056748 0.053021849 -0.049947456
## X579 0.4606666 -0.217056748 0.163822787 0.052613244
## X580 -0.3092700 0.686132674 0.597108298 0.453675417
## X582 -1.0792067 -0.760568966 -0.549440542 -0.607604866
## X583 -0.3092700 -0.828952040 -1.033167401 -1.055357076
## X584 4.3103501 -0.718828649 -0.104253140 -0.195525943
## X586 0.4606666 -0.533217450 0.597108298 1.552727415
## X587 1.2306033 -0.785435539 -0.667892696 -0.717247762
## X588 -0.3092700 0.472990628 0.616094648 1.312981944
## X589 2.0005400 1.404598989 1.743657139 1.514955700
## X591 2.0005400 -0.321851587 0.258754538 0.140484943
## X592 -0.3092700 -0.828952040 -1.033167401 -1.055357076
## X593 1.2306033 -0.217056748 0.410361960 0.280817358
## X594 -1.0792067 -0.683304975 -0.287882317 -0.365498662
## X595 -1.0792067 -0.555419747 -0.941352813 0.534989527
## X596 -0.3092700 0.447235964 1.099821507 1.138812367
## X597 1.2306033 -0.773002252 -0.679794587 -0.728264513
## X598 -1.0792067 -0.227713850 0.023833878 -0.076964725
## X599 -0.3092700 -0.828952040 -1.033167401 -1.055357076
## X600 0.4606666 -0.578510135 0.718960993 0.786276356
## X603 -1.0792067 -0.198406819 0.023833878 -0.076964725
## X604 -0.3092700 0.433914586 0.616094648 1.312981944
## X605 2.0005400 -0.737478578 0.418013175 0.287899555
## X606 -0.3092700 -0.711723914 -0.287882317 -0.365498662
## X608 -0.3092700 -0.612257626 -1.033167401 -1.055357076
## X609 0.4606666 1.231421076 1.743090382 1.734241492
## X611 -0.3092700 -0.812966386 -1.033167401 -1.055357076
## X612 -0.3092700 -0.042990743 0.144836437 0.035038904
## X613 -0.3092700 -0.717052465 -1.033167401 -1.055357076
## X614 -0.3092700 -0.717052465 -1.033167401 -1.055357076
## X616 -1.0792067 -0.799645008 -1.033167401 -1.055357076
## X617 0.4606666 -0.724157200 -0.196067728 -0.280512302
## X619 1.2306033 1.688788384 2.320898856 2.488888891
## X620 -0.3092700 -0.546538828 -1.033167401 -1.055357076
## X621 0.4606666 0.364643421 0.364738044 0.238586482
## X622 0.4606666 -0.834280591 -1.033167401 -1.055357076
## X623 1.2306033 0.353986318 0.714993696 0.562793706
## X625 0.4606666 -0.593607697 0.582372624 0.440035631
## X628 2.0005400 0.801584616 1.654109577 1.432067769
## X629 2.0005400 0.738530094 1.170382718 0.984315558
## X630 1.2306033 -0.353822894 -0.600448647 -0.654819510
## X631 -1.0792067 -0.821847305 -1.033167401 -1.055357076
## X632 -1.0792067 -0.192190176 -1.033167401 -1.055357076
## X633 -0.3092700 -0.100716714 0.285392103 0.165141479
## X635 0.4606666 0.395726636 1.191636095 1.223798726
## X636 2.0005400 1.494296267 2.227383997 1.962707910
## X637 2.0005400 -0.773002252 -0.065713683 -0.159852656
## X638 0.4606666 -0.295208832 0.507560737 0.370787486
## X639 0.4606666 1.231421076 1.743090382 1.734241492
## X641 1.2306033 -0.285439821 0.691189913 0.540760205
## X648 0.4606666 1.712766865 2.069542251 2.036415216
## X650 0.4606666 0.581337835 1.298469737 2.063432485
## X651 1.2306033 -0.705507271 0.117915493 0.010120064
## X653 2.0005400 0.738530094 1.170382718 0.984315558
## X654 -0.3092700 -0.689521618 0.065490497 -0.038406098
## X655 -0.3092700 -0.834280591 -1.033167401 -1.055357076
## X656 0.4606666 -0.760568966 -1.033167401 -1.055357076
## X657 -0.3092700 0.364643421 0.449468173 0.317015252
## X1082 -1.0792067 -0.662878862 -1.033167401 -1.055357076
## X1083 0.4606666 -0.332508690 -0.459892981 -0.524716935
## X1084 -0.3092700 -0.242811412 -0.459892981 -0.524716935
## X1086 -0.3092700 -0.693962077 -1.033167401 -1.055357076
## X1088 -0.3092700 -0.066969224 0.144836437 0.035038904
## X1089 0.4606666 1.123073869 0.151637518 0.041334190
## X1090 -0.3092700 2.164805621 1.334458788 1.136189331
## X1091 -0.3092700 0.380629074 0.113381439 0.005923206
## X1092 -1.0792067 -0.749023772 -0.549440542 -0.607604866
## X1093 -0.3092700 -0.371584732 0.117915493 0.010120064
## X1094 -0.3092700 -0.124695194 0.023833878 -0.076964725
## X1095 0.4606666 -0.087395336 0.381740745 0.254324696
## X1097 -1.0792067 -0.662878862 -1.033167401 -1.055357076
## X1098 1.2306033 0.367307696 1.099821507 0.919001967
## X1101 0.4606666 2.036032302 2.320898856 2.488888891
## X1103 2.0005400 1.679019374 2.005215364 1.757061904
## X1104 0.4606666 1.180799840 1.377815677 1.396132178
## X1105 0.4606666 0.068908831 0.510111142 1.214880405
## X1106 -1.0792067 0.577785467 -0.295816911 -0.372843162
## X1108 -0.3092700 -0.821847305 -1.033167401 -1.055357076
## X1110 -0.3092700 -0.693962077 -1.033167401 -1.055357076
## X1112 0.4606666 1.178135565 1.743090382 1.734241492
## X1113 0.4606666 0.280274694 0.113381439 0.005923206
## X1115 0.4606666 -0.294320740 0.023833878 -0.076964725
## X1116 -0.3092700 -0.646005116 -0.591097161 -0.646163492
## X1117 -0.3092700 0.604428223 0.364738044 0.238586482
## X1119 -0.3092700 -0.005690885 0.285392103 0.165141479
## X1120 2.0005400 0.815794086 1.654109577 1.432067769
## X1121 1.2306033 0.407271830 1.810534431 1.576859345
## X1122 2.0005400 0.792703697 1.654109577 1.432067769
## X1124 0.4606666 -0.711723914 -0.065713683 -0.159852656
## X1125 -1.0792067 -0.192190176 -1.033167401 -1.055357076
## X1126 -0.3092700 -0.612257626 -1.033167401 -1.055357076
## X1127 0.4606666 -0.828952040 -1.033167401 -1.055357076
## X1128 -0.3092700 -0.087395336 -0.208536376 -0.292053660
## X1129 -0.3092700 -0.717052465 -1.033167401 -1.055357076
## X1130 -0.3092700 -0.028781274 0.023833878 -0.076964725
## X1131 -0.3092700 -0.799645008 -1.033167401 -1.055357076
## X1133 0.4606666 0.516507129 0.692890184 0.542334027
## X1135 -1.0792067 -0.749023772 -0.549440542 -0.607604866
## X1136 -0.3092700 -0.717052465 -1.033167401 -1.055357076
## X1138 2.0005400 3.944541710 5.512589313 5.003593308
## X1139 2.0005400 0.815794086 1.654109577 1.432067769
## X1141 -1.0792067 -0.799645008 -1.033167401 -1.055357076
## X1142 -0.3092700 -0.612257626 -1.033167401 -1.055357076
## X1143 1.2306033 -0.676200240 0.601642352 0.457872274
## X1144 2.7704767 0.270505683 0.466754253 0.333015770
## X1145 0.4606666 1.984522974 1.837171997 1.821326281
## X1146 -1.0792067 0.542261793 0.449468173 0.317015252
## X1147 -1.0792067 -0.646005116 -0.457625954 0.141009550
## X1149 -0.3092700 -0.129135654 0.053021849 -0.049947456
## X1150 -1.0792067 -0.698402536 -0.287882317 -0.365498662
## X1151 -0.3092700 -0.661990770 -0.457625954 0.141009550
## X1152 1.2306033 -0.689521618 0.065490497 -0.038406098
## X1153 -0.3092700 0.205674978 -0.585712972 -0.641179724
## X1156 -1.0792067 -0.227713850 0.023833878 -0.076964725
## X1158 1.2306033 1.724312059 2.005215364 1.757061904
## X1159 1.2306033 -0.633571830 0.456836011 0.323835145
## X1160 2.0005400 0.234093917 2.570838568 2.280619849
## [ reached 'max' / getOption("max.print") -- omitted 497 rows ]
##
## $usekernel
## [1] FALSE
##
## $varnames
## [1] "FP001" "FP002" "FP003"
## [4] "FP004" "FP005" "FP006"
## [7] "FP007" "FP008" "FP009"
## [10] "FP010" "FP011" "FP012"
## [13] "FP013" "FP014" "FP015"
## [16] "FP016" "FP017" "FP018"
## [19] "FP019" "FP020" "FP021"
## [22] "FP022" "FP023" "FP024"
## [25] "FP025" "FP026" "FP027"
## [28] "FP028" "FP029" "FP030"
## [31] "FP031" "FP032" "FP033"
## [34] "FP034" "FP035" "FP036"
## [37] "FP037" "FP038" "FP039"
## [40] "FP040" "FP041" "FP042"
## [43] "FP043" "FP044" "FP045"
## [46] "FP046" "FP047" "FP048"
## [49] "FP049" "FP050" "FP051"
## [52] "FP052" "FP053" "FP054"
## [55] "FP055" "FP056" "FP057"
## [58] "FP058" "FP059" "FP060"
## [61] "FP061" "FP062" "FP063"
## [64] "FP064" "FP065" "FP066"
## [67] "FP067" "FP068" "FP069"
## [70] "FP070" "FP071" "FP072"
## [73] "FP073" "FP074" "FP075"
## [76] "FP076" "FP077" "FP078"
## [79] "FP079" "FP080" "FP081"
## [82] "FP082" "FP083" "FP084"
## [85] "FP085" "FP086" "FP087"
## [88] "FP088" "FP089" "FP090"
## [91] "FP091" "FP092" "FP093"
## [94] "FP094" "FP095" "FP096"
## [97] "FP097" "FP098" "FP099"
## [100] "FP100" "FP101" "FP102"
## [103] "FP103" "FP104" "FP105"
## [106] "FP106" "FP107" "FP108"
## [109] "FP109" "FP110" "FP111"
## [112] "FP112" "FP113" "FP114"
## [115] "FP115" "FP116" "FP117"
## [118] "FP118" "FP119" "FP120"
## [121] "FP121" "FP122" "FP123"
## [124] "FP124" "FP125" "FP126"
## [127] "FP127" "FP128" "FP129"
## [130] "FP130" "FP131" "FP132"
## [133] "FP133" "FP134" "FP135"
## [136] "FP136" "FP137" "FP138"
## [139] "FP139" "FP140" "FP141"
## [142] "FP142" "FP143" "FP144"
## [145] "FP145" "FP146" "FP147"
## [148] "FP148" "FP149" "FP150"
## [151] "FP151" "FP152" "FP153"
## [154] "FP155" "FP156" "FP157"
## [157] "FP158" "FP159" "FP160"
## [160] "FP161" "FP162" "FP163"
## [163] "FP164" "FP165" "FP166"
## [166] "FP167" "FP168" "FP169"
## [169] "FP170" "FP171" "FP172"
## [172] "FP173" "FP174" "FP175"
## [175] "FP176" "FP177" "FP178"
## [178] "FP179" "FP180" "FP181"
## [181] "FP182" "FP183" "FP184"
## [184] "FP185" "FP186" "FP187"
## [187] "FP188" "FP189" "FP190"
## [190] "FP191" "FP192" "FP193"
## [193] "FP194" "FP195" "FP196"
## [196] "FP197" "FP198" "FP201"
## [199] "FP202" "FP203" "FP204"
## [202] "FP205" "FP206" "FP207"
## [205] "FP208" "MolWeight" "NumBonds"
## [208] "NumMultBonds" "NumRotBonds" "NumDblBonds"
## [211] "NumCarbon" "NumNitrogen" "NumOxygen"
## [214] "NumSulfer" "NumChlorine" "NumHalogen"
## [217] "NumRings" "HydrophilicFactor" "SurfaceArea1"
## [220] "SurfaceArea2"
##
## $xNames
## [1] "FP001" "FP002" "FP003"
## [4] "FP004" "FP005" "FP006"
## [7] "FP007" "FP008" "FP009"
## [10] "FP010" "FP011" "FP012"
## [13] "FP013" "FP014" "FP015"
## [16] "FP016" "FP017" "FP018"
## [19] "FP019" "FP020" "FP021"
## [22] "FP022" "FP023" "FP024"
## [25] "FP025" "FP026" "FP027"
## [28] "FP028" "FP029" "FP030"
## [31] "FP031" "FP032" "FP033"
## [34] "FP034" "FP035" "FP036"
## [37] "FP037" "FP038" "FP039"
## [40] "FP040" "FP041" "FP042"
## [43] "FP043" "FP044" "FP045"
## [46] "FP046" "FP047" "FP048"
## [49] "FP049" "FP050" "FP051"
## [52] "FP052" "FP053" "FP054"
## [55] "FP055" "FP056" "FP057"
## [58] "FP058" "FP059" "FP060"
## [61] "FP061" "FP062" "FP063"
## [64] "FP064" "FP065" "FP066"
## [67] "FP067" "FP068" "FP069"
## [70] "FP070" "FP071" "FP072"
## [73] "FP073" "FP074" "FP075"
## [76] "FP076" "FP077" "FP078"
## [79] "FP079" "FP080" "FP081"
## [82] "FP082" "FP083" "FP084"
## [85] "FP085" "FP086" "FP087"
## [88] "FP088" "FP089" "FP090"
## [91] "FP091" "FP092" "FP093"
## [94] "FP094" "FP095" "FP096"
## [97] "FP097" "FP098" "FP099"
## [100] "FP100" "FP101" "FP102"
## [103] "FP103" "FP104" "FP105"
## [106] "FP106" "FP107" "FP108"
## [109] "FP109" "FP110" "FP111"
## [112] "FP112" "FP113" "FP114"
## [115] "FP115" "FP116" "FP117"
## [118] "FP118" "FP119" "FP120"
## [121] "FP121" "FP122" "FP123"
## [124] "FP124" "FP125" "FP126"
## [127] "FP127" "FP128" "FP129"
## [130] "FP130" "FP131" "FP132"
## [133] "FP133" "FP134" "FP135"
## [136] "FP136" "FP137" "FP138"
## [139] "FP139" "FP140" "FP141"
## [142] "FP142" "FP143" "FP144"
## [145] "FP145" "FP146" "FP147"
## [148] "FP148" "FP149" "FP150"
## [151] "FP151" "FP152" "FP153"
## [154] "FP155" "FP156" "FP157"
## [157] "FP158" "FP159" "FP160"
## [160] "FP161" "FP162" "FP163"
## [163] "FP164" "FP165" "FP166"
## [166] "FP167" "FP168" "FP169"
## [169] "FP170" "FP171" "FP172"
## [172] "FP173" "FP174" "FP175"
## [175] "FP176" "FP177" "FP178"
## [178] "FP179" "FP180" "FP181"
## [181] "FP182" "FP183" "FP184"
## [184] "FP185" "FP186" "FP187"
## [187] "FP188" "FP189" "FP190"
## [190] "FP191" "FP192" "FP193"
## [193] "FP194" "FP195" "FP196"
## [196] "FP197" "FP198" "FP201"
## [199] "FP202" "FP203" "FP204"
## [202] "FP205" "FP206" "FP207"
## [205] "FP208" "MolWeight" "NumBonds"
## [208] "NumMultBonds" "NumRotBonds" "NumDblBonds"
## [211] "NumCarbon" "NumNitrogen" "NumOxygen"
## [214] "NumSulfer" "NumChlorine" "NumHalogen"
## [217] "NumRings" "HydrophilicFactor" "SurfaceArea1"
## [220] "SurfaceArea2"
##
## $problemType
## [1] "Classification"
##
## $tuneValue
## fL usekernel adjust
## 1 2 FALSE FALSE
##
## $obsLevels
## [1] "Low" "Mid" "High"
## attr(,"ordered")
## [1] FALSE
##
## $param
## list()
##
## attr(,"class")
## [1] "NaiveBayes"NB_Tune$results## usekernel fL adjust logLoss AUC prAUC Accuracy Kappa
## 1 FALSE 2 FALSE 3.224027 0.8205606 0.6408077 0.6434612 0.4593777
## 2 TRUE 2 FALSE NaN NaN NaN NaN NaN
## Mean_F1 Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value
## 1 0.6286132 0.6398324 0.8254896 0.632263
## 2 NaN NaN NaN NaN
## Mean_Neg_Pred_Value Mean_Precision Mean_Recall Mean_Detection_Rate
## 1 0.8219493 0.632263 0.6398324 0.2144871
## 2 NaN NaN NaN NaN
## Mean_Balanced_Accuracy logLossSD AUCSD prAUCSD AccuracySD KappaSD
## 1 0.732661 0.8368251 0.0372749 0.04856058 0.05446968 0.07913488
## 2 NaN NA NA NA NA NA
## Mean_F1SD Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.05603901 0.05290333 0.02607198 0.05134728
## 2 NA NA NA NA
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.0257573 0.05134728 0.05290333 0.01815656
## 2 NA NA NA NA
## Mean_Balanced_AccuracySD
## 1 0.0394039
## 2 NA(NB_Train_Accuracy <- NB_Tune$results[NB_Tune$results$usekernel==NB_Tune$bestTune$usekernel &
NB_Tune$results$adjust==NB_Tune$bestTune$adjust,
c("Accuracy")])## [1] 0.6434612##################################
# Identifying and plotting the
# best model predictors
##################################
# model does not support variable importance measurement
##################################
# Independently evaluating the model
# on the test set
##################################
NB_Test <- data.frame(NB_Observed = PMA_PreModelling_Test_NB$Log_Solubility_Class,
NB_Predicted = predict(NB_Tune,
PMA_PreModelling_Test_NB[,!names(PMA_PreModelling_Test_NB) %in% c("Log_Solubility_Class")],
type = "raw"))
NB_Test## NB_Observed NB_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Mid
## 13 High High
## 14 High High
## 15 High Mid
## 16 High Mid
## 17 High High
## 18 High High
## 19 High High
## 20 High Mid
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High Mid
## 27 High High
## 28 High High
## 29 High Low
## 30 High High
## 31 High Mid
## 32 High High
## 33 High High
## 34 High Mid
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High Low
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High High
## 50 High High
## 51 High High
## 52 High Mid
## 53 High Mid
## 54 High High
## 55 High High
## 56 High Mid
## 57 High High
## 58 Mid High
## 59 Mid Mid
## 60 Mid Mid
## 61 Mid Mid
## 62 Mid High
## 63 Mid Mid
## 64 Mid High
## 65 Mid Mid
## 66 Mid Low
## 67 Mid Mid
## 68 Mid Low
## 69 Mid Mid
## 70 Mid Mid
## 71 Mid Mid
## 72 Mid Mid
## 73 Mid High
## 74 Mid Low
## 75 Mid Mid
## 76 Mid Mid
## 77 Mid Mid
## 78 Mid High
## 79 Mid High
## 80 Mid High
## 81 Mid Mid
## 82 Mid High
## 83 Mid High
## 84 Mid High
## 85 Mid Mid
## 86 Mid High
## 87 Mid Low
## 88 Mid Mid
## 89 Mid Mid
## 90 Mid High
## 91 Mid Mid
## 92 Mid Mid
## 93 Mid Low
## 94 Mid Mid
## 95 Mid Mid
## 96 Mid Mid
## 97 Mid High
## 98 Mid Mid
## 99 Mid Mid
## 100 Mid High
## 101 Mid Low
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid High
## 105 Mid High
## 106 Mid Mid
## 107 Mid Low
## 108 Mid Mid
## 109 Mid Mid
## 110 Mid Mid
## 111 Mid Mid
## 112 Mid Low
## 113 Mid Mid
## 114 Mid Mid
## 115 Mid Low
## 116 Mid Low
## 117 Mid Low
## 118 Mid High
## 119 Low Mid
## 120 Low Low
## 121 Low Low
## 122 Low Mid
## 123 Low Low
## 124 Low High
## 125 Low Low
## 126 Low Mid
## 127 Low High
## 128 Low Mid
## 129 Low High
## 130 Low Low
## 131 Low High
## 132 Low Low
## 133 Low Low
## 134 Low Mid
## 135 Low High
## 136 Low Mid
## 137 Low Low
## 138 Low Mid
## 139 Low High
## 140 Low Low
## 141 Low Mid
## 142 Low Low
## 143 Low Low
## 144 Low Mid
## 145 Low Mid
## 146 Low Mid
## 147 Low Mid
## 148 Low Low
## 149 Low High
## 150 Low Low
## 151 Low Low
## 152 Low Low
## 153 Low High
## 154 Low High
## 155 Low Low
## 156 Low Low
## 157 Low Low
## 158 Low Low
## 159 Low High
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Mid
## 164 Low Low
## 165 Low Low
## 166 Low Mid
## 167 Low Low
## 168 Low Mid
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low High
## 173 Low Low
## 174 Low Mid
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low High
## 181 Low Low
## 182 Low Low
## 183 Low Mid
## 184 Low Mid
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Mid
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Mid
## 226 High Mid
## 227 High High
## 228 High High
## 229 High High
## 230 High Mid
## 231 High High
## 232 High Mid
## 233 High High
## 234 High Mid
## 235 High Mid
## 236 High Mid
## 237 High Mid
## 238 Mid Mid
## 239 Mid Mid
## 240 Mid High
## 241 Mid High
## 242 Mid Mid
## 243 Mid High
## 244 Mid Mid
## 245 Mid Low
## 246 Mid Mid
## 247 Mid High
## 248 Mid Mid
## 249 Mid High
## 250 Mid High
## 251 Mid Mid
## 252 Mid Mid
## 253 Mid Mid
## 254 Mid Low
## 255 Mid Mid
## 256 Mid Mid
## 257 Mid Mid
## 258 Mid Mid
## 259 Mid Low
## 260 Mid Mid
## 261 Mid High
## 262 Mid High
## 263 Mid Low
## 264 Mid Mid
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Mid
## 268 Mid High
## 269 Low Mid
## 270 Low Low
## 271 Low Mid
## 272 Low Mid
## 273 Low Low
## 274 Low Mid
## 275 Low Mid
## 276 Low Low
## 277 Low Low
## 278 Low Mid
## 279 Low Low
## 280 Low Mid
## 281 Low High
## 282 Low Low
## 283 Low Low
## 284 Low Mid
## 285 Low High
## 286 Low Low
## 287 Low High
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low High
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Mid
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(NB_Test_Accuracy <- Accuracy(y_pred = NB_Test$NB_Predicted,
y_true = NB_Test$NB_Observed))## [1] 0.65506331.5.6 Nearest Shrunken Centroids (NSC)
Nearest Shrunken Centroids involve first summarizing the training dataset into a set of centroids, then using the centroids to make predictions for new instances. The algorithm shrinks the centroids of each input variable towards the centroid of the entire training data set. Those variables that are shrunk down to the value of the data centroid can then be removed as they do not help to discriminate between the class labels. The centroids in the input feature space are different for each target label which then represents the model. Given new instances, the distance between a given row of data and each centroid is calculated and the closest centroid is used to assign a class label to the example.
[A] The nearest shrunken centroids model from the pamr package was implemented through the caret package.
[B] The model contains 1 hyperparameter:
[B.1] threshold = shrinkage threshold made to vary across a range of values equal to 0 to 25
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves threshold=1
[C.2] Accuracy = 0.60452
[D] The model allows for ranking of predictors in terms of variable importance. The top-performing predictors in the model are as follows:
[D.1] MolWeight variable (numeric)
[D.2] NumCarbon variable (numeric)
[D.3] NumBonds variable (numeric)
[D.4] NumMultBonds variable (numeric)
[D.5] NumRings variable (numeric)
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.63607
Code Chunk | Output
##################################
# Transforming factor predictors
# as required by the nature of the model
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_NSC <- as.data.frame(lapply(PMA_PreModelling_Train[,!names(PMA_PreModelling_Train) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Train_NSC$Log_Solubility_Class <- PMA_PreModelling_Train$Log_Solubility_Class
dim(PMA_PreModelling_Train_NSC)## [1] 951 221PMA_PreModelling_Test_NSC <- as.data.frame(lapply(PMA_PreModelling_Test[,!names(PMA_PreModelling_Test) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Test_NSC$Log_Solubility_Class <- PMA_PreModelling_Test$Log_Solubility_Class
dim(PMA_PreModelling_Test_NSC)## [1] 316 221##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_NSC$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
NSC_Grid = data.frame(threshold = seq(0, 8, length = 9))
##################################
# Running the nearest shrunken centroids model
# by setting the caret method to 'pam'
##################################
set.seed(12345678)
NSC_Tune <- train(x = PMA_PreModelling_Train_NSC[,!names(PMA_PreModelling_Train_NSC) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_NSC$Log_Solubility_Class,
method = "pam",
tuneGrid = NSC_Grid,
metric = "Accuracy",
preProc = c("center", "scale"),
trControl = KFold_Control)## 1111111111## 1##################################
# Reporting the cross-validation results
# for the train set
##################################
NSC_Tune## Nearest Shrunken Centroids
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## Pre-processing: centered (220), scaled (220)
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## threshold logLoss AUC prAUC Accuracy Kappa Mean_F1
## 0 1.0053088 0.7986117 0.6383621 0.5918682 0.377933196 0.5705143
## 1 0.8852013 0.7986907 0.6435073 0.6045224 0.390689052 0.5629779
## 2 0.8572315 0.7867513 0.6204747 0.5855622 0.354489788 0.5226695
## 3 0.8440090 0.7831023 0.6072123 0.5772620 0.331334495 0.4932871
## 4 0.8836407 0.7798191 0.5959490 0.5815176 0.320109872 0.4547332
## 5 0.9439966 0.7682432 0.5830754 0.5393650 0.211538787 NaN
## 6 0.9879275 0.7701367 0.5881594 0.4710398 0.048665101 NaN
## 7 1.0214083 0.7734845 0.5897285 0.4500637 0.002282919 NaN
## 8 1.0464494 0.7756318 0.5918340 0.4489999 0.000000000 NaN
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.5802349 0.7979792 0.5740786 0.7964560
## 0.5835158 0.8016081 0.5677051 0.8084817
## 0.5582769 0.7882126 0.5367218 0.8032933
## 0.5417570 0.7782304 0.4902777 0.8054533
## 0.5339216 0.7706006 0.4265496 0.8183140
## 0.4605736 0.7316940 NaN 0.8164331
## 0.3623889 0.6806491 NaN 0.8229237
## 0.3347222 0.6673077 NaN 0.8182719
## 0.3333333 0.6666667 NaN NaN
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.5740786 0.5802349 0.1972894 0.6891071
## 0.5677051 0.5835158 0.2015075 0.6925619
## 0.5367218 0.5582769 0.1951874 0.6732448
## 0.4902777 0.5417570 0.1924207 0.6599937
## 0.4265496 0.5339216 0.1938392 0.6522611
## NaN 0.4605736 0.1797883 0.5961338
## NaN 0.3623889 0.1570133 0.5215190
## NaN 0.3347222 0.1500212 0.5010150
## NaN 0.3333333 0.1496666 0.5000000
##
## Accuracy was used to select the optimal model using the largest value.
## The final value used for the model was threshold = 1.NSC_Tune$finalModel## $y
## [1] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [16] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [31] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [46] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [61] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [76] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [91] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [106] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [121] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [136] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [151] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [166] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [181] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [196] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [211] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [226] Low Low Low Low Low Low Low Low Low Low Low Low Low Mid Mid
## [241] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [256] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Low
## [271] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [286] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [301] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [316] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [331] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [346] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [361] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [376] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [391] Low Low Low Low Low Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [406] Mid Mid Mid Mid Mid Mid Mid Mid Low Low Low Low Low Low Low
## [421] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [436] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [451] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [466] Low Low Low Low Low Low Low Low Low Low Low High High Mid Mid
## [481] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [496] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [511] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [526] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [541] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [556] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [571] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [586] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [601] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [616] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [631] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid High High Mid Mid Mid
## [646] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [661] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [676] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [691] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [706] Mid Mid Mid Mid Mid Mid Mid Mid Mid High High High High High High
## [721] High High High High High High High High High High High High High High High
## [736] High High High High High High High High High High High High High High High
## [751] High High High High High High High High High High High High High High High
## [766] High High High High High High High High High High High High High High High
## [781] High High High High High High High High High High High High High High High
## [796] High High High High High High High High High High High High High High High
## [811] High High High High High High High High High High High High High High High
## [826] High High High High High High High High High High High High High High High
## [841] High High High High High High High High High High High High High High High
## [856] High High High High High High High High High High High High High High High
## [871] High High High High High High High High High High High High High High High
## [886] High High High High High High High High High High High High High High High
## [901] High High High High High High High High High High High High High High High
## [916] High High High High High High High High High High High High High High High
## [931] High High High High High High High High High High High High High High High
## [946] High High High High High High
## Levels: Low Mid High
##
## $proby
## NULL
##
## $yhat
## [1] Low Low Mid Mid Low Mid Low High Low Low Low Low Low Low Mid
## [16] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [31] High High High Low Low Low High Low Low Low Low Low Low Low Low
## [46] Low High Low Low Low Low High Low Low Low Low Mid Low Low Low
## [61] High High Low Low Low High Low Low High Low Low High Low Mid Low
## [76] Low Low Low Low Low Low Low Low Low Low High High Low Low Mid
## [91] Low Low Low Low Low Low High Low Low Low Low Low High Low Low
## [106] Low Low Low Mid Low Low Low High Low Low Low High Low Low Low
## [121] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [136] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [151] Low Low Low Low Low Low Low Low Low Low High Low Mid Low Low
## [166] Mid Low Mid High Low Low High Low Low High Low Low Low Low Low
## [181] Low Low Low Low Low Low High Low Low Low Low Low Low Low Low
## [196] Low Low Mid High Low Mid Low Low Low Low Low Low Low Low Low
## [211] Low Low Low Low Low Low Low Low High Low High Low Low Low Low
## [226] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [241] High Low Low Low Low Low Low High High Low Mid Low High Low Low
## [256] High Mid High High Low Low High High Low High High Low High Low Mid
## [271] Low Low High Low High Low Low Mid Low Low Mid Low Mid Low Low
## [286] Low Low Low Low Low High Low Low Mid Low Low Mid Low Low High
## [301] Mid Mid Mid Low Mid Low Low Low Low Low High Low High High Mid
## [316] Low High Low Low Low Low Low Low High Mid Low Mid Low High Low
## [331] Low Low Low Low Mid High Low Low Low Low High Mid Low Low Low
## [346] Mid Low Low Mid Low High Mid Mid Low High Mid Low High Mid Low
## [361] Mid Low Low High Low Low Low High Low Low Low Low Low Low Low
## [376] Low Low Low High High Low Low Low Low Low Low Low Low Low Low
## [391] Low Low Mid Low Mid High Low High Low Low Low Mid Low High Mid
## [406] Mid Mid High Low Low Low Low Mid High Mid Low Low Low Low Low
## [421] Mid Low Low Low Low Low High Low Low Low Low Low High Low High
## [436] Low Low Low High Low Low Low Low High High Low High Mid Low Low
## [451] High Low Low Low Low Low High Low Low Low Low Mid Low Low High
## [466] High Low Low High Low Low Low Low Low Low Mid Mid High Low High
## [481] Mid Mid Low High Mid High Mid High High Low High Mid High Low Mid
## [496] Low Mid Low High Mid Mid Low High High Mid Low Mid Mid High High
## [511] Low High Mid Mid Mid High High High Mid High High Mid Low Low High
## [526] High High High High Low High High Mid Mid Mid Low High Mid High Low
## [541] Mid Low High Mid Mid Low High Mid High Low Low High Low Low High
## [556] High Low Mid High Mid Mid High Low Low Mid High High High Mid High
## [571] Mid Low Mid Mid Low Low Mid Low High High High Low High Low Mid
## [586] Mid Mid Mid High High Low Low Low Low Mid High Mid Low Low Mid
## [601] Low Mid Low Low Mid Low High Low Low High Low Mid Mid Mid Low
## [616] Low Low High Mid Mid Mid High High Mid Mid Mid Low Mid High Mid
## [631] Mid High Mid Low Mid Low Low Low Mid Low High Mid High High Low
## [646] High High Mid High High High High Mid High High High Mid High Mid Mid
## [661] Mid High High Mid Low High High Low Low High Low Low Low Mid Mid
## [676] High Low High Mid Low High High Low High High High Low Mid Low High
## [691] High Mid High Low Low Low Low High Low Low Mid High Low High Mid
## [706] Mid Mid High Low Mid Low Mid Mid Low High High High High High High
## [721] High High High High High High High High High High High High High Mid High
## [736] High Mid High High High High High Mid Mid High High High High High High
## [751] High High High High High High Mid High High High High High High High High
## [766] High Mid High High High High High High High High High High High Mid High
## [781] High High High High Mid High Mid Mid High High High High High High High
## [796] High High High High High High Mid Mid Low Low Mid High Mid High High
## [811] Mid High Mid High Low High Mid Mid High High High High High High Mid
## [826] High Low Mid High High High Mid Mid High Mid Mid Mid Mid High High
## [841] High Mid Mid Mid High Low High Mid Mid Mid Mid High Mid High High
## [856] Mid High Mid High Mid Low Mid High High High Mid High High Mid Low
## [871] High Mid High High High High High High High High High High High Low High
## [886] High High High High High Mid Mid High Mid High High High High High High
## [901] High High High Mid High High High High Mid High High High High High High
## [916] High High High High Mid High High High High High High High Low High High
## [931] High High Mid Mid Mid High High Low High High Mid High Low Mid Low
## [946] Mid Mid Mid High High High
## Levels: Low Mid High
##
## $prob
## Low Mid High
## 1 0.7764453127 0.207248682 1.630601e-02
## 2 0.9432003180 0.056058391 7.412915e-04
## 3 0.2927242160 0.487997757 2.192780e-01
## 4 0.3217539050 0.402775122 2.754710e-01
## 5 0.6191613241 0.323408321 5.743036e-02
## 6 0.2324834089 0.447145513 3.203711e-01
## 7 0.9967636049 0.003230878 5.516706e-06
## 8 0.0696509453 0.288480037 6.418690e-01
## 9 0.9480374682 0.049992194 1.970337e-03
## 10 0.6325734687 0.340294762 2.713177e-02
## 11 0.7668599844 0.220606130 1.253389e-02
## 12 0.8957154527 0.094553468 9.731079e-03
## 13 0.6802977084 0.290763357 2.893893e-02
## 14 0.9660161845 0.033235500 7.483158e-04
## 15 0.3297217458 0.519757142 1.505211e-01
## 16 0.7320439606 0.250913268 1.704277e-02
## 17 0.5604531271 0.415950378 2.359649e-02
## 18 0.9937905994 0.006181845 2.755535e-05
## 19 0.8196395066 0.148871186 3.148931e-02
## 20 0.7148148871 0.262803498 2.238162e-02
## 21 0.9911483884 0.008786075 6.553702e-05
## 22 0.9190251648 0.079389582 1.585253e-03
## 23 0.8264591955 0.169094388 4.446416e-03
## 24 0.5438145070 0.371974838 8.421065e-02
## 25 0.6051165331 0.380873133 1.401033e-02
## 26 0.6849122281 0.306792208 8.295564e-03
## 27 0.9121300047 0.086666806 1.203190e-03
## 28 0.7691150361 0.219229953 1.165501e-02
## 29 0.4807451379 0.458188116 6.106675e-02
## 30 0.8473849503 0.144323273 8.291777e-03
## 31 0.0466986553 0.271788638 6.815127e-01
## 32 0.0138729363 0.140840268 8.452868e-01
## 33 0.0760742887 0.301608588 6.223171e-01
## 34 0.7256760351 0.249507143 2.481682e-02
## 35 0.7919686162 0.201776962 6.254422e-03
## 36 0.6753088204 0.270244691 5.444649e-02
## 37 0.0760742887 0.301608588 6.223171e-01
## 38 0.8151940155 0.153268179 3.153781e-02
## 39 0.7378122881 0.239751622 2.243609e-02
## 40 0.8420402741 0.154193503 3.766223e-03
## 41 0.9312215169 0.064342050 4.436433e-03
## 42 0.8868960592 0.109740774 3.363166e-03
## 43 0.9312979417 0.066379625 2.322433e-03
## 44 0.9949801501 0.005011460 8.389417e-06
## 45 0.6228086196 0.324695382 5.249600e-02
## 46 0.9490673017 0.050291230 6.414682e-04
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## 728 0.0664601951 0.374777368 5.587624e-01
## 729 0.0901397464 0.436776710 4.730835e-01
## 730 0.0083715110 0.109213868 8.824146e-01
## 731 0.0188336265 0.165458157 8.157082e-01
## 732 0.0010503750 0.046976922 9.519727e-01
## 733 0.0979200010 0.411336260 4.907437e-01
## 734 0.1925833112 0.442469387 3.649473e-01
## 735 0.0470770854 0.306842959 6.460800e-01
## 736 0.0212656736 0.119934581 8.587997e-01
## 737 0.1669072043 0.493557053 3.395357e-01
## 738 0.0185121915 0.279245655 7.022422e-01
## 739 0.0017542647 0.055279288 9.429664e-01
## 740 0.0105395831 0.125179320 8.642811e-01
## 741 0.0022475254 0.057962237 9.397902e-01
## 742 0.0143726891 0.117717708 8.679096e-01
## 743 0.1687953102 0.485279513 3.459252e-01
## 744 0.2086920545 0.544653968 2.466540e-01
## 745 0.0202575281 0.147513610 8.322289e-01
## 746 0.0035169071 0.079784607 9.166985e-01
## 747 0.0011972666 0.038450878 9.603519e-01
## 748 0.0139449099 0.185956097 8.000990e-01
## 749 0.0028056368 0.063937280 9.332571e-01
## 750 0.0346167735 0.232193891 7.331893e-01
## 751 0.0021328709 0.058360158 9.395070e-01
## 752 0.0022416114 0.065680031 9.320784e-01
## 753 0.0116186907 0.126245057 8.621363e-01
## 754 0.0067629292 0.116234350 8.770027e-01
## 755 0.0011413859 0.030056093 9.688025e-01
## 756 0.0114305222 0.159253626 8.293159e-01
## 757 0.0946764408 0.482581792 4.227418e-01
## 758 0.1510231660 0.339619986 5.093568e-01
## 759 0.0123627547 0.137733038 8.499042e-01
## 760 0.0252996352 0.275069995 6.996304e-01
## 761 0.0013963610 0.042805971 9.557977e-01
## 762 0.0028206488 0.063466364 9.337130e-01
## 763 0.0617688577 0.377262733 5.609684e-01
## 764 0.0057930190 0.098236019 8.959710e-01
## 765 0.0151799720 0.151303356 8.335167e-01
## 766 0.0198711693 0.217168208 7.629606e-01
## 767 0.3394631426 0.412762438 2.477744e-01
## 768 0.0411750647 0.284390606 6.744343e-01
## 769 0.0044050985 0.082711866 9.128830e-01
## 770 0.0024451812 0.058674151 9.388807e-01
## 771 0.0116360419 0.149494179 8.388698e-01
## 772 0.0043661950 0.078149511 9.174843e-01
## 773 0.0036593997 0.064750546 9.315901e-01
## 774 0.0043908292 0.087313924 9.082952e-01
## 775 0.0021890031 0.047551723 9.502593e-01
## 776 0.1762669997 0.400072272 4.236607e-01
## 777 0.0021294245 0.046322921 9.515477e-01
## 778 0.0398250614 0.205863330 7.543116e-01
## 779 0.1872970463 0.492803927 3.198990e-01
## 780 0.0035309322 0.074295296 9.221738e-01
## 781 0.0019634040 0.069158259 9.288783e-01
## 782 0.0026106003 0.059751628 9.376378e-01
## 783 0.0753136120 0.351283842 5.734025e-01
## 784 0.0029051853 0.060828122 9.362667e-01
## 785 0.1583707637 0.485810977 3.558183e-01
## 786 0.0278371191 0.203012685 7.691502e-01
## 787 0.1513104762 0.505847408 3.428421e-01
## 788 0.3664390039 0.451370983 1.821900e-01
## 789 0.0892618694 0.388274710 5.224634e-01
## 790 0.0031276562 0.067558583 9.293138e-01
## 791 0.2121691606 0.282513076 5.053178e-01
## 792 0.0046677556 0.058500739 9.368315e-01
## 793 0.0374863203 0.262514534 6.999991e-01
## 794 0.0050428615 0.052864692 9.420924e-01
## 795 0.0017543806 0.047326463 9.509192e-01
## 796 0.0028816707 0.064846958 9.322714e-01
## 797 0.0426483912 0.225156969 7.321946e-01
## 798 0.0070891567 0.089186667 9.037242e-01
## 799 0.0038851733 0.086064859 9.100500e-01
## 800 0.0047253238 0.090597234 9.046774e-01
## 801 0.0044944416 0.078024538 9.174810e-01
## 802 0.2148970344 0.535980305 2.491227e-01
## 803 0.1705547153 0.597518529 2.319268e-01
## 804 0.7101978838 0.247998996 4.180312e-02
## 805 0.7677699088 0.207496898 2.473319e-02
## 806 0.1303489957 0.503239756 3.664112e-01
## 807 0.0047063960 0.068319469 9.269741e-01
## 808 0.1338134845 0.437293261 4.288933e-01
## 809 0.0052181572 0.074288442 9.204934e-01
## 810 0.0104967087 0.112987725 8.765156e-01
## 811 0.3213603160 0.459310273 2.193294e-01
## 812 0.0063565415 0.098218550 8.954249e-01
## 813 0.1180963314 0.528546176 3.533575e-01
## 814 0.0012315627 0.040354677 9.584138e-01
## 815 0.7220010072 0.231630737 4.636826e-02
## 816 0.0075941142 0.098933458 8.934724e-01
## 817 0.3565299710 0.515597354 1.278727e-01
## 818 0.0963899787 0.538016150 3.655939e-01
## 819 0.0035199725 0.059594166 9.368859e-01
## 820 0.0110422360 0.133258848 8.556989e-01
## 821 0.0182182304 0.157714843 8.240669e-01
## 822 0.0375611291 0.278728303 6.837106e-01
## 823 0.0086765963 0.117268776 8.740546e-01
## 824 0.0036504433 0.100950774 8.953988e-01
## 825 0.2187612236 0.614604168 1.666346e-01
## 826 0.0086430945 0.101371538 8.899854e-01
## 827 0.5873166742 0.342724887 6.995844e-02
## 828 0.2409984260 0.570909128 1.880924e-01
## 829 0.0205460647 0.139198479 8.402555e-01
## 830 0.0249653989 0.185011697 7.900229e-01
## 831 0.0051562343 0.099765099 8.950787e-01
## 832 0.3369400623 0.484722365 1.783376e-01
## 833 0.1418336404 0.482485863 3.756805e-01
## 834 0.0083431349 0.096528522 8.951283e-01
## 835 0.1249312170 0.527964908 3.471039e-01
## 836 0.1416773489 0.516259454 3.420632e-01
## 837 0.4009396199 0.496661976 1.023984e-01
## 838 0.1407702414 0.598699452 2.605303e-01
## 839 0.0891296653 0.408247593 5.026227e-01
## 840 0.0035404634 0.084711370 9.117482e-01
## 841 0.0095962390 0.107070951 8.833328e-01
## 842 0.1393887303 0.577638509 2.829728e-01
## 843 0.3667001929 0.524623366 1.086764e-01
## 844 0.1748567461 0.580912457 2.442308e-01
## 845 0.0132652801 0.131642398 8.550923e-01
## 846 0.5304766867 0.374004269 9.551904e-02
## 847 0.0083212565 0.111935951 8.797428e-01
## 848 0.1882179789 0.546610156 2.651719e-01
## 849 0.3440330250 0.494887278 1.610797e-01
## 850 0.3435996044 0.488143581 1.682568e-01
## 851 0.3450835587 0.429653341 2.252631e-01
## 852 0.0035367010 0.049026544 9.474368e-01
## 853 0.3681070653 0.480150619 1.517423e-01
## 854 0.0370960140 0.258414284 7.044897e-01
## 855 0.0024835101 0.042195811 9.553207e-01
## 856 0.1568505556 0.532790955 3.103585e-01
## 857 0.0897843101 0.359434642 5.507810e-01
## 858 0.3290326812 0.437420823 2.335465e-01
## 859 0.0121004871 0.124452205 8.634473e-01
## 860 0.3441030643 0.438540462 2.173565e-01
## 861 0.4458256815 0.426021275 1.281530e-01
## 862 0.2399667773 0.704562380 5.547084e-02
## 863 0.0095873935 0.118026654 8.723860e-01
## 864 0.0048155999 0.064829764 9.303546e-01
## 865 0.0523505136 0.444524623 5.031249e-01
## 866 0.2423082935 0.608039618 1.496521e-01
## 867 0.0080394089 0.105245008 8.867156e-01
## 868 0.0102766420 0.135065377 8.546580e-01
## 869 0.2030820902 0.642866904 1.540510e-01
## 870 0.6029682639 0.340131931 5.689981e-02
## 871 0.0122035708 0.146941996 8.408544e-01
## 872 0.1889018580 0.607825370 2.032728e-01
## 873 0.0144556237 0.139943981 8.456004e-01
## 874 0.0010218802 0.051327755 9.476504e-01
## 875 0.0078901604 0.122131756 8.699781e-01
## 876 0.0061022605 0.106158091 8.877396e-01
## 877 0.0043940889 0.068519369 9.270865e-01
## 878 0.0496743617 0.262905598 6.874200e-01
## 879 0.0511696660 0.295381543 6.534488e-01
## 880 0.0004597839 0.032905032 9.666352e-01
## 881 0.0015289714 0.058208506 9.402625e-01
## 882 0.0122027025 0.157818984 8.299783e-01
## 883 0.0045292351 0.091420838 9.040499e-01
## 884 0.5083167501 0.419871952 7.181130e-02
## 885 0.0135989287 0.096191148 8.902099e-01
## 886 0.0011986417 0.025848618 9.729527e-01
## 887 0.0022005938 0.061410847 9.363886e-01
## 888 0.0110589700 0.114397907 8.745431e-01
## 889 0.0363660234 0.233991883 7.296421e-01
## 890 0.0014527877 0.047312446 9.512348e-01
## 891 0.1450530115 0.456884151 3.980628e-01
## 892 0.1874995702 0.519799377 2.927011e-01
## 893 0.0061357888 0.091619721 9.022445e-01
## 894 0.3664390039 0.451370983 1.821900e-01
## 895 0.0054920837 0.093785285 9.007226e-01
## 896 0.0024409909 0.072082871 9.254761e-01
## 897 0.0033233915 0.070585823 9.260908e-01
## 898 0.0040349931 0.081522618 9.144424e-01
## 899 0.0047855926 0.072207791 9.230066e-01
## 900 0.0032900915 0.071046670 9.256632e-01
## 901 0.1057233570 0.433294201 4.609824e-01
## 902 0.0759738097 0.288980799 6.350454e-01
## 903 0.0076090667 0.110693417 8.816975e-01
## 904 0.1243465945 0.501115459 3.745379e-01
## 905 0.0412920664 0.407264961 5.514430e-01
## 906 0.0054254846 0.127155696 8.674188e-01
## 907 0.0210883759 0.297641982 6.812696e-01
## 908 0.0036272856 0.055413115 9.409596e-01
## 909 0.1146754301 0.553258666 3.320659e-01
## 910 0.0068639253 0.093281180 8.998549e-01
## 911 0.0045482724 0.059866029 9.355857e-01
## 912 0.0108657216 0.121384338 8.677499e-01
## 913 0.0058068391 0.092469166 9.017240e-01
## 914 0.0078637623 0.108981733 8.831545e-01
## 915 0.0017230239 0.035597784 9.626792e-01
## 916 0.0573551526 0.357394814 5.852500e-01
## 917 0.0061182890 0.085861888 9.080198e-01
## 918 0.0069728034 0.107096809 8.859304e-01
## 919 0.0017655123 0.056038788 9.421957e-01
## 920 0.2263180847 0.568030555 2.056514e-01
## 921 0.0132368269 0.231698387 7.550648e-01
## 922 0.0903765439 0.342500962 5.671225e-01
## 923 0.0046334787 0.068324474 9.270420e-01
## 924 0.0100116754 0.129584939 8.604034e-01
## 925 0.0058416203 0.086951387 9.072070e-01
## 926 0.0121101591 0.129245173 8.586447e-01
## 927 0.0113614614 0.171454207 8.171843e-01
## 928 0.4547381476 0.419403309 1.258585e-01
## 929 0.0085059349 0.096512675 8.949814e-01
## 930 0.0093663639 0.104624254 8.860094e-01
## 931 0.0436018997 0.328836870 6.275612e-01
## 932 0.0900512637 0.306190153 6.037586e-01
## 933 0.1141438423 0.515708769 3.701474e-01
## 934 0.3206249904 0.548015149 1.313599e-01
## 935 0.1673104595 0.537217626 2.954719e-01
## 936 0.0051605841 0.063672390 9.311670e-01
## 937 0.0071449519 0.111622094 8.812330e-01
## 938 0.7564343894 0.219180153 2.438546e-02
## 939 0.0098888218 0.123504745 8.666064e-01
## 940 0.0033706843 0.049524818 9.471045e-01
## 941 0.2285460856 0.486343239 2.851107e-01
## 942 0.0045493387 0.093179266 9.022714e-01
## 943 0.6225957015 0.324681430 5.272287e-02
## 944 0.1389685572 0.604352816 2.566786e-01
## 945 0.4654232602 0.346056002 1.885207e-01
## 946 0.2781426572 0.486200730 2.356566e-01
## 947 0.0787498050 0.506953693 4.142965e-01
## 948 0.1502072606 0.573983007 2.758097e-01
## 949 0.0122055426 0.134112863 8.536816e-01
## 950 0.0081979123 0.123910993 8.678911e-01
## 951 0.0082448737 0.105605556 8.861496e-01
##
## $centroids
## Low Mid High
## FP001 -0.0495405931 0.1090290057 -0.0402546696
## FP002 0.2801751471 0.0165849639 -0.5158851975
## FP003 0.0078563015 -0.0035344404 -0.0097692701
## FP004 -0.0648109761 0.0684055754 0.0345041865
## FP005 0.2731140521 0.0216957451 -0.5093759174
## FP006 -0.1627379211 0.0693435844 0.2069081240
## FP007 0.0323329262 0.0002701702 -0.0576042226
## FP008 0.1438641781 0.0885286648 -0.3588531791
## FP009 0.3158384274 -0.0956520772 -0.4472758118
## FP010 -0.0936529426 0.0867477394 0.0640672042
## FP011 -0.1402545869 -0.0749100455 0.3364657738
## FP012 -0.0210648464 -0.0740248357 0.1242477922
## FP013 0.3525294156 -0.1899408956 -0.4015634316
## FP014 0.3395684771 -0.1781119853 -0.3924898252
## FP015 -0.1976219622 0.1382642134 0.1877834251
## FP016 0.0304048592 -0.0536234828 0.0090978040
## FP017 0.1365611023 -0.1183641883 -0.1029648357
## FP018 0.1376839830 0.0606487389 -0.3151645388
## FP019 -0.0077540769 0.0051859590 0.0076488151
## FP020 -0.0445786962 0.0443153029 0.0269455293
## FP021 0.0528734620 0.0734215166 -0.1798973339
## FP022 -0.0034575110 0.1334481845 -0.1505787512
## FP023 0.1102175774 -0.0302887859 -0.1597144362
## FP024 -0.0151339870 0.0129510086 0.0116061288
## FP025 -0.0467668980 0.0691933175 0.0016089486
## FP026 0.0681360502 -0.0102618675 -0.1086721367
## FP027 -0.1084091383 0.1346528946 0.0339582277
## FP028 -0.0330410659 -0.1267310204 0.2073585640
## FP029 0.0266586293 0.1649431170 -0.2409217295
## FP030 -0.0559439365 -0.1028859775 0.2199368984
## FP031 0.0314637892 -0.0284034730 -0.0223935897
## FP032 -0.0755646332 0.0699133333 0.0517868259
## FP033 -0.0611027270 0.0605857939 0.0371165343
## FP034 0.0507211678 0.0831446901 -0.1875016014
## FP035 0.1716134688 -0.1161755654 -0.1676401086
## FP036 -0.1267801812 0.1144709086 0.0902069304
## FP037 0.0724131488 -0.0543467273 -0.0644825340
## FP038 -0.0485162835 0.0075280165 0.0771204331
## FP039 0.1791849894 -0.0689076365 -0.2365607027
## FP040 -0.0851987139 0.0371891979 0.1072834351
## FP041 0.1546156832 -0.0559967849 -0.2081900689
## FP042 -0.0328312333 0.1362865919 -0.1018679207
## FP043 0.0631771150 -0.0248164337 -0.0827949268
## FP044 0.2702579940 -0.1928574044 -0.2523714440
## FP045 0.1143089560 -0.0426731214 -0.1524208750
## FP046 0.1929160057 -0.0096858247 -0.3304317263
## FP047 0.1027777588 0.1095909592 -0.3107898111
## FP048 0.0356271104 0.0416232557 -0.1120006536
## FP049 0.2711896254 -0.1351072812 -0.3218365538
## FP050 0.0885684851 0.0129510086 -0.1721322762
## FP051 0.1147803818 0.0571649374 -0.2704933623
## FP052 -0.0329886307 0.1483569779 -0.1157629852
## FP053 0.2173024748 -0.0907599935 -0.2784360108
## FP054 0.1652161806 -0.0857900077 -0.1919864604
## FP055 -0.0612914912 0.0599380542 0.0382116074
## FP056 0.1722025480 -0.0779685742 -0.2135493009
## FP057 0.0418962454 0.0660613571 -0.1518052317
## FP058 0.0111241582 0.0652418711 -0.0963214318
## FP059 0.1508474447 -0.0229008501 -0.2403772543
## FP060 -0.1341771708 -0.0091344161 0.2484593016
## FP061 -0.0133022161 0.0605785154 -0.0475671103
## FP062 -0.0697598332 0.0940192133 0.0131950681
## FP063 -0.0844748190 0.0819906984 0.0533916184
## FP064 -0.0465534477 0.0082942733 0.0727429162
## FP065 0.3609845772 -0.0491439703 -0.5818783024
## FP066 -0.0020183790 0.0101564044 -0.0083502682
## FP067 -0.0390175320 0.1060565259 -0.0554087580
## FP068 -0.0314512908 0.0634456422 -0.0187776580
## FP069 0.0416191755 -0.0247553163 -0.0446706780
## FP070 0.3288123264 -0.1371141337 -0.4215749524
## FP071 0.2861990861 -0.0944636164 -0.3961568727
## FP072 -0.2569932801 0.0797788596 0.3616544123
## FP073 -0.1389273057 -0.0136400374 0.2621663490
## FP074 -0.0486850322 0.0003568214 0.0858403664
## FP075 -0.0721072545 0.0834268735 0.0297925000
## FP076 0.4980955784 -0.2395438143 -0.6012278529
## FP077 0.0704821182 -0.0133349977 -0.1092201665
## FP078 0.0215714109 0.0998150277 -0.1554300635
## FP079 0.3463924370 -0.0474390705 -0.5580261977
## FP080 -0.0576264944 -0.0361518893 0.1445539328
## FP081 0.0783892425 -0.0540315582 -0.0754409775
## FP082 0.3373451696 -0.0707897921 -0.5145762500
## FP083 -0.1404314343 0.1872327477 0.0289516799
## FP084 -0.0317427006 0.0395285466 0.0098238775
## FP085 0.3053242542 -0.0835028923 -0.4429134357
## FP086 0.1058401125 -0.0810658241 -0.0923323645
## FP087 0.3032336017 -0.0208304868 -0.5128038180
## FP088 -0.1076777168 -0.0272410686 0.2227701556
## FP089 0.4204845046 -0.2368909117 -0.4668330103
## FP090 0.1059896126 -0.0124660380 -0.1731521819
## FP091 0.0051218023 0.0703430122 -0.0916766890
## FP092 0.3533487291 -0.1154490775 -0.4904888730
## FP093 0.1680405172 -0.0743315310 -0.2104459650
## FP094 0.0012198879 0.0295818332 -0.0368985516
## FP095 -0.0443233642 -0.0187168372 0.1005101304
## FP096 0.0513720002 0.0376624814 -0.1352461674
## FP097 0.2946913976 -0.1136762166 -0.3886425621
## FP098 -0.0576001198 0.0559791424 0.0363201404
## FP099 0.1732751361 -0.0276281220 -0.2745631725
## FP100 -0.0709402757 0.1217091201 -0.0172289761
## FP101 -0.0331847631 0.0502275852 -0.0001847002
## FP102 0.1329019255 -0.0187898594 -0.2134090953
## FP103 0.1223512151 -0.0162067364 -0.1977488069
## FP104 0.1057946875 0.0247158032 -0.2164684807
## FP105 0.1648155476 -0.0687444345 -0.2112927961
## FP106 0.0909285109 0.0434537458 -0.2121322996
## FP107 0.2794970133 -0.0848941402 -0.3955194316
## FP108 -0.0032188400 0.0259943560 -0.0248214028
## FP109 0.1016843506 0.0648812786 -0.2563511185
## FP110 -0.0694634130 0.0844639572 0.0238903629
## FP111 0.0237735643 0.1186459584 -0.1814444738
## FP112 0.3898869206 -0.2145986455 -0.4387979187
## FP113 -0.0797493581 -0.0120216185 0.1554153277
## FP114 0.0616511082 0.0872740433 -0.2117160889
## FP115 0.0285282062 0.0590950802 -0.1199396337
## FP116 -0.0306812229 0.0227790312 0.0276116861
## FP117 0.1079459529 -0.0054277915 -0.1848832236
## FP118 -0.0544320109 -0.0847289524 0.1959367726
## FP119 -0.0227834972 0.1422316930 -0.1266515179
## FP120 -0.0562343635 -0.0760781283 0.1889717158
## FP121 0.1166372655 -0.0466198703 -0.1519115730
## FP122 0.0060417352 -0.0231058378 0.0164279301
## FP123 0.1543668524 -0.0503089341 -0.2144282889
## FP124 -0.0326977684 0.0304138148 0.0222192427
## FP125 -0.0287478846 0.0288181575 0.0170946396
## FP126 -0.0020362867 0.0997908993 -0.1135739836
## FP127 -0.0655783019 0.1570342255 -0.0682105846
## FP128 -0.0613171651 0.0799142325 0.0147995920
## FP129 0.1268166278 -0.0539427273 -0.1613481670
## FP130 0.0694377724 0.0027845060 -0.1262985229
## FP131 0.0078940912 0.0881740094 -0.1175270607
## FP132 -0.1233145899 0.1130150563 0.0857762197
## FP133 -0.0203022685 -0.0075491446 0.0448360024
## FP134 0.1030500971 0.0635114509 -0.2571623738
## FP135 0.0078940912 -0.0394568627 0.0323465360
## FP136 -0.0117387541 0.0084287810 0.0109008422
## FP137 0.0922870893 -0.0301900697 -0.1280613999
## FP138 0.0773966331 -0.0958798158 -0.0245409729
## FP139 0.0339332602 0.0616344765 -0.1324981700
## FP140 -0.0564832745 0.1061227303 -0.0245409729
## FP141 0.1251015502 0.0546494492 -0.2858263736
## FP142 0.0322795178 -0.0786315376 0.0351426184
## FP143 0.0465668058 0.0399569321 -0.1294267131
## FP144 -0.0801030339 -0.0978425453 0.2568192356
## FP145 -0.0494448247 -0.0053262534 0.0938600409
## FP146 0.2078579157 -0.0948259367 -0.2569277589
## FP147 -0.0221295790 -0.0087288211 0.0494588655
## FP148 -0.0353880639 0.0037631561 0.0582810378
## FP149 0.2479928432 -0.1304327537 -0.2862260363
## FP150 -0.0145471113 0.0220318460 -0.0000970785
## FP151 -0.0183362123 0.1112803629 -0.0981858093
## FP152 0.0595244818 0.0873764120 -0.2080683748
## FP153 0.0766659123 -0.0266454363 -0.1045464153
## FP155 0.1875792705 -0.0922815457 -0.2239861869
## FP156 0.0815597691 0.0422583899 -0.1941292354
## FP157 0.0146415528 -0.0520809231 0.0352155942
## FP158 -0.0716815461 0.0599380542 0.0566205429
## FP159 0.0724131488 0.0974613140 -0.2427467484
## FP160 0.0075591303 0.1771453798 -0.2214103367
## FP161 -0.1721041991 -0.0248164337 0.3340727957
## FP162 0.2505609080 0.0341822504 -0.4840791892
## FP163 -0.0721622323 0.1145245134 -0.0066272370
## FP164 0.3096358948 -0.0047938109 -0.5429787494
## FP165 -0.0347078579 0.0830010210 -0.0359710938
## FP166 0.1669255120 -0.0130428989 -0.2804400550
## FP167 -0.0403232212 0.0613393521 -0.0005851502
## FP168 0.3362987807 -0.0102489808 -0.5838137668
## FP169 0.3279270138 -0.1785070432 -0.3713997580
## FP170 0.1173359826 -0.0644986000 -0.1321550239
## FP171 -0.0954292679 0.0196768916 0.1459740128
## FP172 0.3613894991 -0.2152947986 -0.3874891624
## FP173 0.1501296828 -0.0928300965 -0.1569894492
## FP174 0.0787146283 0.0115359455 -0.1530116964
## FP175 0.0104786270 0.0508047221 -0.0782245232
## FP176 -0.0006016742 0.0051859590 -0.0050236991
## FP177 0.0241569215 0.0842536392 -0.1417376987
## FP178 0.1246648132 -0.0024033416 -0.2180569691
## FP179 0.0649559914 0.0157532634 -0.1335866467
## FP180 -0.0589874279 0.0644474092 0.0288340867
## FP181 0.2012291565 -0.0543820416 -0.2926752367
## FP182 -0.0329874939 -0.0115099253 0.0719625259
## FP183 -0.0648415590 0.0610679976 0.0431746986
## FP184 0.2620896976 -0.1502219661 -0.2879646659
## FP185 0.1478416830 -0.0645777255 -0.1861116278
## FP186 -0.0244176229 0.0302019039 0.0077974530
## FP187 0.0091940870 -0.0617169270 0.0561826357
## FP188 -0.0759229295 0.0371891979 0.0908487465
## FP189 0.0810931354 -0.0228641665 -0.1168307455
## FP190 0.2167299638 -0.1161755654 -0.2475768030
## FP191 -0.0190530545 0.0008561968 0.0327524921
## FP192 0.0876178438 -0.0481068672 -0.0987492774
## FP193 0.2572219829 -0.1692052693 -0.2570485290
## FP194 -0.0213184372 0.1250513647 -0.1090728778
## FP195 -0.1471268054 0.1437464230 0.0918792871
## FP196 0.2099093138 -0.1231441547 -0.2273090506
## FP197 0.1945447303 -0.1721512518 -0.1425385709
## FP198 -0.0834021806 -0.1078835226 0.2744554689
## FP201 -0.0676456763 0.0493857448 0.0618611536
## FP202 0.1551879684 -0.0073284227 -0.2663540202
## FP203 0.0077804344 0.0616813081 -0.0862159987
## FP204 0.1003397095 0.0239904172 -0.2059516350
## FP205 0.1640452059 -0.0530136047 -0.2284002190
## FP206 0.1026221365 0.0154417343 -0.1999571083
## FP207 0.2099093138 -0.1231441547 -0.2273090506
## FP208 0.0144952907 0.0576566680 -0.0933872455
## MolWeight 0.6447051156 -0.2055105795 -0.9009526572
## NumBonds 0.5260886575 -0.2189290955 -0.6750328744
## NumMultBonds 0.4454402105 -0.1400358395 -0.6247835158
## NumRotBonds 0.2155583753 -0.0940739960 -0.2714542962
## NumDblBonds 0.0721770001 0.0706866433 -0.2108875482
## NumCarbon 0.6263248530 -0.2418993837 -0.8256563760
## NumNitrogen -0.0297685707 0.0922561549 -0.0555905068
## NumOxygen -0.0340683964 -0.0050668663 0.0663117361
## NumSulfer 0.1197176427 0.0258929341 -0.2425192273
## NumChlorine 0.3118792000 -0.1802282100 -0.3409453733
## NumHalogen 0.3385012880 -0.1813798078 -0.3867616779
## NumRings 0.4841073403 -0.2058863239 -0.6159668242
## HydrophilicFactor -0.2459914879 0.0447577535 0.3832859796
## SurfaceArea1 -0.0922543563 0.0548152435 0.0990867063
## SurfaceArea2 -0.0416827432 0.0439322001 0.0222643930
## attr(,"scaled:scale")
## y
## Low Mid High
## 427 283 241
##
## $centroid.overall
## FP001 FP002 FP003 FP004
## -4.705437e-16 -1.402958e-15 1.934217e-16 2.294172e-16
## FP005 FP006 FP007 FP008
## -6.214647e-16 9.907439e-16 5.334275e-17 -1.159012e-15
## FP009 FP010 FP011 FP012
## -4.640385e-17 6.791442e-16 1.633242e-15 -3.239596e-16
## FP013 FP014 FP015 FP016
## -3.102553e-15 1.393091e-15 9.418464e-16 1.322727e-16
## FP017 FP018 FP019 FP020
## -1.041810e-15 7.349807e-16 -8.597723e-17 3.003240e-17
## FP021 FP022 FP023 FP024
## -6.719343e-16 -5.159718e-16 7.218618e-16 1.539567e-16
## FP025 FP026 FP027 FP028
## 9.313297e-17 3.960591e-16 1.052652e-15 2.733274e-16
## FP029 FP030 FP031 FP032
## 1.552578e-16 -4.375840e-16 1.444157e-16 4.408366e-16
## FP033 FP034 FP035 FP036
## -1.088539e-16 -5.599904e-16 -7.623025e-16 -5.889386e-16
## FP037 FP038 FP039 FP040
## -3.302480e-16 -3.339343e-17 1.650589e-15 -4.930951e-16
## FP041 FP042 FP043 FP044
## -4.605691e-16 -2.959872e-17 -2.311519e-16 2.242997e-15
## FP045 FP046 FP047 FP048
## -5.824334e-16 6.767590e-16 -1.168770e-15 -3.003240e-17
## FP049 FP050 FP051 FP052
## 1.516040e-15 2.675811e-16 1.824929e-15 -4.484260e-16
## FP053 FP054 FP055 FP056
## 3.544474e-15 -5.811324e-16 -3.388132e-16 2.480546e-15
## FP057 FP058 FP059 FP060
## 3.263449e-17 9.096456e-17 9.394612e-16 -1.858323e-16
## FP061 FP062 FP063 FP064
## -4.835542e-17 4.475587e-16 -6.871673e-16 2.346214e-16
## FP065 FP066 FP067 FP068
## -1.193056e-15 1.216475e-16 1.830133e-16 5.702903e-17
## FP069 FP070 FP071 FP072
## 1.463673e-16 -2.798326e-15 -4.059253e-16 2.845814e-15
## FP073 FP074 FP075 FP076
## -1.244881e-15 4.247904e-16 3.881444e-17 2.500387e-15
## FP077 FP078 FP079 FP080
## 1.773755e-16 -2.452465e-16 2.216543e-15 -9.141993e-16
## FP081 FP082 FP083 FP084
## -1.537399e-16 2.721564e-15 -1.080082e-15 1.494031e-16
## FP085 FP086 FP087 FP088
## 2.658247e-15 -4.772658e-16 3.205335e-15 -6.761085e-16
## FP089 FP090 FP091 FP092
## 3.053981e-15 7.472321e-16 -4.013716e-16 -4.147073e-15
## FP093 FP094 FP095 FP096
## -8.133685e-16 1.071192e-16 2.760379e-16 -7.285839e-17
## FP097 FP098 FP099 FP100
## 1.474515e-16 -1.249001e-16 -1.209753e-15 -4.649059e-16
## FP101 FP102 FP103 FP104
## -4.039737e-16 5.848187e-16 -6.080206e-16 5.551115e-16
## FP105 FP106 FP107 FP108
## -6.364267e-16 -2.515349e-16 3.713176e-15 -1.448494e-16
## FP109 FP110 FP111 FP112
## -4.322714e-16 6.468350e-16 -2.294172e-16 -1.014813e-16
## FP113 FP114 FP115 FP116
## 6.722053e-18 2.267067e-16 -1.387779e-16 -3.538836e-16
## FP117 FP118 FP119 FP120
## 6.713380e-16 3.703635e-16 -1.642566e-16 7.003946e-16
## FP121 FP122 FP123 FP124
## -7.920097e-16 2.466560e-16 1.104694e-15 -2.550044e-16
## FP125 FP126 FP127 FP128
## 1.130823e-16 3.947580e-16 -1.943974e-16 3.726403e-16
## FP129 FP130 FP131 FP132
## 1.116837e-15 -3.095397e-16 -2.568475e-16 4.252241e-16
## FP133 FP134 FP135 FP136
## -2.671474e-16 -5.940344e-16 -9.757820e-19 -4.542807e-17
## FP137 FP138 FP139 FP140
## -4.975404e-16 4.098284e-16 9.028151e-16 3.577867e-16
## FP141 FP142 FP143 FP144
## 1.451421e-15 9.887924e-17 4.093947e-16 -8.455693e-16
## FP145 FP146 FP147 FP148
## -6.356677e-16 4.588344e-16 1.076613e-16 5.798313e-16
## FP149 FP150 FP151 FP152
## 1.992330e-15 -2.093594e-16 -4.627375e-16 7.657720e-16
## FP153 FP155 FP156 FP157
## -8.464366e-16 1.667937e-15 -1.018716e-15 2.547875e-17
## FP158 FP159 FP160 FP161
## -7.200187e-16 -1.192189e-15 -5.867702e-16 1.204332e-15
## FP162 FP163 FP164 FP165
## -2.772522e-15 -7.411606e-16 2.926045e-15 8.131516e-17
## FP166 FP167 FP168 FP169
## -2.318024e-16 7.153566e-16 -7.216450e-16 7.600257e-16
## FP170 FP171 FP172 FP173
## -7.988402e-16 -3.946496e-17 -4.204644e-15 -1.724207e-15
## FP174 FP175 FP176 FP177
## 2.221530e-16 1.591609e-16 -1.883259e-16 -3.477036e-16
## FP178 FP179 FP180 FP181
## -8.611818e-16 9.161508e-17 -4.895173e-16 2.442057e-15
## FP182 FP183 FP184 FP185
## 3.569194e-16 -5.906733e-16 8.999962e-16 3.469447e-17
## FP186 FP187 FP188 FP189
## 1.147086e-16 2.629190e-16 -3.100818e-16 4.855057e-16
## FP190 FP191 FP192 FP193
## -1.207259e-15 1.779176e-16 3.508478e-16 1.484815e-15
## FP194 FP195 FP196 FP197
## 3.686287e-18 3.113829e-16 -5.020940e-16 -4.578586e-16
## FP198 FP201 FP202 FP203
## 5.053466e-16 -3.663519e-16 2.016616e-17 -7.578573e-17
## FP204 FP205 FP206 FP207
## 3.733992e-16 8.880700e-16 -9.029236e-16 -1.758034e-15
## FP208 MolWeight NumBonds NumMultBonds
## 1.240327e-16 -2.558717e-17 -1.849595e-15 8.025264e-16
## NumRotBonds NumDblBonds NumCarbon NumNitrogen
## 3.115455e-16 -1.962406e-16 -4.016969e-16 -2.404760e-16
## NumOxygen NumSulfer NumChlorine NumHalogen
## 1.578056e-16 -7.041893e-16 -2.754199e-15 -1.854203e-15
## NumRings HydrophilicFactor SurfaceArea1 SurfaceArea2
## -8.287641e-16 5.627009e-17 2.384161e-16 -1.447410e-16
##
## $sd
## FP001 FP002 FP003 FP004
## 1.993552 1.943195 1.996058 1.994291
## FP005 FP006 FP007 FP008
## 1.944985 1.983901 1.995429 1.973659
## FP009 FP010 FP011 FP012
## 1.945605 1.992463 1.976252 1.993205
## FP013 FP014 FP015 FP016
## 1.940743 1.944527 1.979840 1.995439
## FP017 FP018 FP019 FP020
## 1.988426 1.978506 1.996061 1.995254
## FP021 FP022 FP023 FP024
## 1.990529 1.990534 1.989959 1.995992
## FP025 FP026 FP027 FP028
## 1.994879 1.993523 1.990577 1.987953
## FP029 FP030 FP031 FP032
## 1.984432 1.987626 1.995679 1.993729
## FP033 FP034 FP035 FP036
## 1.994523 1.989994 1.983804 1.989461
## FP037 FP038 FP039 FP040
## 1.993936 1.994792 1.980934 1.992780
## FP041 FP042 FP043 FP044
## 1.984672 1.991747 1.994224 1.965555
## FP045 FP046 FP047 FP048
## 1.989906 1.973582 1.979517 1.993947
## FP049 FP050 FP051 FP052
## 1.963124 1.990519 1.983262 1.990844
## FP053 FP054 FP055 FP056
## 1.974150 1.984096 1.994519 1.982627
## FP057 FP058 FP059 FP060
## 1.992106 1.994244 1.983472 1.984113
## FP061 FP062 FP063 FP064
## 1.995211 1.993648 1.993112 1.994916
## FP065 FP066 FP067 FP068
## 1.920569 1.996061 1.993674 1.995218
## FP069 FP070 FP071 FP072
## 1.995351 1.945094 1.955581 1.963128
## FP073 FP074 FP075 FP076
## 1.982902 1.994616 1.993763 1.878964
## FP077 FP078 FP079 FP080
## 1.993424 1.991417 1.926821 1.992484
## FP081 FP082 FP083 FP084
## 1.993542 1.934202 1.986268 1.995614
## FP085 FP086 FP087 FP088
## 1.948010 1.991493 1.940395 1.987025
## FP089 FP090 FP091 FP092
## 1.917158 1.989708 1.994274 1.933506
## FP093 FP094 FP095 FP096
## 1.983203 1.995782 1.994307 1.992953
## FP097 FP098 FP099 FP100
## 1.954583 1.994704 1.979508 1.992702
## FP101 FP102 FP103 FP104
## 1.995462 1.986228 1.987678 1.987490
## FP105 FP106 FP107 FP108
## 1.983523 1.988199 1.956802 1.995905
## FP109 FP110 FP111 FP112
## 1.984723 1.993862 1.989659 1.928276
## FP113 FP114 FP115 FP116
## 1.991556 1.988374 1.993552 1.995700
## FP117 FP118 FP119 FP120
## 1.989095 1.989452 1.990903 1.989958
## FP121 FP122 FP123 FP124
## 1.989751 1.995964 1.984442 1.995645
## FP125 FP126 FP127 FP128
## 1.995739 1.992958 1.990837 1.994258
## FP129 FP130 FP131 FP132
## 1.988701 1.992970 1.993155 1.989807
## FP133 FP134 FP135 FP136
## 1.995729 1.984633 1.995707 1.996029
## FP137 FP138 FP139 FP140
## 1.991943 1.993287 1.993027 1.993610
## FP141 FP142 FP143 FP144
## 1.981642 1.994772 1.993229 1.984776
## FP145 FP146 FP147 FP148
## 1.994412 1.976451 1.995654 1.995371
## FP149 FP150 FP151 FP152
## 1.968943 1.995966 1.992935 1.988626
## FP153 FP155 FP156 FP157
## 1.993266 1.980407 1.989516 1.995476
## FP158 FP159 FP160 FP161
## 1.993985 1.985957 1.985109 1.974936
## FP162 FP163 FP164 FP165
## 1.951019 1.992948 1.935228 1.994622
## FP166 FP167 FP168 FP169
## 1.979671 1.995159 1.924811 1.948496
## FP170 FP171 FP172 FP173
## 1.990133 1.991262 1.939106 1.986556
## FP174 FP175 FP176 FP177
## 1.991690 1.994899 1.996079 1.992338
## FP178 FP179 FP180 FP181
## 1.986505 1.992829 1.994577 1.975446
## FP182 FP183 FP184 FP185
## 1.995163 1.994346 1.966295 1.986099
## FP186 FP187 FP188 FP189
## 1.995808 1.995098 1.993532 1.992790
## FP190 FP191 FP192 FP193
## 1.975512 1.995868 1.992770 1.968153
## FP194 FP195 FP196 FP197
## 1.992134 1.987022 1.977173 1.980451
## FP198 FP201 FP202 FP203
## 1.983137 1.994205 1.981546 1.994560
## FP204 FP205 FP206 FP207
## 1.988319 1.982902 1.988576 1.977173
## FP208 MolWeight NumBonds NumMultBonds
## 1.994434 1.766998 1.859496 1.893724
## NumRotBonds NumDblBonds NumCarbon NumNitrogen
## 1.974729 1.988493 1.791678 1.994223
## NumOxygen NumSulfer NumChlorine NumHalogen
## 1.995262 1.985235 1.953703 1.945111
## NumRings HydrophilicFactor SurfaceArea1 SurfaceArea2
## 1.882410 1.962972 1.992470 1.995344
##
## $threshold
## [1] 1
##
## $nonzero
## [1] 159
##
## $threshold.scale
## Low Mid High
## 1 1 1
##
## $se.scale
## y
## Low Mid High
## 0.03592208 0.04982012 0.05565836
##
## $scale.sd
## [1] TRUE
##
## $call
## pamr::pamr.train(data = list(x = t(x), y = y), threshold = param$threshold)
##
## $hetero
## NULL
##
## $norm.cent
## NULL
##
## $prior
##
## Low Mid High
## 0.4490011 0.2975815 0.2534175
##
## $offset
## 50%
## 0.9950317
##
## $sign.contrast
## [1] "both"
##
## $errors
## [1] 368
##
## $gene.subset
## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
## [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
## [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
## [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108
## [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
## [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
## [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
## [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180
## [181] 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198
## [199] 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216
## [217] 217 218 219 220
##
## $sample.subset
## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
## [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
## [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
## [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108
## [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
## [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
## [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
## [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180
## [181] 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198
## [199] 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216
## [217] 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234
## [235] 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252
## [253] 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270
## [271] 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288
## [289] 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306
## [307] 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324
## [325] 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342
## [343] 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360
## [361] 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378
## [379] 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396
## [397] 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414
## [415] 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432
## [433] 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450
## [451] 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468
## [469] 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486
## [487] 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504
## [505] 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522
## [523] 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540
## [541] 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558
## [559] 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576
## [577] 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594
## [595] 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612
## [613] 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630
## [631] 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648
## [649] 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666
## [667] 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684
## [685] 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702
## [703] 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720
## [721] 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738
## [739] 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756
## [757] 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774
## [775] 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792
## [793] 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810
## [811] 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828
## [829] 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846
## [847] 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864
## [865] 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882
## [883] 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900
## [901] 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918
## [919] 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936
## [937] 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951
##
## $ngroup.survival
## [1] 2
##
## $problem.type
## [1] "class"
##
## $xData
## FP001 FP002 FP003 FP004 FP005 FP006
## X1 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X2 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X3 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X4 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X5 -0.9859036 -1.0816660 1.1358733 0.8424278 0.8515806 1.2224933
## X6 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X7 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X8 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X9 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X10 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X11 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X12 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X13 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X14 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X15 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X16 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X17 1.0132314 -1.0816660 1.1358733 0.8424278 0.8515806 1.2224933
## X18 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X19 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X20 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X21 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X22 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X23 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X24 1.0132314 -1.0816660 -0.8794541 0.8424278 -1.1730522 1.2224933
## X25 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X26 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X27 -0.9859036 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X28 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X29 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X30 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X31 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X32 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X33 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X34 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X35 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X36 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X37 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X38 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X39 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X40 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X41 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X42 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X43 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X44 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X45 -0.9859036 -1.0816660 1.1358733 -1.1857971 0.8515806 1.2224933
## X46 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X47 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X48 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X49 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X50 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X51 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X52 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X53 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X54 -0.9859036 -1.0816660 1.1358733 -1.1857971 0.8515806 1.2224933
## X55 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X56 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X57 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X58 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X59 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X60 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X61 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X62 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X63 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X64 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X65 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X66 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 1.2224933
## X67 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X68 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X69 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X70 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X71 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X72 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X73 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X74 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X75 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X76 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X77 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X78 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X79 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X80 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X81 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X82 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X83 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X84 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X85 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X86 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X87 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X88 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X89 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X90 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X91 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X92 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X93 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X94 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X95 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X96 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X97 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X98 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X99 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X100 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X101 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X102 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X103 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X104 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X105 1.0132314 -1.0816660 -0.8794541 0.8424278 -1.1730522 -0.8171403
## X106 -0.9859036 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X107 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X108 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X109 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X110 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X111 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X112 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X113 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X114 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X115 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X116 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X117 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 1.2224933
## X118 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X119 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X120 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X121 -0.9859036 -1.0816660 -0.8794541 0.8424278 -1.1730522 -0.8171403
## X122 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X123 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X124 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X125 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X126 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X127 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X128 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X129 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X130 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X131 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X132 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X133 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X134 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X135 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X136 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X137 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X138 -0.9859036 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X139 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X140 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X141 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X142 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X143 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X144 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X145 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X146 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X147 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X148 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X149 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X150 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X151 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X152 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X153 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X154 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X155 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X156 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X157 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X158 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X159 -0.9859036 -1.0816660 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X160 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X161 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X162 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X163 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X164 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X165 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X166 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X167 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X168 -0.9859036 -1.0816660 1.1358733 0.8424278 0.8515806 1.2224933
## X169 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X170 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X171 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X172 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X173 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X174 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X175 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X176 -0.9859036 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X177 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X178 -0.9859036 -1.0816660 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X179 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X180 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 1.2224933
## X181 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X182 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X183 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X184 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X185 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X186 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X187 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X188 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X189 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X190 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X191 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X192 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X193 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X194 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X195 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X196 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X197 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X198 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X199 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X200 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X201 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X202 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X203 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X204 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X205 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 1.2224933
## X206 -0.9859036 -1.0816660 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X207 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X208 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X209 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X210 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X211 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X212 -0.9859036 -1.0816660 -0.8794541 0.8424278 -1.1730522 -0.8171403
## X213 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X214 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X215 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X216 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X217 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X218 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X219 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X220 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X221 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 1.2224933
## X222 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X223 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X224 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X225 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X226 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X227 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X228 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X229 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X230 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X231 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X232 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X233 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X234 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X235 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X236 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X237 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X238 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X239 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X240 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X241 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X242 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X243 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X244 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X245 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X246 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X247 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X248 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X249 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X250 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X251 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X252 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X253 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X254 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X255 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X256 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X257 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X258 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X259 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X260 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X261 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X262 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X263 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X264 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X265 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X266 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X267 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X268 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X269 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X270 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X271 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X272 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X273 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X274 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X275 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X276 1.0132314 -1.0816660 -0.8794541 0.8424278 0.8515806 1.2224933
## X277 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X278 1.0132314 -1.0816660 -0.8794541 0.8424278 0.8515806 1.2224933
## X279 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X280 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X281 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X282 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X283 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X284 -0.9859036 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X285 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X286 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X287 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X288 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X289 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X290 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X291 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X292 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X293 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X294 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X295 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X296 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X297 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X298 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X299 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X300 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 1.2224933
## X301 -0.9859036 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X302 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X303 -0.9859036 -1.0816660 1.1358733 0.8424278 0.8515806 1.2224933
## X304 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X305 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X306 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X307 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X308 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X309 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X310 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X311 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X312 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X313 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X314 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X315 -0.9859036 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X316 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X317 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X318 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X319 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X320 -0.9859036 -1.0816660 1.1358733 -1.1857971 0.8515806 1.2224933
## X321 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X322 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X323 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X324 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X325 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X326 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X327 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X328 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X329 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X330 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X331 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X332 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X333 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X334 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X335 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X336 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X337 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X338 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X339 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X340 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X341 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X342 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X343 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X344 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X345 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X346 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X347 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X348 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X349 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X350 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X351 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X352 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X353 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X354 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X355 1.0132314 -1.0816660 -0.8794541 0.8424278 -1.1730522 -0.8171403
## X356 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X357 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X358 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X359 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X360 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X361 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X362 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X363 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X364 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X365 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X366 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X367 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X368 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X369 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X370 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X371 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X372 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X373 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X374 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X375 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X376 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X377 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X378 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X379 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X380 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X381 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X382 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X383 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X384 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X385 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X386 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X387 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X388 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X389 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X390 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X391 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X392 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X393 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X394 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X395 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X396 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X397 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 1.2224933
## X398 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 1.2224933
## X399 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X400 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X401 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 1.2224933
## X402 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X403 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X404 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X405 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X406 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X407 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X408 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X409 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X410 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X411 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X412 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X413 1.0132314 -1.0816660 -0.8794541 0.8424278 0.8515806 1.2224933
## X414 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 1.2224933
## X415 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X416 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X417 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X418 -0.9859036 0.9235277 1.1358733 -1.1857971 0.8515806 -0.8171403
## X419 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X420 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X421 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X422 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X423 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X424 1.0132314 -1.0816660 1.1358733 0.8424278 0.8515806 1.2224933
## X425 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X426 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X427 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X428 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X429 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X430 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X431 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X432 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X433 -0.9859036 -1.0816660 -0.8794541 -1.1857971 -1.1730522 -0.8171403
## X434 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X435 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X436 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X437 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X438 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X439 -0.9859036 -1.0816660 1.1358733 -1.1857971 -1.1730522 -0.8171403
## X440 -0.9859036 0.9235277 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X441 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## X442 -0.9859036 0.9235277 -0.8794541 0.8424278 0.8515806 1.2224933
## X443 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X444 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 1.2224933
## X445 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X446 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 1.2224933
## X447 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X448 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X449 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X450 -0.9859036 -1.0816660 -0.8794541 -1.1857971 0.8515806 -0.8171403
## X451 1.0132314 -1.0816660 1.1358733 0.8424278 -1.1730522 -0.8171403
## X452 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X453 1.0132314 0.9235277 -0.8794541 0.8424278 0.8515806 -0.8171403
## X454 1.0132314 0.9235277 1.1358733 0.8424278 0.8515806 -0.8171403
## FP007 FP008 FP009 FP010 FP011 FP012
## X1 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X2 1.3216339 1.4372083 -0.6228265 -0.4663054 1.9125675 -0.462962
## X3 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X4 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X5 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X6 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X7 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X8 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X9 1.3216339 -0.6950617 1.6038953 -0.4663054 1.9125675 -0.462962
## X10 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X11 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X12 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X13 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X14 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X15 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X16 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X17 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X18 1.3216339 -0.6950617 1.6038953 -0.4663054 1.9125675 -0.462962
## X19 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X20 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X21 -0.7558435 1.4372083 1.6038953 -0.4663054 1.9125675 2.157733
## X22 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X23 1.3216339 1.4372083 1.6038953 -0.4663054 -0.5223076 2.157733
## X24 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X25 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X26 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X27 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X28 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X29 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X30 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X31 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X32 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X33 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X34 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X35 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X36 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X37 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X38 1.3216339 -0.6950617 -0.6228265 2.1422621 1.9125675 -0.462962
## X39 1.3216339 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X40 -0.7558435 1.4372083 1.6038953 2.1422621 -0.5223076 -0.462962
## X41 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 2.157733
## X42 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X43 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X44 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X45 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X46 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X47 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X48 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X49 -0.7558435 -0.6950617 1.6038953 2.1422621 -0.5223076 -0.462962
## X50 -0.7558435 1.4372083 1.6038953 2.1422621 -0.5223076 -0.462962
## X51 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X52 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X53 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X54 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X55 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X56 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X57 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X58 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X59 1.3216339 1.4372083 1.6038953 -0.4663054 -0.5223076 2.157733
## X60 -0.7558435 1.4372083 1.6038953 2.1422621 -0.5223076 -0.462962
## X61 1.3216339 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X62 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X63 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X64 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X65 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X66 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X67 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X68 1.3216339 -0.6950617 1.6038953 -0.4663054 1.9125675 2.157733
## X69 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X70 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X71 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X72 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X73 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X74 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X75 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X76 1.3216339 -0.6950617 1.6038953 -0.4663054 1.9125675 2.157733
## X77 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X78 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X79 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X80 -0.7558435 1.4372083 1.6038953 -0.4663054 1.9125675 2.157733
## X81 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X82 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X83 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X84 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X85 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X86 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X87 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X88 1.3216339 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X89 1.3216339 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X90 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X91 1.3216339 -0.6950617 -0.6228265 2.1422621 1.9125675 -0.462962
## X92 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X93 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X94 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X95 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X96 -0.7558435 1.4372083 1.6038953 2.1422621 1.9125675 -0.462962
## X97 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X98 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X99 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X100 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X101 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X102 1.3216339 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X103 1.3216339 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X104 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X105 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X106 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 2.157733
## X107 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X108 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 2.157733
## X109 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X110 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X111 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X112 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X113 1.3216339 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X114 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X115 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X116 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X117 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X118 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X119 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X120 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X121 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X122 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X123 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 2.157733
## X124 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X125 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X126 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X127 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X128 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X129 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X130 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X131 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X132 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X133 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X134 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X135 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X136 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X137 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X138 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 2.157733
## X139 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X140 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X141 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X142 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X143 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X144 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X145 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X146 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X147 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X148 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X149 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X150 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X151 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X152 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X153 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X154 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X155 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X156 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X157 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X158 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X159 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X160 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X161 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X162 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X163 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X164 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 2.157733
## X165 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X166 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X167 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X168 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X169 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X170 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X171 1.3216339 -0.6950617 1.6038953 -0.4663054 1.9125675 2.157733
## X172 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X173 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X174 -0.7558435 1.4372083 1.6038953 2.1422621 -0.5223076 -0.462962
## X175 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X176 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X177 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X178 -0.7558435 -0.6950617 1.6038953 2.1422621 -0.5223076 -0.462962
## X179 1.3216339 -0.6950617 -0.6228265 2.1422621 1.9125675 -0.462962
## X180 1.3216339 1.4372083 -0.6228265 2.1422621 1.9125675 -0.462962
## X181 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X182 1.3216339 -0.6950617 1.6038953 -0.4663054 1.9125675 2.157733
## X183 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X184 -0.7558435 1.4372083 1.6038953 -0.4663054 1.9125675 -0.462962
## X185 1.3216339 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X186 1.3216339 1.4372083 1.6038953 -0.4663054 1.9125675 -0.462962
## X187 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X188 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X189 1.3216339 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X190 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X191 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 2.157733
## X192 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X193 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X194 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X195 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X196 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X197 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X198 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X199 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X200 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X201 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X202 1.3216339 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X203 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X204 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 2.157733
## X205 -0.7558435 -0.6950617 1.6038953 -0.4663054 1.9125675 -0.462962
## X206 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X207 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X208 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X209 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X210 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X211 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X212 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X213 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X214 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 2.157733
## X215 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X216 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X217 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X218 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X219 1.3216339 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X220 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X221 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X222 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X223 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X224 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X225 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X226 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X227 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X228 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X229 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X230 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X231 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X232 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X233 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X234 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X235 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X236 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X237 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X238 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X239 -0.7558435 -0.6950617 1.6038953 2.1422621 -0.5223076 -0.462962
## X240 1.3216339 1.4372083 1.6038953 2.1422621 1.9125675 -0.462962
## X241 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X242 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X243 -0.7558435 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X244 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X245 -0.7558435 1.4372083 1.6038953 2.1422621 -0.5223076 -0.462962
## X246 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X247 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X248 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X249 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X250 -0.7558435 1.4372083 1.6038953 2.1422621 -0.5223076 -0.462962
## X251 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X252 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X253 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X254 1.3216339 1.4372083 -0.6228265 -0.4663054 1.9125675 -0.462962
## X255 -0.7558435 -0.6950617 1.6038953 2.1422621 -0.5223076 -0.462962
## X256 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 2.157733
## X257 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X258 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X259 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X260 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X261 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X262 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X263 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X264 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X265 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X266 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X267 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X268 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X269 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X270 1.3216339 1.4372083 -0.6228265 2.1422621 -0.5223076 2.157733
## X271 -0.7558435 1.4372083 1.6038953 2.1422621 -0.5223076 -0.462962
## X272 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 2.157733
## X273 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X274 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X275 1.3216339 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X276 -0.7558435 -0.6950617 1.6038953 2.1422621 -0.5223076 -0.462962
## X277 1.3216339 1.4372083 -0.6228265 -0.4663054 1.9125675 -0.462962
## X278 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X279 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X280 -0.7558435 1.4372083 1.6038953 2.1422621 -0.5223076 -0.462962
## X281 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X282 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X283 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X284 1.3216339 1.4372083 -0.6228265 -0.4663054 1.9125675 -0.462962
## X285 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X286 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X287 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X288 -0.7558435 1.4372083 1.6038953 2.1422621 1.9125675 -0.462962
## X289 -0.7558435 1.4372083 -0.6228265 2.1422621 1.9125675 -0.462962
## X290 -0.7558435 -0.6950617 1.6038953 -0.4663054 1.9125675 -0.462962
## X291 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X292 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X293 -0.7558435 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X294 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X295 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X296 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X297 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X298 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X299 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X300 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X301 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X302 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X303 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X304 -0.7558435 1.4372083 1.6038953 -0.4663054 1.9125675 -0.462962
## X305 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X306 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X307 1.3216339 1.4372083 -0.6228265 -0.4663054 1.9125675 -0.462962
## X308 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X309 1.3216339 1.4372083 -0.6228265 -0.4663054 1.9125675 -0.462962
## X310 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X311 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X312 1.3216339 1.4372083 -0.6228265 2.1422621 1.9125675 -0.462962
## X313 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X314 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X315 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X316 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X317 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X318 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X319 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X320 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X321 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X322 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X323 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X324 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X325 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X326 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X327 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X328 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X329 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X330 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X331 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X332 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X333 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 2.157733
## X334 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 2.157733
## X335 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X336 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X337 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X338 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X339 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X340 -0.7558435 1.4372083 1.6038953 2.1422621 -0.5223076 -0.462962
## X341 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X342 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X343 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X344 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X345 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X346 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X347 1.3216339 -0.6950617 -0.6228265 2.1422621 1.9125675 -0.462962
## X348 1.3216339 1.4372083 -0.6228265 -0.4663054 1.9125675 -0.462962
## X349 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X350 -0.7558435 1.4372083 1.6038953 -0.4663054 1.9125675 -0.462962
## X351 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X352 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X353 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X354 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X355 1.3216339 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X356 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X357 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X358 1.3216339 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X359 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X360 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X361 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X362 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X363 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X364 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X365 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X366 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X367 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X368 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X369 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X370 -0.7558435 1.4372083 1.6038953 -0.4663054 1.9125675 -0.462962
## X371 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X372 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X373 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X374 -0.7558435 1.4372083 1.6038953 -0.4663054 1.9125675 -0.462962
## X375 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X376 1.3216339 -0.6950617 1.6038953 -0.4663054 1.9125675 -0.462962
## X377 1.3216339 -0.6950617 -0.6228265 2.1422621 1.9125675 -0.462962
## X378 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X379 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X380 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X381 1.3216339 -0.6950617 1.6038953 2.1422621 -0.5223076 -0.462962
## X382 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X383 1.3216339 -0.6950617 1.6038953 -0.4663054 1.9125675 -0.462962
## X384 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X385 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X386 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X387 1.3216339 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X388 -0.7558435 1.4372083 1.6038953 2.1422621 1.9125675 -0.462962
## X389 -0.7558435 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X390 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X391 1.3216339 -0.6950617 -0.6228265 2.1422621 1.9125675 -0.462962
## X392 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X393 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X394 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X395 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 2.157733
## X396 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X397 -0.7558435 1.4372083 -0.6228265 -0.4663054 1.9125675 -0.462962
## X398 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X399 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X400 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X401 1.3216339 1.4372083 -0.6228265 -0.4663054 1.9125675 -0.462962
## X402 -0.7558435 1.4372083 -0.6228265 2.1422621 1.9125675 -0.462962
## X403 1.3216339 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X404 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X405 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X406 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X407 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X408 1.3216339 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X409 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X410 -0.7558435 1.4372083 1.6038953 -0.4663054 1.9125675 -0.462962
## X411 1.3216339 1.4372083 -0.6228265 2.1422621 1.9125675 -0.462962
## X412 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X413 -0.7558435 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X414 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X415 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X416 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X417 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X418 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X419 -0.7558435 1.4372083 -0.6228265 -0.4663054 1.9125675 -0.462962
## X420 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X421 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X422 -0.7558435 -0.6950617 1.6038953 2.1422621 -0.5223076 -0.462962
## X423 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X424 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X425 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X426 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X427 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X428 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X429 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X430 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X431 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X432 -0.7558435 1.4372083 1.6038953 2.1422621 -0.5223076 -0.462962
## X433 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X434 -0.7558435 -0.6950617 1.6038953 -0.4663054 1.9125675 -0.462962
## X435 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X436 -0.7558435 1.4372083 1.6038953 -0.4663054 -0.5223076 -0.462962
## X437 1.3216339 -0.6950617 -0.6228265 2.1422621 1.9125675 2.157733
## X438 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 -0.462962
## X439 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X440 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X441 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X442 1.3216339 1.4372083 -0.6228265 2.1422621 1.9125675 -0.462962
## X443 1.3216339 1.4372083 1.6038953 -0.4663054 1.9125675 -0.462962
## X444 1.3216339 -0.6950617 -0.6228265 -0.4663054 1.9125675 2.157733
## X445 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X446 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 2.157733
## X447 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X448 1.3216339 -0.6950617 -0.6228265 -0.4663054 -0.5223076 2.157733
## X449 1.3216339 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X450 -0.7558435 -0.6950617 1.6038953 -0.4663054 -0.5223076 -0.462962
## X451 1.3216339 -0.6950617 -0.6228265 2.1422621 -0.5223076 -0.462962
## X452 1.3216339 1.4372083 -0.6228265 2.1422621 -0.5223076 -0.462962
## X453 -0.7558435 1.4372083 -0.6228265 -0.4663054 -0.5223076 -0.462962
## X454 -0.7558435 1.4372083 -0.6228265 2.1422621 -0.5223076 2.157733
## FP013 FP014 FP015 FP016 FP017 FP018
## X1 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X2 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X3 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X4 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X5 2.2391315 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X6 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X7 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X8 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X9 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X10 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X11 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X12 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X13 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X14 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X15 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X16 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X17 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X18 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 2.5692512
## X19 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X20 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X21 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X22 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X23 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X24 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X25 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X26 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X27 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 2.5692512
## X28 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X29 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X30 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X31 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X32 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X33 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X34 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X35 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X36 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X37 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X38 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X39 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X40 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X41 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 -0.3888092
## X42 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 -0.3888092
## X43 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X44 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 2.5692512
## X45 2.2391315 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X46 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X47 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X48 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 2.5692512
## X49 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 2.5692512
## X50 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X51 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X52 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X53 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X54 2.2391315 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X55 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X56 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X57 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X58 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X59 2.2391315 2.2825867 0.4030145 -0.4135242 2.4362590 2.5692512
## X60 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 2.5692512
## X61 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X62 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X63 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X64 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X65 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 -0.3888092
## X66 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X67 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 2.5692512
## X68 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X69 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X70 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 2.5692512
## X71 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X72 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X73 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X74 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X75 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X76 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X77 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X78 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X79 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X80 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X81 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X82 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X83 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 2.5692512
## X84 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X85 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X86 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X87 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X88 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X89 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 2.5692512
## X90 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X91 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X92 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X93 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X94 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X95 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X96 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 2.5692512
## X97 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X98 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X99 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X100 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X101 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X102 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X103 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X104 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X105 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X106 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X107 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X108 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 -0.3888092
## X109 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X110 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X111 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X112 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X113 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X114 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 2.5692512
## X115 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X116 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X117 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X118 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X119 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X120 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X121 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X122 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X123 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X124 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X125 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X126 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X127 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X128 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X129 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X130 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X131 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X132 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X133 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X134 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X135 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X136 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X137 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X138 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 -0.3888092
## X139 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X140 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X141 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X142 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X143 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X144 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X145 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X146 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X147 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X148 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X149 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X150 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X151 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X152 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X153 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X154 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X155 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X156 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X157 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X158 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X159 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X160 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 2.5692512
## X161 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X162 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X163 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X164 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 -0.3888092
## X165 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X166 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X167 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X168 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X169 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X170 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X171 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 -0.3888092
## X172 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X173 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X174 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X175 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X176 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X177 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X178 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X179 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X180 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X181 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X182 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X183 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X184 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X185 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X186 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X187 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X188 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X189 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X190 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X191 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 -0.3888092
## X192 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X193 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X194 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X195 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X196 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X197 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X198 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X199 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X200 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X201 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X202 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X203 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 2.5692512
## X204 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X205 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X206 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X207 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 2.5692512
## X208 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X209 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X210 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X211 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X212 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X213 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X214 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 2.5692512
## X215 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X216 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X217 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X218 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X219 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X220 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X221 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X222 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X223 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X224 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X225 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X226 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X227 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X228 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X229 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X230 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X231 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X232 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X233 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X234 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X235 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X236 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 -0.3888092
## X237 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X238 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X239 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 2.5692512
## X240 2.2391315 2.2825867 0.4030145 -0.4135242 2.4362590 -0.3888092
## X241 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X242 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X243 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X244 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X245 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 2.5692512
## X246 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X247 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X248 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X249 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X250 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X251 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X252 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X253 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X254 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 2.5692512
## X255 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 2.5692512
## X256 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X257 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X258 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X259 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X260 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X261 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X262 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X263 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X264 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X265 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X266 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X267 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X268 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X269 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X270 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X271 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X272 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X273 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X274 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X275 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X276 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X277 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 2.5692512
## X278 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X279 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X280 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X281 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X282 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 2.5692512
## X283 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X284 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 2.5692512
## X285 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X286 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X287 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X288 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X289 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X290 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X291 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X292 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X293 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X294 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X295 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X296 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X297 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X298 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X299 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X300 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X301 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X302 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X303 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X304 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 2.5692512
## X305 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X306 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X307 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X308 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X309 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X310 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X311 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X312 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X313 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X314 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X315 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X316 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X317 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X318 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X319 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X320 2.2391315 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X321 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X322 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 2.5692512
## X323 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X324 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X325 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X326 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X327 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X328 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X329 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X330 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X331 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X332 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X333 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X334 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X335 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X336 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X337 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X338 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X339 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X340 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X341 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X342 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X343 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 2.5692512
## X344 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X345 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X346 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X347 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X348 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 2.5692512
## X349 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X350 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X351 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X352 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X353 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X354 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X355 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X356 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X357 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X358 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X359 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X360 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X361 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X362 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X363 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X364 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X365 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X366 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X367 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X368 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X369 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X370 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X371 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X372 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X373 -0.4461321 -0.4376388 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X374 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X375 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 2.5692512
## X376 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X377 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X378 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X379 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X380 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X381 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 2.5692512
## X382 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X383 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X384 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X385 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X386 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X387 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 2.5692512
## X388 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X389 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X390 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 2.5692512
## X391 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X392 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X393 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X394 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X395 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X396 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X397 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X398 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X399 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X400 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X401 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X402 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X403 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X404 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X405 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X406 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X407 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X408 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X409 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X410 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X411 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X412 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X413 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X414 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X415 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X416 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X417 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X418 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X419 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X420 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 2.5692512
## X421 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X422 2.2391315 2.2825867 0.4030145 2.4156953 -0.4100338 2.5692512
## X423 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X424 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X425 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X426 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X427 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X428 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X429 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X430 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X431 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X432 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X433 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X434 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X435 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X436 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X437 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X438 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X439 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 -0.3888092
## X440 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X441 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 2.5692512
## X442 -0.4461321 -0.4376388 0.4030145 -0.4135242 2.4362590 2.5692512
## X443 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X444 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X445 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X446 2.2391315 2.2825867 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X447 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X448 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 -0.3888092
## X449 -0.4461321 -0.4376388 0.4030145 2.4156953 -0.4100338 2.5692512
## X450 2.2391315 2.2825867 -2.4786909 -0.4135242 -0.4100338 -0.3888092
## X451 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 -0.3888092
## X452 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X453 -0.4461321 -0.4376388 0.4030145 -0.4135242 -0.4100338 2.5692512
## X454 -0.4461321 -0.4376388 0.4030145 2.4156953 2.4362590 2.5692512
## FP019 FP020 FP021 FP022 FP023 FP024
## X1 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X2 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X3 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X4 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X5 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X6 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X7 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X8 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X9 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X10 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X11 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X12 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X13 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X14 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X15 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X16 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X17 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X18 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X19 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X20 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X21 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X22 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X23 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X24 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X25 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X26 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X27 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X28 2.6815493 -0.3688597 -0.3706955 2.9320660 -0.3743531 2.8070547
## X29 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X30 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X31 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X32 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X33 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X34 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X35 -0.3725266 2.7082069 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X36 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X37 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X38 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X39 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X40 -0.3725266 -0.3688597 2.6947952 2.9320660 -0.3743531 -0.3558707
## X41 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X42 -0.3725266 -0.3688597 2.6947952 2.9320660 -0.3743531 -0.3558707
## X43 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X44 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X45 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X46 -0.3725266 2.7082069 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X47 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X48 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X49 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X50 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X51 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X52 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X53 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X54 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X55 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X56 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X57 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X58 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X59 -0.3725266 2.7082069 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X60 2.6815493 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X61 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X62 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X63 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X64 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X65 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X66 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X67 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X68 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X69 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X70 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X71 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X72 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X73 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X74 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X75 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X76 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X77 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X78 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X79 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X80 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X81 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X82 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X83 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X84 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X85 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X86 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X87 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X88 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X89 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X90 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X91 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X92 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X93 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X94 -0.3725266 2.7082069 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X95 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X96 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X97 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X98 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X99 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X100 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X101 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X102 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X103 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X104 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X105 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X106 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X107 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X108 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X109 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X110 2.6815493 2.7082069 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X111 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X112 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X113 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X114 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X115 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X116 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X117 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X118 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X119 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X120 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X121 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X122 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X123 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X124 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X125 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X126 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X127 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X128 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X129 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X130 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X131 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X132 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X133 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X134 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X135 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X136 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X137 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X138 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X139 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X140 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X141 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X142 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X143 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X144 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X145 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X146 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X147 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X148 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X149 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X150 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X151 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X152 2.6815493 -0.3688597 2.6947952 -0.3406978 -0.3743531 2.8070547
## X153 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X154 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X155 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X156 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X157 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X158 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X159 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X160 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X161 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X162 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X163 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X164 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X165 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X166 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X167 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X168 2.6815493 2.7082069 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X169 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X170 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X171 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X172 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X173 2.6815493 2.7082069 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X174 2.6815493 -0.3688597 2.6947952 2.9320660 -0.3743531 2.8070547
## X175 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X176 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X177 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X178 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X179 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X180 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X181 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X182 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X183 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X184 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X185 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X186 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X187 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X188 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X189 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X190 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X191 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X192 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X193 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X194 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X195 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X196 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X197 2.6815493 2.7082069 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X198 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X199 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X200 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X201 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X202 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X203 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X204 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X205 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X206 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X207 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X208 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X209 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X210 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X211 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X212 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X213 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X214 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X215 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X216 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X217 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X218 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X219 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X220 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X221 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X222 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X223 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X224 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X225 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X226 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X227 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X228 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X229 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X230 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X231 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X232 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X233 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X234 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X235 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X236 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X237 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X238 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X239 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X240 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X241 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X242 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X243 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X244 2.6815493 2.7082069 -0.3706955 2.9320660 -0.3743531 2.8070547
## X245 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X246 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X247 2.6815493 2.7082069 -0.3706955 2.9320660 -0.3743531 2.8070547
## X248 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X249 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X250 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X251 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X252 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X253 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X254 2.6815493 2.7082069 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X255 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X256 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X257 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X258 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X259 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X260 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X261 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X262 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X263 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X264 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X265 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X266 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X267 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X268 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X269 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X270 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X271 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X272 -0.3725266 2.7082069 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X273 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X274 -0.3725266 2.7082069 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X275 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X276 2.6815493 -0.3688597 -0.3706955 2.9320660 -0.3743531 2.8070547
## X277 2.6815493 2.7082069 -0.3706955 -0.3406978 2.6684658 2.8070547
## X278 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X279 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X280 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X281 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X282 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X283 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X284 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X285 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X286 2.6815493 -0.3688597 -0.3706955 2.9320660 -0.3743531 2.8070547
## X287 2.6815493 2.7082069 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X288 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X289 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X290 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X291 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X292 2.6815493 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X293 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X294 -0.3725266 2.7082069 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X295 -0.3725266 2.7082069 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X296 2.6815493 2.7082069 -0.3706955 2.9320660 -0.3743531 2.8070547
## X297 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X298 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X299 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X300 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X301 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X302 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X303 2.6815493 2.7082069 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X304 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X305 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X306 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X307 2.6815493 -0.3688597 -0.3706955 -0.3406978 2.6684658 2.8070547
## X308 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X309 2.6815493 -0.3688597 -0.3706955 -0.3406978 2.6684658 2.8070547
## X310 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X311 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X312 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X313 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X314 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X315 -0.3725266 2.7082069 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X316 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X317 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X318 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X319 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X320 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X321 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X322 -0.3725266 2.7082069 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X323 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X324 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X325 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X326 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X327 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X328 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X329 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X330 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X331 -0.3725266 -0.3688597 2.6947952 2.9320660 -0.3743531 -0.3558707
## X332 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X333 -0.3725266 2.7082069 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X334 -0.3725266 2.7082069 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X335 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X336 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X337 2.6815493 2.7082069 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X338 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X339 2.6815493 -0.3688597 -0.3706955 2.9320660 -0.3743531 2.8070547
## X340 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X341 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X342 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X343 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X344 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X345 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X346 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X347 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X348 2.6815493 2.7082069 -0.3706955 -0.3406978 2.6684658 2.8070547
## X349 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X350 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X351 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X352 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X353 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X354 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X355 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X356 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X357 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X358 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X359 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X360 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X361 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X362 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X363 2.6815493 -0.3688597 -0.3706955 2.9320660 -0.3743531 2.8070547
## X364 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X365 -0.3725266 2.7082069 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X366 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X367 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X368 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X369 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X370 -0.3725266 -0.3688597 2.6947952 2.9320660 -0.3743531 -0.3558707
## X371 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X372 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X373 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X374 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X375 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X376 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X377 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X378 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X379 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X380 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X381 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X382 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X383 -0.3725266 -0.3688597 2.6947952 -0.3406978 2.6684658 -0.3558707
## X384 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X385 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X386 2.6815493 -0.3688597 -0.3706955 2.9320660 -0.3743531 2.8070547
## X387 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X388 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X389 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X390 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X391 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X392 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X393 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X394 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X395 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X396 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X397 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X398 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X399 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X400 -0.3725266 2.7082069 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X401 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X402 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X403 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X404 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X405 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X406 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X407 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X408 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X409 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X410 -0.3725266 -0.3688597 2.6947952 2.9320660 -0.3743531 -0.3558707
## X411 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X412 2.6815493 -0.3688597 -0.3706955 2.9320660 -0.3743531 2.8070547
## X413 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X414 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X415 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X416 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X417 2.6815493 -0.3688597 -0.3706955 2.9320660 -0.3743531 2.8070547
## X418 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X419 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X420 -0.3725266 2.7082069 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X421 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X422 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X423 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X424 2.6815493 -0.3688597 -0.3706955 -0.3406978 -0.3743531 2.8070547
## X425 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X426 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X427 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X428 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X429 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X430 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X431 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X432 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X433 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X434 -0.3725266 -0.3688597 2.6947952 -0.3406978 -0.3743531 -0.3558707
## X435 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X436 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X437 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X438 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X439 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X440 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X441 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X442 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X443 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X444 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X445 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X446 -0.3725266 -0.3688597 -0.3706955 2.9320660 -0.3743531 -0.3558707
## X447 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X448 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X449 -0.3725266 -0.3688597 -0.3706955 -0.3406978 2.6684658 -0.3558707
## X450 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X451 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X452 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## X453 2.6815493 2.7082069 -0.3706955 -0.3406978 2.6684658 2.8070547
## X454 -0.3725266 -0.3688597 -0.3706955 -0.3406978 -0.3743531 -0.3558707
## FP025 FP026 FP027 FP028 FP029 FP030
## X1 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X2 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X3 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X4 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X5 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 3.1104998
## X6 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X7 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X8 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X9 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X10 -0.361468 -0.3029057 3.0358039 2.8994814 -0.3368437 -0.3211537
## X11 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X12 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X13 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X14 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X15 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X16 2.763587 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X17 -0.361468 3.2978859 -0.3290557 -0.3445266 2.9656139 3.1104998
## X18 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 3.1104998
## X19 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X20 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X21 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X22 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X23 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X24 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X25 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 3.1104998
## X26 -0.361468 3.2978859 3.0358039 2.8994814 -0.3368437 -0.3211537
## X27 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X28 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X29 -0.361468 -0.3029057 3.0358039 -0.3445266 2.9656139 -0.3211537
## X30 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X31 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X32 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X33 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X34 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X35 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X36 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X37 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X38 2.763587 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X39 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X40 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X41 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X42 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X43 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X44 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X45 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X46 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X47 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X48 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X49 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X50 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X51 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X52 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X53 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X54 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 3.1104998
## X55 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X56 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X57 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X58 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X59 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X60 2.763587 3.2978859 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X61 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X62 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X63 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X64 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X65 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X66 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 3.1104998
## X67 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X68 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 3.1104998
## X69 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X70 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X71 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X72 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X73 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X74 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X75 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X76 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 3.1104998
## X77 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X78 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X79 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X80 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X81 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X82 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X83 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X84 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X85 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X86 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X87 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X88 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X89 -0.361468 -0.3029057 3.0358039 2.8994814 2.9656139 3.1104998
## X90 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X91 2.763587 -0.3029057 3.0358039 2.8994814 -0.3368437 3.1104998
## X92 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X93 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X94 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X95 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X96 2.763587 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X97 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X98 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X99 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X100 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X101 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X102 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X103 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X104 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X105 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X106 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X107 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X108 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X109 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X110 2.763587 3.2978859 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X111 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X112 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X113 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X114 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X115 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X116 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X117 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 3.1104998
## X118 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X119 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X120 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X121 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X122 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X123 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X124 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X125 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X126 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X127 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X128 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X129 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X130 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X131 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X132 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X133 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X134 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X135 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X136 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X137 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X138 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X139 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X140 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X141 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X142 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X143 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X144 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X145 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X146 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X147 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X148 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X149 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X150 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X151 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X152 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X153 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X154 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X155 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X156 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X157 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X158 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X159 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X160 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X161 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X162 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X163 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X164 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X165 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X166 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X167 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X168 -0.361468 -0.3029057 -0.3290557 2.8994814 2.9656139 -0.3211537
## X169 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X170 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X171 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X172 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X173 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X174 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X175 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X176 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X177 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X178 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X179 2.763587 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X180 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X181 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X182 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 3.1104998
## X183 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X184 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X185 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X186 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X187 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X188 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X189 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X190 -0.361468 3.2978859 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X191 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X192 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X193 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X194 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X195 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X196 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X197 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X198 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X199 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X200 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X201 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X202 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X203 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X204 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X205 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X206 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X207 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X208 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X209 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X210 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X211 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X212 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X213 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X214 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X215 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X216 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X217 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X218 -0.361468 3.2978859 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X219 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X220 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X221 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 3.1104998
## X222 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X223 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X224 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X225 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X226 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X227 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X228 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X229 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X230 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X231 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X232 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X233 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X234 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X235 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X236 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X237 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X238 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X239 2.763587 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X240 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X241 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X242 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X243 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X244 -0.361468 3.2978859 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X245 2.763587 3.2978859 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X246 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X247 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X248 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X249 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X250 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X251 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X252 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 3.1104998
## X253 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X254 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X255 2.763587 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X256 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X257 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X258 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X259 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X260 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X261 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X262 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X263 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X264 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X265 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X266 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X267 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X268 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X269 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X270 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X271 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X272 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X273 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X274 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X275 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X276 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X277 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X278 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X279 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X280 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X281 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X282 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X283 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X284 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X285 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X286 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X287 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X288 2.763587 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X289 2.763587 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X290 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X291 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X292 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X293 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X294 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X295 -0.361468 -0.3029057 3.0358039 -0.3445266 2.9656139 -0.3211537
## X296 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X297 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X298 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X299 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X300 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 3.1104998
## X301 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X302 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X303 -0.361468 -0.3029057 -0.3290557 2.8994814 2.9656139 3.1104998
## X304 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X305 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 3.1104998
## X306 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X307 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X308 2.763587 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X309 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X310 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 3.1104998
## X311 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X312 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X313 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X314 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X315 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X316 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X317 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X318 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X319 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X320 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 3.1104998
## X321 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X322 -0.361468 -0.3029057 3.0358039 -0.3445266 2.9656139 3.1104998
## X323 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X324 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X325 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X326 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X327 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X328 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X329 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X330 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X331 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X332 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X333 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X334 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X335 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 3.1104998
## X336 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X337 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X338 -0.361468 -0.3029057 3.0358039 -0.3445266 2.9656139 -0.3211537
## X339 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X340 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X341 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X342 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X343 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X344 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X345 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X346 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X347 2.763587 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X348 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X349 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X350 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X351 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X352 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X353 -0.361468 3.2978859 3.0358039 -0.3445266 -0.3368437 3.1104998
## X354 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X355 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X356 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X357 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X358 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X359 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X360 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X361 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X362 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X363 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X364 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X365 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X366 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X367 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X368 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X369 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X370 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X371 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X372 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X373 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X374 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X375 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X376 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 3.1104998
## X377 2.763587 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X378 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 3.1104998
## X379 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X380 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X381 2.763587 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X382 -0.361468 3.2978859 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X383 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 3.1104998
## X384 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X385 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X386 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X387 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X388 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X389 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X390 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X391 2.763587 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X392 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X393 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X394 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X395 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X396 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X397 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X398 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X399 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X400 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X401 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X402 2.763587 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X403 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X404 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X405 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X406 2.763587 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X407 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X408 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X409 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X410 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X411 2.763587 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X412 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X413 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X414 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 3.1104998
## X415 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X416 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X417 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X418 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X419 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X420 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X421 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X422 2.763587 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X423 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 3.1104998
## X424 2.763587 -0.3029057 3.0358039 -0.3445266 -0.3368437 3.1104998
## X425 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 3.1104998
## X426 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X427 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X428 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X429 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X430 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X431 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X432 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X433 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X434 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X435 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X436 -0.361468 3.2978859 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X437 2.763587 -0.3029057 -0.3290557 2.8994814 -0.3368437 -0.3211537
## X438 -0.361468 -0.3029057 -0.3290557 2.8994814 -0.3368437 3.1104998
## X439 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X440 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X441 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X442 -0.361468 -0.3029057 -0.3290557 2.8994814 2.9656139 -0.3211537
## X443 -0.361468 -0.3029057 3.0358039 -0.3445266 -0.3368437 -0.3211537
## X444 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X445 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X446 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X447 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X448 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X449 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X450 -0.361468 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X451 2.763587 -0.3029057 -0.3290557 -0.3445266 -0.3368437 -0.3211537
## X452 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X453 -0.361468 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## X454 2.763587 -0.3029057 -0.3290557 -0.3445266 2.9656139 -0.3211537
## FP031 FP032 FP033 FP034 FP035 FP036
## X1 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X2 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X3 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X4 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X5 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X6 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X7 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X8 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X9 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X10 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X11 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X12 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X13 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X14 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X15 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X16 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X17 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X18 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X19 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X20 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X21 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X22 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X23 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X24 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X25 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X26 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X27 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X28 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X29 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X30 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X31 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X32 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X33 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X34 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X35 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X36 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X37 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X38 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X39 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X40 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X41 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X42 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X43 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X44 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X45 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X46 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X47 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X48 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X49 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X50 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X51 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X52 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X53 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X54 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X55 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X56 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X57 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X58 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X59 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X60 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X61 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X62 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X63 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X64 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X65 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X66 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X67 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X68 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X69 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X70 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X71 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X72 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X73 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X74 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X75 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X76 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X77 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X78 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X79 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X80 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X81 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X82 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X83 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X84 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 3.4922050
## X85 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X86 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X87 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X88 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X89 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X90 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X91 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 3.4922050
## X92 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X93 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X94 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X95 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X96 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X97 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X98 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X99 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X100 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X101 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X102 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X103 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X104 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X105 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X106 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X107 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X108 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X109 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X110 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X111 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X112 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X113 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X114 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X115 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X116 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X117 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X118 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X119 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X120 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X121 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X122 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X123 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X124 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X125 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X126 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X127 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X128 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X129 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X130 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X131 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X132 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X133 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X134 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X135 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X136 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X137 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X138 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X139 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X140 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X141 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X142 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X143 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X144 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X145 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X146 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X147 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X148 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X149 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X150 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X151 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X152 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X153 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X154 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X155 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X156 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X157 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X158 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X159 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X160 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X161 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X162 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X163 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X164 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X165 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X166 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X167 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X168 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X169 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X170 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X171 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X172 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X173 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 3.4922050
## X174 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X175 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X176 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X177 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X178 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X179 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X180 -0.3131281 3.5457693 3.6599168 -0.2945604 3.5733972 -0.2860509
## X181 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X182 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X183 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X184 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X185 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X186 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X187 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X188 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X189 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X190 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X191 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X192 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X193 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X194 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X195 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X196 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X197 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X198 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X199 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X200 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X201 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X202 -0.3131281 3.5457693 3.6599168 -0.2945604 3.5733972 -0.2860509
## X203 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X204 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X205 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X206 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X207 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X208 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X209 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X210 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X211 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X212 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X213 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X214 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X215 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X216 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X217 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X218 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X219 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X220 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X221 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X222 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X223 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X224 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X225 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X226 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X227 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X228 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X229 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X230 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X231 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X232 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X233 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 3.4922050
## X234 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X235 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X236 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X237 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X238 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X239 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X240 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 3.4922050
## X241 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X242 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X243 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X244 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X245 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X246 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 3.4922050
## X247 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X248 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X249 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X250 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X251 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X252 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 3.4922050
## X253 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X254 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X255 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X256 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X257 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X258 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X259 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X260 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X261 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X262 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X263 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X264 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X265 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X266 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X267 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X268 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X269 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X270 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X271 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X272 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X273 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X274 3.1902229 -0.2817297 -0.2729429 -0.2945604 3.5733972 3.4922050
## X275 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X276 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X277 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X278 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X279 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X280 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X281 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X282 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X283 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X284 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X285 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 3.4922050
## X286 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X287 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X288 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X289 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 3.4922050
## X290 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X291 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X292 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X293 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X294 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X295 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X296 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X297 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X298 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 3.4922050
## X299 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 3.4922050
## X300 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X301 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X302 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 3.4922050
## X303 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X304 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X305 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X306 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X307 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X308 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X309 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X310 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X311 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X312 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 3.4922050
## X313 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X314 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X315 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X316 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X317 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X318 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X319 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 3.4922050
## X320 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X321 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X322 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X323 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X324 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X325 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X326 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X327 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X328 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X329 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X330 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X331 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 3.4922050
## X332 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 3.4922050
## X333 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X334 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X335 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X336 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X337 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X338 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X339 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X340 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X341 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X342 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X343 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X344 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X345 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X346 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 3.4922050
## X347 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X348 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X349 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X350 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X351 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X352 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X353 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X354 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X355 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X356 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X357 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X358 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X359 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 3.4922050
## X360 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X361 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X362 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X363 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X364 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X365 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X366 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X367 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X368 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X369 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X370 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X371 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X372 -0.3131281 3.5457693 3.6599168 3.3913200 -0.2795515 -0.2860509
## X373 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X374 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 3.4922050
## X375 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X376 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X377 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X378 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X379 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X380 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X381 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X382 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X383 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X384 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X385 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X386 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X387 3.1902229 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X388 -0.3131281 3.5457693 3.6599168 3.3913200 -0.2795515 -0.2860509
## X389 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X390 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X391 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X392 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X393 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X394 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X395 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X396 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X397 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X398 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X399 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X400 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X401 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X402 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X403 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X404 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X405 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X406 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X407 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X408 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X409 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 3.4922050
## X410 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X411 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X412 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X413 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 3.4922050
## X414 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X415 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X416 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X417 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X418 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X419 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X420 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X421 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X422 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X423 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X424 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X425 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X426 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X427 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X428 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X429 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X430 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 3.4922050
## X431 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X432 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X433 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X434 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X435 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X436 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X437 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X438 -0.3131281 -0.2817297 -0.2729429 -0.2945604 3.5733972 -0.2860509
## X439 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X440 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X441 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X442 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X443 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X444 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X445 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X446 -0.3131281 -0.2817297 -0.2729429 3.3913200 -0.2795515 -0.2860509
## X447 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X448 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X449 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X450 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X451 -0.3131281 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X452 -0.3131281 3.5457693 3.6599168 -0.2945604 -0.2795515 -0.2860509
## X453 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## X454 3.1902229 -0.2817297 -0.2729429 -0.2945604 -0.2795515 -0.2860509
## FP037 FP038 FP039 FP040 FP041 FP042
## X1 -0.2751584 -0.3070214 3.5187119 3.6900455 -0.2593632 -0.2452292
## X2 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X3 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X4 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X5 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X6 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X7 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X8 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X9 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X10 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X11 3.6304485 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X12 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X13 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X14 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X15 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X16 -0.2751584 3.2536775 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X17 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X18 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X19 3.6304485 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X20 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X21 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X22 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X23 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X24 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X25 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X26 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X27 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X28 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 4.0735297
## X29 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X30 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X31 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X32 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X33 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X34 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X35 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X36 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X37 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X38 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X39 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X40 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X41 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X42 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X43 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X44 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X45 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X46 3.6304485 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X47 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X48 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X49 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X50 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X51 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X52 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X53 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X54 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X55 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X56 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X57 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X58 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X59 3.6304485 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X60 -0.2751584 3.2536775 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X61 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X62 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X63 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X64 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X65 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X66 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X67 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X68 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X69 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X70 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X71 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X72 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X73 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X74 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X75 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X76 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X77 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X78 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X79 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X80 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X81 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X82 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X83 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X84 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X85 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X86 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X87 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X88 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X89 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X90 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X91 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X92 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 4.0735297
## X93 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X94 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X95 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X96 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X97 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X98 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X99 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X100 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X101 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X102 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X103 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X104 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X105 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X106 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X107 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X108 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X109 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X110 -0.2751584 3.2536775 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X111 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X112 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X113 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X114 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X115 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X116 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X117 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X118 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X119 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X120 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 4.0735297
## X121 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X122 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X123 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X124 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X125 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X126 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X127 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X128 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X129 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X130 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X131 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X132 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X133 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X134 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X135 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X136 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X137 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X138 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X139 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X140 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X141 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X142 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X143 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X144 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X145 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X146 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X147 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X148 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X149 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X150 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X151 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X152 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X153 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X154 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X155 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X156 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X157 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X158 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X159 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X160 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X161 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X162 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X163 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X164 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X165 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X166 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X167 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X168 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X169 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X170 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X171 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X172 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X173 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 -0.2452292
## X174 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 -0.2452292
## X175 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X176 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X177 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X178 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X179 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X180 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X181 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X182 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X183 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X184 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 -0.2452292
## X185 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X186 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X187 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X188 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X189 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X190 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X191 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X192 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X193 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X194 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X195 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X196 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X197 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X198 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X199 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X200 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X201 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X202 3.6304485 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X203 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X204 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X205 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X206 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X207 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X208 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X209 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X210 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X211 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X212 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X213 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X214 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X215 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X216 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X217 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X218 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X219 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X220 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X221 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X222 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X223 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X224 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X225 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X226 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X227 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X228 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X229 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X230 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X231 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X232 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X233 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X234 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X235 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X236 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X237 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X238 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X239 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X240 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X241 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X242 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X243 -0.2751584 -0.3070214 3.5187119 3.6900455 -0.2593632 -0.2452292
## X244 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X245 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X246 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X247 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 4.0735297
## X248 3.6304485 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X249 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X250 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X251 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 -0.2452292
## X252 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X253 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X254 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 -0.2452292
## X255 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X256 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X257 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X258 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X259 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X260 -0.2751584 3.2536775 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X261 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X262 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X263 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X264 -0.2751584 -0.3070214 3.5187119 3.6900455 -0.2593632 -0.2452292
## X265 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X266 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X267 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X268 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X269 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X270 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X271 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X272 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X273 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X274 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X275 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X276 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X277 -0.2751584 -0.3070214 3.5187119 3.6900455 -0.2593632 -0.2452292
## X278 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 -0.2452292
## X279 -0.2751584 -0.3070214 3.5187119 3.6900455 -0.2593632 -0.2452292
## X280 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X281 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X282 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X283 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X284 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X285 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X286 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 4.0735297
## X287 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 4.0735297
## X288 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X289 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X290 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X291 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X292 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X293 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X294 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X295 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X296 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X297 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X298 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X299 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X300 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X301 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X302 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X303 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X304 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X305 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X306 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X307 -0.2751584 -0.3070214 3.5187119 3.6900455 -0.2593632 -0.2452292
## X308 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X309 -0.2751584 -0.3070214 3.5187119 3.6900455 -0.2593632 -0.2452292
## X310 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X311 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X312 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X313 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X314 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X315 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X316 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X317 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X318 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X319 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X320 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X321 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X322 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X323 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X324 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X325 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X326 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X327 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X328 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X329 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X330 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X331 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X332 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X333 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X334 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X335 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X336 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X337 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X338 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X339 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 -0.2452292
## X340 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X341 3.6304485 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X342 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X343 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X344 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X345 -0.2751584 -0.3070214 3.5187119 3.6900455 -0.2593632 -0.2452292
## X346 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X347 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X348 -0.2751584 -0.3070214 3.5187119 3.6900455 -0.2593632 -0.2452292
## X349 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X350 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X351 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X352 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X353 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X354 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X355 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X356 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X357 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X358 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X359 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X360 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X361 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X362 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X363 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 4.0735297
## X364 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X365 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X366 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X367 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X368 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X369 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X370 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X371 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X372 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X373 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X374 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X375 3.6304485 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X376 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X377 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X378 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X379 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X380 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X381 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X382 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X383 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X384 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X385 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X386 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 4.0735297
## X387 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X388 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X389 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X390 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X391 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X392 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X393 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X394 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X395 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 4.0735297
## X396 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X397 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X398 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X399 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X400 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X401 -0.2751584 -0.3070214 3.5187119 -0.2707144 -0.2593632 -0.2452292
## X402 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X403 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X404 3.6304485 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X405 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X406 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X407 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X408 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X409 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X410 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X411 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X412 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 4.0735297
## X413 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 -0.2452292
## X414 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X415 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X416 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X417 -0.2751584 -0.3070214 -0.2838961 3.6900455 -0.2593632 4.0735297
## X418 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X419 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X420 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X421 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X422 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X423 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X424 -0.2751584 3.2536775 -0.2838961 3.6900455 3.8515432 -0.2452292
## X425 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X426 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X427 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X428 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X429 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X430 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X431 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X432 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X433 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X434 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X435 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X436 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X437 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X438 3.6304485 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## X439 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X440 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X441 3.6304485 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X442 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X443 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X444 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X445 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X446 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X447 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X448 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X449 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X450 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X451 -0.2751584 3.2536775 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X452 -0.2751584 -0.3070214 -0.2838961 -0.2707144 -0.2593632 -0.2452292
## X453 -0.2751584 -0.3070214 3.5187119 3.6900455 -0.2593632 -0.2452292
## X454 -0.2751584 -0.3070214 -0.2838961 -0.2707144 3.8515432 -0.2452292
## FP043 FP044 FP045 FP046 FP047 FP048
## X1 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X2 3.7523881 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X3 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X4 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X5 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X6 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X7 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X8 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X9 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X10 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X11 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X12 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X13 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X14 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X15 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X16 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X17 3.7523881 -0.2523714 4.1140710 -0.6784872 -0.6017334 2.6555412
## X18 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X19 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X20 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X21 -0.2662167 3.9582469 -0.2428127 1.4723173 1.6601181 -0.3761751
## X22 3.7523881 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X23 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 2.6555412
## X24 3.7523881 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X25 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X26 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X27 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X28 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X29 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X30 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X31 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X32 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X33 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X34 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X35 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X36 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X37 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X38 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X39 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X40 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X41 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X42 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X43 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X44 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X45 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X46 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X47 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X48 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X49 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X50 -0.2662167 3.9582469 -0.2428127 1.4723173 1.6601181 -0.3761751
## X51 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X52 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X53 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X54 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X55 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X56 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X57 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 2.6555412
## X58 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X59 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X60 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X61 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X62 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X63 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X64 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X65 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X66 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X67 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X68 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X69 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X70 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X71 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X72 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X73 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X74 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X75 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X76 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X77 -0.2662167 3.9582469 -0.2428127 1.4723173 1.6601181 -0.3761751
## X78 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X79 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X80 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X81 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X82 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X83 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X84 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X85 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X86 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X87 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X88 -0.2662167 3.9582469 -0.2428127 1.4723173 1.6601181 -0.3761751
## X89 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X90 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X91 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X92 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X93 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X94 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X95 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X96 -0.2662167 -0.2523714 4.1140710 -0.6784872 -0.6017334 -0.3761751
## X97 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X98 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X99 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X100 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X101 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X102 3.7523881 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X103 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X104 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X105 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X106 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X107 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X108 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X109 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X110 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X111 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 2.6555412
## X112 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X113 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X114 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X115 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X116 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X117 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X118 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X119 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X120 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X121 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X122 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X123 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X124 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X125 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X126 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X127 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X128 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X129 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X130 -0.2662167 3.9582469 -0.2428127 1.4723173 1.6601181 -0.3761751
## X131 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X132 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X133 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X134 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X135 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X136 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X137 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X138 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X139 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X140 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X141 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X142 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X143 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X144 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X145 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X146 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X147 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X148 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X149 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X150 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X151 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X152 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X153 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X154 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X155 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X156 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X157 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X158 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X159 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X160 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X161 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X162 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X163 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X164 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X165 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X166 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 2.6555412
## X167 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X168 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X169 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X170 3.7523881 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X171 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X172 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X173 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X174 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X175 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X176 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X177 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X178 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X179 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X180 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X181 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X182 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X183 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X184 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X185 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X186 3.7523881 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X187 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X188 3.7523881 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X189 3.7523881 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X190 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X191 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X192 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X193 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X194 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X195 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X196 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X197 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X198 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X199 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X200 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X201 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 2.6555412
## X202 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X203 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X204 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X205 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X206 3.7523881 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X207 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X208 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X209 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X210 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X211 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X212 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X213 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X214 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X215 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X216 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X217 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X218 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X219 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X220 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X221 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X222 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X223 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X224 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X225 -0.2662167 3.9582469 -0.2428127 1.4723173 1.6601181 -0.3761751
## X226 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X227 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X228 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X229 -0.2662167 3.9582469 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X230 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X231 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X232 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X233 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X234 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X235 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X236 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X237 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X238 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X239 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X240 3.7523881 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X241 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X242 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X243 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X244 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X245 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X246 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X247 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X248 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X249 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X250 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X251 -0.2662167 -0.2523714 4.1140710 -0.6784872 -0.6017334 -0.3761751
## X252 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X253 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X254 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X255 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X256 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X257 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X258 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X259 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X260 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X261 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X262 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X263 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X264 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X265 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X266 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X267 -0.2662167 3.9582469 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X268 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X269 3.7523881 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X270 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 2.6555412
## X271 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X272 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X273 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X274 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X275 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X276 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X277 3.7523881 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X278 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X279 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X280 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X281 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X282 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X283 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X284 3.7523881 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X285 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X286 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X287 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X288 -0.2662167 -0.2523714 4.1140710 -0.6784872 -0.6017334 -0.3761751
## X289 3.7523881 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X290 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X291 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X292 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X293 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X294 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X295 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X296 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X297 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X298 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X299 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X300 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X301 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X302 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X303 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X304 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X305 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 2.6555412
## X306 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X307 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X308 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X309 3.7523881 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X310 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X311 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X312 3.7523881 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X313 3.7523881 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X314 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X315 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X316 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X317 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X318 3.7523881 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X319 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X320 3.7523881 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X321 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X322 3.7523881 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X323 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X324 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X325 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X326 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X327 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X328 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X329 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X330 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X331 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X332 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X333 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X334 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X335 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 2.6555412
## X336 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X337 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X338 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X339 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X340 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X341 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X342 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X343 3.7523881 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X344 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X345 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X346 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X347 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X348 3.7523881 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X349 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X350 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X351 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X352 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X353 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 2.6555412
## X354 3.7523881 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X355 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X356 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X357 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X358 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X359 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X360 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X361 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 2.6555412
## X362 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X363 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X364 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X365 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X366 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X367 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X368 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X369 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X370 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X371 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X372 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X373 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X374 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X375 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X376 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X377 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X378 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X379 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X380 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X381 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X382 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X383 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X384 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X385 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X386 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X387 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 2.6555412
## X388 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X389 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X390 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 2.6555412
## X391 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X392 3.7523881 -0.2523714 -0.2428127 -0.6784872 1.6601181 2.6555412
## X393 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X394 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X395 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 2.6555412
## X396 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X397 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X398 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X399 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X400 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X401 -0.2662167 -0.2523714 4.1140710 1.4723173 -0.6017334 -0.3761751
## X402 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X403 -0.2662167 -0.2523714 4.1140710 -0.6784872 1.6601181 2.6555412
## X404 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X405 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X406 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X407 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X408 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X409 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X410 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X411 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X412 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X413 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X414 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X415 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X416 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X417 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X418 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X419 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X420 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X421 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X422 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X423 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X424 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X425 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X426 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## X427 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X428 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X429 -0.2662167 -0.2523714 4.1140710 1.4723173 1.6601181 -0.3761751
## X430 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X431 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X432 -0.2662167 -0.2523714 4.1140710 -0.6784872 -0.6017334 -0.3761751
## X433 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X434 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X435 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X436 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X437 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X438 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X439 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X440 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X441 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X442 3.7523881 -0.2523714 4.1140710 -0.6784872 1.6601181 -0.3761751
## X443 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X444 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X445 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X446 -0.2662167 -0.2523714 -0.2428127 1.4723173 -0.6017334 -0.3761751
## X447 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X448 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X449 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X450 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X451 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 2.6555412
## X452 -0.2662167 -0.2523714 -0.2428127 -0.6784872 1.6601181 -0.3761751
## X453 -0.2662167 -0.2523714 -0.2428127 -0.6784872 -0.6017334 -0.3761751
## X454 -0.2662167 -0.2523714 -0.2428127 1.4723173 1.6601181 -0.3761751
## FP049 FP050 FP051 FP052 FP053 FP054
## X1 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X2 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X3 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X4 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X5 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X6 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X7 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X8 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X9 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X10 -0.3725266 2.8070547 -0.3502245 3.149697 -0.3211537 3.4922050
## X11 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X12 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X13 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X14 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X15 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X16 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X17 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X18 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X19 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X20 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X21 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X22 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X23 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X24 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X25 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X26 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X27 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X28 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X29 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X30 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X31 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X32 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X33 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 3.4922050
## X34 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X35 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X36 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X37 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 3.4922050
## X38 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X39 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X40 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X41 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X42 2.6815493 -0.3558707 -0.3502245 3.149697 3.1104998 -0.2860509
## X43 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X44 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X45 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X46 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X47 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X48 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X49 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X50 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X51 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X52 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X53 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X54 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X55 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X56 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X57 -0.3725266 2.8070547 -0.3502245 3.149697 -0.3211537 -0.2860509
## X58 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X59 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X60 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X61 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X62 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X63 -0.3725266 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X64 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X65 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X66 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X67 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X68 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 3.4922050
## X69 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 3.4922050
## X70 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 3.4922050
## X71 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X72 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X73 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X74 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X75 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X76 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X77 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X78 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X79 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X80 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X81 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X82 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X83 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X84 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X85 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X86 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X87 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X88 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X89 2.6815493 2.8070547 2.8523090 -0.317157 3.1104998 -0.2860509
## X90 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X91 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X92 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X93 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X94 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 3.4922050
## X95 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X96 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X97 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X98 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X99 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X100 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X101 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X102 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X103 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X104 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X105 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X106 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X107 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X108 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X109 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X110 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X111 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X112 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X113 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X114 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X115 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X116 2.6815493 -0.3558707 -0.3502245 3.149697 3.1104998 -0.2860509
## X117 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X118 -0.3725266 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X119 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X120 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X121 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X122 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X123 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X124 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X125 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X126 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X127 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X128 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X129 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X130 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X131 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X132 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X133 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X134 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X135 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X136 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X137 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X138 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X139 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X140 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X141 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X142 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X143 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X144 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X145 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X146 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X147 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X148 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X149 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X150 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X151 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X152 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X153 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X154 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X155 -0.3725266 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X156 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X157 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X158 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X159 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X160 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X161 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X162 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X163 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X164 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X165 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X166 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X167 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X168 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X169 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X170 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X171 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X172 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X173 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X174 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X175 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X176 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X177 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X178 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X179 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X180 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X181 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X182 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X183 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X184 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X185 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X186 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X187 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X188 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X189 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X190 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X191 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X192 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X193 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X194 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X195 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X196 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X197 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X198 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X199 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X200 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X201 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X202 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X203 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X204 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X205 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X206 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X207 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X208 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X209 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X210 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X211 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X212 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X213 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X214 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X215 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X216 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X217 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X218 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X219 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X220 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X221 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X222 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X223 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X224 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X225 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X226 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X227 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X228 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X229 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X230 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X231 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X232 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X233 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X234 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X235 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X236 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X237 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X238 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X239 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X240 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X241 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X242 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X243 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X244 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X245 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X246 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X247 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X248 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X249 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X250 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X251 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X252 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X253 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X254 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 3.4922050
## X255 2.6815493 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X256 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X257 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X258 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X259 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X260 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X261 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X262 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X263 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X264 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X265 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X266 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X267 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X268 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X269 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X270 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X271 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X272 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X273 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X274 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X275 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X276 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X277 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X278 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X279 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X280 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X281 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X282 2.6815493 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X283 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X284 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X285 2.6815493 -0.3558707 -0.3502245 3.149697 3.1104998 -0.2860509
## X286 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X287 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X288 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X289 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X290 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X291 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X292 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X293 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X294 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X295 -0.3725266 -0.3558707 2.8523090 3.149697 -0.3211537 -0.2860509
## X296 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X297 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X298 2.6815493 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X299 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X300 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X301 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X302 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X303 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X304 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X305 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X306 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X307 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X308 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X309 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X310 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X311 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X312 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X313 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X314 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X315 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X316 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X317 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X318 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X319 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X320 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X321 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X322 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X323 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X324 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X325 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X326 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X327 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X328 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X329 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X330 2.6815493 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X331 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X332 2.6815493 -0.3558707 -0.3502245 3.149697 3.1104998 -0.2860509
## X333 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X334 -0.3725266 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X335 -0.3725266 2.8070547 -0.3502245 3.149697 -0.3211537 -0.2860509
## X336 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X337 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X338 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X339 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X340 -0.3725266 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X341 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X342 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X343 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X344 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X345 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X346 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X347 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X348 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X349 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X350 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X351 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X352 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X353 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X354 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X355 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X356 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X357 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X358 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X359 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X360 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X361 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X362 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X363 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X364 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X365 2.6815493 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X366 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X367 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X368 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X369 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X370 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X371 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X372 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X373 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X374 2.6815493 -0.3558707 -0.3502245 3.149697 3.1104998 -0.2860509
## X375 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X376 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X377 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X378 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X379 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X380 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X381 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X382 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X383 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X384 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X385 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X386 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X387 -0.3725266 2.8070547 2.8523090 -0.317157 -0.3211537 3.4922050
## X388 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X389 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X390 -0.3725266 2.8070547 2.8523090 -0.317157 -0.3211537 3.4922050
## X391 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X392 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X393 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X394 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X395 -0.3725266 2.8070547 -0.3502245 3.149697 -0.3211537 -0.2860509
## X396 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X397 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X398 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X399 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X400 2.6815493 -0.3558707 -0.3502245 3.149697 3.1104998 -0.2860509
## X401 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X402 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X403 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X404 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X405 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X406 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X407 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X408 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X409 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X410 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X411 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X412 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X413 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X414 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X415 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X416 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X417 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X418 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X419 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X420 2.6815493 -0.3558707 2.8523090 -0.317157 3.1104998 -0.2860509
## X421 -0.3725266 -0.3558707 -0.3502245 3.149697 -0.3211537 -0.2860509
## X422 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X423 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X424 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X425 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X426 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X427 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X428 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X429 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X430 2.6815493 -0.3558707 -0.3502245 3.149697 3.1104998 -0.2860509
## X431 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X432 2.6815493 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X433 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X434 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## X435 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X436 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X437 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X438 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 3.4922050
## X439 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X440 2.6815493 -0.3558707 -0.3502245 -0.317157 3.1104998 -0.2860509
## X441 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 3.4922050
## X442 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X443 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X444 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X445 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X446 2.6815493 -0.3558707 -0.3502245 3.149697 3.1104998 -0.2860509
## X447 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X448 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X449 -0.3725266 2.8070547 2.8523090 -0.317157 -0.3211537 -0.2860509
## X450 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X451 -0.3725266 2.8070547 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X452 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X453 -0.3725266 -0.3558707 -0.3502245 -0.317157 -0.3211537 -0.2860509
## X454 -0.3725266 -0.3558707 2.8523090 -0.317157 -0.3211537 -0.2860509
## FP055 FP056 FP057 FP058 FP059 FP060
## X1 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X2 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X3 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X4 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X5 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X6 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X7 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X8 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X9 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X10 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X11 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X12 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X13 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X14 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X15 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X16 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X17 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X18 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X19 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X20 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X21 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X22 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X23 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X24 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X25 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X26 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X27 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X28 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X29 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X30 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X31 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X32 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X33 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X34 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X35 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X36 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X37 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X38 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X39 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X40 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X41 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X42 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X43 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X44 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X45 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X46 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X47 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X48 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X49 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X50 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 1.0369606
## X51 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X52 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X53 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X54 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X55 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X56 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X57 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X58 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X59 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X60 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X61 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X62 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X63 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X64 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X65 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X66 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X67 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X68 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X69 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X70 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X71 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X72 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X73 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X74 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X75 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X76 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X77 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X78 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X79 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X80 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X81 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X82 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X83 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X84 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X85 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X86 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X87 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X88 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 1.0369606
## X89 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X90 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X91 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X92 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X93 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X94 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X95 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X96 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X97 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X98 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X99 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X100 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X101 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X102 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X103 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X104 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X105 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X106 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X107 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X108 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X109 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X110 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X111 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X112 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X113 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X114 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X115 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X116 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X117 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X118 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X119 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X120 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X121 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X122 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X123 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X124 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X125 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X126 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X127 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X128 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X129 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X130 -0.2379224 3.7846575 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X131 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X132 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X133 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X134 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X135 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X136 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X137 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X138 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X139 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X140 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X141 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X142 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X143 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X144 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X145 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X146 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X147 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X148 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X149 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X150 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X151 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X152 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X153 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X154 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X155 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X156 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X157 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X158 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X159 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X160 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 1.0369606
## X161 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X162 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X163 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X164 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X165 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X166 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X167 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X168 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X169 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X170 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X171 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X172 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X173 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X174 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X175 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X176 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X177 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X178 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X179 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X180 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X181 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X182 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X183 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X184 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X185 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X186 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X187 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X188 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X189 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X190 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X191 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X192 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X193 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X194 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X195 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X196 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X197 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X198 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X199 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X200 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X201 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X202 4.1986310 3.7846575 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X203 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 1.0369606
## X204 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X205 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X206 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X207 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X208 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X209 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X210 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X211 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X212 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X213 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X214 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 1.0369606
## X215 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X216 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X217 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X218 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X219 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X220 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X221 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X222 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X223 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X224 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X225 -0.2379224 3.7846575 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X226 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X227 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X228 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X229 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X230 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X231 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X232 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X233 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X234 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X235 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X236 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X237 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X238 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X239 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X240 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X241 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X242 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X243 4.1986310 3.7846575 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X244 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X245 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X246 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 1.0369606
## X247 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X248 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X249 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X250 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X251 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X252 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X253 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X254 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X255 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X256 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X257 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X258 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X259 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X260 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X261 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X262 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X263 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X264 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X265 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X266 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X267 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X268 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X269 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X270 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X271 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X272 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X273 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X274 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X275 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X276 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X277 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X278 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X279 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X280 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X281 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X282 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X283 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X284 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X285 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X286 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X287 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X288 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X289 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X290 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X291 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X292 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X293 4.1986310 3.7846575 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X294 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X295 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X296 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X297 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X298 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X299 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X300 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X301 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X302 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X303 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X304 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X305 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X306 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X307 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X308 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X309 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X310 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X311 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X312 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X313 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X314 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X315 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X316 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X317 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X318 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X319 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 1.0369606
## X320 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X321 4.1986310 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X322 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X323 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X324 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X325 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X326 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X327 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X328 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X329 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X330 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X331 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X332 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X333 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X334 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X335 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X336 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X337 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X338 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X339 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X340 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X341 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X342 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X343 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X344 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X345 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X346 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X347 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X348 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X349 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X350 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X351 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X352 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X353 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X354 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X355 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X356 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X357 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X358 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X359 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X360 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X361 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X362 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X363 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X364 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X365 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X366 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X367 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X368 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X369 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X370 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X371 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X372 4.1986310 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X373 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X374 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X375 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X376 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X377 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X378 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X379 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X380 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X381 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X382 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X383 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X384 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X385 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X386 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X387 4.1986310 -0.2639469 -0.3688597 2.7923732 -0.2403773 1.0369606
## X388 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X389 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X390 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X391 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X392 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X393 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 -0.9633427
## X394 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X395 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X396 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X397 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X398 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X399 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X400 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X401 -0.2379224 3.7846575 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X402 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X403 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X404 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X405 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X406 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X407 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X408 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X409 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X410 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X411 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X412 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X413 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X414 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X415 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X416 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X417 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X418 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X419 -0.2379224 -0.2639469 2.7082069 2.7923732 -0.2403773 1.0369606
## X420 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X421 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## X422 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X423 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X424 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X425 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X426 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X427 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X428 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X429 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 -0.9633427
## X430 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X431 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X432 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X433 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X434 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X435 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X436 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X437 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X438 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X439 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X440 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X441 -0.2379224 -0.2639469 -0.3688597 2.7923732 -0.2403773 -0.9633427
## X442 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X443 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X444 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X445 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X446 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X447 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X448 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 -0.9633427
## X449 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X450 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 -0.9633427
## X451 -0.2379224 -0.2639469 -0.3688597 -0.3577418 4.1557529 1.0369606
## X452 4.1986310 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X453 -0.2379224 -0.2639469 -0.3688597 -0.3577418 -0.2403773 1.0369606
## X454 -0.2379224 -0.2639469 2.7082069 -0.3577418 -0.2403773 1.0369606
## FP061 FP062 FP063 FP064 FP065 FP066
## X1 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X2 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 -1.2496793
## X3 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X4 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X5 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X6 -0.898407 1.1334484 1.1604872 1.1832335 -1.2065786 0.7993638
## X7 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X8 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X9 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X10 -0.898407 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X11 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X12 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X13 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X14 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X15 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X16 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X17 1.111911 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X18 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 -1.2496793
## X19 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X20 -0.898407 -0.8813356 -0.8608009 1.1832335 0.8279183 0.7993638
## X21 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X22 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X23 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X24 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X25 1.111911 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X26 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X27 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X28 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X29 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X30 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X31 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X32 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X33 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X34 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X35 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X36 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X37 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X38 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X39 1.111911 -0.8813356 -0.8608009 1.1832335 0.8279183 0.7993638
## X40 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X41 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X42 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 -1.2496793
## X43 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X44 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X45 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X46 -0.898407 1.1334484 1.1604872 -0.8442531 -1.2065786 0.7993638
## X47 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X48 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X49 1.111911 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X50 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X51 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X52 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X53 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X54 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X55 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X56 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X57 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X58 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X59 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X60 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X61 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X62 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X63 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X64 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X65 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X66 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X67 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X68 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X69 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X70 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X71 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X72 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X73 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X74 -0.898407 -0.8813356 1.1604872 1.1832335 -1.2065786 0.7993638
## X75 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X76 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X77 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X78 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X79 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X80 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X81 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X82 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X83 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X84 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X85 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X86 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X87 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X88 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 -1.2496793
## X89 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X90 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X91 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X92 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X93 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X94 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X95 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X96 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 -1.2496793
## X97 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X98 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X99 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X100 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X101 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X102 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X103 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X104 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X105 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X106 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X107 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X108 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X109 1.111911 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X110 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X111 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X112 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X113 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X114 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X115 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X116 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X117 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X118 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X119 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X120 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X121 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X122 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X123 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X124 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X125 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X126 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X127 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X128 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X129 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X130 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X131 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X132 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X133 -0.898407 -0.8813356 -0.8608009 1.1832335 0.8279183 0.7993638
## X134 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X135 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X136 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X137 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X138 1.111911 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X139 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X140 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X141 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X142 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X143 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X144 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X145 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X146 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X147 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X148 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X149 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X150 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X151 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X152 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X153 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X154 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X155 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X156 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X157 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X158 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X159 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X160 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X161 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X162 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X163 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X164 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X165 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X166 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X167 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X168 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X169 1.111911 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X170 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X171 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X172 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X173 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X174 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X175 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X176 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X177 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X178 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X179 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X180 1.111911 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X181 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X182 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X183 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X184 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X185 1.111911 -0.8813356 -0.8608009 1.1832335 0.8279183 0.7993638
## X186 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 -1.2496793
## X187 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X188 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X189 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X190 1.111911 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X191 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X192 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X193 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 -1.2496793
## X194 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X195 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X196 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X197 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X198 -0.898407 1.1334484 1.1604872 1.1832335 -1.2065786 0.7993638
## X199 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X200 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X201 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X202 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X203 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X204 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X205 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X206 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X207 1.111911 -0.8813356 -0.8608009 1.1832335 0.8279183 0.7993638
## X208 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X209 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X210 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X211 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X212 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X213 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X214 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X215 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X216 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X217 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X218 1.111911 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X219 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X220 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X221 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X222 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X223 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X224 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X225 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X226 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X227 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X228 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X229 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X230 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X231 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X232 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X233 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X234 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X235 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X236 1.111911 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X237 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X238 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X239 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 -1.2496793
## X240 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X241 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X242 -0.898407 -0.8813356 -0.8608009 1.1832335 0.8279183 -1.2496793
## X243 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X244 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X245 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X246 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X247 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X248 -0.898407 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X249 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X250 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X251 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X252 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 -1.2496793
## X253 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X254 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X255 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 -1.2496793
## X256 1.111911 1.1334484 1.1604872 1.1832335 -1.2065786 0.7993638
## X257 -0.898407 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X258 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X259 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X260 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 -1.2496793
## X261 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X262 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 -1.2496793
## X263 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X264 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X265 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X266 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X267 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X268 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X269 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X270 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X271 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X272 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X273 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X274 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X275 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X276 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X277 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X278 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X279 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X280 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X281 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X282 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X283 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X284 1.111911 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X285 -0.898407 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X286 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X287 1.111911 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X288 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 -1.2496793
## X289 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X290 -0.898407 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X291 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X292 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X293 1.111911 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X294 -0.898407 -0.8813356 -0.8608009 1.1832335 0.8279183 0.7993638
## X295 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X296 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X297 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X298 -0.898407 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X299 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X300 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X301 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X302 1.111911 1.1334484 1.1604872 1.1832335 -1.2065786 0.7993638
## X303 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X304 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X305 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X306 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X307 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X308 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X309 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X310 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X311 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X312 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X313 -0.898407 -0.8813356 1.1604872 1.1832335 -1.2065786 0.7993638
## X314 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X315 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X316 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X317 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X318 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X319 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X320 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X321 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X322 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X323 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X324 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X325 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X326 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X327 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X328 1.111911 1.1334484 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X329 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X330 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X331 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X332 -0.898407 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X333 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X334 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X335 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X336 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X337 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X338 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X339 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X340 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X341 -0.898407 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X342 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X343 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X344 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X345 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X346 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X347 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X348 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X349 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X350 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 -1.2496793
## X351 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X352 -0.898407 -0.8813356 1.1604872 1.1832335 -1.2065786 0.7993638
## X353 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X354 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X355 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 -1.2496793
## X356 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X357 1.111911 -0.8813356 -0.8608009 1.1832335 0.8279183 0.7993638
## X358 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X359 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X360 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X361 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X362 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X363 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X364 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X365 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X366 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X367 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X368 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X369 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X370 1.111911 -0.8813356 1.1604872 1.1832335 0.8279183 -1.2496793
## X371 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X372 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X373 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X374 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X375 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X376 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X377 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X378 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X379 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X380 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X381 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 -1.2496793
## X382 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X383 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X384 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X385 1.111911 1.1334484 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X386 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X387 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X388 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X389 1.111911 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X390 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X391 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X392 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X393 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X394 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X395 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X396 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X397 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 -1.2496793
## X398 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X399 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X400 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X401 -0.898407 -0.8813356 1.1604872 1.1832335 0.8279183 0.7993638
## X402 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 -1.2496793
## X403 1.111911 -0.8813356 -0.8608009 1.1832335 0.8279183 0.7993638
## X404 -0.898407 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X405 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X406 1.111911 1.1334484 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X407 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X408 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X409 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X410 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X411 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X412 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X413 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X414 -0.898407 -0.8813356 1.1604872 1.1832335 -1.2065786 0.7993638
## X415 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 0.7993638
## X416 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X417 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X418 1.111911 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X419 1.111911 1.1334484 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X420 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X421 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X422 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 -1.2496793
## X423 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X424 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X425 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X426 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X427 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X428 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X429 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X430 -0.898407 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X431 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X432 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 -1.2496793
## X433 -0.898407 -0.8813356 -0.8608009 -0.8442531 -1.2065786 -1.2496793
## X434 -0.898407 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X435 -0.898407 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X436 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 0.7993638
## X437 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X438 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## X439 -0.898407 -0.8813356 -0.8608009 1.1832335 -1.2065786 0.7993638
## X440 -0.898407 -0.8813356 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X441 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X442 1.111911 -0.8813356 1.1604872 -0.8442531 0.8279183 0.7993638
## X443 1.111911 1.1334484 1.1604872 1.1832335 0.8279183 0.7993638
## X444 1.111911 1.1334484 1.1604872 1.1832335 -1.2065786 0.7993638
## X445 -0.898407 1.1334484 1.1604872 1.1832335 -1.2065786 0.7993638
## X446 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 0.7993638
## X447 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X448 -0.898407 1.1334484 1.1604872 1.1832335 -1.2065786 0.7993638
## X449 1.111911 1.1334484 1.1604872 -0.8442531 0.8279183 -1.2496793
## X450 -0.898407 -0.8813356 1.1604872 -0.8442531 0.8279183 -1.2496793
## X451 1.111911 1.1334484 -0.8608009 1.1832335 -1.2065786 0.7993638
## X452 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 -1.2496793
## X453 1.111911 1.1334484 -0.8608009 -0.8442531 0.8279183 0.7993638
## X454 1.111911 1.1334484 -0.8608009 1.1832335 0.8279183 0.7993638
## FP067 FP068 FP069 FP070 FP071 FP072
## X1 1.2777443 -0.7524132 1.3276594 1.3459950 -0.6967256 -1.3871296
## X2 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X3 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X4 -0.7818063 -0.7524132 1.3276594 1.3459950 -0.6967256 -1.3871296
## X5 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X6 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X7 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 -1.3871296
## X8 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X9 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X10 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X11 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X12 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X13 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X14 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X15 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X16 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X17 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X18 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X19 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X20 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X21 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 0.7201551
## X22 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X23 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X24 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X25 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 0.7201551
## X26 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X27 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 0.7201551
## X28 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X29 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 0.7201551
## X30 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X31 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X32 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X33 -0.7818063 -0.7524132 1.3276594 -0.7421636 1.4337761 -1.3871296
## X34 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X35 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X36 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X37 -0.7818063 -0.7524132 1.3276594 -0.7421636 1.4337761 -1.3871296
## X38 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X39 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X40 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X41 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X42 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X43 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X44 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X45 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 -1.3871296
## X46 -0.7818063 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X47 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X48 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X49 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 0.7201551
## X50 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 0.7201551
## X51 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X52 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X53 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X54 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X55 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X56 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X57 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X58 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X59 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X60 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X61 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X62 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X63 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X64 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X65 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X66 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X67 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X68 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X69 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X70 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X71 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X72 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X73 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X74 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X75 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X76 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X77 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X78 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X79 -0.7818063 -0.7524132 1.3276594 1.3459950 -0.6967256 -1.3871296
## X80 -0.7818063 -0.7524132 1.3276594 1.3459950 -0.6967256 0.7201551
## X81 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X82 1.2777443 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X83 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 -1.3871296
## X84 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X85 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X86 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X87 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X88 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X89 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X90 -0.7818063 -0.7524132 1.3276594 1.3459950 -0.6967256 0.7201551
## X91 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X92 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X93 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X94 -0.7818063 -0.7524132 1.3276594 1.3459950 -0.6967256 0.7201551
## X95 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 0.7201551
## X96 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X97 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X98 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X99 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X100 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X101 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X102 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 -1.3871296
## X103 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X104 1.2777443 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X105 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X106 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X107 1.2777443 1.3276594 1.3276594 -0.7421636 1.4337761 -1.3871296
## X108 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X109 -0.7818063 -0.7524132 1.3276594 1.3459950 -0.6967256 0.7201551
## X110 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X111 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X112 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X113 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X114 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X115 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X116 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X117 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X118 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X119 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X120 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X121 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X122 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X123 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X124 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X125 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X126 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X127 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X128 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X129 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X130 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X131 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X132 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X133 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X134 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X135 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X136 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X137 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X138 -0.7818063 -0.7524132 1.3276594 1.3459950 -0.6967256 0.7201551
## X139 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X140 1.2777443 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X141 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X142 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X143 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X144 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X145 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X146 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X147 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X148 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X149 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X150 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X151 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X152 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X153 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X154 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X155 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X156 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X157 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X158 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X159 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X160 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X161 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X162 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X163 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 -1.3871296
## X164 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X165 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X166 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X167 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X168 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 -1.3871296
## X169 -0.7818063 -0.7524132 1.3276594 1.3459950 -0.6967256 0.7201551
## X170 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X171 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X172 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X173 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X174 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X175 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X176 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 -1.3871296
## X177 -0.7818063 -0.7524132 1.3276594 1.3459950 -0.6967256 0.7201551
## X178 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X179 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X180 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X181 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 -1.3871296
## X182 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X183 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X184 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X185 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X186 -0.7818063 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X187 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X188 -0.7818063 1.3276594 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X189 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X190 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X191 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X192 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X193 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X194 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X195 -0.7818063 -0.7524132 1.3276594 -0.7421636 1.4337761 -1.3871296
## X196 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X197 1.2777443 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X198 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X199 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X200 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X201 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X202 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X203 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X204 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X205 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X206 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X207 -0.7818063 -0.7524132 1.3276594 1.3459950 -0.6967256 0.7201551
## X208 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X209 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X210 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X211 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X212 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X213 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X214 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X215 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X216 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X217 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X218 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X219 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X220 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X221 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X222 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X223 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X224 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X225 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X226 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X227 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X228 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X229 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X230 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X231 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X232 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X233 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X234 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X235 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X236 1.2777443 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X237 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X238 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 -1.3871296
## X239 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 0.7201551
## X240 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X241 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X242 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X243 1.2777443 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X244 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 0.7201551
## X245 -0.7818063 -0.7524132 1.3276594 -0.7421636 1.4337761 0.7201551
## X246 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X247 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X248 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X249 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X250 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X251 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X252 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X253 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X254 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 0.7201551
## X255 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X256 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X257 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X258 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X259 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X260 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X261 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X262 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 -1.3871296
## X263 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X264 1.2777443 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X265 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X266 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X267 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X268 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X269 -0.7818063 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X270 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X271 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 0.7201551
## X272 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X273 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X274 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X275 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X276 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X277 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X278 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X279 1.2777443 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X280 -0.7818063 -0.7524132 1.3276594 -0.7421636 1.4337761 0.7201551
## X281 -0.7818063 -0.7524132 1.3276594 -0.7421636 1.4337761 -1.3871296
## X282 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X283 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X284 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X285 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X286 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X287 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X288 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X289 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X290 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X291 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X292 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X293 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X294 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X295 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 0.7201551
## X296 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 0.7201551
## X297 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X298 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X299 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X300 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X301 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X302 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X303 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 -1.3871296
## X304 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X305 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X306 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X307 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X308 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X309 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X310 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X311 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X312 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X313 -0.7818063 1.3276594 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X314 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X315 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X316 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X317 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X318 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X319 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X320 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 -1.3871296
## X321 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 0.7201551
## X322 1.2777443 1.3276594 1.3276594 -0.7421636 1.4337761 0.7201551
## X323 1.2777443 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X324 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X325 -0.7818063 -0.7524132 1.3276594 -0.7421636 1.4337761 -1.3871296
## X326 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X327 -0.7818063 -0.7524132 1.3276594 -0.7421636 1.4337761 -1.3871296
## X328 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 0.7201551
## X329 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X330 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X331 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X332 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X333 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X334 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X335 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X336 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X337 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X338 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X339 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X340 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X341 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X342 -0.7818063 -0.7524132 1.3276594 -0.7421636 1.4337761 -1.3871296
## X343 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X344 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X345 1.2777443 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X346 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X347 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X348 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X349 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X350 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X351 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X352 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X353 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X354 -0.7818063 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X355 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X356 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X357 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X358 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X359 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X360 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X361 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X362 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X363 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X364 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X365 1.2777443 1.3276594 1.3276594 -0.7421636 1.4337761 0.7201551
## X366 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X367 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X368 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X369 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X370 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X371 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X372 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X373 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X374 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X375 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 0.7201551
## X376 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X377 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X378 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X379 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X380 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X381 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 0.7201551
## X382 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X383 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X384 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X385 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X386 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X387 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X388 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X389 1.2777443 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X390 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X391 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X392 -0.7818063 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X393 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X394 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X395 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X396 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X397 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X398 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X399 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X400 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X401 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X402 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X403 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 0.7201551
## X404 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X405 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X406 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X407 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X408 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X409 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X410 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X411 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X412 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X413 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X414 -0.7818063 1.3276594 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X415 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X416 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X417 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X418 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X419 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X420 1.2777443 1.3276594 1.3276594 -0.7421636 1.4337761 -1.3871296
## X421 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X422 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 0.7201551
## X423 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X424 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X425 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X426 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X427 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X428 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X429 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X430 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X431 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X432 -0.7818063 -0.7524132 -0.7524132 -0.7421636 1.4337761 0.7201551
## X433 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X434 1.2777443 1.3276594 -0.7524132 -0.7421636 1.4337761 0.7201551
## X435 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X436 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X437 1.2777443 1.3276594 1.3276594 1.3459950 1.4337761 0.7201551
## X438 -0.7818063 -0.7524132 1.3276594 1.3459950 1.4337761 0.7201551
## X439 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 -1.3871296
## X440 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 -1.3871296
## X441 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X442 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X443 1.2777443 1.3276594 -0.7524132 1.3459950 1.4337761 0.7201551
## X444 1.2777443 1.3276594 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X445 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X446 1.2777443 1.3276594 1.3276594 -0.7421636 -0.6967256 0.7201551
## X447 -0.7818063 -0.7524132 1.3276594 -0.7421636 -0.6967256 0.7201551
## X448 1.2777443 1.3276594 1.3276594 1.3459950 -0.6967256 0.7201551
## X449 1.2777443 1.3276594 -0.7524132 1.3459950 -0.6967256 0.7201551
## X450 1.2777443 -0.7524132 -0.7524132 -0.7421636 1.4337761 -1.3871296
## X451 -0.7818063 -0.7524132 -0.7524132 -0.7421636 -0.6967256 0.7201551
## X452 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## X453 -0.7818063 -0.7524132 -0.7524132 1.3459950 -0.6967256 0.7201551
## X454 -0.7818063 -0.7524132 -0.7524132 1.3459950 1.4337761 0.7201551
## FP073 FP074 FP075 FP076 FP077 FP078
## X1 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X2 1.4904330 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X3 1.4904330 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X4 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X5 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X6 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X7 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X8 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X9 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X10 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X11 -0.6702404 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X12 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X13 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X14 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X15 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X16 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X17 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 1.5126959
## X18 1.4904330 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X19 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X20 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X21 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X22 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X23 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X24 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X25 -0.6702404 1.4406544 1.3969116 -0.6983906 1.4545809 -0.6603763
## X26 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X27 -0.6702404 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X28 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X29 -0.6702404 1.4406544 1.3969116 -0.6983906 -0.6867603 1.5126959
## X30 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X31 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X32 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X33 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X34 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X35 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X36 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X37 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X38 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X39 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X40 1.4904330 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X41 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X42 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X43 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X44 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X45 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X46 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X47 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X48 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X49 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X50 1.4904330 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X51 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X52 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X53 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X54 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X55 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X56 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X57 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X58 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X59 -0.6702404 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X60 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X61 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X62 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X63 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X64 -0.6702404 -0.6933991 -0.7151122 1.4303578 1.4545809 -0.6603763
## X65 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X66 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X67 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X68 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X69 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X70 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X71 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X72 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X73 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X74 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X75 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X76 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X77 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X78 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X79 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X80 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X81 -0.6702404 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X82 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X83 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X84 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X85 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X86 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X87 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X88 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 -0.6603763
## X89 -0.6702404 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X90 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X91 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X92 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X93 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X94 -0.6702404 1.4406544 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X95 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X96 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X97 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X98 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X99 -0.6702404 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X100 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X101 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X102 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X103 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X104 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X105 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 1.5126959
## X106 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X107 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X108 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X109 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X110 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X111 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X112 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X113 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X114 -0.6702404 1.4406544 1.3969116 -0.6983906 -0.6867603 1.5126959
## X115 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X116 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X117 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X118 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X119 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X120 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X121 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X122 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X123 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 1.5126959
## X124 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X125 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X126 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X127 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X128 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X129 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X130 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X131 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X132 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X133 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X134 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X135 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X136 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X137 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X138 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X139 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X140 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X141 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X142 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X143 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X144 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X145 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X146 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X147 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X148 -0.6702404 -0.6933991 -0.7151122 1.4303578 1.4545809 -0.6603763
## X149 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X150 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X151 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X152 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X153 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X154 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X155 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X156 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X157 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X158 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X159 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X160 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X161 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X162 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X163 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X164 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X165 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X166 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X167 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X168 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X169 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X170 -0.6702404 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X171 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X172 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X173 1.4904330 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X174 1.4904330 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X175 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X176 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X177 -0.6702404 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X178 1.4904330 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X179 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X180 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X181 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X182 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X183 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X184 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X185 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X186 1.4904330 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X187 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X188 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X189 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X190 -0.6702404 1.4406544 1.3969116 -0.6983906 -0.6867603 1.5126959
## X191 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X192 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 1.5126959
## X193 -0.6702404 -0.6933991 -0.7151122 1.4303578 1.4545809 -0.6603763
## X194 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X195 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X196 -0.6702404 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X197 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 1.5126959
## X198 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X199 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X200 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X201 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X202 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X203 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X204 -0.6702404 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X205 1.4904330 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X206 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X207 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X208 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X209 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X210 -0.6702404 -0.6933991 -0.7151122 1.4303578 1.4545809 -0.6603763
## X211 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X212 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X213 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X214 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X215 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X216 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X217 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X218 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X219 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X220 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X221 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X222 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X223 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X224 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X225 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X226 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X227 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X228 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X229 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X230 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X231 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X232 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X233 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 1.5126959
## X234 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X235 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X236 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 1.5126959
## X237 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X238 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X239 1.4904330 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X240 1.4904330 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X241 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X242 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X243 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X244 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 1.5126959
## X245 1.4904330 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X246 -0.6702404 1.4406544 -0.7151122 1.4303578 1.4545809 -0.6603763
## X247 -0.6702404 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X248 -0.6702404 1.4406544 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X249 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X250 1.4904330 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X251 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X252 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X253 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X254 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X255 1.4904330 -0.6933991 1.3969116 -0.6983906 -0.6867603 1.5126959
## X256 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X257 -0.6702404 1.4406544 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X258 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X259 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X260 1.4904330 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X261 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 1.5126959
## X262 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X263 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X264 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X265 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X266 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X267 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X268 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X269 -0.6702404 1.4406544 1.3969116 -0.6983906 1.4545809 1.5126959
## X270 1.4904330 1.4406544 -0.7151122 -0.6983906 1.4545809 1.5126959
## X271 1.4904330 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X272 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X273 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X274 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 1.5126959
## X275 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X276 1.4904330 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X277 1.4904330 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X278 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X279 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X280 1.4904330 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X281 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X282 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 1.5126959
## X283 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X284 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X285 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X286 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X287 -0.6702404 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X288 1.4904330 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X289 1.4904330 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X290 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 1.5126959
## X291 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X292 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X293 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X294 -0.6702404 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X295 -0.6702404 1.4406544 1.3969116 -0.6983906 -0.6867603 1.5126959
## X296 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 1.5126959
## X297 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X298 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X299 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 1.5126959
## X300 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X301 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X302 1.4904330 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X303 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X304 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 1.5126959
## X305 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X306 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X307 1.4904330 1.4406544 1.3969116 1.4303578 1.4545809 -0.6603763
## X308 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X309 1.4904330 1.4406544 1.3969116 1.4303578 1.4545809 -0.6603763
## X310 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X311 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X312 1.4904330 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X313 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X314 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X315 -0.6702404 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X316 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X317 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X318 -0.6702404 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X319 -0.6702404 1.4406544 1.3969116 1.4303578 1.4545809 -0.6603763
## X320 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X321 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X322 -0.6702404 1.4406544 1.3969116 -0.6983906 1.4545809 1.5126959
## X323 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X324 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X325 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X326 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X327 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X328 1.4904330 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X329 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X330 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X331 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X332 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X333 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X334 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X335 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X336 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X337 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 1.5126959
## X338 -0.6702404 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X339 -0.6702404 1.4406544 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X340 1.4904330 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X341 -0.6702404 1.4406544 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X342 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X343 -0.6702404 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X344 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 1.5126959
## X345 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X346 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 1.5126959
## X347 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X348 1.4904330 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X349 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X350 1.4904330 1.4406544 1.3969116 1.4303578 -0.6867603 -0.6603763
## X351 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X352 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X353 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X354 -0.6702404 1.4406544 1.3969116 1.4303578 1.4545809 -0.6603763
## X355 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X356 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X357 -0.6702404 1.4406544 1.3969116 -0.6983906 -0.6867603 1.5126959
## X358 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X359 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 1.5126959
## X360 -0.6702404 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X361 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X362 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X363 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X364 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X365 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X366 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X367 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X368 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X369 -0.6702404 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X370 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 1.5126959
## X371 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X372 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X373 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X374 1.4904330 -0.6933991 1.3969116 1.4303578 -0.6867603 1.5126959
## X375 -0.6702404 1.4406544 1.3969116 -0.6983906 -0.6867603 1.5126959
## X376 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X377 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X378 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 -0.6603763
## X379 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X380 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X381 1.4904330 1.4406544 -0.7151122 -0.6983906 1.4545809 1.5126959
## X382 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X383 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X384 -0.6702404 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X385 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X386 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X387 1.4904330 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X388 1.4904330 1.4406544 1.3969116 1.4303578 -0.6867603 1.5126959
## X389 -0.6702404 1.4406544 1.3969116 -0.6983906 -0.6867603 1.5126959
## X390 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 1.5126959
## X391 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X392 -0.6702404 1.4406544 1.3969116 -0.6983906 1.4545809 1.5126959
## X393 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X394 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X395 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X396 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X397 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X398 1.4904330 1.4406544 -0.7151122 -0.6983906 1.4545809 1.5126959
## X399 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X400 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X401 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X402 1.4904330 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X403 1.4904330 1.4406544 -0.7151122 -0.6983906 1.4545809 1.5126959
## X404 -0.6702404 1.4406544 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X405 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 1.5126959
## X406 1.4904330 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X407 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 1.5126959
## X408 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X409 -0.6702404 -0.6933991 1.3969116 1.4303578 1.4545809 1.5126959
## X410 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 1.5126959
## X411 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X412 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X413 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X414 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X415 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X416 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X417 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 -0.6603763
## X418 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X419 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 -0.6603763
## X420 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X421 1.4904330 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X422 1.4904330 1.4406544 -0.7151122 -0.6983906 -0.6867603 1.5126959
## X423 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X424 1.4904330 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X425 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X426 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X427 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X428 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X429 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X430 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X431 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X432 1.4904330 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X433 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X434 -0.6702404 -0.6933991 -0.7151122 1.4303578 -0.6867603 1.5126959
## X435 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X436 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X437 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X438 1.4904330 1.4406544 -0.7151122 1.4303578 1.4545809 1.5126959
## X439 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X440 -0.6702404 -0.6933991 -0.7151122 -0.6983906 -0.6867603 -0.6603763
## X441 -0.6702404 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X442 1.4904330 1.4406544 1.3969116 1.4303578 1.4545809 1.5126959
## X443 -0.6702404 -0.6933991 1.3969116 1.4303578 -0.6867603 1.5126959
## X444 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X445 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X446 -0.6702404 1.4406544 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X447 -0.6702404 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X448 -0.6702404 -0.6933991 1.3969116 -0.6983906 1.4545809 -0.6603763
## X449 -0.6702404 1.4406544 1.3969116 1.4303578 1.4545809 -0.6603763
## X450 -0.6702404 -0.6933991 1.3969116 -0.6983906 -0.6867603 -0.6603763
## X451 1.4904330 -0.6933991 -0.7151122 -0.6983906 1.4545809 -0.6603763
## X452 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X453 -0.6702404 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## X454 1.4904330 1.4406544 -0.7151122 1.4303578 -0.6867603 1.5126959
## FP079 FP080 FP081 FP082 FP083 FP084
## X1 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X2 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X3 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X4 0.6702404 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X5 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 1.5791449
## X6 -1.4904330 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X7 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X8 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X9 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X10 0.6702404 -0.6587354 1.6080912 0.6325882 1.6293857 -0.6325882
## X11 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X12 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X13 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X14 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X15 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X16 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X17 0.6702404 1.5164639 1.6080912 0.6325882 1.6293857 1.5791449
## X18 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X19 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X20 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X21 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X22 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X23 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X24 0.6702404 1.5164639 -0.6212014 -1.5791449 1.6293857 1.5791449
## X25 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 -0.6325882
## X26 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X27 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X28 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X29 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X30 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X31 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X32 -1.4904330 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X33 0.6702404 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X34 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X35 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X36 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X37 0.6702404 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X38 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X39 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X40 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X41 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X42 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 -0.6325882
## X43 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X44 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X45 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X46 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X47 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X48 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X49 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X50 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X51 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X52 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X53 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X54 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 1.5791449
## X55 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X56 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X57 0.6702404 1.5164639 1.6080912 0.6325882 1.6293857 -0.6325882
## X58 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X59 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 1.5791449
## X60 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X61 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X62 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X63 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X64 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X65 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X66 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X67 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X68 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X69 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X70 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X71 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X72 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X73 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X74 -1.4904330 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X75 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X76 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X77 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X78 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X79 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X80 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X81 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X82 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X83 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X84 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X85 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X86 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X87 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X88 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X89 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 -0.6325882
## X90 -1.4904330 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X91 0.6702404 1.5164639 1.6080912 0.6325882 1.6293857 -0.6325882
## X92 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X93 -1.4904330 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X94 -1.4904330 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X95 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X96 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X97 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X98 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X99 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X100 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X101 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X102 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X103 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X104 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X105 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X106 0.6702404 -0.6587354 1.6080912 -1.5791449 -0.6130829 1.5791449
## X107 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X108 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X109 -1.4904330 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X110 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X111 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X112 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X113 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X114 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X115 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X116 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X117 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X118 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X119 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X120 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X121 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X122 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X123 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X124 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X125 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X126 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X127 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X128 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X129 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X130 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X131 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X132 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X133 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X134 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X135 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X136 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X137 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X138 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X139 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X140 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X141 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X142 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X143 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X144 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X145 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X146 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X147 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X148 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X149 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X150 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X151 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X152 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X153 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X154 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X155 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X156 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X157 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X158 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X159 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X160 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X161 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X162 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X163 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X164 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X165 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X166 0.6702404 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X167 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X168 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X169 -1.4904330 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X170 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X171 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X172 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X173 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X174 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X175 -1.4904330 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X176 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X177 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 1.5791449
## X178 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X179 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X180 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X181 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X182 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X183 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X184 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X185 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X186 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X187 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X188 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X189 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X190 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X191 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X192 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X193 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X194 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X195 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X196 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X197 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X198 -1.4904330 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X199 -1.4904330 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X200 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X201 0.6702404 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X202 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X203 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X204 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X205 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X206 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X207 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X208 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X209 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X210 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X211 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X212 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X213 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X214 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X215 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X216 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X217 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X218 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X219 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X220 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X221 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X222 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X223 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X224 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X225 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X226 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X227 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X228 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X229 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X230 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X231 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X232 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X233 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X234 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X235 0.6702404 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X236 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X237 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X238 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X239 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X240 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X241 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X242 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X243 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X244 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X245 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X246 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 1.5791449
## X247 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X248 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X249 0.6702404 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X250 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X251 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 1.5791449
## X252 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 1.5791449
## X253 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X254 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X255 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X256 -1.4904330 1.5164639 1.6080912 -1.5791449 1.6293857 -0.6325882
## X257 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X258 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X259 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X260 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X261 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X262 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X263 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X264 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X265 -1.4904330 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X266 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X267 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X268 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X269 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X270 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X271 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X272 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X273 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X274 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X275 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X276 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X277 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X278 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X279 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X280 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X281 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X282 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X283 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X284 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X285 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X286 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X287 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X288 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X289 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X290 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X291 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X292 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X293 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X294 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X295 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X296 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X297 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X298 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X299 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X300 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X301 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X302 0.6702404 -0.6587354 1.6080912 0.6325882 1.6293857 -0.6325882
## X303 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 1.5791449
## X304 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X305 0.6702404 1.5164639 1.6080912 0.6325882 1.6293857 -0.6325882
## X306 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X307 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X308 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X309 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X310 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X311 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X312 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X313 -1.4904330 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X314 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X315 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X316 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X317 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X318 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X319 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 1.5791449
## X320 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 1.5791449
## X321 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X322 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 -0.6325882
## X323 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X324 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X325 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X326 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X327 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X328 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X329 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X330 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X331 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X332 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X333 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X334 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X335 0.6702404 1.5164639 1.6080912 0.6325882 1.6293857 -0.6325882
## X336 0.6702404 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X337 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X338 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X339 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X340 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X341 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X342 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X343 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X344 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X345 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X346 0.6702404 -0.6587354 1.6080912 0.6325882 1.6293857 1.5791449
## X347 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X348 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X349 0.6702404 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X350 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X351 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X352 -1.4904330 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X353 0.6702404 1.5164639 1.6080912 0.6325882 1.6293857 -0.6325882
## X354 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X355 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X356 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X357 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X358 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X359 0.6702404 -0.6587354 1.6080912 0.6325882 1.6293857 1.5791449
## X360 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X361 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X362 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X363 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X364 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X365 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X366 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X367 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X368 -1.4904330 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X369 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X370 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X371 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X372 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X373 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X374 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X375 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X376 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X377 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X378 0.6702404 1.5164639 1.6080912 0.6325882 1.6293857 1.5791449
## X379 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X380 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X381 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X382 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 1.5791449
## X383 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X384 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X385 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X386 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X387 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 1.5791449
## X388 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X389 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 1.5791449
## X390 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 1.5791449
## X391 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X392 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X393 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X394 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X395 0.6702404 1.5164639 1.6080912 0.6325882 1.6293857 -0.6325882
## X396 -1.4904330 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X397 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X398 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X399 0.6702404 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X400 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X401 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X402 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X403 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 -0.6325882
## X404 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X405 -1.4904330 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X406 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X407 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X408 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X409 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X410 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X411 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X412 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X413 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X414 -1.4904330 1.5164639 1.6080912 -1.5791449 1.6293857 -0.6325882
## X415 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X416 0.6702404 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X417 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X418 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X419 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X420 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X421 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X422 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X423 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X424 0.6702404 1.5164639 -0.6212014 0.6325882 1.6293857 1.5791449
## X425 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X426 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X427 -1.4904330 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X428 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X429 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X430 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X431 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X432 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X433 0.6702404 -0.6587354 -0.6212014 -1.5791449 -0.6130829 -0.6325882
## X434 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X435 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X436 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X437 0.6702404 -0.6587354 1.6080912 0.6325882 1.6293857 1.5791449
## X438 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X439 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X440 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X441 0.6702404 -0.6587354 1.6080912 0.6325882 -0.6130829 1.5791449
## X442 0.6702404 1.5164639 1.6080912 0.6325882 -0.6130829 1.5791449
## X443 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X444 -1.4904330 1.5164639 1.6080912 -1.5791449 1.6293857 -0.6325882
## X445 -1.4904330 1.5164639 1.6080912 0.6325882 -0.6130829 -0.6325882
## X446 0.6702404 -0.6587354 -0.6212014 0.6325882 1.6293857 -0.6325882
## X447 -1.4904330 1.5164639 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X448 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 -0.6325882
## X449 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## X450 -1.4904330 -0.6587354 -0.6212014 0.6325882 1.6293857 1.5791449
## X451 -1.4904330 -0.6587354 1.6080912 -1.5791449 -0.6130829 -0.6325882
## X452 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X453 0.6702404 -0.6587354 -0.6212014 0.6325882 -0.6130829 1.5791449
## X454 0.6702404 1.5164639 -0.6212014 0.6325882 -0.6130829 1.5791449
## FP085 FP086 FP087 FP088 FP089 FP090
## X1 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X2 1.706024 -0.6065954 0.6130829 1.6736342 1.7445930 1.7347883
## X3 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X4 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X5 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X6 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X7 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X8 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X9 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X10 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X11 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X12 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X13 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X14 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X15 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X16 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X17 1.706024 1.6468118 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X18 1.706024 -0.6065954 0.6130829 1.6736342 1.7445930 1.7347883
## X19 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X20 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X21 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X22 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X23 1.706024 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X24 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X25 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X26 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X27 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X28 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X29 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X30 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X31 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X32 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X33 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X34 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X35 1.706024 1.6468118 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X36 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X37 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X38 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X39 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 1.7347883
## X40 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X41 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X42 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X43 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X44 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 1.7347883
## X45 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X46 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X47 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X48 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X49 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X50 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X51 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X52 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X53 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X54 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X55 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X56 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X57 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X58 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X59 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X60 1.706024 1.6468118 0.6130829 1.6736342 1.7445930 -0.5758331
## X61 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X62 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X63 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X64 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X65 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X66 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X67 1.706024 1.6468118 0.6130829 1.6736342 1.7445930 1.7347883
## X68 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X69 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X70 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 1.7347883
## X71 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X72 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X73 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X74 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X75 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X76 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X77 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X78 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X79 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X80 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X81 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X82 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X83 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X84 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X85 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X86 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X87 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X88 -0.585542 -0.6065954 0.6130829 1.6736342 1.7445930 -0.5758331
## X89 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 1.7347883
## X90 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X91 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X92 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X93 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X94 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X95 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X96 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X97 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X98 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X99 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X100 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X101 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X102 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X103 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X104 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X105 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X106 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X107 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X108 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X109 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X110 1.706024 1.6468118 0.6130829 1.6736342 1.7445930 -0.5758331
## X111 1.706024 1.6468118 0.6130829 1.6736342 1.7445930 -0.5758331
## X112 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X113 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X114 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X115 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X116 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X117 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X118 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X119 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X120 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X121 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X122 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X123 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X124 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X125 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X126 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X127 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X128 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X129 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X130 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X131 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X132 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X133 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X134 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X135 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X136 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X137 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X138 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X139 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X140 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X141 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X142 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X143 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X144 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X145 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X146 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X147 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X148 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X149 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X150 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X151 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X152 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X153 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X154 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X155 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X156 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X157 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X158 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X159 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X160 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X161 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X162 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X163 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X164 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X165 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X166 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X167 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X168 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X169 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X170 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X171 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X172 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X173 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X174 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X175 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X176 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X177 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X178 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X179 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X180 1.706024 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X181 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X182 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X183 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X184 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X185 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 1.7347883
## X186 -0.585542 -0.6065954 0.6130829 1.6736342 1.7445930 1.7347883
## X187 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X188 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X189 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 1.7347883
## X190 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X191 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X192 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X193 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X194 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X195 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X196 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X197 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X198 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X199 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X200 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X201 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X202 1.706024 1.6468118 0.6130829 1.6736342 1.7445930 1.7347883
## X203 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X204 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X205 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X206 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X207 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X208 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X209 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X210 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X211 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X212 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X213 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X214 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X215 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X216 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X217 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X218 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X219 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X220 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X221 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X222 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X223 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X224 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X225 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X226 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X227 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X228 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X229 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X230 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X231 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X232 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X233 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X234 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X235 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X236 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X237 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X238 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X239 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X240 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X241 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X242 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X243 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X244 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X245 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X246 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 -0.5758331
## X247 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X248 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X249 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X250 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X251 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X252 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 1.7347883
## X253 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X254 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X255 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X256 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X257 -0.585542 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X258 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X259 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X260 -0.585542 -0.6065954 0.6130829 1.6736342 1.7445930 -0.5758331
## X261 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X262 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X263 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X264 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X265 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X266 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X267 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X268 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X269 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X270 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 -0.5758331
## X271 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X272 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X273 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X274 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X275 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X276 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X277 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 1.7347883
## X278 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X279 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X280 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X281 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X282 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X283 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X284 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X285 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X286 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X287 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X288 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X289 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X290 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X291 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X292 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X293 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X294 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X295 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X296 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X297 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X298 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X299 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X300 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X301 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X302 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X303 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X304 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X305 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X306 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X307 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 1.7347883
## X308 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X309 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 1.7347883
## X310 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X311 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X312 1.706024 1.6468118 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X313 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X314 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X315 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X316 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X317 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X318 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X319 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 -0.5758331
## X320 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X321 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X322 1.706024 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X323 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X324 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X325 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X326 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X327 1.706024 1.6468118 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X328 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X329 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X330 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X331 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X332 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X333 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 1.7347883
## X334 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X335 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X336 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X337 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X338 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X339 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X340 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X341 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X342 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X343 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 1.7347883
## X344 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X345 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X346 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X347 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X348 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 1.7347883
## X349 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X350 1.706024 -0.6065954 0.6130829 1.6736342 1.7445930 -0.5758331
## X351 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X352 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X353 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X354 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X355 -0.585542 -0.6065954 -1.6293857 1.6736342 -0.5725969 1.7347883
## X356 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X357 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X358 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X359 -0.585542 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X360 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X361 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 -0.5758331
## X362 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X363 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X364 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X365 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X366 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X367 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X368 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X369 -0.585542 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X370 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X371 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X372 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X373 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X374 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X375 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X376 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X377 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X378 1.706024 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X379 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X380 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X381 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X382 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X383 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X384 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X385 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X386 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X387 -0.585542 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X388 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X389 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X390 -0.585542 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X391 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X392 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X393 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X394 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X395 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X396 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X397 -0.585542 -0.6065954 0.6130829 1.6736342 1.7445930 -0.5758331
## X398 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X399 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X400 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X401 -0.585542 1.6468118 0.6130829 -0.5968738 1.7445930 -0.5758331
## X402 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X403 1.706024 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X404 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X405 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X406 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X407 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X408 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X409 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X410 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X411 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X412 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X413 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X414 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X415 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X416 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X417 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X418 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X419 -0.585542 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X420 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X421 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X422 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X423 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X424 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X425 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X426 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X427 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X428 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X429 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X430 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X431 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X432 1.706024 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X433 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X434 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X435 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X436 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X437 -0.585542 -0.6065954 0.6130829 1.6736342 -0.5725969 -0.5758331
## X438 -0.585542 1.6468118 0.6130829 1.6736342 -0.5725969 1.7347883
## X439 -0.585542 -0.6065954 -1.6293857 -0.5968738 -0.5725969 -0.5758331
## X440 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X441 -0.585542 1.6468118 0.6130829 1.6736342 1.7445930 -0.5758331
## X442 1.706024 1.6468118 0.6130829 -0.5968738 -0.5725969 1.7347883
## X443 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X444 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X445 -0.585542 1.6468118 -1.6293857 -0.5968738 -0.5725969 1.7347883
## X446 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X447 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X448 -0.585542 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X449 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 1.7347883
## X450 1.706024 -0.6065954 0.6130829 -0.5968738 -0.5725969 -0.5758331
## X451 -0.585542 1.6468118 -1.6293857 1.6736342 -0.5725969 1.7347883
## X452 1.706024 -0.6065954 0.6130829 1.6736342 1.7445930 -0.5758331
## X453 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## X454 1.706024 -0.6065954 0.6130829 -0.5968738 1.7445930 -0.5758331
## FP091 FP092 FP093 FP094 FP095 FP096
## X1 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X2 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X3 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X4 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X5 1.8548056 1.7595110 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X6 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X7 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X8 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X9 -0.5385731 1.7595110 1.7595110 -0.5483075 1.8832169 1.8948413
## X10 1.8548056 -0.5677421 1.7595110 -0.5483075 1.8832169 -0.5271937
## X11 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X12 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X13 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X14 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X15 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X16 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X17 1.8548056 -0.5677421 -0.5677421 1.8218763 -0.5304479 1.8948413
## X18 1.8548056 1.7595110 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X19 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X20 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X21 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X22 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X23 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X24 1.8548056 1.7595110 1.7595110 -0.5483075 1.8832169 -0.5271937
## X25 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X26 1.8548056 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X27 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X28 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X29 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X30 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X31 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X32 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X33 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X34 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X35 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X36 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X37 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X38 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X39 -0.5385731 -0.5677421 -0.5677421 1.8218763 1.8832169 -0.5271937
## X40 -0.5385731 1.7595110 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X41 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X42 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X43 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X44 1.8548056 1.7595110 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X45 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X46 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X47 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X48 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X49 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X50 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X51 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X52 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X53 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X54 1.8548056 1.7595110 -0.5677421 1.8218763 1.8832169 -0.5271937
## X55 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X56 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X57 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X58 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X59 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X60 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X61 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X62 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X63 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X64 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X65 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X66 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X67 1.8548056 1.7595110 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X68 -0.5385731 1.7595110 1.7595110 1.8218763 1.8832169 1.8948413
## X69 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X70 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X71 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X72 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X73 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X74 1.8548056 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X75 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X76 -0.5385731 1.7595110 1.7595110 -0.5483075 1.8832169 1.8948413
## X77 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X78 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X79 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X80 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X81 -0.5385731 1.7595110 1.7595110 -0.5483075 -0.5304479 1.8948413
## X82 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X83 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X84 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X85 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X86 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X87 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X88 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X89 1.8548056 1.7595110 1.7595110 -0.5483075 1.8832169 1.8948413
## X90 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X91 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X92 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X93 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X94 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 1.8948413
## X95 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X96 -0.5385731 1.7595110 -0.5677421 -0.5483075 1.8832169 1.8948413
## X97 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X98 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X99 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X100 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X101 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X102 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X103 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X104 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X105 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X106 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X107 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X108 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X109 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 1.8948413
## X110 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X111 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 1.8948413
## X112 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X113 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X114 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X115 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X116 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X117 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X118 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X119 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X120 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X121 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X122 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X123 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 1.8948413
## X124 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X125 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X126 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X127 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X128 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X129 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X130 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X131 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X132 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X133 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X134 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X135 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X136 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X137 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X138 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 1.8948413
## X139 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X140 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X141 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X142 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X143 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X144 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X145 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X146 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X147 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X148 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X149 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X150 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X151 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X152 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X153 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X154 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X155 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X156 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X157 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X158 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X159 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X160 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X161 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X162 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X163 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X164 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 1.8948413
## X165 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X166 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X167 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X168 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X169 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X170 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X171 -0.5385731 1.7595110 1.7595110 -0.5483075 1.8832169 1.8948413
## X172 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X173 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X174 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X175 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X176 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X177 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 1.8948413
## X178 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X179 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X180 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 -0.5271937
## X181 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X182 -0.5385731 1.7595110 1.7595110 -0.5483075 1.8832169 1.8948413
## X183 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X184 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X185 -0.5385731 -0.5677421 -0.5677421 1.8218763 1.8832169 -0.5271937
## X186 -0.5385731 1.7595110 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X187 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X188 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X189 1.8548056 1.7595110 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X190 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X191 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X192 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X193 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X194 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X195 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X196 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 1.8948413
## X197 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X198 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X199 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X200 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X201 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X202 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X203 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X204 -0.5385731 1.7595110 1.7595110 1.8218763 -0.5304479 1.8948413
## X205 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X206 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X207 -0.5385731 1.7595110 1.7595110 1.8218763 -0.5304479 -0.5271937
## X208 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X209 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X210 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X211 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X212 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X213 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X214 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X215 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X216 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X217 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X218 -0.5385731 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X219 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X220 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X221 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X222 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X223 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X224 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X225 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X226 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X227 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X228 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X229 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X230 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X231 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X232 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X233 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X234 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X235 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X236 -0.5385731 1.7595110 1.7595110 1.8218763 -0.5304479 1.8948413
## X237 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X238 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X239 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X240 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 1.8948413
## X241 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X242 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X243 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X244 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X245 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X246 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X247 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X248 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X249 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X250 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X251 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X252 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X253 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X254 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X255 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X256 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X257 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X258 -0.5385731 1.7595110 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X259 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X260 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X261 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X262 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X263 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X264 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X265 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X266 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X267 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X268 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X269 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 1.8948413
## X270 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 1.8948413
## X271 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X272 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X273 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X274 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 1.8948413
## X275 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X276 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X277 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X278 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X279 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X280 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X281 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X282 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X283 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X284 1.8548056 -0.5677421 1.7595110 1.8218763 1.8832169 -0.5271937
## X285 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X286 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X287 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X288 -0.5385731 1.7595110 -0.5677421 -0.5483075 1.8832169 1.8948413
## X289 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X290 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X291 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X292 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X293 -0.5385731 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X294 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X295 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X296 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X297 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X298 -0.5385731 1.7595110 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X299 1.8548056 -0.5677421 1.7595110 1.8218763 1.8832169 1.8948413
## X300 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X301 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X302 -0.5385731 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X303 1.8548056 -0.5677421 -0.5677421 1.8218763 1.8832169 -0.5271937
## X304 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 1.8948413
## X305 1.8548056 -0.5677421 -0.5677421 1.8218763 1.8832169 1.8948413
## X306 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X307 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X308 -0.5385731 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X309 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X310 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X311 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X312 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X313 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X314 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X315 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X316 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X317 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X318 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X319 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X320 1.8548056 1.7595110 -0.5677421 1.8218763 1.8832169 -0.5271937
## X321 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X322 1.8548056 1.7595110 -0.5677421 1.8218763 1.8832169 -0.5271937
## X323 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X324 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X325 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X326 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X327 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X328 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X329 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X330 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X331 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 1.8948413
## X332 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X333 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X334 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X335 1.8548056 -0.5677421 1.7595110 1.8218763 1.8832169 -0.5271937
## X336 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X337 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X338 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X339 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X340 -0.5385731 1.7595110 -0.5677421 -0.5483075 1.8832169 1.8948413
## X341 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X342 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X343 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X344 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 1.8948413
## X345 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X346 1.8548056 -0.5677421 1.7595110 1.8218763 1.8832169 -0.5271937
## X347 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X348 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X349 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X350 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X351 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X352 -0.5385731 1.7595110 1.7595110 1.8218763 -0.5304479 -0.5271937
## X353 1.8548056 -0.5677421 -0.5677421 1.8218763 1.8832169 1.8948413
## X354 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X355 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X356 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X357 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 1.8948413
## X358 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X359 1.8548056 -0.5677421 1.7595110 1.8218763 1.8832169 -0.5271937
## X360 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 1.8948413
## X361 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X362 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X363 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X364 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X365 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X366 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X367 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X368 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X369 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X370 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 1.8948413
## X371 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X372 -0.5385731 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X373 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X374 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X375 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X376 -0.5385731 1.7595110 1.7595110 -0.5483075 1.8832169 1.8948413
## X377 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X378 1.8548056 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X379 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X380 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X381 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X382 1.8548056 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X383 -0.5385731 1.7595110 1.7595110 -0.5483075 1.8832169 1.8948413
## X384 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X385 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X386 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X387 1.8548056 -0.5677421 -0.5677421 1.8218763 -0.5304479 1.8948413
## X388 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 1.8948413
## X389 1.8548056 -0.5677421 -0.5677421 1.8218763 -0.5304479 1.8948413
## X390 1.8548056 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X391 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X392 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 1.8948413
## X393 -0.5385731 -0.5677421 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X394 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X395 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X396 -0.5385731 1.7595110 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X397 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X398 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X399 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X400 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X401 1.8548056 -0.5677421 -0.5677421 1.8218763 1.8832169 -0.5271937
## X402 -0.5385731 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X403 -0.5385731 -0.5677421 1.7595110 1.8218763 1.8832169 -0.5271937
## X404 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X405 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X406 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X407 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X408 -0.5385731 1.7595110 -0.5677421 1.8218763 -0.5304479 -0.5271937
## X409 1.8548056 -0.5677421 1.7595110 1.8218763 1.8832169 1.8948413
## X410 1.8548056 1.7595110 -0.5677421 -0.5483075 1.8832169 1.8948413
## X411 -0.5385731 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X412 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X413 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X414 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X415 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X416 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X417 1.8548056 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X418 -0.5385731 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X419 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X420 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X421 -0.5385731 -0.5677421 -0.5677421 -0.5483075 1.8832169 -0.5271937
## X422 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X423 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X424 1.8548056 -0.5677421 1.7595110 1.8218763 1.8832169 1.8948413
## X425 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X426 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X427 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X428 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X429 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X430 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X431 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X432 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X433 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 -0.5271937
## X434 1.8548056 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X435 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X436 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X437 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X438 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X439 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X440 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X441 1.8548056 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X442 -0.5385731 -0.5677421 1.7595110 -0.5483075 1.8832169 1.8948413
## X443 1.8548056 1.7595110 -0.5677421 1.8218763 1.8832169 1.8948413
## X444 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X445 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X446 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X447 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X448 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X449 -0.5385731 -0.5677421 1.7595110 -0.5483075 -0.5304479 1.8948413
## X450 -0.5385731 1.7595110 -0.5677421 -0.5483075 -0.5304479 -0.5271937
## X451 -0.5385731 -0.5677421 1.7595110 1.8218763 -0.5304479 -0.5271937
## X452 -0.5385731 -0.5677421 -0.5677421 -0.5483075 1.8832169 1.8948413
## X453 -0.5385731 -0.5677421 -0.5677421 -0.5483075 -0.5304479 1.8948413
## X454 -0.5385731 -0.5677421 -0.5677421 1.8218763 1.8832169 1.8948413
## FP097 FP098 FP099 FP100 FP101 FP102
## X1 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X2 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X3 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X4 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X5 -0.5547896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X6 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X7 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X8 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X9 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X10 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X11 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X12 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X13 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X14 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X15 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X16 1.8005896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X17 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X18 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X19 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X20 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X21 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X22 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X23 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X24 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X25 -0.5547896 -0.558029 1.8436919 1.8218763 -0.5564094 1.9872011
## X26 -0.5547896 -0.558029 1.8436919 1.8218763 -0.5564094 1.9872011
## X27 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X28 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X29 -0.5547896 1.790137 1.8436919 1.8218763 -0.5564094 -0.5026912
## X30 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X31 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X32 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X33 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X34 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X35 1.8005896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X36 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X37 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X38 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X39 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X40 -0.5547896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X41 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X42 -0.5547896 1.790137 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X43 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X44 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X45 -0.5547896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X46 -0.5547896 -0.558029 1.8436919 -0.5483075 1.7953478 1.9872011
## X47 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X48 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X49 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X50 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X51 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X52 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X53 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X54 -0.5547896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X55 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X56 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X57 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X58 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X59 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X60 1.8005896 1.790137 -0.5418196 1.8218763 1.7953478 1.9872011
## X61 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X62 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X63 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X64 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X65 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X66 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X67 1.8005896 1.790137 -0.5418196 -0.5483075 1.7953478 1.9872011
## X68 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X69 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X70 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X71 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X72 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X73 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X74 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 1.9872011
## X75 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X76 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X77 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X78 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X79 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X80 -0.5547896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X81 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X82 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X83 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X84 1.8005896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X85 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X86 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X87 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X88 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X89 -0.5547896 -0.558029 1.8436919 1.8218763 -0.5564094 1.9872011
## X90 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 1.9872011
## X91 1.8005896 1.790137 1.8436919 1.8218763 -0.5564094 -0.5026912
## X92 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X93 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X94 -0.5547896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X95 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X96 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X97 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X98 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X99 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X100 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X101 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X102 1.8005896 -0.558029 1.8436919 -0.5483075 1.7953478 1.9872011
## X103 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X104 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X105 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X106 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X107 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 1.9872011
## X108 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X109 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 1.9872011
## X110 1.8005896 1.790137 -0.5418196 1.8218763 1.7953478 1.9872011
## X111 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X112 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X113 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X114 -0.5547896 1.790137 1.8436919 1.8218763 1.7953478 1.9872011
## X115 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X116 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X117 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X118 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X119 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X120 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X121 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X122 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X123 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X124 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X125 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X126 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X127 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X128 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X129 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X130 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X131 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X132 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X133 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X134 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X135 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X136 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X137 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X138 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X139 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X140 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X141 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X142 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X143 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X144 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X145 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X146 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X147 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X148 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X149 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X150 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X151 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X152 -0.5547896 -0.558029 1.8436919 -0.5483075 1.7953478 1.9872011
## X153 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X154 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X155 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X156 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X157 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X158 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X159 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X160 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X161 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X162 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X163 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X164 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X165 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X166 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X167 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X168 -0.5547896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X169 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 1.9872011
## X170 1.8005896 1.790137 -0.5418196 -0.5483075 1.7953478 1.9872011
## X171 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X172 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X173 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X174 -0.5547896 1.790137 1.8436919 -0.5483075 1.7953478 -0.5026912
## X175 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X176 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X177 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X178 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X179 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X180 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X181 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X182 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X183 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X184 -0.5547896 -0.558029 1.8436919 -0.5483075 1.7953478 -0.5026912
## X185 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X186 -0.5547896 -0.558029 1.8436919 -0.5483075 1.7953478 1.9872011
## X187 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X188 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 1.9872011
## X189 1.8005896 -0.558029 1.8436919 -0.5483075 1.7953478 1.9872011
## X190 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 1.9872011
## X191 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X192 1.8005896 1.790137 -0.5418196 1.8218763 1.7953478 -0.5026912
## X193 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X194 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X195 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X196 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X197 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X198 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X199 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X200 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X201 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X202 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X203 -0.5547896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X204 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 1.9872011
## X205 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X206 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X207 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 1.9872011
## X208 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X209 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X210 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X211 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X212 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X213 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X214 -0.5547896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X215 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X216 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X217 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X218 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 1.9872011
## X219 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X220 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X221 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X222 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X223 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X224 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X225 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X226 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X227 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X228 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X229 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X230 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X231 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X232 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X233 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 -0.5026912
## X234 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X235 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X236 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X237 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X238 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X239 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X240 1.8005896 -0.558029 1.8436919 1.8218763 -0.5564094 1.9872011
## X241 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X242 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X243 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X244 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X245 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X246 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X247 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X248 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X249 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X250 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X251 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X252 -0.5547896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X253 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X254 -0.5547896 -0.558029 1.8436919 -0.5483075 1.7953478 -0.5026912
## X255 1.8005896 1.790137 -0.5418196 1.8218763 1.7953478 1.9872011
## X256 -0.5547896 1.790137 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X257 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X258 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X259 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X260 1.8005896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X261 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X262 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X263 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X264 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X265 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X266 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X267 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X268 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X269 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 1.9872011
## X270 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X271 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X272 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X273 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X274 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X275 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X276 -0.5547896 1.790137 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X277 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X278 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X279 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X280 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X281 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X282 -0.5547896 1.790137 -0.5418196 1.8218763 1.7953478 1.9872011
## X283 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X284 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X285 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X286 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X287 -0.5547896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X288 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X289 1.8005896 -0.558029 1.8436919 1.8218763 -0.5564094 1.9872011
## X290 -0.5547896 -0.558029 -0.5418196 1.8218763 1.7953478 1.9872011
## X291 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X292 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X293 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X294 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X295 -0.5547896 1.790137 1.8436919 1.8218763 -0.5564094 1.9872011
## X296 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X297 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X298 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X299 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 -0.5026912
## X300 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X301 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 1.9872011
## X302 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X303 -0.5547896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X304 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X305 -0.5547896 -0.558029 1.8436919 1.8218763 -0.5564094 1.9872011
## X306 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X307 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X308 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X309 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X310 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X311 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X312 1.8005896 -0.558029 1.8436919 1.8218763 -0.5564094 1.9872011
## X313 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 1.9872011
## X314 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X315 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X316 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X317 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X318 1.8005896 1.790137 -0.5418196 -0.5483075 1.7953478 1.9872011
## X319 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X320 -0.5547896 -0.558029 1.8436919 -0.5483075 1.7953478 -0.5026912
## X321 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X322 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X323 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X324 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X325 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X326 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X327 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X328 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X329 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X330 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X331 -0.5547896 -0.558029 1.8436919 1.8218763 -0.5564094 1.9872011
## X332 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X333 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X334 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X335 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X336 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X337 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X338 1.8005896 1.790137 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X339 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X340 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X341 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X342 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X343 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X344 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X345 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X346 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 -0.5026912
## X347 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X348 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X349 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X350 -0.5547896 -0.558029 1.8436919 -0.5483075 1.7953478 1.9872011
## X351 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X352 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 1.9872011
## X353 -0.5547896 -0.558029 1.8436919 1.8218763 -0.5564094 1.9872011
## X354 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 1.9872011
## X355 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X356 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X357 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 1.9872011
## X358 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X359 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 -0.5026912
## X360 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X361 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X362 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X363 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X364 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X365 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X366 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X367 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X368 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X369 1.8005896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X370 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X371 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X372 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X373 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X374 1.8005896 -0.558029 -0.5418196 1.8218763 1.7953478 -0.5026912
## X375 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X376 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X377 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X378 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 1.9872011
## X379 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X380 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X381 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X382 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X383 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X384 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X385 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X386 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X387 -0.5547896 -0.558029 -0.5418196 1.8218763 1.7953478 1.9872011
## X388 -0.5547896 -0.558029 1.8436919 1.8218763 -0.5564094 1.9872011
## X389 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X390 -0.5547896 -0.558029 -0.5418196 1.8218763 1.7953478 1.9872011
## X391 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X392 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 1.9872011
## X393 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X394 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X395 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X396 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X397 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X398 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X399 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X400 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X401 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X402 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X403 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X404 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X405 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X406 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X407 1.8005896 -0.558029 -0.5418196 1.8218763 1.7953478 -0.5026912
## X408 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X409 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 -0.5026912
## X410 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X411 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X412 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X413 1.8005896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X414 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X415 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X416 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X417 -0.5547896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X418 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X419 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X420 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 1.9872011
## X421 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X422 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X423 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X424 1.8005896 1.790137 -0.5418196 -0.5483075 1.7953478 1.9872011
## X425 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X426 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X427 -0.5547896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X428 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X429 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X430 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X431 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X432 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X433 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X434 -0.5547896 -0.558029 -0.5418196 1.8218763 1.7953478 1.9872011
## X435 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X436 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X437 1.8005896 1.790137 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X438 1.8005896 -0.558029 1.8436919 -0.5483075 -0.5564094 -0.5026912
## X439 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X440 -0.5547896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X441 -0.5547896 -0.558029 -0.5418196 1.8218763 1.7953478 1.9872011
## X442 1.8005896 -0.558029 1.8436919 -0.5483075 1.7953478 1.9872011
## X443 1.8005896 -0.558029 1.8436919 1.8218763 1.7953478 1.9872011
## X444 -0.5547896 1.790137 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X445 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X446 -0.5547896 1.790137 -0.5418196 1.8218763 -0.5564094 -0.5026912
## X447 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X448 -0.5547896 -0.558029 -0.5418196 1.8218763 -0.5564094 1.9872011
## X449 1.8005896 1.790137 -0.5418196 1.8218763 1.7953478 1.9872011
## X450 -0.5547896 -0.558029 -0.5418196 -0.5483075 1.7953478 -0.5026912
## X451 -0.5547896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X452 1.8005896 -0.558029 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X453 1.8005896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## X454 1.8005896 1.790137 -0.5418196 -0.5483075 -0.5564094 -0.5026912
## FP103 FP104 FP105 FP106 FP107 FP108 FP109
## X1 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X2 -0.5288211 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 2.157733
## X3 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X4 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X5 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X6 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X7 1.8890101 1.8660610 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X8 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X9 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X10 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 2.157733
## X11 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X12 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X13 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X14 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X15 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X16 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X17 1.8890101 1.8660610 1.906619 2.0544663 -0.5174149 1.9679549 2.157733
## X18 -0.5288211 1.8660610 1.906619 2.0544663 1.9306527 -0.5076074 2.157733
## X19 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X20 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X21 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 -0.462962
## X22 1.8890101 -0.5353247 1.906619 2.0544663 -0.5174149 -0.5076074 2.157733
## X23 -0.5288211 -0.5353247 1.906619 -0.4862326 1.9306527 1.9679549 2.157733
## X24 -0.5288211 1.8660610 1.906619 2.0544663 1.9306527 -0.5076074 -0.462962
## X25 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 1.9679549 -0.462962
## X26 -0.5288211 -0.5353247 1.906619 2.0544663 -0.5174149 -0.5076074 -0.462962
## X27 1.8890101 1.8660610 -0.523937 2.0544663 -0.5174149 1.9679549 2.157733
## X28 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X29 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X30 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X31 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X32 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X33 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X34 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X35 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X36 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X37 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X38 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X39 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X40 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X41 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X42 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 2.157733
## X43 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X44 -0.5288211 1.8660610 1.906619 2.0544663 1.9306527 -0.5076074 2.157733
## X45 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X46 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X47 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X48 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X49 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 -0.462962
## X50 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X51 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X52 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X53 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X54 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X55 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X56 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X57 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 1.9679549 2.157733
## X58 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X59 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 -0.462962
## X60 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 -0.462962
## X61 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X62 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X63 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X64 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X65 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X66 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X67 1.8890101 1.8660610 1.906619 2.0544663 1.9306527 1.9679549 2.157733
## X68 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X69 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X70 1.8890101 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 2.157733
## X71 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X72 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X73 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X74 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 -0.5076074 -0.462962
## X75 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X76 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X77 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X78 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 2.157733
## X79 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X80 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X81 1.8890101 -0.5353247 1.906619 -0.4862326 1.9306527 1.9679549 -0.462962
## X82 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X83 1.8890101 1.8660610 1.906619 2.0544663 1.9306527 -0.5076074 2.157733
## X84 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X85 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X86 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X87 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X88 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X89 -0.5288211 1.8660610 1.906619 2.0544663 1.9306527 1.9679549 -0.462962
## X90 -0.5288211 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 -0.462962
## X91 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X92 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X93 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X94 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X95 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X96 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X97 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X98 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X99 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X100 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X101 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X102 1.8890101 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 2.157733
## X103 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X104 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X105 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X106 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X107 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X108 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X109 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 1.9679549 -0.462962
## X110 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X111 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X112 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X113 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X114 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 1.9679549 2.157733
## X115 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X116 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X117 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X118 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X119 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X120 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X121 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X122 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X123 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 1.9679549 -0.462962
## X124 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X125 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X126 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X127 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X128 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X129 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X130 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X131 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X132 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X133 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X134 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X135 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X136 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X137 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X138 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X139 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X140 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X141 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X142 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X143 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X144 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X145 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X146 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X147 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X148 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X149 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X150 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X151 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X152 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 -0.462962
## X153 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X154 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X155 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X156 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X157 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X158 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X159 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X160 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X161 1.8890101 1.8660610 1.906619 -0.4862326 1.9306527 -0.5076074 -0.462962
## X162 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X163 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X164 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X165 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X166 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X167 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X168 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X169 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 1.9679549 -0.462962
## X170 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X171 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X172 -0.5288211 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X173 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X174 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X175 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X176 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X177 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X178 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X179 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X180 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X181 1.8890101 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 2.157733
## X182 1.8890101 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X183 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X184 -0.5288211 1.8660610 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X185 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X186 -0.5288211 -0.5353247 1.906619 -0.4862326 1.9306527 -0.5076074 -0.462962
## X187 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X188 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X189 -0.5288211 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 2.157733
## X190 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 1.9679549 -0.462962
## X191 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X192 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X193 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X194 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X195 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X196 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X197 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 1.9679549 -0.462962
## X198 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X199 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X200 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X201 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X202 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X203 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X204 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 1.9679549 -0.462962
## X205 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X206 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X207 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 1.9679549 -0.462962
## X208 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X209 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X210 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X211 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X212 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X213 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X214 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 -0.462962
## X215 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X216 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X217 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X218 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 1.9679549 -0.462962
## X219 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X220 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X221 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X222 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X223 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X224 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X225 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X226 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X227 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X228 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X229 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X230 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X231 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X232 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X233 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X234 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X235 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X236 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 1.9679549 -0.462962
## X237 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X238 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X239 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 -0.462962
## X240 1.8890101 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X241 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X242 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X243 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X244 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 1.9679549 2.157733
## X245 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 -0.462962
## X246 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 2.157733
## X247 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 1.9679549 2.157733
## X248 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X249 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X250 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X251 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X252 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X253 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X254 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X255 -0.5288211 1.8660610 -0.523937 -0.4862326 1.9306527 -0.5076074 2.157733
## X256 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X257 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X258 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X259 -0.5288211 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X260 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X261 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X262 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X263 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X264 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X265 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X266 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X267 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X268 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X269 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X270 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X271 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X272 1.8890101 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 2.157733
## X273 1.8890101 -0.5353247 1.906619 -0.4862326 1.9306527 -0.5076074 -0.462962
## X274 1.8890101 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 -0.462962
## X275 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X276 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X277 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X278 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X279 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X280 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X281 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X282 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X283 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X284 1.8890101 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X285 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 2.157733
## X286 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X287 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 1.9679549 2.157733
## X288 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X289 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 -0.5076074 -0.462962
## X290 -0.5288211 1.8660610 -0.523937 -0.4862326 1.9306527 -0.5076074 2.157733
## X291 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X292 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X293 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X294 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X295 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 1.9679549 2.157733
## X296 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 1.9679549 2.157733
## X297 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X298 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 2.157733
## X299 1.8890101 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 -0.462962
## X300 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X301 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X302 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X303 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X304 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X305 -0.5288211 -0.5353247 1.906619 2.0544663 -0.5174149 -0.5076074 -0.462962
## X306 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X307 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X308 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X309 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X310 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X311 1.8890101 -0.5353247 1.906619 -0.4862326 1.9306527 -0.5076074 -0.462962
## X312 1.8890101 -0.5353247 -0.523937 2.0544663 -0.5174149 -0.5076074 -0.462962
## X313 -0.5288211 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X314 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X315 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X316 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X317 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X318 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X319 1.8890101 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X320 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X321 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X322 1.8890101 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 2.157733
## X323 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X324 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X325 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X326 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X327 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X328 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X329 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X330 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 2.157733
## X331 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X332 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X333 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 2.157733
## X334 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 2.157733
## X335 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 2.157733
## X336 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X337 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 1.9679549 2.157733
## X338 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X339 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X340 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X341 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X342 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X343 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X344 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 1.9679549 -0.462962
## X345 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X346 1.8890101 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 -0.462962
## X347 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X348 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X349 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X350 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 -0.462962
## X351 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X352 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X353 -0.5288211 -0.5353247 1.906619 2.0544663 -0.5174149 -0.5076074 -0.462962
## X354 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X355 -0.5288211 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X356 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X357 1.8890101 -0.5353247 -0.523937 2.0544663 -0.5174149 1.9679549 -0.462962
## X358 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X359 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 -0.462962
## X360 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X361 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X362 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X363 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X364 -0.5288211 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X365 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 2.157733
## X366 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X367 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X368 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X369 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X370 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X371 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X372 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X373 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X374 -0.5288211 1.8660610 -0.523937 -0.4862326 1.9306527 -0.5076074 2.157733
## X375 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 1.9679549 -0.462962
## X376 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X377 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X378 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 2.157733
## X379 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X380 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X381 -0.5288211 -0.5353247 1.906619 -0.4862326 1.9306527 1.9679549 -0.462962
## X382 -0.5288211 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 -0.462962
## X383 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X384 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X385 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X386 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X387 -0.5288211 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 2.157733
## X388 -0.5288211 -0.5353247 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X389 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 1.9679549 -0.462962
## X390 -0.5288211 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 2.157733
## X391 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X392 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X393 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X394 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X395 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 1.9679549 2.157733
## X396 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X397 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X398 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X399 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X400 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 2.157733
## X401 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X402 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X403 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X404 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X405 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 -0.5076074 -0.462962
## X406 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X407 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X408 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X409 1.8890101 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 -0.462962
## X410 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X411 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X412 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X413 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X414 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X415 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X416 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X417 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X418 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X419 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X420 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 2.157733
## X421 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X422 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 -0.462962
## X423 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X424 -0.5288211 1.8660610 1.906619 2.0544663 -0.5174149 -0.5076074 2.157733
## X425 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X426 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X427 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X428 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X429 -0.5288211 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X430 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X431 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X432 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X433 -0.5288211 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X434 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 2.157733
## X435 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X436 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X437 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 1.9679549 -0.462962
## X438 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X439 1.8890101 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X440 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 -0.5076074 -0.462962
## X441 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 -0.5076074 2.157733
## X442 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X443 -0.5288211 1.8660610 -0.523937 2.0544663 1.9306527 -0.5076074 2.157733
## X444 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X445 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X446 -0.5288211 -0.5353247 -0.523937 -0.4862326 1.9306527 1.9679549 2.157733
## X447 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 1.9679549 -0.462962
## X448 1.8890101 -0.5353247 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X449 -0.5288211 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X450 -0.5288211 -0.5353247 -0.523937 2.0544663 -0.5174149 -0.5076074 -0.462962
## X451 1.8890101 1.8660610 1.906619 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X452 -0.5288211 -0.5353247 -0.523937 -0.4862326 -0.5174149 -0.5076074 -0.462962
## X453 -0.5288211 1.8660610 -0.523937 -0.4862326 -0.5174149 1.9679549 -0.462962
## X454 -0.5288211 1.8660610 -0.523937 2.0544663 -0.5174149 1.9679549 -0.462962
## FP110 FP111 FP112 FP113 FP114 FP115
## X1 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X2 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X3 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X4 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X5 -0.5092442 2.0202142 2.0337617 -0.4928302 2.3280830 -0.4663054
## X6 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X7 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X8 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X9 -0.5092442 -0.4944765 2.0337617 2.0269629 -0.4290863 2.1422621
## X10 1.9616295 2.0202142 -0.4911827 2.0269629 2.3280830 -0.4663054
## X11 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X12 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X13 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X14 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X15 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X16 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X17 1.9616295 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X18 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X19 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X20 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X21 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X22 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X23 1.9616295 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X24 1.9616295 2.0202142 -0.4911827 2.0269629 -0.4290863 2.1422621
## X25 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X26 1.9616295 2.0202142 -0.4911827 2.0269629 2.3280830 2.1422621
## X27 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X28 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X29 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X30 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X31 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X32 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X33 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X34 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X35 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X36 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X37 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X38 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X39 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X40 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X41 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 2.1422621
## X42 1.9616295 2.0202142 2.0337617 2.0269629 2.3280830 -0.4663054
## X43 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X44 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X45 -0.5092442 2.0202142 2.0337617 -0.4928302 2.3280830 -0.4663054
## X46 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X47 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X48 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X49 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X50 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X51 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X52 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X53 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X54 -0.5092442 2.0202142 2.0337617 -0.4928302 2.3280830 -0.4663054
## X55 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X56 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X57 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X58 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X59 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 2.1422621
## X60 1.9616295 -0.4944765 2.0337617 -0.4928302 -0.4290863 2.1422621
## X61 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X62 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X63 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X64 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X65 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X66 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X67 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X68 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 2.1422621
## X69 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X70 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X71 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X72 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X73 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X74 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X75 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X76 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 2.1422621
## X77 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X78 -0.5092442 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X79 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X80 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X81 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 2.1422621
## X82 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X83 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X84 1.9616295 -0.4944765 2.0337617 -0.4928302 2.3280830 2.1422621
## X85 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X86 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X87 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X88 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 2.1422621
## X89 1.9616295 2.0202142 2.0337617 2.0269629 2.3280830 2.1422621
## X90 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X91 1.9616295 -0.4944765 -0.4911827 2.0269629 -0.4290863 2.1422621
## X92 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X93 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X94 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X95 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X96 -0.5092442 -0.4944765 2.0337617 2.0269629 -0.4290863 -0.4663054
## X97 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X98 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X99 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X100 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X101 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X102 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X103 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X104 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X105 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X106 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X107 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X108 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 2.1422621
## X109 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X110 1.9616295 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X111 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X112 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X113 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X114 1.9616295 2.0202142 2.0337617 -0.4928302 2.3280830 -0.4663054
## X115 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X116 1.9616295 2.0202142 2.0337617 -0.4928302 2.3280830 2.1422621
## X117 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X118 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X119 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X120 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X121 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X122 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X123 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X124 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X125 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X126 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X127 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X128 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X129 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X130 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X131 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X132 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X133 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X134 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X135 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X136 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X137 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X138 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X139 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X140 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X141 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X142 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X143 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X144 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X145 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X146 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X147 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X148 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X149 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X150 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X151 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X152 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X153 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X154 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X155 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X156 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X157 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X158 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X159 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X160 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X161 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X162 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X163 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X164 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 2.1422621
## X165 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X166 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X167 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X168 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X169 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X170 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X171 -0.5092442 -0.4944765 2.0337617 2.0269629 -0.4290863 2.1422621
## X172 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X173 1.9616295 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X174 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X175 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X176 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X177 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X178 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X179 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X180 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X181 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X182 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 2.1422621
## X183 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X184 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X185 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X186 -0.5092442 -0.4944765 2.0337617 2.0269629 -0.4290863 -0.4663054
## X187 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X188 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X189 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X190 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X191 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 2.1422621
## X192 1.9616295 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X193 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X194 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X195 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X196 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X197 1.9616295 2.0202142 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X198 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X199 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X200 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X201 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X202 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X203 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X204 -0.5092442 2.0202142 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X205 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X206 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X207 -0.5092442 2.0202142 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X208 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X209 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X210 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X211 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X212 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X213 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X214 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X215 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X216 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X217 -0.5092442 2.0202142 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X218 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X219 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X220 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X221 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X222 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X223 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X224 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X225 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X226 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X227 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X228 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X229 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X230 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X231 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X232 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X233 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X234 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X235 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X236 1.9616295 2.0202142 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X237 -0.5092442 2.0202142 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X238 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X239 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X240 1.9616295 -0.4944765 2.0337617 2.0269629 2.3280830 2.1422621
## X241 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X242 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X243 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X244 1.9616295 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X245 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X246 1.9616295 -0.4944765 -0.4911827 2.0269629 2.3280830 -0.4663054
## X247 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X248 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X249 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X250 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X251 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X252 -0.5092442 -0.4944765 -0.4911827 2.0269629 2.3280830 -0.4663054
## X253 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X254 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X255 1.9616295 2.0202142 2.0337617 -0.4928302 -0.4290863 2.1422621
## X256 1.9616295 2.0202142 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X257 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X258 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X259 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X260 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X261 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X262 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X263 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X264 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X265 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X266 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X267 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X268 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X269 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X270 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X271 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X272 1.9616295 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X273 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X274 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X275 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X276 -0.5092442 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X277 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X278 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X279 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X280 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X281 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X282 1.9616295 2.0202142 2.0337617 -0.4928302 2.3280830 2.1422621
## X283 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X284 1.9616295 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X285 1.9616295 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X286 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X287 -0.5092442 2.0202142 -0.4911827 2.0269629 2.3280830 -0.4663054
## X288 -0.5092442 -0.4944765 2.0337617 2.0269629 -0.4290863 -0.4663054
## X289 1.9616295 -0.4944765 -0.4911827 -0.4928302 2.3280830 2.1422621
## X290 1.9616295 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X291 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X292 1.9616295 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X293 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X294 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X295 1.9616295 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X296 1.9616295 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X297 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X298 1.9616295 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X299 1.9616295 2.0202142 -0.4911827 2.0269629 -0.4290863 2.1422621
## X300 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X301 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X302 1.9616295 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X303 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X304 -0.5092442 2.0202142 2.0337617 -0.4928302 -0.4290863 2.1422621
## X305 1.9616295 2.0202142 -0.4911827 2.0269629 -0.4290863 2.1422621
## X306 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X307 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X308 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X309 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X310 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 2.1422621
## X311 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X312 1.9616295 -0.4944765 -0.4911827 2.0269629 2.3280830 2.1422621
## X313 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X314 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X315 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X316 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X317 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X318 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X319 1.9616295 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X320 -0.5092442 2.0202142 2.0337617 -0.4928302 2.3280830 -0.4663054
## X321 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X322 1.9616295 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X323 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X324 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X325 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X326 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X327 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X328 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X329 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X330 -0.5092442 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X331 1.9616295 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X332 1.9616295 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X333 1.9616295 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X334 -0.5092442 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X335 -0.5092442 -0.4944765 -0.4911827 2.0269629 2.3280830 -0.4663054
## X336 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X337 1.9616295 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X338 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X339 1.9616295 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X340 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X341 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X342 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X343 1.9616295 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X344 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X345 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X346 1.9616295 2.0202142 -0.4911827 2.0269629 -0.4290863 2.1422621
## X347 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X348 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X349 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X350 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X351 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X352 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X353 1.9616295 2.0202142 -0.4911827 2.0269629 -0.4290863 2.1422621
## X354 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X355 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X356 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X357 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X358 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X359 1.9616295 2.0202142 -0.4911827 2.0269629 -0.4290863 2.1422621
## X360 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X361 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X362 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X363 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X364 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X365 1.9616295 2.0202142 2.0337617 -0.4928302 2.3280830 -0.4663054
## X366 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X367 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X368 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X369 1.9616295 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X370 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X371 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X372 1.9616295 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X373 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X374 1.9616295 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X375 1.9616295 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X376 -0.5092442 -0.4944765 2.0337617 2.0269629 -0.4290863 2.1422621
## X377 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X378 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X379 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X380 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X381 -0.5092442 -0.4944765 2.0337617 2.0269629 -0.4290863 -0.4663054
## X382 1.9616295 2.0202142 -0.4911827 2.0269629 2.3280830 2.1422621
## X383 -0.5092442 -0.4944765 2.0337617 2.0269629 -0.4290863 2.1422621
## X384 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X385 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X386 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X387 1.9616295 -0.4944765 -0.4911827 -0.4928302 2.3280830 2.1422621
## X388 1.9616295 2.0202142 2.0337617 -0.4928302 2.3280830 2.1422621
## X389 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X390 1.9616295 -0.4944765 -0.4911827 -0.4928302 2.3280830 2.1422621
## X391 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X392 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X393 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X394 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X395 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X396 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X397 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X398 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X399 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X400 1.9616295 2.0202142 2.0337617 -0.4928302 2.3280830 -0.4663054
## X401 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X402 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X403 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X404 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X405 1.9616295 2.0202142 2.0337617 -0.4928302 -0.4290863 2.1422621
## X406 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X407 1.9616295 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X408 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X409 1.9616295 2.0202142 -0.4911827 2.0269629 -0.4290863 2.1422621
## X410 -0.5092442 2.0202142 2.0337617 -0.4928302 -0.4290863 2.1422621
## X411 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X412 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X413 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X414 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X415 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X416 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X417 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X418 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X419 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X420 -0.5092442 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X421 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X422 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X423 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 2.1422621
## X424 -0.5092442 2.0202142 -0.4911827 -0.4928302 2.3280830 2.1422621
## X425 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 2.1422621
## X426 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## X427 -0.5092442 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X428 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X429 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X430 1.9616295 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X431 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X432 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X433 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X434 1.9616295 -0.4944765 2.0337617 -0.4928302 2.3280830 -0.4663054
## X435 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X436 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X437 -0.5092442 -0.4944765 -0.4911827 -0.4928302 2.3280830 2.1422621
## X438 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 2.1422621
## X439 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X440 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X441 1.9616295 -0.4944765 -0.4911827 -0.4928302 2.3280830 2.1422621
## X442 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X443 1.9616295 2.0202142 2.0337617 -0.4928302 -0.4290863 2.1422621
## X444 1.9616295 2.0202142 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X445 1.9616295 2.0202142 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X446 1.9616295 2.0202142 2.0337617 -0.4928302 2.3280830 -0.4663054
## X447 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X448 1.9616295 2.0202142 -0.4911827 -0.4928302 2.3280830 -0.4663054
## X449 1.9616295 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X450 -0.5092442 -0.4944765 2.0337617 -0.4928302 -0.4290863 -0.4663054
## X451 -0.5092442 -0.4944765 -0.4911827 2.0269629 -0.4290863 -0.4663054
## X452 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X453 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 -0.4663054
## X454 -0.5092442 -0.4944765 -0.4911827 -0.4928302 -0.4290863 2.1422621
## FP116 FP117 FP118 FP119 FP120 FP121
## X1 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X2 2.0475127 -0.4663054 2.0475127 -0.4410429 -0.4461321 2.4786909
## X3 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X4 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X5 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X6 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X7 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X8 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X9 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X10 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X11 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X12 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X13 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X14 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X15 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X16 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X17 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 2.4786909
## X18 2.0475127 -0.4663054 2.0475127 -0.4410429 2.2391315 2.4786909
## X19 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X20 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X21 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X22 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X23 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 2.4786909
## X24 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X25 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X26 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X27 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 2.4786909
## X28 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X29 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X30 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X31 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X32 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X33 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X34 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X35 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X36 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X37 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X38 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X39 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X40 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X41 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X42 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X43 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X44 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X45 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X46 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X47 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X48 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X49 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X50 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X51 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X52 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X53 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X54 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X55 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X56 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X57 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X58 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X59 -0.4878839 2.1422621 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X60 -0.4878839 2.1422621 2.0475127 2.2649688 -0.4461321 2.4786909
## X61 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X62 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X63 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X64 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X65 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X66 -0.4878839 -0.4663054 2.0475127 -0.4410429 2.2391315 -0.4030145
## X67 2.0475127 -0.4663054 -0.4878839 -0.4410429 2.2391315 2.4786909
## X68 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X69 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X70 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X71 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X72 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X73 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X74 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X75 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X76 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X77 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X78 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X79 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X80 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X81 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X82 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X83 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X84 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X85 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X86 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X87 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X88 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X89 -0.4878839 -0.4663054 2.0475127 2.2649688 -0.4461321 -0.4030145
## X90 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X91 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X92 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X93 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X94 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X95 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X96 -0.4878839 -0.4663054 2.0475127 2.2649688 -0.4461321 -0.4030145
## X97 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X98 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X99 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X100 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X101 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X102 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X103 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X104 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X105 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X106 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X107 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X108 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X109 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X110 -0.4878839 2.1422621 2.0475127 2.2649688 -0.4461321 2.4786909
## X111 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X112 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X113 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X114 -0.4878839 2.1422621 -0.4878839 2.2649688 -0.4461321 2.4786909
## X115 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X116 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X117 -0.4878839 -0.4663054 2.0475127 -0.4410429 2.2391315 -0.4030145
## X118 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X119 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X120 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X121 2.0475127 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X122 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X123 -0.4878839 2.1422621 -0.4878839 -0.4410429 2.2391315 2.4786909
## X124 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X125 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X126 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X127 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X128 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X129 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X130 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X131 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X132 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X133 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X134 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X135 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X136 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X137 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X138 2.0475127 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X139 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X140 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X141 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X142 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X143 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X144 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X145 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X146 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X147 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X148 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X149 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X150 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X151 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X152 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X153 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X154 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X155 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X156 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X157 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X158 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X159 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X160 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X161 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X162 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X163 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X164 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X165 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X166 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X167 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X168 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X169 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X170 2.0475127 2.1422621 -0.4878839 2.2649688 2.2391315 2.4786909
## X171 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X172 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X173 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X174 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X175 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X176 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X177 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X178 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X179 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X180 -0.4878839 2.1422621 2.0475127 2.2649688 -0.4461321 -0.4030145
## X181 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X182 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X183 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X184 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X185 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X186 2.0475127 -0.4663054 2.0475127 -0.4410429 -0.4461321 2.4786909
## X187 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X188 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X189 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X190 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X191 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X192 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X193 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X194 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X195 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X196 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X197 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X198 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X199 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X200 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X201 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X202 -0.4878839 2.1422621 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X203 -0.4878839 -0.4663054 -0.4878839 2.2649688 2.2391315 -0.4030145
## X204 2.0475127 -0.4663054 -0.4878839 2.2649688 2.2391315 -0.4030145
## X205 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X206 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X207 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X208 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X209 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X210 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X211 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X212 2.0475127 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X213 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X214 -0.4878839 -0.4663054 -0.4878839 2.2649688 2.2391315 -0.4030145
## X215 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X216 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X217 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X218 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X219 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X220 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X221 -0.4878839 -0.4663054 2.0475127 -0.4410429 2.2391315 -0.4030145
## X222 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X223 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X224 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X225 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X226 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X227 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X228 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X229 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X230 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X231 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X232 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X233 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X234 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X235 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X236 2.0475127 -0.4663054 -0.4878839 2.2649688 2.2391315 -0.4030145
## X237 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X238 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X239 -0.4878839 -0.4663054 2.0475127 2.2649688 2.2391315 -0.4030145
## X240 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 2.4786909
## X241 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X242 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X243 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X244 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X245 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X246 2.0475127 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X247 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X248 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X249 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X250 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X251 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X252 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 2.4786909
## X253 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X254 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X255 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 2.4786909
## X256 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X257 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X258 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X259 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X260 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X261 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X262 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X263 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X264 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X265 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X266 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X267 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X268 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X269 -0.4878839 -0.4663054 -0.4878839 2.2649688 2.2391315 2.4786909
## X270 -0.4878839 -0.4663054 -0.4878839 2.2649688 2.2391315 -0.4030145
## X271 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X272 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 2.4786909
## X273 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X274 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X275 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X276 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X277 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 2.4786909
## X278 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X279 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X280 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X281 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X282 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X283 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X284 2.0475127 2.1422621 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X285 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X286 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X287 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X288 -0.4878839 -0.4663054 2.0475127 2.2649688 -0.4461321 -0.4030145
## X289 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 2.4786909
## X290 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X291 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X292 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X293 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X294 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X295 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 2.4786909
## X296 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X297 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X298 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X299 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X300 -0.4878839 -0.4663054 2.0475127 -0.4410429 2.2391315 -0.4030145
## X301 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X302 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X303 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X304 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X305 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X306 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X307 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X308 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X309 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X310 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X311 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X312 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 2.4786909
## X313 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X314 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X315 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X316 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X317 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X318 2.0475127 2.1422621 -0.4878839 2.2649688 2.2391315 2.4786909
## X319 2.0475127 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X320 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X321 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X322 -0.4878839 -0.4663054 2.0475127 2.2649688 -0.4461321 2.4786909
## X323 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X324 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X325 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X326 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X327 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X328 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X329 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X330 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X331 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X332 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X333 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 2.4786909
## X334 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X335 -0.4878839 -0.4663054 2.0475127 -0.4410429 2.2391315 -0.4030145
## X336 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X337 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X338 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X339 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X340 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X341 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X342 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X343 2.0475127 2.1422621 -0.4878839 -0.4410429 2.2391315 2.4786909
## X344 -0.4878839 2.1422621 -0.4878839 -0.4410429 2.2391315 2.4786909
## X345 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X346 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X347 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X348 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 2.4786909
## X349 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X350 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 2.4786909
## X351 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X352 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X353 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X354 -0.4878839 -0.4663054 -0.4878839 2.2649688 2.2391315 2.4786909
## X355 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X356 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X357 -0.4878839 2.1422621 -0.4878839 2.2649688 2.2391315 -0.4030145
## X358 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X359 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X360 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X361 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X362 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X363 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X364 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X365 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X366 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X367 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X368 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X369 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 2.4786909
## X370 2.0475127 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X371 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X372 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X373 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X374 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X375 -0.4878839 2.1422621 -0.4878839 2.2649688 -0.4461321 2.4786909
## X376 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X377 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X378 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 2.4786909
## X379 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X380 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X381 -0.4878839 -0.4663054 2.0475127 2.2649688 2.2391315 -0.4030145
## X382 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 2.4786909
## X383 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X384 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X385 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X386 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X387 -0.4878839 2.1422621 -0.4878839 2.2649688 -0.4461321 2.4786909
## X388 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X389 -0.4878839 2.1422621 -0.4878839 2.2649688 2.2391315 -0.4030145
## X390 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X391 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X392 -0.4878839 -0.4663054 -0.4878839 2.2649688 2.2391315 2.4786909
## X393 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X394 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X395 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X396 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X397 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X398 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X399 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X400 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X401 -0.4878839 2.1422621 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X402 -0.4878839 -0.4663054 2.0475127 2.2649688 -0.4461321 -0.4030145
## X403 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X404 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X405 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X406 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X407 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X408 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X409 2.0475127 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X410 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X411 2.0475127 2.1422621 2.0475127 2.2649688 2.2391315 -0.4030145
## X412 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X413 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X414 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X415 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X416 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X417 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X418 -0.4878839 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X419 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X420 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X421 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X422 -0.4878839 -0.4663054 2.0475127 2.2649688 2.2391315 -0.4030145
## X423 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X424 2.0475127 -0.4663054 2.0475127 -0.4410429 -0.4461321 2.4786909
## X425 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X426 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X427 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X428 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X429 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X430 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X431 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X432 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X433 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X434 2.0475127 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X435 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X436 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X437 2.0475127 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X438 -0.4878839 2.1422621 2.0475127 -0.4410429 2.2391315 -0.4030145
## X439 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X440 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X441 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X442 2.0475127 2.1422621 -0.4878839 2.2649688 -0.4461321 2.4786909
## X443 2.0475127 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X444 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X445 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X446 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X447 -0.4878839 -0.4663054 -0.4878839 -0.4410429 2.2391315 -0.4030145
## X448 -0.4878839 -0.4663054 -0.4878839 -0.4410429 -0.4461321 2.4786909
## X449 2.0475127 2.1422621 -0.4878839 2.2649688 2.2391315 2.4786909
## X450 -0.4878839 2.1422621 -0.4878839 -0.4410429 -0.4461321 -0.4030145
## X451 -0.4878839 -0.4663054 2.0475127 -0.4410429 -0.4461321 -0.4030145
## X452 2.0475127 -0.4663054 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X453 2.0475127 2.1422621 -0.4878839 2.2649688 -0.4461321 -0.4030145
## X454 2.0475127 -0.4663054 -0.4878839 2.2649688 2.2391315 -0.4030145
## FP122 FP123 FP124 FP125 FP126 FP127
## X1 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X2 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 -0.4030145
## X3 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X4 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X5 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 2.4786909
## X6 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X7 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 2.4786909
## X8 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X9 2.2562790 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X10 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 2.4786909
## X11 -0.4427415 -0.4478242 -0.439342 2.3280830 -0.4170024 -0.4030145
## X12 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X13 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X14 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X15 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X16 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X17 -0.4427415 -0.4478242 2.273738 -0.4290863 2.3955459 2.4786909
## X18 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X19 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X20 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X21 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X22 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X23 -0.4427415 -0.4478242 -0.439342 2.3280830 -0.4170024 -0.4030145
## X24 2.2562790 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X25 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X26 2.2562790 -0.4478242 -0.439342 2.3280830 2.3955459 2.4786909
## X27 -0.4427415 -0.4478242 2.273738 -0.4290863 2.3955459 -0.4030145
## X28 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X29 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X30 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X31 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X32 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X33 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X34 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X35 -0.4427415 2.2306713 2.273738 2.3280830 -0.4170024 -0.4030145
## X36 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X37 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X38 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X39 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X40 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 -0.4030145
## X41 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X42 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X43 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X44 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X45 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 2.4786909
## X46 -0.4427415 2.2306713 2.273738 -0.4290863 2.3955459 -0.4030145
## X47 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X48 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X49 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X50 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X51 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X52 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X53 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X54 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 2.4786909
## X55 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X56 2.2562790 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X57 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X58 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X59 -0.4427415 2.2306713 2.273738 2.3280830 -0.4170024 -0.4030145
## X60 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X61 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X62 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X63 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X64 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X65 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X66 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X67 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X68 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X69 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X70 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X71 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X72 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X73 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X74 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X75 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X76 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X77 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X78 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X79 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X80 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X81 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X82 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X83 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X84 -0.4427415 2.2306713 -0.439342 -0.4290863 2.3955459 -0.4030145
## X85 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X86 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X87 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X88 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X89 2.2562790 -0.4478242 2.273738 2.3280830 2.3955459 2.4786909
## X90 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X91 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X92 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X93 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X94 -0.4427415 2.2306713 2.273738 -0.4290863 -0.4170024 -0.4030145
## X95 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X96 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X97 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X98 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X99 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X100 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X101 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X102 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X103 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X104 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X105 -0.4427415 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X106 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X107 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 2.4786909
## X108 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X109 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X110 -0.4427415 2.2306713 2.273738 -0.4290863 -0.4170024 -0.4030145
## X111 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X112 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X113 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X114 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 -0.4030145
## X115 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X116 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 2.4786909
## X117 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X118 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X119 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X120 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X121 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X122 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X123 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 -0.4030145
## X124 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X125 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X126 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X127 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X128 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X129 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X130 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X131 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X132 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X133 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X134 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X135 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X136 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X137 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X138 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X139 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X140 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X141 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X142 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X143 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X144 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X145 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X146 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X147 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X148 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X149 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X150 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X151 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X152 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 2.4786909
## X153 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X154 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X155 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X156 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X157 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X158 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X159 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X160 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X161 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X162 2.2562790 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X163 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X164 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X165 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X166 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X167 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X168 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 2.4786909
## X169 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X170 -0.4427415 -0.4478242 2.273738 2.3280830 -0.4170024 -0.4030145
## X171 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X172 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X173 -0.4427415 2.2306713 2.273738 2.3280830 2.3955459 2.4786909
## X174 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X175 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X176 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X177 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X178 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X179 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X180 2.2562790 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X181 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X182 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X183 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X184 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X185 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X186 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 -0.4030145
## X187 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X188 -0.4427415 2.2306713 2.273738 -0.4290863 -0.4170024 -0.4030145
## X189 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X190 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X191 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X192 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 -0.4030145
## X193 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X194 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X195 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X196 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X197 -0.4427415 -0.4478242 2.273738 -0.4290863 2.3955459 -0.4030145
## X198 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X199 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X200 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X201 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X202 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X203 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X204 -0.4427415 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X205 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X206 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X207 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X208 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X209 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X210 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X211 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X212 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X213 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X214 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X215 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X216 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X217 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X218 -0.4427415 -0.4478242 -0.439342 2.3280830 -0.4170024 -0.4030145
## X219 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X220 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X221 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X222 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X223 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X224 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X225 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X226 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X227 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X228 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X229 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X230 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X231 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X232 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X233 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 2.4786909
## X234 2.2562790 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X235 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X236 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 -0.4030145
## X237 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X238 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X239 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X240 2.2562790 2.2306713 2.273738 2.3280830 2.3955459 -0.4030145
## X241 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X242 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X243 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 -0.4030145
## X244 -0.4427415 -0.4478242 2.273738 -0.4290863 2.3955459 2.4786909
## X245 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X246 2.2562790 2.2306713 -0.439342 2.3280830 2.3955459 -0.4030145
## X247 -0.4427415 -0.4478242 2.273738 -0.4290863 2.3955459 2.4786909
## X248 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X249 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X250 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X251 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X252 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 2.4786909
## X253 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X254 -0.4427415 -0.4478242 2.273738 -0.4290863 2.3955459 2.4786909
## X255 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X256 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X257 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X258 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X259 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X260 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X261 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 2.4786909
## X262 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X263 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X264 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X265 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X266 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X267 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X268 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X269 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X270 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X271 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X272 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X273 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X274 2.2562790 2.2306713 2.273738 2.3280830 2.3955459 2.4786909
## X275 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X276 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X277 2.2562790 2.2306713 2.273738 -0.4290863 -0.4170024 -0.4030145
## X278 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 2.4786909
## X279 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X280 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X281 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X282 -0.4427415 -0.4478242 2.273738 2.3280830 2.3955459 2.4786909
## X283 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X284 2.2562790 -0.4478242 2.273738 -0.4290863 2.3955459 -0.4030145
## X285 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X286 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X287 -0.4427415 -0.4478242 2.273738 2.3280830 -0.4170024 2.4786909
## X288 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X289 -0.4427415 2.2306713 2.273738 2.3280830 2.3955459 -0.4030145
## X290 -0.4427415 2.2306713 -0.439342 -0.4290863 2.3955459 -0.4030145
## X291 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X292 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 -0.4030145
## X293 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X294 -0.4427415 2.2306713 2.273738 -0.4290863 -0.4170024 -0.4030145
## X295 -0.4427415 -0.4478242 2.273738 -0.4290863 2.3955459 2.4786909
## X296 -0.4427415 -0.4478242 2.273738 2.3280830 2.3955459 2.4786909
## X297 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X298 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X299 2.2562790 2.2306713 -0.439342 2.3280830 2.3955459 2.4786909
## X300 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X301 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X302 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X303 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 2.4786909
## X304 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X305 2.2562790 -0.4478242 -0.439342 2.3280830 2.3955459 2.4786909
## X306 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X307 2.2562790 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X308 -0.4427415 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X309 2.2562790 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X310 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X311 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X312 2.2562790 2.2306713 2.273738 2.3280830 2.3955459 -0.4030145
## X313 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X314 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X315 -0.4427415 2.2306713 2.273738 -0.4290863 -0.4170024 -0.4030145
## X316 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X317 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X318 -0.4427415 -0.4478242 2.273738 2.3280830 2.3955459 -0.4030145
## X319 2.2562790 2.2306713 -0.439342 2.3280830 2.3955459 -0.4030145
## X320 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 2.4786909
## X321 -0.4427415 -0.4478242 -0.439342 2.3280830 -0.4170024 -0.4030145
## X322 2.2562790 -0.4478242 2.273738 2.3280830 2.3955459 -0.4030145
## X323 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X324 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X325 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X326 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X327 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X328 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X329 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X330 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X331 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X332 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X333 -0.4427415 -0.4478242 2.273738 2.3280830 -0.4170024 -0.4030145
## X334 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X335 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X336 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X337 -0.4427415 -0.4478242 2.273738 -0.4290863 2.3955459 2.4786909
## X338 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X339 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 -0.4030145
## X340 -0.4427415 -0.4478242 -0.439342 2.3280830 -0.4170024 -0.4030145
## X341 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X342 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X343 -0.4427415 2.2306713 -0.439342 2.3280830 2.3955459 -0.4030145
## X344 -0.4427415 -0.4478242 -0.439342 2.3280830 -0.4170024 -0.4030145
## X345 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X346 2.2562790 -0.4478242 -0.439342 2.3280830 2.3955459 2.4786909
## X347 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X348 2.2562790 2.2306713 2.273738 -0.4290863 -0.4170024 -0.4030145
## X349 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X350 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X351 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X352 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X353 2.2562790 -0.4478242 -0.439342 2.3280830 2.3955459 2.4786909
## X354 -0.4427415 2.2306713 2.273738 -0.4290863 -0.4170024 -0.4030145
## X355 2.2562790 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X356 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X357 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X358 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X359 2.2562790 2.2306713 -0.439342 2.3280830 2.3955459 2.4786909
## X360 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X361 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X362 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X363 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X364 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X365 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 2.4786909
## X366 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X367 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X368 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X369 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X370 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X371 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X372 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 -0.4030145
## X373 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X374 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X375 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X376 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X377 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X378 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 -0.4030145
## X379 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X380 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X381 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X382 2.2562790 -0.4478242 -0.439342 2.3280830 2.3955459 2.4786909
## X383 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X384 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X385 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X386 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X387 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 -0.4030145
## X388 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 -0.4030145
## X389 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X390 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 -0.4030145
## X391 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X392 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X393 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X394 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X395 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X396 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X397 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X398 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X399 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X400 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 2.4786909
## X401 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X402 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X403 2.2562790 -0.4478242 -0.439342 2.3280830 -0.4170024 -0.4030145
## X404 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X405 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 2.4786909
## X406 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X407 -0.4427415 -0.4478242 -0.439342 2.3280830 -0.4170024 -0.4030145
## X408 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X409 2.2562790 2.2306713 -0.439342 2.3280830 2.3955459 2.4786909
## X410 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X411 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X412 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X413 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 2.4786909
## X414 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X415 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X416 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X417 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X418 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X419 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X420 -0.4427415 -0.4478242 2.273738 -0.4290863 -0.4170024 2.4786909
## X421 -0.4427415 -0.4478242 2.273738 -0.4290863 2.3955459 -0.4030145
## X422 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X423 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X424 2.2562790 2.2306713 -0.439342 2.3280830 2.3955459 2.4786909
## X425 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X426 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X427 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X428 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X429 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X430 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X431 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X432 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X433 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X434 -0.4427415 2.2306713 -0.439342 -0.4290863 2.3955459 -0.4030145
## X435 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X436 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X437 2.2562790 2.2306713 -0.439342 2.3280830 2.3955459 -0.4030145
## X438 2.2562790 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## X439 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X440 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X441 -0.4427415 -0.4478242 -0.439342 2.3280830 2.3955459 -0.4030145
## X442 2.2562790 2.2306713 2.273738 -0.4290863 -0.4170024 -0.4030145
## X443 -0.4427415 -0.4478242 -0.439342 -0.4290863 2.3955459 2.4786909
## X444 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X445 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X446 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X447 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X448 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X449 -0.4427415 2.2306713 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X450 -0.4427415 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X451 2.2562790 -0.4478242 -0.439342 -0.4290863 -0.4170024 -0.4030145
## X452 2.2562790 -0.4478242 -0.439342 2.3280830 -0.4170024 -0.4030145
## X453 -0.4427415 2.2306713 2.273738 2.3280830 -0.4170024 -0.4030145
## X454 -0.4427415 2.2306713 -0.439342 2.3280830 -0.4170024 -0.4030145
## FP128 FP129 FP130 FP131 FP132 FP133
## X1 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X2 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X3 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X4 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X5 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X6 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X7 -0.4170024 -0.4012514 2.9156563 2.6301555 -0.3779927 -0.3798059
## X8 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X9 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X10 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X11 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X12 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X13 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X14 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X15 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X16 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X17 2.3955459 -0.4012514 2.9156563 2.6301555 -0.3779927 2.6301555
## X18 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X19 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X20 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X21 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X22 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 2.6301555
## X23 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X24 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X25 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 2.6301555
## X26 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X27 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 2.6301555
## X28 -0.4170024 -0.4012514 -0.3426153 2.6301555 2.6427722 -0.3798059
## X29 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X30 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X31 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X32 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X33 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X34 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X35 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X36 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X37 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X38 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X39 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X40 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X41 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X42 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X43 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X44 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X45 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 2.6301555
## X46 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X47 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X48 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X49 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X50 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X51 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X52 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X53 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X54 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X55 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X56 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X57 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X58 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X59 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X60 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X61 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X62 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X63 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X64 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X65 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X66 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X67 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X68 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X69 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X70 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X71 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X72 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X73 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X74 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X75 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X76 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X77 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X78 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X79 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X80 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X81 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X82 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X83 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 2.6301555
## X84 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X85 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X86 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X87 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X88 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X89 2.3955459 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X90 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X91 2.3955459 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X92 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X93 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X94 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X95 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X96 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X97 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X98 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X99 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X100 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X101 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X102 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 2.6301555
## X103 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X104 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X105 2.3955459 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X106 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X107 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X108 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X109 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X110 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X111 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X112 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X113 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X114 2.3955459 2.4895825 2.9156563 2.6301555 -0.3779927 2.6301555
## X115 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X116 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X117 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X118 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X119 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X120 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X121 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X122 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X123 2.3955459 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X124 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X125 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X126 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X127 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X128 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X129 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X130 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X131 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X132 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X133 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X134 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X135 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X136 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X137 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X138 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X139 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X140 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X141 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X142 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X143 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X144 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X145 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X146 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X147 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X148 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X149 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X150 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X151 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X152 -0.4170024 2.4895825 2.9156563 2.6301555 -0.3779927 -0.3798059
## X153 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X154 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X155 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X156 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X157 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X158 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X159 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X160 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X161 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X162 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X163 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X164 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X165 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X166 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X167 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X168 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 2.6301555
## X169 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X170 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X171 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X172 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X173 2.3955459 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X174 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X175 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X176 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X177 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X178 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X179 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X180 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X181 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 2.6301555
## X182 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X183 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X184 -0.4170024 2.4895825 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X185 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X186 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X187 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X188 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X189 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X190 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X191 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X192 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X193 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X194 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X195 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X196 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X197 2.3955459 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X198 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X199 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X200 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X201 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X202 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X203 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X204 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X205 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X206 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X207 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X208 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X209 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X210 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X211 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X212 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X213 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X214 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X215 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X216 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X217 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X218 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X219 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X220 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X221 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X222 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X223 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X224 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X225 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X226 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X227 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X228 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X229 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X230 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X231 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X232 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X233 2.3955459 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X234 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X235 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X236 2.3955459 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X237 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X238 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X239 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X240 2.3955459 2.4895825 -0.3426153 -0.3798059 2.6427722 2.6301555
## X241 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X242 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X243 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X244 2.3955459 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X245 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X246 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X247 -0.4170024 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X248 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X249 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X250 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X251 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X252 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X253 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X254 -0.4170024 2.4895825 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X255 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X256 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X257 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X258 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X259 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X260 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X261 2.3955459 -0.4012514 2.9156563 2.6301555 -0.3779927 2.6301555
## X262 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X263 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X264 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X265 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X266 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X267 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X268 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X269 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X270 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X271 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X272 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X273 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X274 2.3955459 2.4895825 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X275 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X276 -0.4170024 -0.4012514 -0.3426153 2.6301555 2.6427722 -0.3798059
## X277 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X278 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X279 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X280 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X281 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X282 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X283 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X284 2.3955459 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X285 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X286 -0.4170024 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X287 -0.4170024 -0.4012514 -0.3426153 2.6301555 2.6427722 -0.3798059
## X288 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X289 2.3955459 2.4895825 -0.3426153 -0.3798059 2.6427722 2.6301555
## X290 2.3955459 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X291 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X292 2.3955459 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X293 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X294 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X295 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X296 2.3955459 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X297 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X298 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X299 2.3955459 2.4895825 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X300 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X301 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X302 2.3955459 -0.4012514 2.9156563 -0.3798059 -0.3779927 2.6301555
## X303 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 2.6301555
## X304 -0.4170024 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X305 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X306 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X307 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X308 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X309 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X310 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X311 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X312 2.3955459 2.4895825 -0.3426153 -0.3798059 2.6427722 2.6301555
## X313 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X314 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X315 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X316 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X317 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X318 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X319 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X320 -0.4170024 2.4895825 -0.3426153 2.6301555 -0.3779927 2.6301555
## X321 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X322 2.3955459 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X323 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X324 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X325 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X326 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X327 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X328 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X329 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X330 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X331 2.3955459 -0.4012514 2.9156563 2.6301555 -0.3779927 -0.3798059
## X332 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X333 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X334 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X335 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X336 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X337 2.3955459 -0.4012514 2.9156563 -0.3798059 2.6427722 -0.3798059
## X338 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X339 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X340 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X341 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X342 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X343 2.3955459 2.4895825 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X344 2.3955459 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X345 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X346 2.3955459 2.4895825 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X347 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X348 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X349 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X350 -0.4170024 2.4895825 2.9156563 2.6301555 -0.3779927 -0.3798059
## X351 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X352 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X353 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X354 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X355 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X356 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X357 -0.4170024 2.4895825 2.9156563 -0.3798059 -0.3779927 2.6301555
## X358 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X359 2.3955459 2.4895825 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X360 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X361 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X362 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X363 -0.4170024 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X364 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X365 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X366 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X367 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X368 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X369 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X370 -0.4170024 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X371 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X372 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X373 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X374 2.3955459 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X375 2.3955459 2.4895825 2.9156563 2.6301555 -0.3779927 2.6301555
## X376 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X377 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X378 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X379 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X380 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X381 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X382 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X383 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X384 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X385 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X386 -0.4170024 -0.4012514 2.9156563 -0.3798059 2.6427722 -0.3798059
## X387 2.3955459 -0.4012514 2.9156563 2.6301555 -0.3779927 -0.3798059
## X388 2.3955459 -0.4012514 2.9156563 -0.3798059 2.6427722 -0.3798059
## X389 -0.4170024 -0.4012514 2.9156563 -0.3798059 2.6427722 -0.3798059
## X390 2.3955459 -0.4012514 2.9156563 2.6301555 -0.3779927 -0.3798059
## X391 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X392 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X393 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X394 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X395 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X396 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X397 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X398 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X399 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X400 -0.4170024 -0.4012514 2.9156563 -0.3798059 -0.3779927 -0.3798059
## X401 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X402 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X403 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X404 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X405 2.3955459 2.4895825 2.9156563 -0.3798059 -0.3779927 2.6301555
## X406 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X407 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X408 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X409 2.3955459 2.4895825 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X410 -0.4170024 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X411 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X412 -0.4170024 -0.4012514 2.9156563 -0.3798059 2.6427722 -0.3798059
## X413 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X414 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X415 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X416 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X417 -0.4170024 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X418 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X419 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X420 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X421 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X422 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X423 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X424 -0.4170024 -0.4012514 -0.3426153 2.6301555 -0.3779927 -0.3798059
## X425 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X426 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X427 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X428 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X429 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X430 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X431 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X432 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X433 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X434 2.3955459 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X435 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X436 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X437 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X438 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X439 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X440 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X441 2.3955459 -0.4012514 2.9156563 2.6301555 -0.3779927 -0.3798059
## X442 -0.4170024 2.4895825 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X443 2.3955459 -0.4012514 2.9156563 2.6301555 2.6427722 -0.3798059
## X444 -0.4170024 -0.4012514 -0.3426153 -0.3798059 2.6427722 -0.3798059
## X445 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X446 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 2.6301555
## X447 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X448 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X449 2.3955459 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X450 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X451 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X452 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X453 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## X454 -0.4170024 -0.4012514 -0.3426153 -0.3798059 -0.3779927 -0.3798059
## FP134 FP135 FP136 FP137 FP138 FP139
## X1 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X2 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X3 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X4 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X5 -0.3816148 -0.3798059 2.6947952 2.763587 2.8219347 -0.2987526
## X6 2.6176881 -0.3798059 -0.3706955 2.763587 -0.3539942 -0.2987526
## X7 -0.3816148 2.6301555 2.6947952 2.763587 2.8219347 3.3437313
## X8 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X9 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X10 -0.3816148 2.6301555 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X11 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X12 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X13 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X14 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X15 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X16 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X17 2.6176881 -0.3798059 2.6947952 -0.361468 2.8219347 3.3437313
## X18 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X19 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X20 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X21 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X22 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X23 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X24 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X25 2.6176881 2.6301555 -0.3706955 -0.361468 2.8219347 3.3437313
## X26 2.6176881 2.6301555 -0.3706955 -0.361468 -0.3539942 3.3437313
## X27 2.6176881 -0.3798059 -0.3706955 2.763587 2.8219347 -0.2987526
## X28 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X29 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X30 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X31 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X32 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X33 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X34 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X35 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X36 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X37 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X38 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X39 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X40 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X41 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X42 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X43 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X44 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X45 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X46 -0.3816148 -0.3798059 -0.3706955 2.763587 -0.3539942 -0.2987526
## X47 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X48 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X49 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X50 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X51 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X52 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X53 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X54 -0.3816148 -0.3798059 2.6947952 -0.361468 2.8219347 -0.2987526
## X55 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X56 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X57 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X58 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X59 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X60 -0.3816148 -0.3798059 2.6947952 2.763587 -0.3539942 -0.2987526
## X61 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X62 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X63 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X64 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X65 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X66 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X67 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X68 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X69 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X70 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X71 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X72 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X73 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X74 2.6176881 -0.3798059 -0.3706955 2.763587 2.8219347 -0.2987526
## X75 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X76 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X77 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X78 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X79 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X80 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X81 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X82 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X83 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X84 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X85 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X86 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X87 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X88 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X89 2.6176881 2.6301555 -0.3706955 -0.361468 2.8219347 3.3437313
## X90 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X91 -0.3816148 2.6301555 -0.3706955 -0.361468 2.8219347 -0.2987526
## X92 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X93 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X94 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X95 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X96 -0.3816148 2.6301555 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X97 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X98 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X99 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X100 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X101 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X102 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X103 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X104 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X105 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X106 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X107 -0.3816148 -0.3798059 -0.3706955 2.763587 -0.3539942 -0.2987526
## X108 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X109 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X110 -0.3816148 -0.3798059 2.6947952 2.763587 -0.3539942 -0.2987526
## X111 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X112 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X113 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X114 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X115 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X116 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X117 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X118 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X119 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X120 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X121 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X122 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X123 2.6176881 2.6301555 -0.3706955 2.763587 -0.3539942 -0.2987526
## X124 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X125 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X126 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X127 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X128 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X129 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X130 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X131 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X132 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X133 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X134 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X135 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X136 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X137 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X138 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X139 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X140 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X141 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X142 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X143 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X144 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X145 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X146 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X147 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X148 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X149 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X150 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X151 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X152 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X153 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X154 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X155 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X156 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X157 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X158 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X159 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X160 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X161 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X162 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X163 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X164 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X165 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X166 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X167 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X168 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X169 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X170 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X171 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X172 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X173 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X174 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X175 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X176 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X177 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X178 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X179 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X180 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X181 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X182 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X183 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X184 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X185 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X186 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X187 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X188 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X189 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X190 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X191 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X192 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X193 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X194 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X195 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X196 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X197 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X198 2.6176881 -0.3798059 -0.3706955 2.763587 -0.3539942 -0.2987526
## X199 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X200 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X201 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X202 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X203 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X204 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X205 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X206 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X207 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X208 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X209 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X210 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X211 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X212 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X213 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X214 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X215 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X216 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X217 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X218 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X219 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X220 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X221 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X222 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X223 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X224 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X225 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X226 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X227 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X228 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X229 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X230 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X231 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X232 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X233 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X234 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X235 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X236 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X237 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X238 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X239 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X240 -0.3816148 -0.3798059 -0.3706955 2.763587 -0.3539942 -0.2987526
## X241 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X242 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X243 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X244 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X245 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X246 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X247 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X248 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X249 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X250 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X251 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X252 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X253 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X254 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X255 2.6176881 -0.3798059 -0.3706955 2.763587 2.8219347 -0.2987526
## X256 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X257 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X258 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X259 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X260 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X261 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X262 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X263 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X264 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X265 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X266 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X267 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X268 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X269 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X270 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X271 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X272 -0.3816148 2.6301555 -0.3706955 2.763587 -0.3539942 -0.2987526
## X273 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X274 -0.3816148 -0.3798059 -0.3706955 2.763587 -0.3539942 -0.2987526
## X275 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X276 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X277 -0.3816148 2.6301555 2.6947952 2.763587 2.8219347 -0.2987526
## X278 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X279 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X280 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X281 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X282 -0.3816148 -0.3798059 -0.3706955 2.763587 -0.3539942 3.3437313
## X283 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X284 -0.3816148 2.6301555 -0.3706955 2.763587 -0.3539942 -0.2987526
## X285 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X286 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X287 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X288 -0.3816148 2.6301555 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X289 -0.3816148 -0.3798059 -0.3706955 2.763587 -0.3539942 -0.2987526
## X290 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X291 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X292 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X293 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X294 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X295 -0.3816148 -0.3798059 -0.3706955 2.763587 -0.3539942 -0.2987526
## X296 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X297 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X298 -0.3816148 2.6301555 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X299 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X300 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X301 -0.3816148 -0.3798059 -0.3706955 2.763587 2.8219347 -0.2987526
## X302 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X303 2.6176881 -0.3798059 2.6947952 -0.361468 2.8219347 -0.2987526
## X304 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X305 2.6176881 2.6301555 -0.3706955 -0.361468 2.8219347 3.3437313
## X306 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X307 -0.3816148 2.6301555 2.6947952 2.763587 2.8219347 -0.2987526
## X308 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X309 -0.3816148 2.6301555 2.6947952 2.763587 2.8219347 -0.2987526
## X310 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X311 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X312 -0.3816148 -0.3798059 -0.3706955 2.763587 -0.3539942 -0.2987526
## X313 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X314 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X315 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X316 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X317 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X318 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X319 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X320 -0.3816148 -0.3798059 2.6947952 -0.361468 2.8219347 -0.2987526
## X321 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X322 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X323 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X324 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X325 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X326 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X327 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X328 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X329 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X330 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X331 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X332 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X333 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X334 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X335 -0.3816148 2.6301555 -0.3706955 -0.361468 2.8219347 -0.2987526
## X336 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X337 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X338 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X339 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X340 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X341 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X342 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X343 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X344 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X345 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X346 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X347 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X348 -0.3816148 2.6301555 2.6947952 2.763587 2.8219347 -0.2987526
## X349 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X350 -0.3816148 2.6301555 2.6947952 -0.361468 2.8219347 3.3437313
## X351 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X352 2.6176881 -0.3798059 -0.3706955 2.763587 2.8219347 -0.2987526
## X353 2.6176881 2.6301555 -0.3706955 -0.361468 2.8219347 3.3437313
## X354 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X355 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X356 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X357 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X358 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X359 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X360 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X361 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X362 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X363 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X364 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X365 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X366 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X367 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X368 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X369 -0.3816148 -0.3798059 -0.3706955 2.763587 2.8219347 -0.2987526
## X370 2.6176881 2.6301555 -0.3706955 -0.361468 -0.3539942 3.3437313
## X371 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X372 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X373 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X374 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X375 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X376 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X377 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X378 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X379 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X380 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X381 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X382 2.6176881 2.6301555 -0.3706955 -0.361468 2.8219347 3.3437313
## X383 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X384 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X385 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X386 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X387 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X388 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X389 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X390 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X391 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X392 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X393 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X394 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X395 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X396 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X397 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X398 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X399 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X400 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X401 -0.3816148 2.6301555 2.6947952 -0.361468 -0.3539942 -0.2987526
## X402 -0.3816148 2.6301555 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X403 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X404 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X405 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X406 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X407 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X408 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X409 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X410 2.6176881 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X411 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X412 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X413 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X414 -0.3816148 2.6301555 -0.3706955 -0.361468 2.8219347 -0.2987526
## X415 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X416 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X417 2.6176881 -0.3798059 2.6947952 -0.361468 -0.3539942 3.3437313
## X418 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X419 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X420 -0.3816148 -0.3798059 -0.3706955 2.763587 -0.3539942 -0.2987526
## X421 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X422 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X423 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X424 -0.3816148 2.6301555 2.6947952 2.763587 2.8219347 -0.2987526
## X425 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X426 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X427 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X428 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X429 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X430 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X431 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X432 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X433 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X434 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X435 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X436 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X437 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X438 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X439 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X440 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X441 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 3.3437313
## X442 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X443 2.6176881 2.6301555 -0.3706955 -0.361468 -0.3539942 3.3437313
## X444 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X445 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X446 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X447 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X448 2.6176881 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X449 -0.3816148 2.6301555 -0.3706955 2.763587 2.8219347 -0.2987526
## X450 -0.3816148 -0.3798059 2.6947952 -0.361468 -0.3539942 -0.2987526
## X451 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X452 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X453 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## X454 -0.3816148 -0.3798059 -0.3706955 -0.361468 -0.3539942 -0.2987526
## FP140 FP141 FP142 FP143 FP144 FP145
## X1 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X2 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X3 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X4 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X5 -0.3539942 -0.3633234 2.8523090 -0.2966615 2.9320660 -0.3406978
## X6 -0.3539942 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X7 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X8 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X9 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X10 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X11 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X12 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X13 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X14 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X15 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X16 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X17 -0.3539942 2.7494745 2.8523090 3.3673007 2.9320660 -0.3406978
## X18 -0.3539942 2.7494745 2.8523090 -0.2966615 2.9320660 2.9320660
## X19 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X20 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X21 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X22 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X23 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X24 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X25 -0.3539942 2.7494745 -0.3502245 3.3673007 2.9320660 -0.3406978
## X26 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X27 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X28 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X29 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X30 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X31 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X32 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X33 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X34 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X35 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X36 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X37 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X38 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X39 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X40 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X41 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X42 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X43 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X44 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X45 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X46 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X47 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X48 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X49 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X50 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X51 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X52 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X53 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X54 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X55 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X56 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X57 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X58 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X59 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X60 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X61 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X62 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X63 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X64 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X65 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X66 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X67 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 2.9320660
## X68 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X69 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X70 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X71 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X72 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X73 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X74 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X75 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X76 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X77 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X78 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X79 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X80 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X81 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X82 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X83 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X84 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X85 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X86 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X87 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X88 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X89 -0.3539942 2.7494745 -0.3502245 3.3673007 2.9320660 -0.3406978
## X90 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X91 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 2.9320660
## X92 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X93 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X94 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X95 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X96 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X97 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X98 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X99 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X100 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X101 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X102 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X103 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X104 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X105 2.8219347 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X106 -0.3539942 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X107 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X108 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X109 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X110 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X111 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X112 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X113 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X114 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X115 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X116 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X117 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X118 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X119 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X120 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X121 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X122 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X123 2.8219347 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X124 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X125 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X126 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X127 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X128 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X129 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X130 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X131 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X132 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X133 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X134 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X135 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X136 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X137 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X138 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X139 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X140 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X141 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X142 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X143 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X144 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X145 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X146 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X147 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X148 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X149 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X150 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X151 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X152 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X153 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X154 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X155 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X156 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X157 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X158 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X159 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X160 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X161 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X162 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X163 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X164 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X165 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X166 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X167 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X168 -0.3539942 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X169 -0.3539942 2.7494745 2.8523090 3.3673007 -0.3406978 -0.3406978
## X170 2.8219347 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X171 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X172 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X173 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 2.9320660
## X174 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X175 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X176 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X177 2.8219347 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X178 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X179 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X180 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X181 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X182 2.8219347 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X183 2.8219347 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X184 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X185 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X186 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X187 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X188 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X189 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X190 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X191 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X192 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X193 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X194 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X195 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X196 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X197 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X198 -0.3539942 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X199 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X200 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X201 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X202 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X203 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X204 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X205 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X206 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X207 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X208 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X209 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X210 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X211 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X212 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X213 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X214 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X215 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X216 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X217 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X218 -0.3539942 -0.3633234 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X219 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X220 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X221 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X222 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X223 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X224 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X225 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X226 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X227 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X228 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X229 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X230 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X231 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X232 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X233 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X234 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X235 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X236 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X237 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X238 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X239 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X240 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X241 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X242 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X243 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X244 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X245 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X246 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X247 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 2.9320660
## X248 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X249 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X250 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X251 2.8219347 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X252 2.8219347 -0.3633234 2.8523090 -0.2966615 2.9320660 -0.3406978
## X253 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X254 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X255 2.8219347 2.7494745 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X256 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X257 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X258 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X259 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X260 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X261 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X262 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X263 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X264 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X265 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X266 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X267 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X268 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X269 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X270 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X271 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X272 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X273 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X274 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X275 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X276 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X277 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X278 -0.3539942 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X279 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X280 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X281 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X282 2.8219347 -0.3633234 -0.3502245 3.3673007 -0.3406978 2.9320660
## X283 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X284 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X285 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X286 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X287 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X288 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X289 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X290 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X291 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X292 2.8219347 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X293 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X294 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X295 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X296 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X297 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X298 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X299 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X300 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X301 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X302 -0.3539942 -0.3633234 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X303 -0.3539942 2.7494745 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X304 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X305 -0.3539942 2.7494745 -0.3502245 3.3673007 2.9320660 -0.3406978
## X306 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X307 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X308 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X309 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X310 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X311 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X312 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X313 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X314 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X315 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X316 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X317 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X318 2.8219347 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X319 -0.3539942 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X320 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X321 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X322 -0.3539942 -0.3633234 2.8523090 -0.2966615 2.9320660 -0.3406978
## X323 2.8219347 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X324 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X325 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X326 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X327 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X328 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X329 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X330 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X331 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X332 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X333 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X334 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X335 -0.3539942 -0.3633234 2.8523090 -0.2966615 2.9320660 2.9320660
## X336 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X337 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 2.9320660
## X338 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X339 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X340 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X341 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X342 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X343 2.8219347 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X344 2.8219347 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X345 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X346 -0.3539942 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X347 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X348 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X349 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X350 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X351 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X352 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X353 -0.3539942 2.7494745 -0.3502245 3.3673007 2.9320660 -0.3406978
## X354 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X355 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X356 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X357 2.8219347 -0.3633234 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X358 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X359 -0.3539942 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X360 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X361 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X362 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X363 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X364 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X365 -0.3539942 -0.3633234 -0.3502245 3.3673007 -0.3406978 2.9320660
## X366 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X367 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X368 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X369 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X370 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X371 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X372 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X373 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X374 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X375 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X376 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X377 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X378 -0.3539942 -0.3633234 2.8523090 -0.2966615 2.9320660 -0.3406978
## X379 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X380 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X381 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X382 -0.3539942 2.7494745 2.8523090 3.3673007 -0.3406978 2.9320660
## X383 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X384 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X385 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X386 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X387 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X388 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X389 2.8219347 2.7494745 -0.3502245 3.3673007 -0.3406978 2.9320660
## X390 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X391 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X392 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 2.9320660
## X393 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X394 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X395 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X396 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X397 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X398 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X399 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X400 -0.3539942 -0.3633234 -0.3502245 3.3673007 -0.3406978 2.9320660
## X401 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X402 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X403 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X404 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X405 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X406 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X407 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X408 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X409 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X410 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X411 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X412 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X413 -0.3539942 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X414 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X415 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X416 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X417 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X418 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X419 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X420 -0.3539942 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X421 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X422 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X423 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X424 -0.3539942 -0.3633234 2.8523090 -0.2966615 2.9320660 -0.3406978
## X425 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X426 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X427 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X428 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X429 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X430 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X431 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X432 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X433 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X434 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X435 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X436 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X437 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X438 -0.3539942 -0.3633234 -0.3502245 -0.2966615 2.9320660 -0.3406978
## X439 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X440 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X441 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 2.9320660
## X442 2.8219347 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X443 -0.3539942 2.7494745 -0.3502245 3.3673007 -0.3406978 -0.3406978
## X444 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X445 -0.3539942 2.7494745 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X446 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X447 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X448 -0.3539942 2.7494745 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X449 2.8219347 -0.3633234 2.8523090 -0.2966615 -0.3406978 -0.3406978
## X450 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X451 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X452 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X453 2.8219347 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## X454 -0.3539942 -0.3633234 -0.3502245 -0.2966615 -0.3406978 -0.3406978
## FP146 FP147 FP148 FP149 FP150 FP151 FP152
## X1 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X2 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X3 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X4 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X5 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X6 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X7 -0.338774 -0.3426153 -0.3090656 3.1697891 3.415804 -0.2428127 -0.2987526
## X8 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X9 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X10 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X11 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X12 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X13 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X14 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X15 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X16 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X17 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X18 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X19 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X20 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X21 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X22 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X23 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X24 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X25 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X26 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X27 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X28 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X29 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X30 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X31 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X32 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X33 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X34 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X35 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X36 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X37 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X38 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X39 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X40 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X41 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X42 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X43 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X44 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X45 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X46 2.948717 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X47 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X48 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X49 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X50 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X51 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X52 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X53 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X54 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X55 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X56 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X57 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X58 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X59 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X60 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X61 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X62 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X63 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X64 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X65 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X66 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X67 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X68 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X69 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X70 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X71 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X72 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X73 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X74 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X75 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X76 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X77 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X78 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X79 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X80 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X81 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X82 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X83 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X84 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X85 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X86 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X87 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X88 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X89 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X90 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X91 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X92 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X93 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X94 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X95 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X96 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X97 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X98 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X99 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X100 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X101 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X102 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X103 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X104 -0.338774 -0.3426153 -0.3090656 3.1697891 3.415804 -0.2428127 -0.2987526
## X105 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X106 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X107 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X108 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X109 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X110 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X111 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X112 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X113 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X114 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X115 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X116 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X117 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X118 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X119 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X120 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X121 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X122 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X123 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X124 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X125 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X126 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X127 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X128 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X129 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X130 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X131 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X132 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X133 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X134 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X135 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X136 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X137 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X138 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X139 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X140 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X141 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X142 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X143 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X144 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X145 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X146 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X147 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X148 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X149 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X150 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X151 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X152 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X153 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X154 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X155 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X156 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X157 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X158 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X159 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X160 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X161 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X162 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X163 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X164 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X165 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X166 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X167 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X168 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X169 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X170 -0.338774 2.9156563 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X171 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X172 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X173 2.948717 -0.3426153 3.2321563 -0.3151467 3.415804 -0.2428127 3.3437313
## X174 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X175 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X176 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X177 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X178 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X179 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X180 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X181 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X182 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X183 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X184 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X185 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X186 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X187 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X188 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X189 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X190 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X191 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X192 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X193 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X194 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X195 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X196 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X197 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X198 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X199 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X200 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X201 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X202 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X203 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X204 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X205 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X206 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X207 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X208 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X209 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X210 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X211 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X212 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X213 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X214 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X215 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X216 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X217 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X218 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X219 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X220 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X221 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X222 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X223 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X224 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X225 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X226 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X227 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X228 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X229 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X230 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X231 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X232 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X233 -0.338774 -0.3426153 -0.3090656 3.1697891 3.415804 -0.2428127 -0.2987526
## X234 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X235 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X236 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X237 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X238 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X239 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X240 2.948717 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X241 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X242 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X243 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X244 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X245 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X246 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X247 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X248 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X249 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X250 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X251 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X252 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X253 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X254 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X255 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X256 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X257 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X258 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X259 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X260 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X261 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X262 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X263 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X264 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X265 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X266 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X267 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X268 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X269 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X270 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X271 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X272 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X273 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X274 2.948717 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X275 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X276 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X277 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X278 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 3.3437313
## X279 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X280 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X281 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X282 -0.338774 2.9156563 -0.3090656 3.1697891 3.415804 -0.2428127 -0.2987526
## X283 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X284 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X285 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X286 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X287 -0.338774 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X288 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X289 2.948717 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X290 2.948717 -0.3426153 -0.3090656 3.1697891 3.415804 -0.2428127 -0.2987526
## X291 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X292 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 4.1140710 3.3437313
## X293 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X294 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X295 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X296 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X297 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X298 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X299 2.948717 -0.3426153 3.2321563 3.1697891 -0.292449 -0.2428127 -0.2987526
## X300 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X301 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X302 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 4.1140710 -0.2987526
## X303 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X304 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X305 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X306 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X307 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X308 2.948717 2.9156563 3.2321563 3.1697891 -0.292449 -0.2428127 -0.2987526
## X309 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X310 2.948717 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X311 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X312 2.948717 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X313 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X314 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X315 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X316 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X317 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X318 -0.338774 2.9156563 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X319 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X320 -0.338774 -0.3426153 3.2321563 -0.3151467 3.415804 -0.2428127 -0.2987526
## X321 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X322 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X323 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X324 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X325 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X326 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X327 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X328 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X329 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X330 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X331 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 4.1140710 3.3437313
## X332 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X333 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X334 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X335 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X336 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X337 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 4.1140710 3.3437313
## X338 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X339 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X340 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X341 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X342 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X343 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X344 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X345 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X346 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 3.3437313
## X347 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X348 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X349 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X350 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X351 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X352 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X353 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X354 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X355 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X356 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X357 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 3.3437313
## X358 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X359 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 3.3437313
## X360 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X361 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X362 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X363 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X364 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X365 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X366 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X367 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X368 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X369 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X370 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 4.1140710 3.3437313
## X371 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X372 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X373 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X374 -0.338774 2.9156563 -0.3090656 3.1697891 3.415804 -0.2428127 -0.2987526
## X375 -0.338774 2.9156563 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X376 2.948717 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X377 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X378 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X379 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X380 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X381 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X382 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 4.1140710 3.3437313
## X383 2.948717 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X384 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X385 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X386 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 4.1140710 3.3437313
## X387 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X388 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 4.1140710 3.3437313
## X389 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 4.1140710 3.3437313
## X390 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X391 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X392 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X393 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X394 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X395 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X396 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X397 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X398 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X399 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X400 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X401 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X402 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X403 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X404 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X405 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 -0.2987526
## X406 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X407 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X408 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X409 2.948717 -0.3426153 3.2321563 3.1697891 -0.292449 -0.2428127 -0.2987526
## X410 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 4.1140710 3.3437313
## X411 2.948717 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X412 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X413 -0.338774 -0.3426153 -0.3090656 -0.3151467 3.415804 -0.2428127 3.3437313
## X414 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X415 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X416 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X417 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 4.1140710 3.3437313
## X418 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X419 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X420 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X421 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X422 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X423 2.948717 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X424 2.948717 -0.3426153 -0.3090656 3.1697891 3.415804 -0.2428127 -0.2987526
## X425 2.948717 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X426 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X427 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X428 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X429 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X430 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X431 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X432 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X433 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X434 2.948717 -0.3426153 -0.3090656 3.1697891 3.415804 -0.2428127 -0.2987526
## X435 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X436 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X437 -0.338774 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X438 2.948717 2.9156563 3.2321563 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X439 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X440 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X441 -0.338774 -0.3426153 -0.3090656 3.1697891 -0.292449 -0.2428127 -0.2987526
## X442 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X443 -0.338774 -0.3426153 3.2321563 -0.3151467 -0.292449 4.1140710 3.3437313
## X444 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X445 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X446 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X447 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X448 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X449 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X450 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X451 -0.338774 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X452 -0.338774 2.9156563 3.2321563 3.1697891 -0.292449 -0.2428127 -0.2987526
## X453 -0.338774 2.9156563 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## X454 2.948717 -0.3426153 -0.3090656 -0.3151467 -0.292449 -0.2428127 -0.2987526
## FP153 FP155 FP156 FP157 FP158 FP159
## X1 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X2 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X3 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X4 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X5 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X6 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X7 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X8 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X9 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X10 -0.2903271 -0.2729429 -0.2751584 -0.2570485 4.1986310 -0.2751584
## X11 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X12 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X13 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X14 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X15 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X16 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X17 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X18 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X19 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X20 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X21 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X22 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X23 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X24 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X25 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X26 -0.2903271 -0.2729429 3.6304485 -0.2570485 4.1986310 3.6304485
## X27 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X28 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X29 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X30 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X31 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X32 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X33 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X34 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X35 -0.2903271 3.6599168 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X36 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X37 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X38 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X39 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X40 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X41 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X42 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X43 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X44 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X45 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X46 3.4407687 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X47 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X48 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X49 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X50 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X51 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X52 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X53 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X54 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X55 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X56 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X57 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X58 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X59 -0.2903271 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X60 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X61 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X62 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X63 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X64 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X65 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X66 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X67 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X68 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X69 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X70 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X71 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X72 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X73 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X74 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X75 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X76 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X77 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X78 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X79 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X80 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X81 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X82 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X83 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X84 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X85 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X86 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X87 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X88 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X89 -0.2903271 -0.2729429 3.6304485 -0.2570485 4.1986310 3.6304485
## X90 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X91 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X92 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X93 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X94 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X95 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X96 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X97 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X98 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X99 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X100 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X101 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X102 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X103 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X104 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X105 3.4407687 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X106 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X107 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X108 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X109 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X110 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X111 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X112 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X113 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X114 3.4407687 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X115 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X116 -0.2903271 -0.2729429 -0.2751584 -0.2570485 4.1986310 -0.2751584
## X117 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X118 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X119 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X120 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X121 -0.2903271 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X122 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X123 3.4407687 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X124 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X125 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X126 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X127 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X128 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X129 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X130 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X131 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X132 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X133 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X134 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X135 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X136 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X137 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X138 -0.2903271 3.6599168 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X139 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X140 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X141 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X142 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X143 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X144 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X145 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X146 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X147 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X148 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X149 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X150 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X151 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X152 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X153 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X154 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X155 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X156 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X157 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X158 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X159 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X160 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X161 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X162 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X163 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X164 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X165 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X166 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X167 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X168 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X169 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X170 3.4407687 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X171 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X172 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X173 3.4407687 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X174 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X175 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X176 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X177 -0.2903271 3.6599168 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X178 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X179 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X180 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X181 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X182 -0.2903271 3.6599168 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X183 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X184 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X185 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X186 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X187 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X188 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X189 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X190 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X191 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X192 -0.2903271 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X193 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X194 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X195 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X196 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X197 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X198 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X199 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X200 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X201 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X202 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X203 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X204 -0.2903271 3.6599168 3.6304485 3.8862252 -0.2379224 -0.2751584
## X205 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X206 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X207 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X208 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X209 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X210 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X211 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X212 -0.2903271 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X213 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X214 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X215 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X216 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X217 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X218 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X219 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X220 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X221 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X222 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X223 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X224 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X225 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X226 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X227 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X228 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X229 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X230 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X231 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X232 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X233 -0.2903271 -0.2729429 -0.2751584 -0.2570485 4.1986310 -0.2751584
## X234 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X235 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X236 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X237 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X238 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X239 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X240 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X241 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X242 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X243 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X244 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X245 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X246 -0.2903271 3.6599168 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X247 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X248 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X249 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X250 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X251 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X252 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X253 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X254 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X255 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X256 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X257 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X258 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X259 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X260 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X261 3.4407687 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X262 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X263 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X264 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X265 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X266 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X267 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X268 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X269 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X270 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X271 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X272 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X273 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X274 3.4407687 3.6599168 -0.2751584 -0.2570485 4.1986310 -0.2751584
## X275 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X276 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X277 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X278 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X279 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X280 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X281 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X282 3.4407687 -0.2729429 -0.2751584 3.8862252 4.1986310 -0.2751584
## X283 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X284 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X285 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X286 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X287 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X288 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X289 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X290 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X291 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X292 -0.2903271 -0.2729429 3.6304485 3.8862252 -0.2379224 3.6304485
## X293 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X294 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X295 -0.2903271 -0.2729429 -0.2751584 -0.2570485 4.1986310 -0.2751584
## X296 -0.2903271 -0.2729429 3.6304485 -0.2570485 4.1986310 3.6304485
## X297 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X298 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X299 -0.2903271 3.6599168 -0.2751584 -0.2570485 4.1986310 -0.2751584
## X300 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X301 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X302 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X303 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X304 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X305 -0.2903271 -0.2729429 3.6304485 -0.2570485 4.1986310 3.6304485
## X306 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X307 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X308 -0.2903271 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X309 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X310 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X311 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X312 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X313 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X314 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X315 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X316 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X317 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X318 3.4407687 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X319 -0.2903271 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X320 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X321 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X322 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X323 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 3.6304485
## X324 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X325 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X326 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X327 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X328 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X329 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X330 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X331 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X332 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X333 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X334 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X335 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X336 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X337 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X338 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X339 -0.2903271 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X340 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X341 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X342 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X343 -0.2903271 3.6599168 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X344 3.4407687 -0.2729429 3.6304485 -0.2570485 -0.2379224 -0.2751584
## X345 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X346 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X347 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X348 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X349 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X350 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X351 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X352 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X353 -0.2903271 -0.2729429 3.6304485 -0.2570485 4.1986310 3.6304485
## X354 -0.2903271 3.6599168 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X355 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X356 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X357 -0.2903271 -0.2729429 3.6304485 3.8862252 -0.2379224 -0.2751584
## X358 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X359 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X360 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X361 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X362 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X363 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X364 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X365 -0.2903271 -0.2729429 -0.2751584 -0.2570485 4.1986310 -0.2751584
## X366 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X367 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X368 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X369 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X370 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X371 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X372 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X373 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X374 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X375 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X376 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X377 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X378 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X379 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X380 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X381 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X382 3.4407687 -0.2729429 3.6304485 -0.2570485 4.1986310 3.6304485
## X383 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X384 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X385 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X386 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X387 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X388 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X389 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X390 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X391 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X392 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X393 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X394 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X395 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X396 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X397 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X398 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X399 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X400 -0.2903271 -0.2729429 -0.2751584 -0.2570485 4.1986310 -0.2751584
## X401 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X402 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X403 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X404 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X405 3.4407687 -0.2729429 -0.2751584 -0.2570485 4.1986310 -0.2751584
## X406 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X407 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X408 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X409 -0.2903271 3.6599168 -0.2751584 -0.2570485 4.1986310 -0.2751584
## X410 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X411 -0.2903271 3.6599168 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X412 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X413 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X414 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X415 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X416 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X417 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X418 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X419 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X420 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X421 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X422 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X423 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X424 3.4407687 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X425 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X426 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X427 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X428 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X429 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X430 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X431 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X432 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X433 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X434 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X435 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X436 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X437 -0.2903271 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X438 -0.2903271 3.6599168 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X439 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X440 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X441 3.4407687 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X442 3.4407687 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X443 -0.2903271 -0.2729429 3.6304485 -0.2570485 -0.2379224 3.6304485
## X444 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X445 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X446 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X447 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X448 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X449 3.4407687 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X450 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X451 -0.2903271 -0.2729429 -0.2751584 -0.2570485 -0.2379224 -0.2751584
## X452 -0.2903271 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X453 -0.2903271 -0.2729429 -0.2751584 3.8862252 -0.2379224 -0.2751584
## X454 -0.2903271 3.6599168 -0.2751584 3.8862252 -0.2379224 -0.2751584
## FP160 FP161 FP162 FP163 FP164 FP165
## X1 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X2 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X3 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X4 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 1.3647334
## X5 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X6 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X7 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X8 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X9 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X10 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X11 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X12 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X13 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X14 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X15 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X16 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X17 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 -0.7319733
## X18 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X19 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 -0.7319733
## X20 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X21 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X22 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X23 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X24 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 -0.7319733
## X25 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X26 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X27 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X28 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X29 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X30 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X31 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X32 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X33 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X34 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X35 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X36 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X37 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X38 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X39 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 1.3647334
## X40 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X41 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X42 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X43 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X44 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X45 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X46 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X47 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X48 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X49 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X50 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X51 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X52 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X53 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X54 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X55 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X56 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X57 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X58 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X59 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X60 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X61 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X62 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X63 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X64 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X65 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X66 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X67 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X68 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X69 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X70 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X71 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X72 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X73 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X74 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 1.3647334
## X75 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X76 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X77 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X78 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X79 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X80 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X81 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X82 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X83 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X84 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X85 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X86 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X87 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X88 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X89 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X90 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 -0.7319733
## X91 -0.2707144 3.7523881 -0.9900597 1.0479417 -1.2979474 1.3647334
## X92 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X93 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X94 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X95 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X96 -0.2707144 3.7523881 1.0089780 1.0479417 0.7696371 1.3647334
## X97 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X98 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X99 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X100 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X101 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X102 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X103 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X104 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X105 3.6900455 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X106 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X107 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X108 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X109 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X110 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X111 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X112 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X113 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X114 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X115 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X116 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X117 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X118 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X119 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X120 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X121 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X122 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X123 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X124 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 1.3647334
## X125 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X126 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X127 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X128 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X129 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X130 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X131 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X132 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X133 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X134 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 1.3647334
## X135 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X136 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X137 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X138 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X139 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X140 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X141 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X142 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X143 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X144 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X145 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X146 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X147 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X148 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X149 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X150 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X151 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X152 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X153 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X154 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X155 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X156 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X157 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X158 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X159 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X160 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X161 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X162 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X163 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X164 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X165 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X166 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X167 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X168 3.6900455 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X169 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X170 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X171 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X172 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X173 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X174 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X175 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 1.3647334
## X176 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X177 3.6900455 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X178 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X179 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X180 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X181 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X182 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X183 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X184 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X185 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X186 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X187 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X188 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X189 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X190 3.6900455 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X191 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X192 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X193 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X194 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X195 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X196 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X197 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X198 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X199 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 1.3647334
## X200 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X201 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X202 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X203 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X204 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X205 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X206 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X207 3.6900455 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X208 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X209 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X210 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X211 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X212 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X213 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X214 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X215 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X216 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X217 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X218 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X219 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X220 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X221 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X222 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X223 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X224 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X225 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X226 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X227 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X228 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X229 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X230 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X231 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X232 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X233 -0.2707144 3.7523881 1.0089780 1.0479417 0.7696371 -0.7319733
## X234 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X235 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X236 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X237 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X238 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X239 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X240 -0.2707144 3.7523881 1.0089780 1.0479417 0.7696371 1.3647334
## X241 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X242 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X243 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X244 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X245 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X246 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X247 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X248 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X249 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X250 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X251 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X252 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X253 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X254 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X255 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X256 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X257 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X258 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X259 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X260 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X261 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X262 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X263 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X264 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X265 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X266 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X267 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X268 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X269 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X270 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X271 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X272 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X273 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X274 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X275 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X276 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X277 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X278 3.6900455 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X279 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X280 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X281 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X282 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X283 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X284 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X285 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X286 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X287 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X288 -0.2707144 3.7523881 -0.9900597 1.0479417 0.7696371 1.3647334
## X289 -0.2707144 3.7523881 1.0089780 1.0479417 0.7696371 1.3647334
## X290 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X291 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X292 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X293 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X294 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X295 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X296 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X297 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X298 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X299 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X300 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X301 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X302 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X303 3.6900455 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X304 3.6900455 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X305 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X306 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X307 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X308 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X309 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X310 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X311 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X312 -0.2707144 3.7523881 1.0089780 1.0479417 0.7696371 1.3647334
## X313 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X314 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X315 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X316 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X317 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X318 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X319 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X320 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X321 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X322 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X323 3.6900455 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X324 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X325 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X326 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X327 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X328 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X329 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X330 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X331 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X332 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X333 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X334 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X335 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X336 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X337 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X338 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X339 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X340 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X341 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X342 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X343 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X344 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X345 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X346 3.6900455 -0.2662167 -0.9900597 1.0479417 -1.2979474 -0.7319733
## X347 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X348 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X349 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X350 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X351 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X352 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 1.3647334
## X353 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X354 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X355 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X356 -0.2707144 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X357 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X358 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X359 3.6900455 -0.2662167 -0.9900597 1.0479417 -1.2979474 -0.7319733
## X360 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X361 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X362 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X363 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X364 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X365 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X366 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X367 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X368 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X369 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X370 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X371 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X372 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X373 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X374 -0.2707144 3.7523881 1.0089780 1.0479417 0.7696371 -0.7319733
## X375 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X376 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X377 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X378 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X379 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X380 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X381 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X382 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X383 -0.2707144 3.7523881 -0.9900597 1.0479417 0.7696371 1.3647334
## X384 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X385 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X386 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X387 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X388 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X389 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X390 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X391 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X392 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X393 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X394 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X395 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X396 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X397 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X398 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X399 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X400 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X401 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X402 -0.2707144 3.7523881 1.0089780 1.0479417 0.7696371 1.3647334
## X403 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X404 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X405 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 -0.7319733
## X406 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X407 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X408 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X409 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X410 3.6900455 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X411 -0.2707144 3.7523881 1.0089780 1.0479417 0.7696371 -0.7319733
## X412 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X413 3.6900455 -0.2662167 -0.9900597 -0.9532482 0.7696371 -0.7319733
## X414 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X415 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X416 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X417 3.6900455 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X418 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X419 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X420 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X421 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X422 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X423 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X424 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X425 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X426 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X427 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X428 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X429 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X430 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X431 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X432 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X433 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X434 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X435 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 -0.7319733
## X436 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X437 -0.2707144 3.7523881 -0.9900597 1.0479417 0.7696371 1.3647334
## X438 -0.2707144 -0.2662167 -0.9900597 1.0479417 0.7696371 1.3647334
## X439 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X440 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X441 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X442 -0.2707144 -0.2662167 1.0089780 -0.9532482 0.7696371 -0.7319733
## X443 3.6900455 -0.2662167 -0.9900597 1.0479417 0.7696371 -0.7319733
## X444 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X445 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X446 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X447 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X448 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X449 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## X450 -0.2707144 -0.2662167 -0.9900597 -0.9532482 -1.2979474 -0.7319733
## X451 -0.2707144 -0.2662167 -0.9900597 1.0479417 -1.2979474 1.3647334
## X452 -0.2707144 3.7523881 1.0089780 1.0479417 0.7696371 -0.7319733
## X453 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 -0.7319733
## X454 -0.2707144 -0.2662167 1.0089780 1.0479417 0.7696371 1.3647334
## FP166 FP167 FP168 FP169 FP170 FP171
## X1 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X2 1.4201847 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X3 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X4 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X5 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X6 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X7 1.4201847 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X8 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X9 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X10 1.4201847 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X11 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X12 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X13 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X14 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X15 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X16 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 2.2139721
## X17 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X18 1.4201847 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X19 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X20 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X21 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X22 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X23 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X24 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 2.2139721
## X25 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X26 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X27 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 2.2139721
## X28 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X29 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X30 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X31 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X32 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X33 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 -0.4512019
## X34 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X35 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X36 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X37 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 -0.4512019
## X38 -0.7033934 1.4303578 -1.4101322 -0.4779558 2.1046669 2.2139721
## X39 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X40 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X41 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X42 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X43 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X44 1.4201847 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X45 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X46 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X47 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X48 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X49 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X50 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 2.2139721
## X51 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X52 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X53 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X54 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X55 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X56 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X57 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X58 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X59 -0.7033934 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X60 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X61 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X62 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X63 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X64 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X65 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X66 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X67 1.4201847 1.4303578 0.7084077 2.0900438 2.1046669 -0.4512019
## X68 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X69 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 -0.4512019
## X70 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X71 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X72 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X73 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X74 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X75 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X76 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X77 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X78 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X79 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X80 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X81 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X82 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X83 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X84 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X85 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X86 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X87 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X88 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X89 -0.7033934 1.4303578 0.7084077 2.0900438 2.1046669 -0.4512019
## X90 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X91 -0.7033934 1.4303578 -1.4101322 -0.4779558 2.1046669 2.2139721
## X92 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X93 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X94 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X95 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X96 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 2.2139721
## X97 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X98 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X99 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X100 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X101 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X102 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X103 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X104 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X105 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 2.2139721
## X106 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 -0.4512019
## X107 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X108 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X109 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X110 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X111 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X112 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X113 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X114 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 2.2139721
## X115 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X116 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X117 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X118 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X119 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X120 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X121 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X122 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X123 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X124 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X125 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X126 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X127 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X128 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X129 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X130 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X131 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X132 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X133 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X134 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X135 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X136 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X137 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X138 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X139 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X140 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X141 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X142 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X143 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X144 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X145 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X146 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X147 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X148 1.4201847 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X149 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X150 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X151 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X152 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X153 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X154 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X155 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X156 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X157 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X158 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X159 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X160 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X161 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X162 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X163 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X164 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X165 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X166 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X167 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X168 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X169 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X170 -0.7033934 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X171 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X172 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 -0.4512019
## X173 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X174 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X175 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X176 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X177 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X178 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X179 -0.7033934 1.4303578 -1.4101322 -0.4779558 2.1046669 2.2139721
## X180 -0.7033934 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X181 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X182 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X183 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X184 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X185 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X186 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X187 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X188 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X189 1.4201847 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X190 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X191 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X192 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X193 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X194 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X195 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X196 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X197 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X198 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X199 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X200 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X201 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X202 -0.7033934 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X203 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X204 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X205 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X206 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X207 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X208 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X209 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X210 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X211 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X212 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X213 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X214 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X215 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X216 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X217 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X218 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X219 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X220 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X221 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X222 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X223 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X224 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X225 1.4201847 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X226 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X227 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X228 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X229 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X230 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X231 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X232 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X233 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X234 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X235 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X236 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X237 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X238 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X239 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X240 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X241 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X242 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X243 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X244 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X245 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 2.2139721
## X246 1.4201847 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X247 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X248 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X249 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 -0.4512019
## X250 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X251 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X252 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X253 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X254 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X255 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X256 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X257 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X258 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X259 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 -0.4512019
## X260 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X261 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X262 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X263 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X264 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X265 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X266 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X267 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X268 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X269 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X270 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X271 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X272 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X273 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X274 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X275 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X276 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X277 -0.7033934 -0.6983906 0.7084077 2.0900438 2.1046669 2.2139721
## X278 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X279 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X280 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X281 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X282 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X283 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X284 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X285 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X286 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X287 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X288 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 2.2139721
## X289 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X290 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X291 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X292 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X293 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X294 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X295 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X296 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X297 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X298 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X299 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X300 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X301 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X302 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X303 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X304 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X305 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X306 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X307 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 2.2139721
## X308 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X309 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 2.2139721
## X310 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X311 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X312 1.4201847 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X313 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X314 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X315 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X316 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X317 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X318 -0.7033934 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X319 1.4201847 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X320 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X321 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X322 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X323 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X324 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X325 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X326 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X327 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X328 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X329 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X330 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X331 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X332 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X333 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X334 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X335 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X336 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X337 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X338 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X339 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X340 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X341 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X342 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X343 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X344 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X345 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X346 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X347 -0.7033934 1.4303578 -1.4101322 -0.4779558 2.1046669 2.2139721
## X348 -0.7033934 -0.6983906 0.7084077 2.0900438 2.1046669 2.2139721
## X349 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X350 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X351 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X352 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X353 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X354 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X355 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X356 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X357 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X358 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X359 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X360 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X361 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X362 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X363 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X364 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 -0.4512019
## X365 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X366 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X367 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X368 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X369 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X370 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X371 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X372 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X373 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X374 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X375 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X376 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X377 -0.7033934 1.4303578 -1.4101322 -0.4779558 2.1046669 2.2139721
## X378 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X379 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X380 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X381 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X382 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X383 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X384 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X385 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 2.2139721
## X386 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X387 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X388 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X389 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X390 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X391 -0.7033934 1.4303578 -1.4101322 -0.4779558 2.1046669 2.2139721
## X392 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X393 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X394 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X395 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X396 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X397 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X398 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 2.2139721
## X399 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X400 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X401 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 2.2139721
## X402 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X403 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X404 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X405 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X406 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X407 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X408 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X409 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X410 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 2.2139721
## X411 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X412 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X413 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X414 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X415 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X416 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X417 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X418 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X419 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## X420 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X421 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X422 -0.7033934 1.4303578 0.7084077 2.0900438 -0.4746349 -0.4512019
## X423 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X424 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X425 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X426 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X427 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X428 1.4201847 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X429 1.4201847 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X430 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X431 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X432 -0.7033934 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X433 -0.7033934 -0.6983906 -1.4101322 -0.4779558 2.1046669 -0.4512019
## X434 1.4201847 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X435 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X436 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X437 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X438 -0.7033934 1.4303578 0.7084077 -0.4779558 2.1046669 -0.4512019
## X439 -0.7033934 -0.6983906 -1.4101322 -0.4779558 -0.4746349 2.2139721
## X440 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X441 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X442 -0.7033934 -0.6983906 0.7084077 -0.4779558 2.1046669 -0.4512019
## X443 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X444 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X445 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X446 1.4201847 1.4303578 0.7084077 2.0900438 -0.4746349 2.2139721
## X447 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X448 -0.7033934 1.4303578 -1.4101322 -0.4779558 2.1046669 -0.4512019
## X449 -0.7033934 1.4303578 0.7084077 2.0900438 2.1046669 -0.4512019
## X450 -0.7033934 -0.6983906 0.7084077 -0.4779558 -0.4746349 -0.4512019
## X451 -0.7033934 1.4303578 -1.4101322 -0.4779558 -0.4746349 -0.4512019
## X452 -0.7033934 -0.6983906 0.7084077 2.0900438 2.1046669 -0.4512019
## X453 -0.7033934 -0.6983906 0.7084077 2.0900438 -0.4746349 -0.4512019
## X454 1.4201847 1.4303578 0.7084077 -0.4779558 -0.4746349 2.2139721
## FP172 FP173 FP174 FP175 FP176 FP177
## X1 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X2 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X3 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X4 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X5 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X6 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X7 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X8 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X9 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X10 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X11 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X12 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X13 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X14 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X15 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X16 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X17 -0.4221979 -0.4065307 -0.3870166 2.5343493 2.6815493 2.6947952
## X18 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X19 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X20 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X21 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X22 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X23 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X24 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X25 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X26 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X27 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X28 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X29 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X30 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X31 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X32 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X33 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X34 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X35 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X36 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X37 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X38 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X39 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X40 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X41 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X42 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X43 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X44 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X45 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X46 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X47 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X48 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X49 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X50 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X51 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X52 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X53 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X54 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X55 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X56 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X57 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X58 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X59 2.3660671 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X60 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X61 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X62 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X63 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X64 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X65 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X66 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X67 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X68 -0.4221979 2.4572522 2.5811513 2.5343493 -0.3725266 -0.3706955
## X69 -0.4221979 2.4572522 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X70 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X71 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X72 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X73 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X74 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X75 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X76 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X77 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X78 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X79 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X80 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X81 2.3660671 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X82 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X83 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X84 2.3660671 -0.4065307 2.5811513 -0.3941637 -0.3725266 2.6947952
## X85 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X86 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X87 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X88 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X89 2.3660671 2.4572522 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X90 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X91 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X92 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X93 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X94 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X95 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X96 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X97 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X98 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X99 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X100 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X101 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X102 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X103 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X104 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X105 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X106 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X107 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X108 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X109 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X110 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X111 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X112 2.3660671 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X113 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X114 2.3660671 -0.4065307 2.5811513 -0.3941637 2.6815493 -0.3706955
## X115 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X116 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X117 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X118 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X119 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X120 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X121 2.3660671 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X122 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X123 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X124 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X125 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X126 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X127 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X128 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X129 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X130 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X131 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X132 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X133 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X134 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X135 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X136 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X137 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X138 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X139 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X140 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X141 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X142 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X143 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X144 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X145 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X146 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X147 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X148 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X149 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X150 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X151 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X152 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X153 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X154 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X155 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X156 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X157 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X158 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X159 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X160 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X161 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X162 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X163 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X164 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X165 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X166 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X167 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X168 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X169 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X170 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X171 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X172 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X173 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X174 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X175 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X176 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X177 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X178 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X179 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X180 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X181 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X182 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X183 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X184 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X185 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X186 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X187 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X188 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X189 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X190 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X191 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X192 -0.4221979 -0.4065307 2.5811513 -0.3941637 2.6815493 -0.3706955
## X193 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X194 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X195 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X196 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X197 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X198 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X199 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X200 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X201 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X202 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X203 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X204 2.3660671 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X205 2.3660671 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X206 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X207 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X208 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X209 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X210 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X211 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X212 2.3660671 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X213 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X214 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X215 2.3660671 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X216 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X217 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X218 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X219 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X220 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X221 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X222 2.3660671 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X223 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X224 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X225 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X226 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X227 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X228 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X229 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X230 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X231 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X232 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X233 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X234 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X235 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X236 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X237 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X238 2.3660671 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X239 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X240 2.3660671 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X241 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X242 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X243 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X244 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X245 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X246 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X247 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X248 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X249 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X250 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X251 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X252 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X253 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X254 -0.4221979 2.4572522 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X255 2.3660671 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X256 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X257 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X258 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X259 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X260 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X261 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X262 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X263 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X264 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X265 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X266 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X267 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X268 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X269 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X270 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X271 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X272 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X273 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X274 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X275 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X276 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X277 -0.4221979 2.4572522 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X278 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X279 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X280 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X281 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X282 2.3660671 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X283 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X284 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X285 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X286 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X287 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X288 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X289 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X290 2.3660671 -0.4065307 2.5811513 -0.3941637 2.6815493 -0.3706955
## X291 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X292 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X293 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X294 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X295 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X296 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X297 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X298 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X299 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X300 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X301 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X302 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X303 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X304 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X305 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 2.6947952
## X306 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X307 -0.4221979 2.4572522 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X308 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X309 -0.4221979 2.4572522 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X310 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X311 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X312 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X313 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X314 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X315 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X316 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X317 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X318 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X319 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X320 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X321 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X322 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X323 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X324 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X325 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X326 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X327 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X328 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X329 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X330 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X331 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X332 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X333 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X334 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X335 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 2.6947952
## X336 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X337 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X338 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X339 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X340 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X341 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X342 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X343 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X344 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X345 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X346 -0.4221979 -0.4065307 2.5811513 2.5343493 -0.3725266 -0.3706955
## X347 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X348 -0.4221979 2.4572522 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X349 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X350 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X351 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X352 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X353 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 2.6947952
## X354 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X355 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X356 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X357 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X358 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X359 -0.4221979 -0.4065307 2.5811513 2.5343493 -0.3725266 -0.3706955
## X360 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X361 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X362 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X363 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X364 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X365 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X366 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X367 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X368 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X369 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X370 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X371 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X372 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X373 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X374 2.3660671 2.4572522 2.5811513 -0.3941637 2.6815493 -0.3706955
## X375 2.3660671 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X376 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X377 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X378 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X379 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X380 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X381 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X382 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X383 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X384 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X385 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X386 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X387 -0.4221979 2.4572522 2.5811513 2.5343493 -0.3725266 -0.3706955
## X388 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X389 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X390 -0.4221979 2.4572522 2.5811513 2.5343493 -0.3725266 -0.3706955
## X391 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X392 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X393 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X394 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X395 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X396 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X397 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X398 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X399 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X400 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X401 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X402 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X403 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X404 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X405 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X406 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X407 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X408 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X409 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X410 2.3660671 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X411 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X412 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X413 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 -0.3706955
## X414 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X415 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X416 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X417 -0.4221979 -0.4065307 -0.3870166 -0.3941637 2.6815493 2.6947952
## X418 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X419 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X420 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X421 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X422 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X423 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X424 -0.4221979 -0.4065307 2.5811513 -0.3941637 2.6815493 -0.3706955
## X425 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X426 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X427 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X428 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X429 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X430 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X431 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X432 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X433 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X434 -0.4221979 -0.4065307 2.5811513 -0.3941637 2.6815493 -0.3706955
## X435 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X436 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X437 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X438 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X439 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X440 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X441 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X442 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X443 2.3660671 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X444 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X445 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X446 2.3660671 -0.4065307 -0.3870166 -0.3941637 -0.3725266 2.6947952
## X447 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X448 -0.4221979 2.4572522 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X449 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X450 -0.4221979 -0.4065307 -0.3870166 -0.3941637 -0.3725266 -0.3706955
## X451 -0.4221979 -0.4065307 -0.3870166 2.5343493 -0.3725266 -0.3706955
## X452 -0.4221979 2.4572522 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X453 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## X454 -0.4221979 -0.4065307 2.5811513 -0.3941637 -0.3725266 -0.3706955
## FP178 FP179 FP180 FP181 FP182 FP183
## X1 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X2 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X3 -0.3706955 -0.3290557 2.8835355 -0.3211537 3.017853 -0.2860509
## X4 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X5 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X6 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X7 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X8 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X9 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X10 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X11 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X12 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X13 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X14 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X15 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X16 -0.3706955 -0.3290557 2.8835355 -0.3211537 3.017853 -0.2860509
## X17 2.6947952 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X18 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X19 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X20 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X21 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X22 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X23 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X24 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X25 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X26 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X27 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X28 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X29 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X30 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X31 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X32 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X33 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X34 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X35 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X36 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X37 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X38 -0.3706955 -0.3290557 2.8835355 3.1104998 3.017853 -0.2860509
## X39 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X40 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X41 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X42 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X43 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X44 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X45 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X46 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X47 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X48 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X49 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X50 -0.3706955 -0.3290557 2.8835355 -0.3211537 3.017853 -0.2860509
## X51 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X52 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X53 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X54 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X55 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X56 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X57 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X58 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X59 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X60 -0.3706955 3.0358039 2.8835355 -0.3211537 -0.331013 -0.2860509
## X61 2.6947952 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X62 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X63 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X64 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X65 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X66 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X67 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X68 2.6947952 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X69 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X70 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X71 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X72 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X73 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X74 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X75 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X76 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X77 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X78 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X79 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X80 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X81 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X82 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X83 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X84 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X85 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X86 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X87 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X88 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X89 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X90 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X91 -0.3706955 -0.3290557 2.8835355 3.1104998 3.017853 -0.2860509
## X92 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X93 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X94 2.6947952 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X95 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X96 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 3.4922050
## X97 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X98 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X99 -0.3706955 3.0358039 -0.3464318 3.1104998 -0.331013 -0.2860509
## X100 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X101 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X102 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X103 2.6947952 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X104 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X105 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X106 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X107 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X108 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X109 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X110 -0.3706955 3.0358039 2.8835355 -0.3211537 -0.331013 -0.2860509
## X111 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X112 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X113 2.6947952 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X114 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X115 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X116 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X117 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X118 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X119 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X120 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X121 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X122 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X123 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X124 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X125 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X126 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X127 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X128 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X129 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X130 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X131 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X132 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X133 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X134 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X135 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X136 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X137 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X138 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X139 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X140 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X141 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X142 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X143 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X144 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X145 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X146 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X147 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X148 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X149 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X150 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X151 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X152 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X153 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X154 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X155 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X156 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X157 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X158 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X159 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X160 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X161 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X162 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X163 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X164 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X165 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X166 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X167 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X168 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X169 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X170 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X171 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X172 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X173 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X174 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X175 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X176 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X177 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X178 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X179 -0.3706955 -0.3290557 2.8835355 3.1104998 3.017853 -0.2860509
## X180 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 3.4922050
## X181 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X182 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X183 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X184 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X185 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X186 2.6947952 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X187 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X188 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X189 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X190 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X191 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X192 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X193 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X194 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X195 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X196 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X197 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X198 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X199 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X200 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X201 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X202 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 3.4922050
## X203 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X204 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X205 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X206 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X207 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X208 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X209 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X210 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X211 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X212 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X213 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X214 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X215 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X216 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X217 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X218 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 3.4922050
## X219 2.6947952 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X220 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X221 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X222 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X223 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X224 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X225 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X226 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X227 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X228 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X229 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X230 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X231 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X232 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X233 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X234 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X235 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X236 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X237 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X238 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X239 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X240 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 3.4922050
## X241 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X242 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X243 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X244 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X245 -0.3706955 3.0358039 2.8835355 -0.3211537 3.017853 -0.2860509
## X246 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X247 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X248 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X249 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X250 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X251 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X252 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X253 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X254 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X255 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X256 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X257 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X258 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X259 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X260 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X261 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X262 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X263 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X264 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X265 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X266 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X267 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X268 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X269 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X270 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X271 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X272 -0.3706955 3.0358039 -0.3464318 -0.3211537 3.017853 -0.2860509
## X273 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X274 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X275 2.6947952 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X276 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X277 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X278 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X279 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X280 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 3.4922050
## X281 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X282 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X283 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X284 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X285 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X286 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X287 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X288 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 3.4922050
## X289 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 3.4922050
## X290 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X291 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X292 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X293 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X294 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X295 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X296 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X297 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X298 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X299 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X300 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X301 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X302 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X303 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X304 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X305 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X306 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X307 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X308 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X309 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X310 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X311 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X312 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 3.4922050
## X313 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X314 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X315 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X316 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X317 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X318 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X319 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X320 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X321 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X322 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X323 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X324 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X325 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X326 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X327 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X328 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X329 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X330 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X331 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X332 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X333 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X334 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X335 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X336 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X337 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X338 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X339 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X340 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 3.4922050
## X341 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X342 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X343 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X344 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X345 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X346 -0.3706955 -0.3290557 -0.3464318 3.1104998 3.017853 -0.2860509
## X347 -0.3706955 -0.3290557 2.8835355 3.1104998 3.017853 -0.2860509
## X348 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X349 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X350 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X351 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X352 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X353 2.6947952 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X354 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X355 2.6947952 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X356 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X357 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X358 2.6947952 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X359 -0.3706955 -0.3290557 -0.3464318 3.1104998 3.017853 -0.2860509
## X360 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X361 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X362 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X363 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X364 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X365 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X366 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X367 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X368 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X369 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X370 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X371 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X372 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X373 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X374 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X375 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X376 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X377 -0.3706955 -0.3290557 2.8835355 3.1104998 3.017853 -0.2860509
## X378 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X379 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X380 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X381 2.6947952 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X382 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X383 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X384 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X385 -0.3706955 -0.3290557 2.8835355 -0.3211537 3.017853 -0.2860509
## X386 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X387 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X388 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 3.4922050
## X389 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X390 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X391 -0.3706955 -0.3290557 2.8835355 3.1104998 3.017853 -0.2860509
## X392 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X393 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X394 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X395 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X396 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X397 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X398 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X399 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X400 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X401 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X402 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 3.4922050
## X403 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X404 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X405 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X406 -0.3706955 3.0358039 2.8835355 -0.3211537 -0.331013 -0.2860509
## X407 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X408 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X409 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X410 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X411 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 3.4922050
## X412 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X413 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X414 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X415 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X416 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X417 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X418 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X419 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X420 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X421 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X422 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X423 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X424 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X425 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X426 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X427 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X428 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X429 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X430 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X431 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X432 -0.3706955 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X433 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X434 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X435 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X436 -0.3706955 3.0358039 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X437 -0.3706955 -0.3290557 2.8835355 3.1104998 -0.331013 -0.2860509
## X438 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 -0.2860509
## X439 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X440 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X441 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X442 -0.3706955 -0.3290557 -0.3464318 3.1104998 -0.331013 3.4922050
## X443 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X444 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X445 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X446 -0.3706955 -0.3290557 -0.3464318 -0.3211537 3.017853 -0.2860509
## X447 2.6947952 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X448 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X449 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X450 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X451 2.6947952 -0.3290557 2.8835355 -0.3211537 -0.331013 -0.2860509
## X452 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## X453 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 -0.2860509
## X454 -0.3706955 -0.3290557 -0.3464318 -0.3211537 -0.331013 3.4922050
## FP184 FP185 FP186 FP187 FP188 FP189
## X1 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X2 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X3 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X4 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X5 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X6 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X7 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X8 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X9 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X10 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X11 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X12 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X13 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X14 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X15 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X16 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X17 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X18 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X19 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X20 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X21 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X22 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X23 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X24 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 3.4662300
## X25 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X26 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X27 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 3.4662300
## X28 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X29 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X30 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X31 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X32 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X33 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X34 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X35 -0.3029057 -0.3049681 3.4662300 -0.2795515 3.6900455 -0.2881945
## X36 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X37 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X38 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X39 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X40 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X41 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X42 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X43 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X44 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X45 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X46 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 3.4662300
## X47 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X48 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X49 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X50 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X51 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X52 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X53 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X54 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X55 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X56 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X57 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X58 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X59 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X60 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X61 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X62 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X63 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X64 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X65 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X66 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X67 -0.3029057 -0.3049681 -0.2881945 -0.2795515 3.6900455 3.4662300
## X68 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X69 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X70 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X71 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X72 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X73 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X74 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X75 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X76 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X77 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X78 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X79 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X80 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X81 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X82 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X83 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X84 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X85 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X86 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X87 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X88 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X89 -0.3029057 3.2755834 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X90 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X91 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X92 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X93 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X94 -0.3029057 -0.3049681 3.4662300 3.5733972 3.6900455 -0.2881945
## X95 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X96 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X97 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X98 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X99 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X100 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X101 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X102 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 3.4662300
## X103 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X104 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X105 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 3.4662300
## X106 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X107 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X108 -0.3029057 3.2755834 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X109 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X110 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X111 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X112 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X113 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X114 3.2978859 -0.3049681 -0.2881945 3.5733972 -0.2707144 3.4662300
## X115 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X116 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X117 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X118 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X119 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X120 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X121 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X122 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X123 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X124 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X125 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X126 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X127 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X128 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X129 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X130 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X131 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X132 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X133 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X134 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X135 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X136 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X137 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X138 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X139 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X140 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X141 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X142 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X143 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X144 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X145 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X146 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X147 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X148 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X149 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X150 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X151 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X152 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X153 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X154 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X155 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X156 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X157 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X158 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X159 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X160 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X161 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X162 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X163 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X164 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X165 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X166 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X167 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X168 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X169 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X170 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 3.4662300
## X171 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X172 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X173 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X174 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X175 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X176 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X177 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X178 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X179 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X180 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X181 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X182 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X183 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X184 3.2978859 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X185 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X186 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X187 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X188 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X189 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 3.4662300
## X190 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X191 -0.3029057 3.2755834 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X192 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X193 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X194 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X195 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X196 -0.3029057 3.2755834 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X197 3.2978859 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X198 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X199 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X200 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X201 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X202 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X203 -0.3029057 -0.3049681 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X204 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X205 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X206 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X207 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X208 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X209 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X210 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X211 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X212 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X213 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X214 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X215 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X216 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X217 3.2978859 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X218 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X219 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X220 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X221 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X222 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X223 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X224 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X225 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X226 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X227 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X228 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X229 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X230 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X231 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X232 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X233 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X234 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X235 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X236 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X237 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X238 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X239 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X240 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X241 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X242 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X243 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X244 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X245 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X246 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X247 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X248 -0.3029057 -0.3049681 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X249 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X250 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X251 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X252 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X253 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X254 -0.3029057 3.2755834 3.4662300 3.5733972 -0.2707144 -0.2881945
## X255 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X256 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X257 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X258 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X259 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X260 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X261 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X262 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X263 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X264 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X265 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X266 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X267 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X268 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X269 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X270 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X271 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X272 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X273 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X274 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X275 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X276 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X277 -0.3029057 3.2755834 3.4662300 -0.2795515 -0.2707144 3.4662300
## X278 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X279 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X280 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X281 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X282 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X283 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X284 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X285 -0.3029057 -0.3049681 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X286 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X287 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X288 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X289 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X290 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X291 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X292 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X293 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X294 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X295 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X296 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X297 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X298 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X299 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X300 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X301 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X302 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X303 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X304 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X305 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X306 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X307 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X308 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X309 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X310 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X311 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X312 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X313 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X314 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X315 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X316 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X317 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X318 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 3.4662300
## X319 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X320 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X321 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X322 3.2978859 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X323 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X324 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X325 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X326 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X327 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X328 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X329 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X330 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X331 -0.3029057 -0.3049681 -0.2881945 3.5733972 3.6900455 -0.2881945
## X332 -0.3029057 -0.3049681 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X333 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X334 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X335 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X336 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X337 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X338 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X339 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X340 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X341 -0.3029057 -0.3049681 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X342 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X343 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X344 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X345 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X346 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X347 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X348 -0.3029057 3.2755834 3.4662300 -0.2795515 -0.2707144 3.4662300
## X349 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X350 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X351 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X352 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X353 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X354 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X355 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X356 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X357 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X358 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X359 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X360 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X361 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X362 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X363 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X364 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X365 3.2978859 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X366 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X367 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X368 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X369 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X370 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X371 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X372 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X373 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X374 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X375 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X376 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X377 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X378 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X379 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X380 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X381 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X382 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X383 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X384 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X385 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X386 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X387 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X388 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X389 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X390 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X391 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X392 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X393 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X394 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X395 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X396 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X397 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X398 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X399 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X400 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X401 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X402 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X403 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X404 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X405 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X406 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X407 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X408 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X409 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X410 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X411 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X412 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X413 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X414 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X415 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X416 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X417 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X418 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X419 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X420 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X421 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X422 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X423 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X424 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X425 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X426 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X427 -0.3029057 -0.3049681 -0.2881945 3.5733972 -0.2707144 -0.2881945
## X428 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X429 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X430 -0.3029057 -0.3049681 -0.2881945 -0.2795515 3.6900455 -0.2881945
## X431 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X432 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X433 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X434 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X435 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X436 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X437 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X438 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X439 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X440 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X441 -0.3029057 -0.3049681 -0.2881945 -0.2795515 3.6900455 3.4662300
## X442 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X443 3.2978859 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X444 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X445 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X446 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X447 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X448 -0.3029057 3.2755834 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X449 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 3.4662300
## X450 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X451 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X452 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## X453 -0.3029057 -0.3049681 3.4662300 -0.2795515 -0.2707144 -0.2881945
## X454 -0.3029057 -0.3049681 -0.2881945 -0.2795515 -0.2707144 -0.2881945
## FP190 FP191 FP192 FP193 FP194 FP195
## X1 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X2 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X3 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X4 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X5 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X6 -0.2795515 3.6304485 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X7 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X8 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X9 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X10 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X11 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X12 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X13 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X14 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X15 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X16 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X17 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X18 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X19 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X20 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X21 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X22 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X23 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X24 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X25 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X26 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X27 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X28 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X29 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X30 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X31 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X32 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X33 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X34 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X35 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X36 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X37 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X38 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X39 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X40 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X41 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X42 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X43 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X44 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X45 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X46 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X47 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X48 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X49 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X50 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X51 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X52 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X53 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X54 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X55 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X56 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X57 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X58 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X59 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X60 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X61 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X62 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X63 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X64 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X65 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X66 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X67 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X68 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X69 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X70 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X71 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X72 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X73 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X74 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X75 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X76 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X77 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X78 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X79 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X80 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X81 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X82 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X83 3.5733972 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X84 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X85 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X86 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X87 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X88 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X89 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X90 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X91 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X92 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X93 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X94 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X95 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X96 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X97 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X98 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X99 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X100 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X101 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X102 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X103 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X104 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X105 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X106 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X107 -0.2795515 3.6304485 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X108 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X109 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X110 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X111 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X112 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X113 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X114 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X115 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X116 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X117 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X118 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X119 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X120 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X121 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X122 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X123 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X124 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X125 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X126 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X127 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X128 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X129 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X130 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X131 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X132 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X133 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X134 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X135 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X136 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X137 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X138 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X139 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X140 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X141 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X142 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X143 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X144 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X145 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X146 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X147 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X148 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X149 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X150 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X151 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X152 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X153 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X154 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X155 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X156 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X157 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X158 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X159 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X160 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X161 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X162 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X163 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X164 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X165 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X166 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X167 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X168 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X169 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X170 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X171 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X172 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X173 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X174 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X175 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X176 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X177 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X178 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X179 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X180 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X181 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X182 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X183 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X184 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X185 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X186 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X187 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X188 -0.2795515 3.6304485 3.9217804 3.8862252 -0.2500081 -0.2547181
## X189 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X190 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X191 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X192 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X193 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X194 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X195 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X196 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X197 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X198 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X199 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X200 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X201 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X202 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X203 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X204 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X205 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X206 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X207 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X208 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X209 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X210 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X211 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X212 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X213 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X214 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X215 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X216 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X217 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X218 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X219 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X220 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X221 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X222 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X223 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X224 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X225 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X226 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X227 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X228 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X229 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X230 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X231 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X232 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X233 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X234 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X235 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X236 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X237 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X238 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X239 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X240 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X241 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X242 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X243 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X244 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X245 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X246 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X247 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X248 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X249 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X250 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X251 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X252 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 3.9217804
## X253 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X254 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X255 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X256 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X257 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X258 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X259 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X260 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X261 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 3.9217804
## X262 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X263 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X264 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X265 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X266 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X267 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X268 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X269 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X270 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X271 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X272 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X273 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X274 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X275 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X276 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X277 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X278 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X279 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X280 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X281 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X282 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X283 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X284 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X285 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X286 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X287 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X288 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X289 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X290 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X291 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X292 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X293 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X294 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X295 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X296 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X297 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X298 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X299 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X300 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X301 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X302 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X303 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X304 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X305 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X306 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X307 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X308 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X309 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X310 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X311 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X312 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X313 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X314 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X315 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X316 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X317 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X318 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X319 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X320 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X321 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X322 -0.2795515 -0.2751584 3.9217804 -0.2570485 3.9956648 -0.2547181
## X323 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X324 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X325 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X326 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X327 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X328 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X329 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X330 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X331 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X332 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X333 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X334 3.5733972 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X335 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X336 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X337 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X338 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X339 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X340 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X341 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X342 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X343 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X344 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X345 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X346 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X347 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X348 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X349 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X350 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X351 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X352 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X353 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X354 -0.2795515 3.6304485 3.9217804 3.8862252 -0.2500081 -0.2547181
## X355 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X356 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X357 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X358 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X359 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X360 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X361 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X362 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X363 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X364 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X365 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X366 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X367 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X368 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X369 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X370 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X371 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X372 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X373 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X374 3.5733972 -0.2751584 -0.2547181 3.8862252 -0.2500081 3.9217804
## X375 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X376 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X377 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X378 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X379 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X380 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X381 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X382 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X383 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X384 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X385 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X386 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X387 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X388 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X389 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X390 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X391 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X392 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X393 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X394 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X395 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X396 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X397 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X398 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X399 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X400 3.5733972 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X401 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X402 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X403 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X404 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X405 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X406 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X407 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 3.9217804
## X408 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X409 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X410 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X411 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X412 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X413 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 3.9217804
## X414 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X415 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X416 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X417 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X418 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X419 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X420 3.5733972 3.6304485 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X421 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X422 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X423 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X424 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 3.9217804
## X425 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X426 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## X427 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X428 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X429 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X430 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X431 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X432 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X433 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X434 -0.2795515 -0.2751584 -0.2547181 -0.2570485 3.9956648 -0.2547181
## X435 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X436 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X437 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X438 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X439 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X440 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X441 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X442 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X443 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 3.9217804
## X444 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X445 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X446 3.5733972 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X447 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X448 -0.2795515 -0.2751584 3.9217804 -0.2570485 -0.2500081 -0.2547181
## X449 -0.2795515 3.6304485 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X450 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X451 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X452 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X453 -0.2795515 -0.2751584 -0.2547181 -0.2570485 -0.2500081 -0.2547181
## X454 -0.2795515 -0.2751584 -0.2547181 3.8862252 -0.2500081 -0.2547181
## FP196 FP197 FP198 FP201 FP202 FP203
## X1 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X2 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X3 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X4 -0.2452292 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X5 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X6 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X7 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X8 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X9 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X10 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X11 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X12 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X13 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X14 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X15 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X16 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X17 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X18 -0.2452292 -0.2354475 4.0735297 -0.2354475 1.6966445 -0.3596075
## X19 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X20 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X21 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X22 -0.2452292 4.2427646 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X23 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X24 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X25 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X26 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X27 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X28 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X29 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X30 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X31 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X32 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X33 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X34 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X35 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X36 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X37 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X38 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X39 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X40 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X41 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X42 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X43 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X44 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X45 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X46 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X47 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X48 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X49 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X50 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X51 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X52 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X53 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X54 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X55 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X56 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X57 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X58 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X59 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X60 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X61 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X62 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X63 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X64 -0.2452292 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X65 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X66 -0.2452292 -0.2354475 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X67 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X68 4.0735297 4.2427646 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X69 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X70 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X71 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X72 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X73 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X74 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X75 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X76 4.0735297 4.2427646 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X77 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X78 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X79 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X80 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X81 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X82 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X83 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X84 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X85 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X86 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X87 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X88 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X89 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X90 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X91 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X92 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X93 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X94 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X95 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X96 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X97 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X98 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X99 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X100 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X101 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X102 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X103 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X104 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X105 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X106 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X107 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X108 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X109 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X110 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X111 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X112 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X113 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X114 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X115 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X116 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X117 -0.2452292 -0.2354475 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X118 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X119 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X120 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X121 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X122 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X123 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X124 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X125 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X126 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X127 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X128 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X129 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X130 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X131 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X132 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X133 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X134 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X135 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X136 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X137 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X138 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X139 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X140 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X141 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X142 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X143 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X144 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X145 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X146 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X147 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X148 -0.2452292 4.2427646 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X149 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X150 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X151 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X152 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X153 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X154 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X155 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X156 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X157 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X158 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X159 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X160 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X161 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X162 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X163 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X164 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X165 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X166 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X167 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X168 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X169 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X170 -0.2452292 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X171 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X172 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X173 -0.2452292 -0.2354475 -0.2452292 4.2427646 1.6966445 -0.3596075
## X174 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X175 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X176 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X177 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X178 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X179 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X180 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X181 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X182 4.0735297 4.2427646 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X183 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X184 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X185 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X186 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X187 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X188 -0.2452292 4.2427646 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X189 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X190 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X191 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X192 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X193 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X194 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X195 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X196 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X197 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X198 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X199 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X200 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X201 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X202 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X203 4.0735297 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X204 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X205 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X206 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X207 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X208 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X209 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X210 -0.2452292 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X211 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X212 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X213 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X214 4.0735297 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X215 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X216 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X217 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X218 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X219 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X220 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X221 -0.2452292 -0.2354475 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X222 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X223 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X224 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X225 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X226 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X227 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X228 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X229 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X230 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X231 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X232 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X233 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X234 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X235 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X236 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X237 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X238 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X239 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X240 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X241 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X242 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X243 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X244 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X245 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X246 -0.2452292 4.2427646 -0.2452292 -0.2354475 1.6966445 2.7778855
## X247 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X248 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X249 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X250 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X251 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X252 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X253 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X254 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X255 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X256 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X257 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X258 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X259 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X260 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X261 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X262 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X263 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X264 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X265 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X266 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X267 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X268 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X269 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X270 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X271 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X272 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X273 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X274 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X275 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X276 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X277 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X278 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X279 -0.2452292 -0.2354475 -0.2452292 4.2427646 1.6966445 -0.3596075
## X280 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X281 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X282 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X283 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X284 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X285 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X286 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X287 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X288 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X289 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X290 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X291 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X292 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X293 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X294 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X295 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X296 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X297 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X298 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X299 -0.2452292 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X300 -0.2452292 -0.2354475 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X301 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X302 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X303 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X304 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X305 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X306 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X307 -0.2452292 -0.2354475 -0.2452292 4.2427646 1.6966445 -0.3596075
## X308 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X309 -0.2452292 -0.2354475 -0.2452292 4.2427646 1.6966445 -0.3596075
## X310 4.0735297 4.2427646 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X311 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X312 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X313 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X314 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X315 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X316 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X317 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X318 -0.2452292 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X319 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X320 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X321 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X322 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X323 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X324 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X325 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X326 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X327 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X328 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X329 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X330 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X331 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X332 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X333 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X334 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X335 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X336 -0.2452292 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X337 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X338 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X339 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X340 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X341 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X342 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X343 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X344 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X345 -0.2452292 -0.2354475 -0.2452292 4.2427646 1.6966445 -0.3596075
## X346 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X347 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X348 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X349 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X350 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X351 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X352 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X353 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X354 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X355 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X356 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X357 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X358 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X359 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X360 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X361 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X362 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X363 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X364 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X365 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X366 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X367 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X368 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X369 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X370 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X371 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X372 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X373 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X374 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X375 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X376 4.0735297 4.2427646 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X377 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X378 -0.2452292 4.2427646 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X379 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X380 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X381 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X382 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X383 4.0735297 4.2427646 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X384 4.0735297 4.2427646 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X385 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X386 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X387 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X388 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X389 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X390 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X391 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X392 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X393 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X394 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X395 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X396 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X397 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X398 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X399 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X400 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X401 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X402 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X403 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X404 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X405 4.0735297 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X406 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X407 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X408 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X409 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X410 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X411 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X412 -0.2452292 -0.2354475 -0.2452292 4.2427646 1.6966445 -0.3596075
## X413 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X414 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X415 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X416 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X417 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X418 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X419 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X420 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X421 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X422 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X423 4.0735297 4.2427646 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X424 -0.2452292 -0.2354475 -0.2452292 4.2427646 -0.5887789 -0.3596075
## X425 4.0735297 -0.2354475 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X426 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X427 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X428 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X429 -0.2452292 4.2427646 -0.2452292 -0.2354475 1.6966445 -0.3596075
## X430 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X431 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X432 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X433 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X434 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X435 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X436 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X437 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X438 4.0735297 4.2427646 4.0735297 -0.2354475 -0.5887789 -0.3596075
## X439 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X440 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X441 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 2.7778855
## X442 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X443 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X444 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X445 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X446 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X447 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X448 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X449 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X450 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X451 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X452 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X453 -0.2452292 -0.2354475 -0.2452292 -0.2354475 -0.5887789 -0.3596075
## X454 -0.2452292 -0.2354475 -0.2452292 -0.2354475 1.6966445 -0.3596075
## FP204 FP205 FP206 FP207 FP208 MolWeight
## X1 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.304017769
## X2 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.474751336
## X3 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.284237960
## X4 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.579130036
## X5 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.508214019
## X6 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.846130172
## X7 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.343679568
## X8 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.223329553
## X9 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.536294032
## X10 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.531725024
## X11 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.513009822
## X12 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.981923863
## X13 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.294344540
## X14 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 -0.211043577
## X15 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 -0.403319666
## X16 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.513009822
## X17 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.174798750
## X18 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.683069116
## X19 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.996447520
## X20 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.294344540
## X21 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.880198541
## X22 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.923239370
## X23 3.017853 3.4407687 -0.2523714 -0.2452292 -0.3558707 1.144391553
## X24 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.836745684
## X25 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 1.649573481
## X26 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.038577746
## X27 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.252510849
## X28 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.158871193
## X29 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.792852769
## X30 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.094205025
## X31 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.771172819
## X32 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.218301524
## X33 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.982753213
## X34 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.294344540
## X35 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.636103875
## X36 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 -0.321429192
## X37 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.982753213
## X38 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.706734262
## X39 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.831678296
## X40 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.929168040
## X41 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.675379106
## X42 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.750468797
## X43 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.291891037
## X44 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.522316745
## X45 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.508214019
## X46 -0.331013 3.4407687 -0.2523714 -0.2452292 2.8070547 1.257699471
## X47 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.982753213
## X48 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.026037466
## X49 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.989629709
## X50 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.635848282
## X51 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.163654675
## X52 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -1.218301524
## X53 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.098097256
## X54 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.237099891
## X55 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.378611406
## X56 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.052782459
## X57 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.558425111
## X58 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.060245711
## X59 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.400858350
## X60 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.430265786
## X61 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.223329553
## X62 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.072232210
## X63 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.378611406
## X64 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.321429192
## X65 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.907820092
## X66 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.072790642
## X67 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.889098307
## X68 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 2.027107324
## X69 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.982753213
## X70 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.135094949
## X71 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.294344540
## X72 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.475066868
## X73 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.201609653
## X74 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.039771029
## X75 -0.331013 3.4407687 -0.2523714 -0.2452292 2.8070547 0.098097256
## X76 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.834687162
## X77 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.165345469
## X78 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.710001130
## X79 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.115366351
## X80 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.803708352
## X81 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.677549637
## X82 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.152986644
## X83 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.190653352
## X84 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.188302449
## X85 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 1.163654675
## X86 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.737607576
## X87 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.147051515
## X88 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.719516934
## X89 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 2.101817743
## X90 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.162199568
## X91 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.978779123
## X92 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.148236508
## X93 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.865295430
## X94 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.135296034
## X95 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.303418106
## X96 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 2.675894881
## X97 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.945628244
## X98 -0.331013 -0.2903271 -0.2523714 4.0735297 2.8070547 0.447081835
## X99 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.327364381
## X100 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.447081835
## X101 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.447081835
## X102 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.398910560
## X103 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.496130384
## X104 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.735984417
## X105 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.378795179
## X106 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.108515489
## X107 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.017548306
## X108 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.956176482
## X109 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.580162693
## X110 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 1.380821445
## X111 3.017853 -0.2903271 -0.2523714 -0.2452292 2.8070547 1.147725526
## X112 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.317009930
## X113 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.953373701
## X114 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.355892859
## X115 -0.331013 3.4407687 -0.2523714 4.0735297 -0.3558707 0.745867382
## X116 -0.331013 3.4407687 -0.2523714 4.0735297 -0.3558707 1.136435150
## X117 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.364681635
## X118 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.745867382
## X119 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.242973688
## X120 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.627652706
## X121 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.560421390
## X122 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.745867382
## X123 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.630165630
## X124 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.184902006
## X125 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.447081835
## X126 -0.331013 3.4407687 -0.2523714 4.0735297 -0.3558707 1.007095938
## X127 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.198080407
## X128 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.447081835
## X129 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.007095938
## X130 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.382560531
## X131 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.495036672
## X132 -0.331013 3.4407687 -0.2523714 4.0735297 -0.3558707 1.007095938
## X133 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.284137074
## X134 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.184902006
## X135 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.513371322
## X136 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.239163633
## X137 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.007095938
## X138 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.737322938
## X139 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 1.007095938
## X140 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.823597252
## X141 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.447932035
## X142 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.239163633
## X143 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.447932035
## X144 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.447932035
## X145 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.007095938
## X146 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 1.239163633
## X147 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.637655670
## X148 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.831600743
## X149 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.703248097
## X150 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.447932035
## X151 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.703248097
## X152 -0.331013 3.4407687 -0.2523714 -0.2452292 2.8070547 1.552263693
## X153 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.447932035
## X154 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 1.447932035
## X155 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.447932035
## X156 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.703248097
## X157 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.811520606
## X158 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.811520606
## X159 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 2.120939599
## X160 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 -0.115977627
## X161 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.603559640
## X162 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.080766715
## X163 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.403319666
## X164 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.675379106
## X165 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.016880687
## X166 3.017853 -0.2903271 -0.2523714 -0.2452292 2.8070547 -0.610215946
## X167 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.563194962
## X168 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.611250316
## X169 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.769013180
## X170 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.574200229
## X171 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 2.035474501
## X172 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.982753213
## X173 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.270551909
## X174 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.936481465
## X175 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.476723028
## X176 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.952788440
## X177 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.747037108
## X178 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.815641020
## X179 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.623602913
## X180 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.038647958
## X181 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.952788440
## X182 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.834687162
## X183 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.049093577
## X184 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.269483899
## X185 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.847285078
## X186 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.532919242
## X187 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.009904078
## X188 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.900780208
## X189 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.701175131
## X190 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.907670555
## X191 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.882368345
## X192 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.448387506
## X193 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.026494249
## X194 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.175127549
## X195 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.294344540
## X196 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.327058775
## X197 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.214275611
## X198 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.095780590
## X199 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.771569118
## X200 -0.331013 -0.2903271 -0.2523714 4.0735297 2.8070547 0.098097256
## X201 3.017853 -0.2903271 3.9582469 -0.2452292 2.8070547 -0.215143211
## X202 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.815953602
## X203 -0.331013 3.4407687 -0.2523714 -0.2452292 2.8070547 1.387244764
## X204 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.459034034
## X205 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.413034907
## X206 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.812356063
## X207 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.341677499
## X208 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.447081835
## X209 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.137547205
## X210 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.304417449
## X211 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.745867382
## X212 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.560421390
## X213 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.745867382
## X214 -0.331013 3.4407687 -0.2523714 -0.2452292 2.8070547 1.616540792
## X215 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.518473204
## X216 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.007095938
## X217 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.410804929
## X218 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 1.745837809
## X219 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.737283220
## X220 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 1.007095938
## X221 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.620626671
## X222 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.471104074
## X223 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.703248097
## X224 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.239163633
## X225 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.382560531
## X226 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.495036672
## X227 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.447932035
## X228 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 1.447932035
## X229 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.703248097
## X230 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.495036672
## X231 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.447932035
## X232 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.971974745
## X233 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.703000619
## X234 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.981923863
## X235 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.998810596
## X236 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.387897880
## X237 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.410804929
## X238 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.712430972
## X239 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.427774521
## X240 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.975155875
## X241 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.960986946
## X242 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.455773295
## X243 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.447297107
## X244 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.024063318
## X245 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.366815837
## X246 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.392161232
## X247 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.922422855
## X248 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.489295914
## X249 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.632068261
## X250 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.289953121
## X251 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.983309595
## X252 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.808360205
## X253 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.243179485
## X254 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.736065616
## X255 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.630729830
## X256 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.254497849
## X257 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.390166117
## X258 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.089862985
## X259 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.960986946
## X260 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.071003132
## X261 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.601744921
## X262 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.632068261
## X263 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.960986946
## X264 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.002838576
## X265 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.507220812
## X266 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.725281754
## X267 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.048980624
## X268 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.267476312
## X269 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.808360205
## X270 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.158871193
## X271 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.667472628
## X272 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.948173754
## X273 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -1.089862985
## X274 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.566721151
## X275 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.267476312
## X276 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.611681349
## X277 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.226628531
## X278 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.190792410
## X279 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.008626296
## X280 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.289288562
## X281 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.098274791
## X282 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.774201646
## X283 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -1.098274791
## X284 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.239546173
## X285 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 -0.123326972
## X286 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.800109202
## X287 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.995515874
## X288 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.827201901
## X289 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 1.881712881
## X290 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.433604324
## X291 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.364519110
## X292 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.823597252
## X293 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.242509175
## X294 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.404021657
## X295 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.915283282
## X296 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.134223355
## X297 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 -0.043759055
## X298 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.399810034
## X299 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.686767950
## X300 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.459952245
## X301 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 -0.389468783
## X302 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.430503397
## X303 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.486632405
## X304 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.033797758
## X305 3.017853 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.736309194
## X306 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.421224013
## X307 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.024487502
## X308 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.079045894
## X309 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.024487502
## X310 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.445796891
## X311 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.832540404
## X312 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 1.881712881
## X313 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.061817968
## X314 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.107436062
## X315 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.404021657
## X316 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.436794393
## X317 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.271995992
## X318 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.731140385
## X319 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.558159799
## X320 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.605379378
## X321 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.362642398
## X322 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.062383808
## X323 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.152364404
## X324 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.901900752
## X325 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.839972199
## X326 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.128651681
## X327 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.839972199
## X328 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.343414497
## X329 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.581515202
## X330 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.218737027
## X331 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.133955099
## X332 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.774201646
## X333 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.842661605
## X334 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.418526237
## X335 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.687183627
## X336 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.303931995
## X337 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.922422855
## X338 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.232450944
## X339 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.232450944
## X340 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.609081003
## X341 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.293545411
## X342 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.839972199
## X343 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.289745203
## X344 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.058701570
## X345 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.008626296
## X346 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.619596479
## X347 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.706734262
## X348 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.226628531
## X349 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 -0.839972199
## X350 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.072631922
## X351 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.267476312
## X352 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.453788004
## X353 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.847208104
## X354 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.915506765
## X355 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.049545329
## X356 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.839972199
## X357 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.966789467
## X358 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.090698960
## X359 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.720253413
## X360 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.066475255
## X361 3.017853 -0.2903271 -0.2523714 -0.2452292 2.8070547 -0.020037904
## X362 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.563194962
## X363 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.686601657
## X364 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.260676413
## X365 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.676599640
## X366 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.105975307
## X367 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.732339628
## X368 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.532160955
## X369 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.854891424
## X370 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 1.771027243
## X371 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.016880687
## X372 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.353099452
## X373 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.706360421
## X374 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.205416250
## X375 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 1.019887558
## X376 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.622913686
## X377 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.623602913
## X378 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.816422389
## X379 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -1.020552429
## X380 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.570417230
## X381 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.676516088
## X382 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.141453232
## X383 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.633333725
## X384 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.967298146
## X385 -0.331013 3.4407687 -0.2523714 -0.2452292 2.8070547 0.719516934
## X386 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.686601657
## X387 3.017853 -0.2903271 -0.2523714 -0.2452292 2.8070547 1.226307769
## X388 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 1.412917599
## X389 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.752403196
## X390 3.017853 -0.2903271 -0.2523714 -0.2452292 2.8070547 1.121037974
## X391 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.623602913
## X392 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.017548306
## X393 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 -0.610215946
## X394 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.211043577
## X395 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.430503397
## X396 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.089862985
## X397 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.201609653
## X398 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.293545411
## X399 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 -0.284112271
## X400 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.366912794
## X401 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.094121874
## X402 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.014240641
## X403 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.159406860
## X404 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.489295914
## X405 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.188446950
## X406 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.580658068
## X407 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.419242736
## X408 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.089862985
## X409 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.784301940
## X410 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.559218908
## X411 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.065435819
## X412 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.678353466
## X413 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.190792410
## X414 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.688575293
## X415 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.098274791
## X416 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.260904394
## X417 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.800109202
## X418 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.495127837
## X419 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.343414497
## X420 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 0.184958063
## X421 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.362866384
## X422 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.729152370
## X423 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.457427050
## X424 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.086675495
## X425 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.525264217
## X426 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.092028152
## X427 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.083816857
## X428 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 -0.421224013
## X429 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.875243942
## X430 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.361087352
## X431 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 -0.732339628
## X432 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.594543822
## X433 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.581515202
## X434 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 0.813999190
## X435 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.489295914
## X436 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -0.105975307
## X437 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 2.722777775
## X438 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.445796891
## X439 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 -1.581515202
## X440 -0.331013 -0.2903271 -0.2523714 4.0735297 -0.3558707 -0.421224013
## X441 -0.331013 -0.2903271 -0.2523714 -0.2452292 2.8070547 1.213307444
## X442 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.959436086
## X443 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.991282387
## X444 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.078774283
## X445 3.017853 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.254569455
## X446 -0.331013 3.4407687 -0.2523714 -0.2452292 -0.3558707 0.357292051
## X447 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 -0.090698960
## X448 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.373978500
## X449 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.959436086
## X450 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 2.401813942
## X451 3.017853 -0.2903271 3.9582469 -0.2452292 -0.3558707 0.072232210
## X452 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.980480348
## X453 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 0.381694291
## X454 -0.331013 -0.2903271 -0.2523714 -0.2452292 -0.3558707 1.705409579
## NumBonds NumMultBonds NumRotBonds NumDblBonds NumCarbon NumNitrogen
## X1 0.49840233 1.90489650 -0.9347280 -0.831341597 0.85821946 1.0008314
## X2 1.69828720 1.32482715 0.7260405 -0.831341597 1.80408084 1.8438701
## X3 0.69697444 0.16468846 0.7260405 -0.005212173 0.70131917 -0.6852460
## X4 0.20728011 -0.80209379 -0.5195359 0.820917251 0.18177643 -0.6852460
## X5 0.56629095 -0.02866799 1.1412327 -0.831341597 -0.01199386 3.5299475
## X6 0.56629095 -0.80209379 1.1412327 0.820917251 0.18177643 0.1577927
## X7 0.99793817 2.29160940 -0.5195359 -0.005212173 1.29203392 2.6869088
## X8 0.94039386 -0.99545024 3.2171934 -0.005212173 0.53699786 -0.6852460
## X9 1.99292450 -0.41538089 -0.5195359 2.473176098 1.92274051 -0.6852460
## X10 0.99793817 0.16468846 -0.1043438 -0.005212173 0.85821946 1.0008314
## X11 0.63244961 0.55140136 -0.1043438 1.647046674 0.85821946 -0.6852460
## X12 1.69828720 -0.80209379 -0.9347280 0.820917251 1.55615914 -0.6852460
## X13 0.12893412 0.93811425 -0.9347280 -0.831341597 0.53699786 -0.6852460
## X14 -0.40240913 0.93811425 -0.9347280 -0.831341597 0.18177643 -0.6852460
## X15 0.28325136 -0.02866799 -0.1043438 -0.831341597 0.36423857 -0.6852460
## X16 0.63244961 1.13147070 0.3108484 -0.005212173 0.85821946 -0.6852460
## X17 1.36999732 0.35804491 2.3868091 0.820917251 0.70131917 2.6869088
## X18 1.87027471 1.13147070 1.5564248 -0.831341597 1.80408084 1.8438701
## X19 1.78555525 -0.99545024 -0.9347280 -0.005212173 1.55615914 -0.6852460
## X20 0.12893412 0.93811425 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X21 0.63244961 1.32482715 -0.1043438 -0.005212173 1.00853037 -0.6852460
## X22 1.46773946 1.13147070 0.7260405 -0.831341597 1.55615914 1.0008314
## X23 1.46773946 0.16468846 2.3868091 -0.005212173 1.29203392 0.1577927
## X24 0.88159159 -0.80209379 0.7260405 0.820917251 0.18177643 2.6869088
## X25 1.46773946 0.55140136 3.2171934 1.647046674 0.85821946 0.1577927
## X26 1.16359252 0.55140136 0.3108484 1.647046674 0.85821946 1.0008314
## X27 1.56220886 1.13147070 1.1412327 -0.831341597 1.55615914 1.0008314
## X28 0.28325136 1.90489650 -0.9347280 -0.831341597 0.70131917 1.0008314
## X29 1.31981693 0.16468846 0.7260405 -0.005212173 1.15294194 0.1577927
## X30 -1.09071695 0.16468846 -0.9347280 -0.831341597 -0.44251753 0.1577927
## X31 0.04803954 -0.99545024 1.1412327 -0.831341597 -0.01199386 -0.6852460
## X32 -0.12219740 -1.18880668 -0.1043438 -0.831341597 -0.44251753 -0.6852460
## X33 0.04803954 -1.18880668 -0.9347280 -0.831341597 -0.21915966 -0.6852460
## X34 0.12893412 0.93811425 -0.9347280 -0.831341597 0.53699786 -0.6852460
## X35 0.82146772 0.55140136 0.3108484 1.647046674 1.00853037 -0.6852460
## X36 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X37 0.04803954 -1.18880668 -0.9347280 -0.831341597 -0.21915966 -0.6852460
## X38 2.47286768 -0.99545024 0.7260405 -0.005212173 2.15069776 -0.6852460
## X39 1.16359252 1.32482715 0.7260405 -0.005212173 1.42629884 -0.6852460
## X40 0.56629095 1.32482715 0.3108484 -0.005212173 0.85821946 0.1577927
## X41 2.11068236 -0.22202444 0.7260405 3.299305521 2.03820634 -0.6852460
## X42 0.12893412 0.35804491 0.3108484 -0.005212173 0.36423857 0.1577927
## X43 -0.40240913 0.93811425 -0.9347280 -0.831341597 0.18177643 -0.6852460
## X44 1.69828720 1.13147070 0.7260405 -0.831341597 1.68198027 1.8438701
## X45 0.56629095 -0.02866799 0.7260405 -0.831341597 -0.01199386 3.5299475
## X46 1.10948462 1.71154005 -0.1043438 1.647046674 1.55615914 0.1577927
## X47 -0.03559810 -0.99545024 1.1412327 -0.005212173 -0.21915966 -0.6852460
## X48 0.12893412 1.32482715 -0.1043438 -0.005212173 0.53699786 1.0008314
## X49 0.12893412 1.13147070 -0.1043438 -0.831341597 0.53699786 -0.6852460
## X50 0.63244961 1.32482715 0.3108484 -0.005212173 1.00853037 -0.6852460
## X51 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X52 -0.12219740 -1.18880668 0.7260405 -0.831341597 -0.44251753 -0.6852460
## X53 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X54 0.12893412 -0.02866799 0.7260405 -0.831341597 -0.44251753 3.5299475
## X55 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X56 1.65364219 -0.60873734 -0.9347280 0.820917251 1.68198027 -0.6852460
## X57 0.99793817 0.16468846 2.3868091 -0.005212173 0.85821946 0.1577927
## X58 -0.21200528 1.32482715 -0.5195359 0.820917251 0.36423857 0.1577927
## X59 1.26871571 0.55140136 0.3108484 1.647046674 1.29203392 -0.6852460
## X60 1.26871571 2.29160940 0.7260405 0.820917251 1.55615914 0.1577927
## X61 0.94039386 -0.99545024 3.2171934 -0.005212173 0.53699786 -0.6852460
## X62 0.75995351 -0.99545024 2.8020012 -0.005212173 0.36423857 -0.6852460
## X63 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X64 0.04803954 0.93811425 -0.9347280 -0.831341597 0.53699786 -0.6852460
## X65 1.21665476 0.35804491 2.3868091 0.820917251 1.15294194 -0.6852460
## X66 0.99793817 -1.18880668 3.2171934 -0.831341597 0.53699786 -0.6852460
## X67 2.07194628 1.32482715 2.3868091 -0.005212173 2.03820634 1.8438701
## X68 2.54041376 -0.22202444 1.9716169 3.299305521 2.47218708 -0.6852460
## X69 0.04803954 -1.18880668 -0.1043438 -0.831341597 -0.21915966 -0.6852460
## X70 1.46773946 1.13147070 -0.1043438 -0.831341597 1.55615914 1.0008314
## X71 0.12893412 0.93811425 -0.9347280 -0.831341597 0.53699786 -0.6852460
## X72 -0.12219740 -1.18880668 0.7260405 -0.831341597 -0.44251753 -0.6852460
## X73 0.49840233 1.13147070 -0.1043438 -0.831341597 0.85821946 -0.6852460
## X74 0.82146772 -0.80209379 1.9716169 0.820917251 0.18177643 1.0008314
## X75 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X76 2.22396656 -0.22202444 0.7260405 3.299305521 2.15069776 -0.6852460
## X77 0.12893412 1.13147070 -0.9347280 -0.831341597 0.70131917 -0.6852460
## X78 0.28325136 1.13147070 -0.5195359 -0.831341597 0.53699786 1.0008314
## X79 0.35700394 0.93811425 -0.9347280 -0.831341597 0.70131917 -0.6852460
## X80 1.05428349 1.32482715 1.1412327 -0.005212173 1.29203392 -0.6852460
## X81 1.95260717 -0.02866799 0.3108484 4.125434945 2.03820634 -0.6852460
## X82 0.04803954 1.71154005 -0.9347280 -0.831341597 0.53699786 0.1577927
## X83 1.21665476 1.13147070 0.7260405 -0.831341597 1.29203392 1.0008314
## X84 0.20728011 0.74475780 -0.5195359 2.473176098 0.53699786 0.1577927
## X85 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X86 0.20728011 -0.99545024 1.5564248 -0.005212173 -0.01199386 -0.6852460
## X87 0.12893412 -1.18880668 1.1412327 -0.831341597 -0.21915966 -0.6852460
## X88 0.75995351 1.51818360 1.1412327 0.820917251 1.15294194 -0.6852460
## X89 2.14892180 1.90489650 2.3868091 2.473176098 2.03820634 1.8438701
## X90 1.26871571 -0.99545024 4.0475776 -0.005212173 0.53699786 -0.6852460
## X91 2.70310385 -0.80209379 1.5564248 0.820917251 2.36752103 0.1577927
## X92 0.35700394 1.90489650 -0.9347280 -0.831341597 0.85821946 0.1577927
## X93 -1.37754378 -0.80209379 -0.9347280 0.820917251 -0.95516548 -0.6852460
## X94 1.82822307 -0.60873734 3.6323855 1.647046674 1.55615914 -0.6852460
## X95 0.20728011 1.51818360 -0.9347280 0.820917251 0.85821946 -0.6852460
## X96 0.88159159 1.32482715 1.1412327 -0.005212173 1.00853037 0.1577927
## X97 0.12893412 -1.18880668 1.1412327 -0.831341597 -0.21915966 -0.6852460
## X98 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X99 2.03269881 -0.41538089 -0.5195359 2.473176098 2.03820634 -0.6852460
## X100 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X101 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X102 1.36999732 1.13147070 0.7260405 -0.831341597 1.42629884 1.0008314
## X103 1.26871571 -0.99545024 4.0475776 -0.005212173 0.85821946 -0.6852460
## X104 0.82146772 3.06503519 -0.5195359 -0.831341597 1.42629884 1.0008314
## X105 0.35700394 -0.60873734 -0.1043438 1.647046674 0.18177643 0.1577927
## X106 1.82822307 -1.18880668 -0.9347280 -0.831341597 1.55615914 -0.6852460
## X107 1.41929339 1.51818360 0.7260405 0.820917251 1.55615914 1.8438701
## X108 2.60651481 -0.41538089 1.5564248 2.473176098 2.47218708 -0.6852460
## X109 1.10948462 -0.80209379 4.0475776 0.820917251 -0.01199386 -0.6852460
## X110 1.46773946 2.48496584 1.1412327 1.647046674 1.80408084 0.1577927
## X111 1.31981693 1.51818360 2.8020012 0.820917251 1.55615914 -0.6852460
## X112 0.04803954 -0.80209379 -0.9347280 0.820917251 0.18177643 -0.6852460
## X113 1.82822307 -0.99545024 5.7083462 -0.005212173 1.42629884 -0.6852460
## X114 1.16359252 0.35804491 0.7260405 0.820917251 1.00853037 1.0008314
## X115 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X116 0.56629095 1.51818360 -0.1043438 0.820917251 0.85821946 1.0008314
## X117 1.31981693 -1.18880668 4.0475776 -0.831341597 0.85821946 -0.6852460
## X118 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X119 0.42867850 2.48496584 -0.9347280 -0.831341597 1.15294194 -0.6852460
## X120 0.82146772 2.87167874 -0.9347280 -0.831341597 1.42629884 0.1577927
## X121 0.56629095 -0.99545024 -0.9347280 -0.005212173 0.53699786 -0.6852460
## X122 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X123 1.16359252 0.55140136 1.9716169 1.647046674 0.85821946 0.1577927
## X124 0.28325136 1.32482715 -0.1043438 -0.005212173 0.85821946 -0.6852460
## X125 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X126 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X127 0.42867850 1.13147070 -0.1043438 -0.831341597 0.85821946 -0.6852460
## X128 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X129 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X130 0.63244961 2.09825295 -0.9347280 -0.831341597 1.29203392 -0.6852460
## X131 0.69697444 2.87167874 -0.9347280 -0.831341597 1.42629884 -0.6852460
## X132 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X133 0.63244961 1.90489650 -0.5195359 -0.831341597 1.15294194 -0.6852460
## X134 0.28325136 1.32482715 -0.1043438 -0.005212173 0.85821946 -0.6852460
## X135 0.75995351 2.29160940 -0.1043438 -0.831341597 1.42629884 -0.6852460
## X136 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X137 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X138 2.63904482 -0.99545024 -0.9347280 -0.005212173 2.47218708 -0.6852460
## X139 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X140 0.99793817 3.64510454 -0.9347280 -0.831341597 1.68198027 0.1577927
## X141 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X142 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X143 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X144 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X145 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X146 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X147 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X148 1.16359252 2.87167874 -0.9347280 -0.831341597 1.80408084 -0.6852460
## X149 0.88159159 3.45174809 -0.9347280 -0.831341597 1.68198027 -0.6852460
## X150 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X151 0.88159159 3.45174809 -0.9347280 -0.831341597 1.68198027 -0.6852460
## X152 1.46773946 3.25839164 0.7260405 -0.831341597 1.92274051 1.8438701
## X153 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X154 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X155 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X156 0.88159159 3.45174809 -0.9347280 -0.831341597 1.68198027 -0.6852460
## X157 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X158 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X159 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X160 0.04803954 1.13147070 -0.1043438 -0.831341597 0.53699786 -0.6852460
## X161 -0.12219740 -1.18880668 0.7260405 -0.831341597 -0.44251753 -0.6852460
## X162 1.82822307 -0.80209379 -0.9347280 0.820917251 1.68198027 -0.6852460
## X163 0.28325136 -0.02866799 -0.9347280 -0.831341597 0.36423857 -0.6852460
## X164 2.11068236 -0.22202444 0.7260405 3.299305521 2.03820634 -0.6852460
## X165 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X166 0.04803954 -0.02866799 0.3108484 -0.831341597 0.18177643 -0.6852460
## X167 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X168 0.82146772 -0.02866799 1.1412327 -0.831341597 0.18177643 3.5299475
## X169 0.42867850 -0.99545024 2.3868091 -0.005212173 -0.44251753 -0.6852460
## X170 1.74225056 1.32482715 0.3108484 -0.005212173 1.80408084 0.1577927
## X171 2.33314222 -0.02866799 1.5564248 4.125434945 2.26041072 -0.6852460
## X172 0.04803954 -1.18880668 -0.9347280 -0.831341597 -0.21915966 -0.6852460
## X173 0.99793817 1.90489650 -0.1043438 2.473176098 1.00853037 1.8438701
## X174 0.49840233 1.32482715 0.3108484 -0.005212173 0.70131917 1.0008314
## X175 -1.70965649 -0.80209379 -0.5195359 0.820917251 -1.25901822 -0.6852460
## X176 1.21665476 1.13147070 0.3108484 -0.831341597 1.29203392 1.0008314
## X177 2.22396656 -0.41538089 -0.1043438 2.473176098 2.15069776 -0.6852460
## X178 -1.09071695 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X179 2.43853015 -0.99545024 0.7260405 -0.005212173 2.15069776 -0.6852460
## X180 1.56220886 0.16468846 -0.9347280 -0.831341597 1.68198027 -0.6852460
## X181 1.21665476 1.13147070 0.7260405 -0.831341597 1.29203392 1.0008314
## X182 2.26079827 -0.41538089 -0.1043438 2.473176098 2.15069776 -0.6852460
## X183 -0.03559810 1.71154005 -0.9347280 -0.831341597 0.53699786 -0.6852460
## X184 0.88159159 2.29160940 0.3108484 -0.831341597 1.29203392 1.0008314
## X185 1.26871571 1.13147070 1.1412327 -0.831341597 1.42629884 -0.6852460
## X186 1.65364219 1.32482715 1.5564248 -0.005212173 1.80408084 0.1577927
## X187 -0.12219740 -1.18880668 0.7260405 -0.831341597 -0.44251753 -0.6852460
## X188 1.41929339 1.32482715 0.3108484 -0.005212173 1.68198027 0.1577927
## X189 1.82822307 1.13147070 0.7260405 -0.831341597 1.80408084 1.8438701
## X190 0.56629095 0.16468846 1.1412327 -0.005212173 0.18177643 -0.6852460
## X191 2.43853015 -0.22202444 1.1412327 3.299305521 2.36752103 -0.6852460
## X192 0.35700394 1.51818360 -0.5195359 0.820917251 0.85821946 0.1577927
## X193 0.42867850 1.13147070 0.3108484 -0.831341597 0.85821946 -0.6852460
## X194 1.95260717 -0.80209379 -0.5195359 0.820917251 1.80408084 -0.6852460
## X195 0.12893412 0.93811425 -0.9347280 -0.831341597 0.53699786 -0.6852460
## X196 1.87027471 -0.41538089 -0.1043438 1.647046674 1.92274051 -0.6852460
## X197 -0.03559810 0.16468846 0.7260405 -0.005212173 -0.44251753 0.1577927
## X198 0.56629095 -0.80209379 1.1412327 0.820917251 0.18177643 0.1577927
## X199 -1.70965649 -0.80209379 -0.5195359 0.820917251 -1.25901822 -0.6852460
## X200 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X201 0.49840233 -0.02866799 1.1412327 -0.831341597 0.53699786 -0.6852460
## X202 1.16359252 1.13147070 -0.9347280 -0.005212173 1.42629884 -0.6852460
## X203 1.78555525 1.51818360 1.9716169 0.820917251 2.03820634 -0.6852460
## X204 1.05428349 0.55140136 1.5564248 1.647046674 0.85821946 -0.6852460
## X205 0.12893412 -0.80209379 -0.9347280 0.820917251 0.18177643 -0.6852460
## X206 -0.96037479 0.35804491 -0.9347280 -0.831341597 -0.21915966 1.0008314
## X207 0.75995351 0.16468846 2.3868091 -0.005212173 0.36423857 -0.6852460
## X208 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X209 0.42867850 1.90489650 -0.9347280 -0.831341597 1.00853037 -0.6852460
## X210 0.82146772 0.93811425 -0.9347280 -0.831341597 1.15294194 -0.6852460
## X211 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X212 0.56629095 -0.99545024 -0.9347280 -0.005212173 0.53699786 -0.6852460
## X213 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X214 1.51536781 1.51818360 1.9716169 0.820917251 1.80408084 -0.6852460
## X215 0.04803954 -0.80209379 -0.9347280 0.820917251 0.18177643 -0.6852460
## X216 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X217 0.42867850 1.13147070 -0.1043438 -0.831341597 0.85821946 -0.6852460
## X218 1.69828720 2.48496584 1.5564248 -0.005212173 1.80408084 -0.6852460
## X219 1.56220886 -0.99545024 4.8779619 -0.005212173 1.15294194 -0.6852460
## X220 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X221 1.60829128 -1.18880668 4.8779619 -0.831341597 1.15294194 -0.6852460
## X222 0.42867850 -0.80209379 -0.9347280 0.820917251 0.53699786 -0.6852460
## X223 0.88159159 3.45174809 -0.9347280 -0.831341597 1.68198027 -0.6852460
## X224 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X225 0.63244961 2.09825295 -0.9347280 -0.831341597 1.29203392 -0.6852460
## X226 0.69697444 2.87167874 -0.9347280 -0.831341597 1.42629884 -0.6852460
## X227 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X228 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X229 0.88159159 3.45174809 -0.9347280 -0.831341597 1.68198027 -0.6852460
## X230 0.69697444 2.87167874 -0.9347280 -0.831341597 1.42629884 -0.6852460
## X231 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X232 -0.03559810 1.13147070 -0.5195359 -0.831341597 0.53699786 -0.6852460
## X233 0.69697444 1.51818360 -0.1043438 0.820917251 1.00853037 1.0008314
## X234 1.69828720 -0.80209379 -0.9347280 0.820917251 1.55615914 -0.6852460
## X235 -0.50369472 -1.18880668 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X236 0.42867850 0.16468846 1.5564248 -0.005212173 -0.01199386 0.1577927
## X237 0.42867850 1.13147070 -0.1043438 -0.831341597 0.85821946 -0.6852460
## X238 0.20728011 -0.99545024 -0.9347280 -0.005212173 0.18177643 -0.6852460
## X239 -0.40240913 0.16468846 0.3108484 -0.005212173 -0.21915966 -0.6852460
## X240 1.87027471 0.93811425 -0.1043438 3.299305521 1.80408084 1.0008314
## X241 -0.96037479 -0.99545024 -0.5195359 -0.005212173 -0.95516548 -0.6852460
## X242 -0.83728034 -0.02866799 -0.9347280 -0.831341597 -0.44251753 -0.6852460
## X243 -0.40240913 0.93811425 -0.9347280 -0.831341597 -0.01199386 0.1577927
## X244 0.82146772 1.51818360 0.7260405 0.820917251 0.53699786 2.6869088
## X245 0.12893412 0.16468846 0.3108484 -0.005212173 0.18177643 -0.6852460
## X246 0.63244961 0.35804491 -0.1043438 0.820917251 0.70131917 0.1577927
## X247 0.63244961 1.51818360 0.7260405 0.820917251 0.36423857 2.6869088
## X248 0.28325136 -0.99545024 1.5564248 -0.005212173 -0.01199386 -0.6852460
## X249 -0.72058540 -0.99545024 -0.9347280 -0.005212173 -0.68595798 -0.6852460
## X250 -0.83728034 0.16468846 -0.5195359 -0.005212173 -0.44251753 -0.6852460
## X251 -0.83728034 -0.22202444 -0.5195359 -0.831341597 -0.68595798 -0.6852460
## X252 1.16359252 1.32482715 1.1412327 -0.005212173 1.29203392 1.8438701
## X253 -2.10721958 -1.18880668 -0.9347280 -0.831341597 -2.04708364 -0.6852460
## X254 0.94039386 1.13147070 0.7260405 -0.831341597 1.00853037 1.0008314
## X255 -0.12219740 0.35804491 -0.1043438 0.820917251 -0.01199386 0.1577927
## X256 0.28325136 -0.99545024 1.9716169 -0.005212173 -0.21915966 0.1577927
## X257 -0.12219740 0.16468846 -0.1043438 -0.005212173 -0.01199386 0.1577927
## X258 -0.72058540 -1.18880668 -0.1043438 -0.831341597 -0.95516548 -0.6852460
## X259 -0.83728034 -1.18880668 -0.9347280 -0.831341597 -0.95516548 -0.6852460
## X260 0.12893412 1.13147070 -0.1043438 -0.005212173 0.53699786 -0.6852460
## X261 0.42867850 0.55140136 -0.5195359 1.647046674 0.18177643 1.0008314
## X262 -0.83728034 -0.80209379 0.3108484 0.820917251 -0.68595798 -0.6852460
## X263 -0.96037479 -0.99545024 -0.1043438 -0.005212173 -0.95516548 -0.6852460
## X264 0.04803954 1.90489650 -0.9347280 -0.831341597 0.53699786 1.0008314
## X265 -0.72058540 -1.18880668 -0.5195359 -0.831341597 -0.95516548 -0.6852460
## X266 -1.09071695 -1.18880668 -0.5195359 -0.831341597 -1.25901822 -0.6852460
## X267 0.28325136 1.13147070 -0.5195359 -0.831341597 0.53699786 1.0008314
## X268 0.35700394 -0.99545024 1.9716169 -0.005212173 -0.01199386 -0.6852460
## X269 1.21665476 0.16468846 2.8020012 -0.005212173 1.00853037 0.1577927
## X270 0.35700394 0.16468846 1.1412327 -0.005212173 0.36423857 -0.6852460
## X271 -0.83728034 0.16468846 -0.5195359 -0.005212173 -0.44251753 -0.6852460
## X272 1.16359252 0.16468846 1.1412327 -0.005212173 1.00853037 0.1577927
## X273 -0.72058540 -1.18880668 -0.1043438 -0.831341597 -0.95516548 -0.6852460
## X274 0.75995351 -0.41538089 -0.5195359 2.473176098 0.53699786 1.0008314
## X275 0.35700394 -0.99545024 1.9716169 -0.005212173 -0.01199386 -0.6852460
## X276 -0.72058540 0.16468846 -0.5195359 -0.005212173 -0.68595798 1.0008314
## X277 1.65364219 1.13147070 0.7260405 -0.005212173 1.68198027 1.0008314
## X278 -0.72058540 0.35804491 -0.9347280 0.820917251 -0.68595798 2.6869088
## X279 0.12893412 1.90489650 -0.9347280 -0.831341597 0.70131917 0.1577927
## X280 -0.40240913 -0.02866799 -0.9347280 -0.831341597 -0.21915966 -0.6852460
## X281 -0.50369472 -0.02866799 -0.9347280 -0.831341597 -0.21915966 -0.6852460
## X282 -0.03559810 0.35804491 -0.5195359 0.820917251 -0.01199386 1.0008314
## X283 -0.50369472 -0.02866799 -0.9347280 -0.831341597 -0.21915966 -0.6852460
## X284 1.82822307 -0.02866799 -0.5195359 -0.831341597 1.68198027 1.0008314
## X285 -0.40240913 0.16468846 -0.5195359 -0.005212173 -0.21915966 0.1577927
## X286 0.56629095 1.51818360 0.3108484 0.820917251 0.36423857 2.6869088
## X287 1.10948462 1.13147070 1.1412327 -0.831341597 0.85821946 2.6869088
## X288 0.04803954 0.16468846 0.3108484 -0.005212173 -0.01199386 0.1577927
## X289 1.99292450 0.93811425 -0.1043438 3.299305521 1.92274051 1.0008314
## X290 0.04803954 0.55140136 -0.5195359 1.647046674 0.18177643 1.8438701
## X291 -0.72058540 -1.18880668 -0.5195359 -0.831341597 -0.95516548 -0.6852460
## X292 0.63244961 1.32482715 0.3108484 0.820917251 0.36423857 1.8438701
## X293 -0.21200528 0.93811425 -0.9347280 -0.831341597 0.18177643 -0.6852460
## X294 -0.03559810 0.16468846 0.3108484 -0.005212173 0.18177643 -0.6852460
## X295 1.16359252 0.35804491 0.7260405 0.820917251 0.85821946 1.8438701
## X296 0.88159159 1.51818360 1.1412327 0.820917251 0.53699786 2.6869088
## X297 0.12893412 0.35804491 0.7260405 0.820917251 0.36423857 -0.6852460
## X298 -0.12219740 0.16468846 -0.1043438 -0.005212173 -0.01199386 0.1577927
## X299 0.94039386 -0.41538089 -0.1043438 2.473176098 0.70131917 1.0008314
## X300 0.42867850 -1.18880668 1.9716169 -0.831341597 -0.01199386 -0.6852460
## X301 0.20728011 -0.02866799 0.3108484 -0.831341597 0.18177643 0.1577927
## X302 0.82146772 0.16468846 0.7260405 -0.005212173 0.70131917 0.1577927
## X303 0.63244961 -0.02866799 1.1412327 -0.831341597 -0.01199386 3.5299475
## X304 0.04803954 0.93811425 -0.5195359 3.299305521 -0.44251753 1.8438701
## X305 0.69697444 0.55140136 1.1412327 1.647046674 0.36423857 1.0008314
## X306 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X307 1.46773946 1.13147070 0.3108484 -0.005212173 1.55615914 1.0008314
## X308 0.75995351 1.51818360 -0.5195359 0.820917251 1.00853037 -0.6852460
## X309 1.46773946 1.13147070 0.3108484 -0.005212173 1.55615914 1.0008314
## X310 1.91172984 -0.41538089 -0.1043438 2.473176098 1.80408084 -0.6852460
## X311 -0.40240913 -1.18880668 0.3108484 -0.831341597 -0.68595798 -0.6852460
## X312 1.99292450 0.93811425 -0.1043438 3.299305521 1.92274051 1.0008314
## X313 1.05428349 -1.18880668 2.8020012 -0.831341597 0.53699786 0.1577927
## X314 -2.10721958 -1.18880668 -0.9347280 -0.831341597 -2.04708364 -0.6852460
## X315 -0.03559810 0.16468846 -0.1043438 -0.005212173 0.18177643 -0.6852460
## X316 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X317 -2.92387959 -1.18880668 -0.9347280 -0.831341597 -2.64432555 -0.6852460
## X318 1.91172984 1.32482715 0.7260405 -0.005212173 1.92274051 0.1577927
## X319 0.49840233 0.35804491 -0.1043438 0.820917251 0.53699786 0.1577927
## X320 0.42867850 0.16468846 0.7260405 -0.831341597 -0.01199386 4.3729862
## X321 0.28325136 1.32482715 0.3108484 -0.005212173 0.70131917 -0.6852460
## X322 1.21665476 0.16468846 1.9716169 -0.005212173 0.85821946 1.8438701
## X323 -0.72058540 0.74475780 -0.9347280 -0.831341597 -0.44251753 0.1577927
## X324 -0.72058540 -1.18880668 -0.1043438 -0.831341597 -0.95516548 -0.6852460
## X325 -0.21200528 -0.02866799 -0.9347280 -0.831341597 -0.01199386 -0.6852460
## X326 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X327 -0.21200528 -0.02866799 -0.5195359 -0.831341597 -0.01199386 -0.6852460
## X328 0.42867850 1.32482715 0.3108484 -0.005212173 0.85821946 -0.6852460
## X329 -0.60958681 -0.99545024 0.3108484 -0.005212173 -0.68595798 -0.6852460
## X330 -0.96037479 -0.02866799 -0.9347280 -0.831341597 -0.68595798 0.1577927
## X331 0.69697444 0.55140136 0.3108484 1.647046674 0.36423857 1.0008314
## X332 -0.40240913 0.16468846 -0.5195359 -0.005212173 -0.21915966 0.1577927
## X333 0.99793817 0.16468846 1.1412327 -0.005212173 0.85821946 0.1577927
## X334 -0.30530231 0.16468846 -0.1043438 -0.005212173 -0.21915966 0.1577927
## X335 1.10948462 0.16468846 2.8020012 -0.005212173 0.85821946 1.0008314
## X336 -0.40240913 -0.99545024 -0.9347280 -0.005212173 -0.44251753 -0.6852460
## X337 0.63244961 1.51818360 0.7260405 0.820917251 0.36423857 2.6869088
## X338 0.28325136 1.13147070 -0.1043438 -0.005212173 0.53699786 0.1577927
## X339 0.28325136 1.13147070 -0.1043438 -0.005212173 0.53699786 0.1577927
## X340 -0.72058540 0.16468846 -0.5195359 -0.005212173 -0.44251753 -0.6852460
## X341 0.49840233 -0.99545024 1.9716169 -0.005212173 0.18177643 -0.6852460
## X342 -0.21200528 -0.02866799 -0.9347280 -0.831341597 -0.01199386 -0.6852460
## X343 1.74225056 0.35804491 -0.9347280 0.820917251 1.80408084 1.0008314
## X344 0.75995351 0.55140136 1.1412327 1.647046674 0.53699786 0.1577927
## X345 0.12893412 1.90489650 -0.9347280 -0.831341597 0.70131917 0.1577927
## X346 0.75995351 -0.60873734 0.7260405 1.647046674 0.36423857 1.0008314
## X347 2.47286768 -0.99545024 0.7260405 -0.005212173 2.15069776 -0.6852460
## X348 1.65364219 1.13147070 0.7260405 -0.005212173 1.68198027 1.0008314
## X349 -0.21200528 -0.02866799 -0.1043438 -0.831341597 -0.01199386 -0.6852460
## X350 0.94039386 2.09825295 0.7260405 -0.831341597 1.15294194 1.8438701
## X351 0.35700394 -0.99545024 1.9716169 -0.005212173 -0.01199386 -0.6852460
## X352 0.12893412 -0.80209379 1.1412327 0.820917251 -0.21915966 0.1577927
## X353 0.88159159 0.55140136 1.1412327 1.647046674 0.53699786 1.0008314
## X354 1.31981693 1.32482715 0.3108484 -0.005212173 1.55615914 0.1577927
## X355 0.63244961 -0.80209379 2.8020012 0.820917251 0.36423857 -0.6852460
## X356 -0.21200528 -0.02866799 -0.9347280 -0.831341597 -0.01199386 -0.6852460
## X357 0.99793817 0.35804491 0.7260405 0.820917251 0.70131917 -0.6852460
## X358 0.56629095 -0.99545024 2.3868091 -0.005212173 0.18177643 -0.6852460
## X359 0.82146772 -0.41538089 1.1412327 2.473176098 0.53699786 1.0008314
## X360 1.56220886 -0.41538089 -0.9347280 2.473176098 1.55615914 -0.6852460
## X361 0.28325136 0.16468846 1.1412327 -0.005212173 0.36423857 -0.6852460
## X362 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X363 0.35700394 1.51818360 0.3108484 0.820917251 0.18177643 2.6869088
## X364 -0.21200528 -1.18880668 -0.9347280 -0.831341597 -0.44251753 -0.6852460
## X365 0.12893412 0.16468846 -0.1043438 -0.005212173 -0.01199386 1.0008314
## X366 -0.83728034 -0.02866799 -0.9347280 -0.831341597 -0.44251753 -0.6852460
## X367 -0.83728034 -0.02866799 -0.9347280 -0.831341597 -0.44251753 -0.6852460
## X368 -0.40240913 -1.18880668 -0.5195359 -0.831341597 -0.68595798 -0.6852460
## X369 1.21665476 1.13147070 1.1412327 -0.005212173 1.29203392 0.1577927
## X370 1.26871571 1.90489650 0.3108484 2.473176098 1.00853037 1.8438701
## X371 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X372 0.35700394 1.32482715 -0.1043438 -0.005212173 0.70131917 0.1577927
## X373 -0.40240913 0.93811425 -0.9347280 -0.831341597 0.18177643 -0.6852460
## X374 0.69697444 1.51818360 -0.5195359 0.820917251 1.00853037 1.0008314
## X375 0.94039386 1.13147070 1.1412327 -0.005212173 0.85821946 1.8438701
## X376 2.03269881 -0.41538089 -0.1043438 2.473176098 1.92274051 -0.6852460
## X377 2.43853015 -0.99545024 0.7260405 -0.005212173 2.15069776 -0.6852460
## X378 1.31981693 1.13147070 0.7260405 -0.831341597 1.42629884 1.0008314
## X379 -0.21200528 -0.99545024 0.7260405 -0.831341597 -0.21915966 -0.6852460
## X380 -2.10721958 -1.18880668 -0.9347280 -0.831341597 -2.04708364 -0.6852460
## X381 0.12893412 0.16468846 1.1412327 -0.005212173 0.18177643 -0.6852460
## X382 1.26871571 0.55140136 0.3108484 1.647046674 0.85821946 1.8438701
## X383 1.95260717 -0.41538089 -0.1043438 2.473176098 1.80408084 -0.6852460
## X384 1.60829128 -0.60873734 -0.9347280 1.647046674 1.55615914 -0.6852460
## X385 0.75995351 1.51818360 0.7260405 0.820917251 1.15294194 -0.6852460
## X386 0.35700394 1.51818360 0.3108484 0.820917251 0.18177643 2.6869088
## X387 1.41929339 1.51818360 1.1412327 0.820917251 1.55615914 1.0008314
## X388 1.05428349 1.71154005 0.3108484 1.647046674 1.00853037 1.0008314
## X389 0.28325136 1.13147070 0.3108484 0.820917251 -0.01199386 1.0008314
## X390 1.36999732 1.51818360 1.1412327 0.820917251 1.55615914 1.0008314
## X391 2.43853015 -0.99545024 0.7260405 -0.005212173 2.15069776 -0.6852460
## X392 1.51536781 0.16468846 3.6323855 -0.005212173 1.29203392 0.1577927
## X393 0.04803954 -0.02866799 -0.1043438 -0.831341597 0.18177643 -0.6852460
## X394 -0.40240913 0.93811425 -0.9347280 -0.831341597 0.18177643 -0.6852460
## X395 0.82146772 0.16468846 1.9716169 -0.005212173 0.70131917 0.1577927
## X396 -0.72058540 -1.18880668 -0.5195359 -0.831341597 -0.95516548 -0.6852460
## X397 0.49840233 1.13147070 0.3108484 -0.831341597 0.85821946 -0.6852460
## X398 0.56629095 -1.18880668 -0.5195359 -0.831341597 0.18177643 -0.6852460
## X399 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X400 0.12893412 0.16468846 -0.1043438 -0.005212173 -0.01199386 1.0008314
## X401 0.56629095 0.74475780 0.3108484 -0.831341597 0.53699786 1.0008314
## X402 0.04803954 0.16468846 0.3108484 -0.005212173 -0.01199386 0.1577927
## X403 0.63244961 -0.02866799 1.1412327 -0.831341597 0.53699786 -0.6852460
## X404 0.28325136 -0.99545024 1.5564248 -0.005212173 -0.01199386 -0.6852460
## X405 -0.60958681 -0.80209379 -0.9347280 0.820917251 -0.95516548 1.0008314
## X406 -0.50369472 0.16468846 -0.5195359 -0.005212173 -0.21915966 -0.6852460
## X407 -0.60958681 0.35804491 -0.9347280 0.820917251 -0.21915966 0.1577927
## X408 -0.72058540 -1.18880668 -0.1043438 -0.831341597 -0.95516548 -0.6852460
## X409 1.05428349 -0.41538089 -0.1043438 2.473176098 0.85821946 1.0008314
## X410 0.42867850 0.74475780 -0.5195359 2.473176098 -0.21915966 1.8438701
## X411 0.94039386 0.74475780 -0.9347280 2.473176098 1.15294194 -0.6852460
## X412 0.42867850 1.51818360 0.3108484 0.820917251 0.36423857 1.8438701
## X413 -0.72058540 0.35804491 -0.9347280 0.820917251 -0.68595798 2.6869088
## X414 0.28325136 -1.18880668 1.5564248 -0.831341597 -0.21915966 0.1577927
## X415 -0.50369472 -0.02866799 -0.9347280 -0.831341597 -0.21915966 -0.6852460
## X416 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X417 0.56629095 1.51818360 0.3108484 0.820917251 0.36423857 2.6869088
## X418 0.75995351 1.13147070 -0.1043438 -0.831341597 1.00853037 -0.6852460
## X419 0.42867850 1.32482715 0.3108484 -0.005212173 0.85821946 -0.6852460
## X420 0.20728011 0.16468846 -0.1043438 -0.005212173 0.18177643 1.0008314
## X421 -0.30530231 0.16468846 -0.1043438 -0.005212173 -0.21915966 0.1577927
## X422 -0.40240913 0.16468846 0.3108484 -0.005212173 -0.21915966 -0.6852460
## X423 1.99292450 -0.60873734 -0.1043438 1.647046674 1.80408084 -0.6852460
## X424 1.16359252 0.55140136 0.3108484 1.647046674 0.85821946 3.5299475
## X425 2.03269881 -0.41538089 -0.1043438 2.473176098 1.92274051 -0.6852460
## X426 -0.12219740 0.55140136 -0.9347280 1.647046674 0.36423857 -0.6852460
## X427 -2.10721958 -1.18880668 -0.9347280 -0.831341597 -2.04708364 -0.6852460
## X428 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X429 -0.30530231 -0.02866799 -0.9347280 -0.831341597 -0.01199386 -0.6852460
## X430 -0.40240913 0.16468846 -0.5195359 -0.005212173 -0.21915966 0.1577927
## X431 -0.83728034 -0.02866799 -0.9347280 -0.831341597 -0.44251753 -0.6852460
## X432 -0.50369472 0.16468846 -0.1043438 -0.005212173 -0.21915966 -0.6852460
## X433 -0.50369472 -1.18880668 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X434 0.04803954 0.55140136 -0.5195359 1.647046674 0.18177643 1.8438701
## X435 0.28325136 -0.99545024 1.9716169 -0.005212173 -0.01199386 -0.6852460
## X436 -0.83728034 -0.02866799 -0.9347280 -0.831341597 -0.44251753 -0.6852460
## X437 3.22789945 0.16468846 0.3108484 4.951564368 3.05604172 0.1577927
## X438 1.91172984 -0.41538089 -0.1043438 2.473176098 1.80408084 -0.6852460
## X439 -0.60958681 -0.99545024 -0.1043438 -0.005212173 -0.68595798 -0.6852460
## X440 -1.22934392 -0.02866799 -0.9347280 -0.831341597 -0.68595798 -0.6852460
## X441 1.31981693 1.71154005 1.1412327 1.647046674 1.55615914 1.0008314
## X442 1.31981693 0.16468846 -0.9347280 -0.005212173 1.29203392 0.1577927
## X443 0.56629095 0.55140136 -0.1043438 1.647046674 0.18177643 1.8438701
## X444 0.49840233 -0.99545024 2.3868091 -0.005212173 -0.01199386 0.1577927
## X445 0.69697444 -0.99545024 1.9716169 -0.005212173 0.18177643 0.1577927
## X446 0.20728011 0.16468846 0.3108484 -0.005212173 0.18177643 0.1577927
## X447 0.56629095 -0.99545024 2.3868091 -0.005212173 0.18177643 -0.6852460
## X448 0.82146772 -0.99545024 0.7260405 -0.005212173 0.36423857 0.1577927
## X449 1.21665476 0.55140136 0.3108484 1.647046674 1.29203392 0.1577927
## X450 -1.53694587 -0.22202444 -0.9347280 -0.831341597 -1.25901822 0.1577927
## X451 0.75995351 -0.99545024 2.8020012 -0.005212173 0.36423857 -0.6852460
## X452 0.82146772 1.32482715 -0.5195359 -0.005212173 1.00853037 -0.6852460
## X453 0.20728011 1.13147070 -0.5195359 0.820917251 0.53699786 -0.6852460
## X454 1.56220886 2.09825295 1.1412327 3.299305521 1.92274051 -0.6852460
## NumOxygen NumSulfer NumChlorine NumHalogen NumRings HydrophilicFactor
## X1 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.741919037
## X2 -0.3320280 1.7123815 -0.3972472 -0.4741055 2.0005400 -0.310306393
## X3 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.274782719
## X4 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.834280591
## X5 -0.9103405 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.042990743
## X6 -0.3320280 1.7123815 1.0310404 0.8839497 -1.0792067 -0.559860206
## X7 -0.9103405 -0.3360145 1.0310404 0.8839497 2.0005400 -0.629131371
## X8 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.723269108
## X9 1.4029096 -0.3360145 -0.3972472 0.2049221 2.0005400 0.190577416
## X10 -0.3320280 -0.3360145 -0.3972472 -0.4741055 0.4606666 0.331784022
## X11 0.8245970 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.698402536
## X12 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.365368089
## X13 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.842273418
## X14 -0.9103405 -0.3360145 0.3168966 0.2049221 0.4606666 -0.760568966
## X15 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.838721050
## X16 0.8245970 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.260573249
## X17 0.8245970 1.7123815 -0.3972472 -0.4741055 -0.3092700 -0.115814276
## X18 -0.3320280 1.7123815 0.3168966 0.2049221 2.0005400 -0.288992189
## X19 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.365368089
## X20 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.842273418
## X21 0.8245970 -0.3360145 0.3168966 0.2049221 1.2306033 -0.249028055
## X22 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.773002252
## X23 0.2462845 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.689521618
## X24 0.2462845 -0.3360145 3.8876154 3.6000599 -0.3092700 0.566240273
## X25 1.4029096 5.8091734 -0.3972472 -0.4741055 -0.3092700 -0.119366643
## X26 0.8245970 1.7123815 -0.3972472 -0.4741055 0.4606666 0.382405258
## X27 -0.3320280 1.7123815 -0.3972472 -0.4741055 1.2306033 -0.705507271
## X28 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 0.343329216
## X29 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.295208832
## X30 -0.9103405 -0.3360145 1.0310404 0.8839497 -0.3092700 -0.578510135
## X31 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.828952040
## X32 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.812966386
## X33 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.821847305
## X34 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.842273418
## X35 0.8245970 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.708171547
## X36 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.842273418
## X37 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.821847305
## X38 1.9812221 -0.3360145 -0.3972472 -0.4741055 2.0005400 1.404598989
## X39 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 0.207451161
## X40 0.2462845 -0.3360145 -0.3972472 1.5629772 0.4606666 0.382405258
## X41 2.5595346 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.190577416
## X42 0.2462845 -0.3360145 1.0310404 0.8839497 -0.3092700 -0.130911837
## X43 -0.9103405 -0.3360145 -0.3972472 0.2049221 0.4606666 -0.760568966
## X44 -0.9103405 1.7123815 0.3168966 0.2049221 2.0005400 -0.683304975
## X45 -0.9103405 -0.3360145 0.3168966 0.2049221 -0.3092700 0.574233100
## X46 -0.3320280 -0.3360145 -0.3972472 1.5629772 1.2306033 -0.676200240
## X47 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.821847305
## X48 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.723269108
## X49 0.2462845 -0.3360145 1.7451841 1.5629772 0.4606666 -0.157554593
## X50 0.2462845 -0.3360145 -0.3972472 0.2049221 0.4606666 -0.278335086
## X51 -0.9103405 -0.3360145 -0.3972472 1.5629772 -0.3092700 -0.546538828
## X52 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.812966386
## X53 -0.9103405 -0.3360145 0.3168966 0.2049221 0.4606666 -0.778330804
## X54 -0.9103405 -0.3360145 0.3168966 0.2049221 -0.3092700 0.687908858
## X55 -0.9103405 -0.3360145 2.4593279 2.2420048 -0.3092700 -0.493253316
## X56 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.376025191
## X57 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 0.331784022
## X58 -0.9103405 1.7123815 -0.3972472 -0.4741055 0.4606666 -0.711723914
## X59 2.5595346 -0.3360145 0.3168966 0.2049221 1.2306033 -0.602488615
## X60 1.4029096 -0.3360145 0.3168966 0.2049221 1.2306033 -0.263237525
## X61 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.252580422
## X62 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.711723914
## X63 -0.9103405 -0.3360145 2.4593279 2.2420048 -0.3092700 -0.493253316
## X64 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.842273418
## X65 1.4029096 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.680640699
## X66 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.294320740
## X67 0.2462845 1.7123815 0.3168966 0.2049221 2.0005400 -0.655774127
## X68 2.5595346 -0.3360145 -0.3972472 0.2049221 2.0005400 0.148837099
## X69 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.821847305
## X70 -0.9103405 1.7123815 -0.3972472 -0.4741055 2.0005400 -0.737478578
## X71 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.842273418
## X72 -0.9103405 -0.3360145 -0.3972472 0.2049221 -1.0792067 -0.717052465
## X73 -0.3320280 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.791652182
## X74 -0.9103405 7.8575693 -0.3972472 -0.4741055 -1.0792067 -0.525224623
## X75 -0.9103405 -0.3360145 0.3168966 0.2049221 0.4606666 -0.778330804
## X76 2.5595346 -0.3360145 -0.3972472 0.2049221 2.0005400 0.189689324
## X77 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.844937693
## X78 -0.9103405 -0.3360145 1.0310404 0.8839497 0.4606666 1.916139901
## X79 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.844937693
## X80 0.8245970 -0.3360145 -0.3972472 0.8839497 0.4606666 -0.257020882
## X81 1.4029096 -0.3360145 0.3168966 0.2049221 2.0005400 -0.703731087
## X82 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.294320740
## X83 -0.9103405 1.7123815 0.3168966 0.2049221 1.2306033 -0.689521618
## X84 0.8245970 -0.3360145 1.7451841 1.5629772 0.4606666 -0.111373817
## X85 -0.9103405 -0.3360145 -0.3972472 1.5629772 -0.3092700 -0.546538828
## X86 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.828952040
## X87 -0.9103405 -0.3360145 -0.3972472 0.2049221 -1.0792067 -0.734814302
## X88 0.8245970 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.295208832
## X89 1.9812221 1.7123815 0.3168966 0.2049221 1.2306033 0.810465534
## X90 -0.3320280 5.8091734 -0.3972472 -0.4741055 -1.0792067 -0.596271972
## X91 2.5595346 -0.3360145 -0.3972472 -0.4741055 2.0005400 2.044025128
## X92 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 0.285603245
## X93 -0.9103405 -0.3360145 3.8876154 3.6000599 -0.3092700 -0.371584732
## X94 0.8245970 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.737478578
## X95 0.2462845 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.741919037
## X96 1.4029096 -0.3360145 -0.3972472 1.5629772 0.4606666 1.712766865
## X97 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.821847305
## X98 -0.9103405 -0.3360145 1.0310404 0.8839497 0.4606666 -0.723269108
## X99 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.788987906
## X100 -0.9103405 -0.3360145 1.0310404 0.8839497 0.4606666 -0.723269108
## X101 -0.9103405 -0.3360145 1.0310404 0.8839497 0.4606666 -0.723269108
## X102 -0.9103405 1.7123815 -0.3972472 1.5629772 1.2306033 -0.638900382
## X103 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.294320740
## X104 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.768561793
## X105 0.2462845 1.7123815 2.4593279 2.2420048 0.4606666 -0.465722469
## X106 -0.3320280 1.7123815 -0.3972472 -0.4741055 2.7704767 -0.365368089
## X107 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.737478578
## X108 2.5595346 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.135515721
## X109 1.4029096 7.8575693 -0.3972472 -0.4741055 -1.0792067 -0.395563212
## X110 1.4029096 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.310306393
## X111 1.4029096 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.705507271
## X112 -0.9103405 -0.3360145 3.8876154 3.6000599 1.2306033 -0.525224623
## X113 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.353822894
## X114 0.8245970 -0.3360145 1.0310404 0.8839497 0.4606666 -0.578510135
## X115 -0.9103405 -0.3360145 1.7451841 1.5629772 0.4606666 -0.675312148
## X116 0.2462845 -0.3360145 0.3168966 1.5629772 0.4606666 0.395726636
## X117 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.332508690
## X118 -0.9103405 -0.3360145 1.7451841 1.5629772 0.4606666 -0.675312148
## X119 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.851154336
## X120 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.183472681
## X121 -0.3320280 -0.3360145 3.8876154 3.6000599 2.7704767 -0.533217450
## X122 -0.9103405 -0.3360145 1.7451841 1.5629772 0.4606666 -0.675312148
## X123 1.4029096 3.7607774 0.3168966 0.2049221 0.4606666 -0.515455613
## X124 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.659326494
## X125 -0.9103405 -0.3360145 1.0310404 0.8839497 0.4606666 -0.723269108
## X126 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.633571830
## X127 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.659326494
## X128 -0.9103405 -0.3360145 1.0310404 0.8839497 0.4606666 -0.723269108
## X129 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.633571830
## X130 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.852042428
## X131 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.853818612
## X132 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.633571830
## X133 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.851154336
## X134 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.659326494
## X135 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.853818612
## X136 -0.9103405 -0.3360145 3.1734717 2.9210324 0.4606666 -0.596271972
## X137 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.633571830
## X138 0.8245970 -0.3360145 -0.3972472 -0.4741055 3.5404134 -0.408884590
## X139 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.633571830
## X140 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.7704767 -0.407108406
## X141 -0.9103405 -0.3360145 3.8876154 3.6000599 0.4606666 -0.562524482
## X142 -0.9103405 -0.3360145 3.1734717 2.9210324 0.4606666 -0.596271972
## X143 -0.9103405 -0.3360145 3.8876154 3.6000599 0.4606666 -0.562524482
## X144 -0.9103405 -0.3360145 3.8876154 3.6000599 0.4606666 -0.562524482
## X145 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.633571830
## X146 -0.9103405 -0.3360145 3.1734717 2.9210324 0.4606666 -0.596271972
## X147 -0.9103405 -0.3360145 4.6017592 4.2790875 0.4606666 -0.533217450
## X148 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.7704767 -0.856482887
## X149 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.7704767 -0.855594796
## X150 -0.9103405 -0.3360145 3.8876154 3.6000599 0.4606666 -0.562524482
## X151 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.7704767 -0.855594796
## X152 -0.9103405 -0.3360145 -0.3972472 1.5629772 2.0005400 -0.672647872
## X153 -0.9103405 -0.3360145 3.8876154 3.6000599 0.4606666 -0.562524482
## X154 -0.9103405 -0.3360145 3.8876154 3.6000599 0.4606666 -0.562524482
## X155 -0.9103405 -0.3360145 3.8876154 3.6000599 0.4606666 -0.562524482
## X156 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.7704767 -0.855594796
## X157 -0.9103405 -0.3360145 5.3159030 4.9581151 0.4606666 -0.505686603
## X158 -0.9103405 -0.3360145 5.3159030 4.9581151 0.4606666 -0.505686603
## X159 -0.9103405 -0.3360145 6.7441905 6.3161702 0.4606666 -0.459505826
## X160 -0.3320280 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.778330804
## X161 -0.9103405 -0.3360145 0.3168966 0.2049221 -1.0792067 -0.717052465
## X162 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.376025191
## X163 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.838721050
## X164 2.5595346 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.311194485
## X165 -0.9103405 -0.3360145 1.7451841 1.5629772 -0.3092700 -0.546538828
## X166 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.834280591
## X167 -0.9103405 -0.3360145 -0.3972472 0.8839497 -0.3092700 -0.612257626
## X168 -0.9103405 1.7123815 -0.3972472 -0.4741055 -0.3092700 0.527164231
## X169 0.2462845 5.8091734 -0.3972472 -0.4741055 -1.0792067 -0.446184448
## X170 2.5595346 -0.3360145 -0.3972472 -0.4741055 2.7704767 -0.640676565
## X171 3.7161597 -0.3360145 -0.3972472 0.2049221 2.0005400 0.201234518
## X172 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.821847305
## X173 1.4029096 1.7123815 -0.3972472 -0.4741055 1.2306033 0.379740982
## X174 0.2462845 -0.3360145 -0.3972472 1.5629772 0.4606666 0.425921759
## X175 -0.9103405 -0.3360145 3.1734717 2.9210324 -1.0792067 -0.358263354
## X176 -0.9103405 1.7123815 -0.3972472 -0.4741055 1.2306033 -0.724157200
## X177 1.4029096 1.7123815 -0.3972472 -0.4741055 2.7704767 -0.709059639
## X178 -0.3320280 -0.3360145 3.1734717 2.9210324 -0.3092700 0.088446852
## X179 1.4029096 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.738530094
## X180 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.168375119
## X181 -0.9103405 1.7123815 -0.3972472 -0.4741055 1.2306033 -0.724157200
## X182 2.5595346 -0.3360145 -0.3972472 0.2049221 2.7704767 0.189689324
## X183 -0.9103405 1.7123815 -0.3972472 -0.4741055 1.2306033 -0.778330804
## X184 -0.3320280 -0.3360145 1.0310404 0.8839497 1.2306033 -0.257020882
## X185 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 0.207451161
## X186 0.2462845 -0.3360145 0.3168966 0.8839497 1.2306033 -0.310306393
## X187 -0.9103405 -0.3360145 -0.3972472 0.2049221 -1.0792067 -0.717052465
## X188 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.814742570
## X189 -0.9103405 1.7123815 -0.3972472 1.5629772 2.0005400 -0.640676565
## X190 0.8245970 3.7607774 -0.3972472 -0.4741055 -0.3092700 -0.525224623
## X191 2.5595346 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.147949007
## X192 0.2462845 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.698402536
## X193 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.847601969
## X194 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.385794201
## X195 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.842273418
## X196 0.8245970 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.753464232
## X197 0.8245970 1.7123815 1.7451841 1.5629772 -0.3092700 -0.361815721
## X198 -0.3320280 1.7123815 1.7451841 1.5629772 -1.0792067 -0.525224623
## X199 -0.9103405 -0.3360145 3.8876154 3.6000599 -1.0792067 -0.322739679
## X200 -0.9103405 -0.3360145 0.3168966 0.2049221 0.4606666 -0.778330804
## X201 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.842273418
## X202 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.353822894
## X203 0.8245970 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.757904691
## X204 1.9812221 1.7123815 0.3168966 0.2049221 0.4606666 -0.538546001
## X205 -0.3320280 -0.3360145 3.8876154 3.6000599 1.2306033 -0.055424029
## X206 -0.9103405 -0.3360145 2.4593279 2.2420048 -0.3092700 -0.476379571
## X207 0.2462845 5.8091734 0.3168966 0.2049221 -0.3092700 -0.514567521
## X208 -0.9103405 -0.3360145 1.0310404 0.8839497 0.4606666 -0.723269108
## X209 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.849378152
## X210 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.851154336
## X211 -0.9103405 -0.3360145 1.7451841 1.5629772 0.4606666 -0.675312148
## X212 -0.3320280 -0.3360145 3.8876154 3.6000599 2.7704767 -0.533217450
## X213 -0.9103405 -0.3360145 1.7451841 1.5629772 0.4606666 -0.675312148
## X214 0.8245970 -0.3360145 1.0310404 0.8839497 1.2306033 -0.690409709
## X215 -0.9103405 -0.3360145 4.6017592 4.2790875 1.2306033 -0.494141408
## X216 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.633571830
## X217 -0.9103405 -0.3360145 3.1734717 2.9210324 0.4606666 -0.624690912
## X218 3.1378471 -0.3360145 -0.3972472 -0.4741055 1.2306033 0.840660658
## X219 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.327180139
## X220 -0.9103405 -0.3360145 2.4593279 2.2420048 0.4606666 -0.633571830
## X221 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.362703813
## X222 -0.9103405 -0.3360145 3.8876154 3.6000599 2.0005400 -0.562524482
## X223 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.7704767 -0.855594796
## X224 -0.9103405 -0.3360145 3.1734717 2.9210324 0.4606666 -0.596271972
## X225 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.852042428
## X226 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.853818612
## X227 -0.9103405 -0.3360145 3.8876154 3.6000599 0.4606666 -0.562524482
## X228 -0.9103405 -0.3360145 3.8876154 3.6000599 0.4606666 -0.562524482
## X229 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.7704767 -0.855594796
## X230 -0.9103405 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.853818612
## X231 -0.9103405 -0.3360145 3.8876154 3.6000599 0.4606666 -0.562524482
## X232 -0.9103405 -0.3360145 6.0300467 5.6371426 0.4606666 -0.481708122
## X233 0.2462845 -0.3360145 -0.3972472 -0.4741055 1.2306033 0.321126919
## X234 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.365368089
## X235 -0.9103405 -0.3360145 3.8876154 3.6000599 -0.3092700 -0.411548865
## X236 0.8245970 1.7123815 1.7451841 1.5629772 -0.3092700 -0.417765508
## X237 -0.9103405 -0.3360145 3.1734717 2.9210324 0.4606666 -0.624690912
## X238 -0.9103405 -0.3360145 5.3159030 4.9581151 1.2306033 -0.465722469
## X239 0.8245970 -0.3360145 1.0310404 0.8839497 -0.3092700 -0.028781274
## X240 3.7161597 -0.3360145 0.3168966 0.2049221 2.0005400 3.680778427
## X241 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.779218896
## X242 -0.9103405 -0.3360145 0.3168966 0.8839497 -0.3092700 -0.640676565
## X243 -0.3320280 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.164659328
## X244 0.8245970 1.7123815 -0.3972472 -0.4741055 0.4606666 1.129290512
## X245 0.8245970 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.129135654
## X246 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.240147136
## X247 0.8245970 1.7123815 -0.3972472 -0.4741055 0.4606666 1.175471289
## X248 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.749023772
## X249 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.799645008
## X250 0.2462845 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.039438376
## X251 -0.9103405 1.7123815 -0.3972472 -0.4741055 -0.3092700 -0.693962077
## X252 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.310306393
## X253 -0.9103405 -0.3360145 3.1734717 2.9210324 -1.0792067 -0.218832932
## X254 0.2462845 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.249028055
## X255 0.8245970 1.7123815 0.3168966 0.2049221 0.4606666 -0.042990743
## X256 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 0.604428223
## X257 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -0.3092700 0.527164231
## X258 -0.9103405 -0.3360145 0.3168966 0.2049221 -1.0792067 -0.662878862
## X259 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.779218896
## X260 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.252580422
## X261 0.8245970 1.7123815 -0.3972472 -0.4741055 0.4606666 -0.076738234
## X262 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.799645008
## X263 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.779218896
## X264 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.723269108
## X265 -0.9103405 -0.3360145 1.0310404 0.8839497 -1.0792067 -0.574957768
## X266 -0.9103405 -0.3360145 1.0310404 0.8839497 -1.0792067 -0.527000807
## X267 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 1.948111208
## X268 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.683304975
## X269 0.8245970 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.670871689
## X270 0.8245970 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.190413992
## X271 0.2462845 -0.3360145 -0.3972472 0.2049221 -0.3092700 -0.039438376
## X272 0.2462845 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.670871689
## X273 -0.9103405 -0.3360145 0.3168966 0.2049221 -1.0792067 -0.662878862
## X274 0.8245970 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.157554593
## X275 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.164659328
## X276 0.2462845 -0.3360145 1.7451841 1.5629772 -0.3092700 1.517386655
## X277 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.321851587
## X278 -0.9103405 1.7123815 -0.3972472 -0.4741055 0.4606666 0.068908831
## X279 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.785435539
## X280 -0.3320280 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.124695194
## X281 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.821847305
## X282 0.8245970 -0.3360145 1.0310404 0.8839497 0.4606666 -0.470162928
## X283 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.821847305
## X284 0.2462845 -0.3360145 -0.3972472 -0.4741055 3.5404134 0.208339253
## X285 -0.3320280 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.087395336
## X286 0.2462845 1.7123815 -0.3972472 -0.4741055 0.4606666 1.178135565
## X287 0.8245970 -0.3360145 -0.3972472 -0.4741055 0.4606666 1.766052376
## X288 0.8245970 -0.3360145 -0.3972472 0.8839497 -0.3092700 2.105303467
## X289 3.7161597 -0.3360145 -0.3972472 -0.4741055 2.0005400 3.653247579
## X290 -0.3320280 -0.3360145 0.3168966 0.2049221 0.4606666 0.516507129
## X291 -0.9103405 -0.3360145 -0.3972472 0.2049221 -1.0792067 -0.662878862
## X292 0.8245970 1.7123815 -0.3972472 -0.4741055 0.4606666 1.178135565
## X293 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 0.470326352
## X294 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.760568966
## X295 0.8245970 -0.3360145 -0.3972472 -0.4741055 -0.3092700 0.382405258
## X296 1.4029096 1.7123815 -0.3972472 -0.4741055 0.4606666 1.128402420
## X297 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.711723914
## X298 -0.3320280 -0.3360145 1.0310404 0.8839497 -0.3092700 -0.094500071
## X299 0.8245970 -0.3360145 -0.3972472 -0.4741055 0.4606666 0.399279003
## X300 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.209952013
## X301 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.760568966
## X302 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 0.364643421
## X303 -0.9103405 1.7123815 -0.3972472 -0.4741055 -0.3092700 0.574233100
## X304 1.4029096 3.7607774 0.3168966 0.2049221 0.4606666 1.385060968
## X305 0.8245970 1.7123815 -0.3972472 -0.4741055 -0.3092700 0.485423914
## X306 -0.9103405 -0.3360145 1.0310404 0.8839497 -0.3092700 -0.612257626
## X307 -0.3320280 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.336061057
## X308 3.1378471 -0.3360145 -0.3972472 -0.4741055 1.2306033 2.486294875
## X309 -0.3320280 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.336061057
## X310 1.9812221 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.207451161
## X311 -0.9103405 -0.3360145 0.3168966 0.2049221 -1.0792067 -0.693962077
## X312 3.7161597 -0.3360145 -0.3972472 -0.4741055 2.0005400 3.653247579
## X313 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.778330804
## X314 -0.9103405 -0.3360145 1.0310404 3.6000599 -1.0792067 -0.192190176
## X315 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.760568966
## X316 -0.9103405 -0.3360145 -0.3972472 0.8839497 -0.3092700 -0.612257626
## X317 -0.9103405 -0.3360145 -0.3972472 2.2420048 -1.0792067 -0.141568940
## X318 3.1378471 -0.3360145 -0.3972472 -0.4741055 2.7704767 -0.626467096
## X319 0.2462845 1.7123815 -0.3972472 -0.4741055 0.4606666 -0.185085441
## X320 -0.9103405 -0.3360145 0.3168966 0.2049221 -0.3092700 0.581337835
## X321 0.8245970 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.240147136
## X322 0.2462845 -0.3360145 0.3168966 0.2049221 -0.3092700 1.041369418
## X323 -0.9103405 3.7607774 -0.3972472 -0.4741055 0.4606666 -0.039438376
## X324 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.779218896
## X325 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.828952040
## X326 -0.9103405 -0.3360145 0.3168966 0.8839497 -0.3092700 -0.612257626
## X327 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.828952040
## X328 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.294320740
## X329 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.799645008
## X330 -0.9103405 -0.3360145 1.0310404 0.8839497 -0.3092700 0.766949033
## X331 0.8245970 1.7123815 -0.3972472 1.5629772 -0.3092700 0.512954761
## X332 -0.3320280 -0.3360145 -0.3972472 0.2049221 -0.3092700 -0.087395336
## X333 0.2462845 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.659326494
## X334 0.2462845 -0.3360145 1.0310404 0.8839497 -0.3092700 0.621301968
## X335 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 1.032488500
## X336 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.812966386
## X337 0.8245970 1.7123815 -0.3972472 -0.4741055 0.4606666 1.175471289
## X338 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.217056748
## X339 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.217056748
## X340 0.8245970 -0.3360145 -0.3972472 0.8839497 -0.3092700 0.686132674
## X341 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.760568966
## X342 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.828952040
## X343 0.2462845 -0.3360145 -0.3972472 -0.4741055 4.3103501 -0.718828649
## X344 1.4029096 1.7123815 -0.3972472 -0.4741055 0.4606666 -0.533217450
## X345 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.785435539
## X346 0.2462845 1.7123815 -0.3972472 -0.4741055 -0.3092700 0.472990628
## X347 1.9812221 -0.3360145 -0.3972472 -0.4741055 2.0005400 1.404598989
## X348 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.321851587
## X349 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.828952040
## X350 -0.3320280 -0.3360145 -0.3972472 0.8839497 1.2306033 -0.217056748
## X351 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.683304975
## X352 -0.9103405 3.7607774 0.3168966 0.2049221 -1.0792067 -0.555419747
## X353 0.8245970 1.7123815 -0.3972472 -0.4741055 -0.3092700 0.447235964
## X354 -0.3320280 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.773002252
## X355 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.227713850
## X356 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.828952040
## X357 1.9812221 1.7123815 -0.3972472 -0.4741055 0.4606666 -0.578510135
## X358 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.198406819
## X359 0.2462845 1.7123815 -0.3972472 -0.4741055 -0.3092700 0.433914586
## X360 0.8245970 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.737478578
## X361 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.711723914
## X362 -0.9103405 -0.3360145 -0.3972472 0.8839497 -0.3092700 -0.612257626
## X363 0.2462845 1.7123815 -0.3972472 -0.4741055 0.4606666 1.231421076
## X364 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.812966386
## X365 0.2462845 -0.3360145 1.0310404 0.8839497 -0.3092700 -0.042990743
## X366 -0.9103405 -0.3360145 -0.3972472 0.2049221 -0.3092700 -0.717052465
## X367 -0.9103405 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.717052465
## X368 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.799645008
## X369 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.724157200
## X370 1.4029096 3.7607774 -0.3972472 1.5629772 1.2306033 1.688788384
## X371 -0.9103405 -0.3360145 1.7451841 1.5629772 -0.3092700 -0.546538828
## X372 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 0.364643421
## X373 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.834280591
## X374 0.2462845 -0.3360145 1.0310404 0.8839497 1.2306033 0.353986318
## X375 0.2462845 -0.3360145 0.3168966 0.2049221 0.4606666 -0.593607697
## X376 1.9812221 -0.3360145 -0.3972472 0.2049221 2.0005400 0.801584616
## X377 1.4029096 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.738530094
## X378 -0.9103405 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.353822894
## X379 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.821847305
## X380 -0.9103405 -0.3360145 3.8876154 3.6000599 -1.0792067 -0.192190176
## X381 0.8245970 -0.3360145 1.0310404 0.8839497 -0.3092700 -0.100716714
## X382 0.8245970 1.7123815 -0.3972472 -0.4741055 0.4606666 0.395726636
## X383 2.5595346 -0.3360145 -0.3972472 0.2049221 2.0005400 1.494296267
## X384 0.2462845 -0.3360145 -0.3972472 -0.4741055 2.0005400 -0.773002252
## X385 0.8245970 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.295208832
## X386 0.2462845 1.7123815 -0.3972472 -0.4741055 0.4606666 1.231421076
## X387 0.8245970 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.285439821
## X388 1.4029096 1.7123815 0.3168966 0.2049221 0.4606666 1.712766865
## X389 0.8245970 3.7607774 -0.3972472 -0.4741055 0.4606666 0.581337835
## X390 0.2462845 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.705507271
## X391 1.4029096 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.738530094
## X392 0.8245970 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.689521618
## X393 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.834280591
## X394 -0.9103405 -0.3360145 0.3168966 0.2049221 0.4606666 -0.760568966
## X395 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 0.364643421
## X396 -0.9103405 -0.3360145 0.3168966 0.2049221 -1.0792067 -0.662878862
## X397 -0.3320280 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.332508690
## X398 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.242811412
## X399 -0.9103405 -0.3360145 -0.3972472 0.2049221 -0.3092700 -0.693962077
## X400 0.2462845 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.066969224
## X401 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 1.123073869
## X402 0.8245970 -0.3360145 -0.3972472 -0.4741055 -0.3092700 2.164805621
## X403 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 0.380629074
## X404 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.749023772
## X405 0.2462845 -0.3360145 1.0310404 0.8839497 -0.3092700 -0.371584732
## X406 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.124695194
## X407 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.087395336
## X408 -0.9103405 -0.3360145 0.3168966 0.2049221 -1.0792067 -0.662878862
## X409 0.8245970 -0.3360145 -0.3972472 -0.4741055 1.2306033 0.367307696
## X410 1.4029096 3.7607774 1.7451841 1.5629772 0.4606666 2.036032302
## X411 2.5595346 -0.3360145 -0.3972472 -0.4741055 2.0005400 1.679019374
## X412 0.2462845 1.7123815 -0.3972472 -0.4741055 0.4606666 1.180799840
## X413 -0.9103405 1.7123815 -0.3972472 -0.4741055 0.4606666 0.068908831
## X414 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 0.577785467
## X415 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.821847305
## X416 -0.9103405 -0.3360145 -0.3972472 0.2049221 -0.3092700 -0.693962077
## X417 0.2462845 1.7123815 -0.3972472 -0.4741055 0.4606666 1.178135565
## X418 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 0.280274694
## X419 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.294320740
## X420 -0.9103405 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.646005116
## X421 0.2462845 -0.3360145 -0.3972472 -0.4741055 -0.3092700 0.604428223
## X422 0.8245970 -0.3360145 1.7451841 1.5629772 -0.3092700 -0.005690885
## X423 1.9812221 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.815794086
## X424 0.8245970 -0.3360145 -0.3972472 -0.4741055 1.2306033 0.407271830
## X425 1.9812221 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.792703697
## X426 0.2462845 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.711723914
## X427 -0.9103405 -0.3360145 1.7451841 3.6000599 -1.0792067 -0.192190176
## X428 -0.9103405 -0.3360145 1.0310404 0.8839497 -0.3092700 -0.612257626
## X429 -0.9103405 -0.3360145 -0.3972472 -0.4741055 0.4606666 -0.828952040
## X430 -0.3320280 -0.3360145 -0.3972472 0.2049221 -0.3092700 -0.087395336
## X431 -0.9103405 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.717052465
## X432 0.2462845 -0.3360145 1.7451841 1.5629772 -0.3092700 -0.028781274
## X433 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -0.3092700 -0.799645008
## X434 -0.3320280 -0.3360145 -0.3972472 0.2049221 0.4606666 0.516507129
## X435 -0.3320280 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.749023772
## X436 -0.9103405 -0.3360145 -0.3972472 0.2049221 -0.3092700 -0.717052465
## X437 6.6077223 -0.3360145 -0.3972472 -0.4741055 2.0005400 3.944541710
## X438 1.9812221 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.815794086
## X439 -0.9103405 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.799645008
## X440 -0.9103405 -0.3360145 1.0310404 0.8839497 -0.3092700 -0.612257626
## X441 0.8245970 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.676200240
## X442 0.8245970 -0.3360145 -0.3972472 -0.4741055 2.7704767 0.270505683
## X443 0.8245970 1.7123815 0.3168966 0.2049221 0.4606666 1.984522974
## X444 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 0.542261793
## X445 -0.3320280 1.7123815 -0.3972472 -0.4741055 -1.0792067 -0.646005116
## X446 0.2462845 -0.3360145 0.3168966 0.2049221 -0.3092700 -0.129135654
## X447 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.698402536
## X448 -0.3320280 1.7123815 -0.3972472 -0.4741055 -0.3092700 -0.661990770
## X449 0.8245970 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.689521618
## X450 -0.9103405 -0.3360145 -0.3972472 2.2420048 -0.3092700 0.205674978
## X451 0.2462845 -0.3360145 -0.3972472 -0.4741055 -1.0792067 -0.227713850
## X452 2.5595346 -0.3360145 -0.3972472 -0.4741055 1.2306033 1.724312059
## X453 1.4029096 -0.3360145 -0.3972472 -0.4741055 1.2306033 -0.633571830
## X454 3.7161597 -0.3360145 -0.3972472 -0.4741055 2.0005400 0.234093917
## SurfaceArea1 SurfaceArea2
## X1 -0.302617991 -0.379138448
## X2 0.445784255 1.054350614
## X3 0.023833878 -0.076964725
## X4 -1.033167401 -1.055357076
## X5 0.495375467 0.359508432
## X6 -0.457625954 0.141009550
## X7 0.187343191 0.074384441
## X8 -0.287882317 -0.365498662
## X9 1.080835157 0.901427627
## X10 0.132367790 0.023497546
## X11 0.418013175 0.287899555
## X12 0.023833878 -0.076964725
## X13 -1.033167401 -1.055357076
## X14 -1.033167401 -1.055357076
## X15 -1.033167401 -1.055357076
## X16 0.285392103 0.165141479
## X17 1.359112705 1.378820142
## X18 -0.136558273 0.515316758
## X19 0.023833878 -0.076964725
## X20 -1.033167401 -1.055357076
## X21 0.285392103 0.165141479
## X22 -0.849538224 -0.885384357
## X23 -0.196067728 -0.280512302
## X24 0.799723825 0.641222476
## X25 0.798306933 2.622401413
## X26 1.099821507 1.138812367
## X27 -0.540089056 0.141796461
## X28 0.069457794 -0.034733848
## X29 0.053021849 -0.049947456
## X30 -0.359010285 -0.431336861
## X31 -1.033167401 -1.055357076
## X32 -1.033167401 -1.055357076
## X33 -1.033167401 -1.055357076
## X34 -1.033167401 -1.055357076
## X35 0.084476847 -0.020831759
## X36 -1.033167401 -1.055357076
## X37 -1.033167401 -1.055357076
## X38 1.743657139 1.514955700
## X39 0.113381439 0.005923206
## X40 0.364738044 0.238586482
## X41 1.826120241 1.591286041
## X42 0.053021849 -0.049947456
## X43 -1.033167401 -1.055357076
## X44 -0.709832693 -0.015323383
## X45 0.744465045 0.590073278
## X46 -0.409735011 -0.478289201
## X47 -1.033167401 -1.055357076
## X48 -0.332656097 -0.406942628
## X49 -0.198334755 -0.282610731
## X50 0.023833878 -0.076964725
## X51 -1.033167401 -1.055357076
## X52 -1.033167401 -1.055357076
## X53 -1.033167401 -1.055357076
## X54 0.744465045 0.590073278
## X55 -1.033167401 -1.055357076
## X56 0.023833878 -0.076964725
## X57 0.449468173 0.317015252
## X58 -0.682911749 0.110582335
## X59 0.980519218 0.808572160
## X60 0.908824493 0.742209354
## X61 0.023833878 -0.076964725
## X62 -0.287882317 -0.365498662
## X63 -1.033167401 -1.055357076
## X64 -1.033167401 -1.055357076
## X65 0.457402767 0.324359752
## X66 -0.459892981 -0.524716935
## X67 0.035452391 0.674535031
## X68 1.826120241 1.591286041
## X69 -1.033167401 -1.055357076
## X70 -0.801647282 -0.100309743
## X71 -1.033167401 -1.055357076
## X72 -1.033167401 -1.055357076
## X73 -0.771609176 -0.813250873
## X74 -0.849538224 2.125336130
## X75 -1.033167401 -1.055357076
## X76 1.826120241 1.591286041
## X77 -1.033167401 -1.055357076
## X78 0.441533579 0.309670752
## X79 -1.033167401 -1.055357076
## X80 0.285392103 0.165141479
## X81 0.679571401 0.530005758
## X82 -0.585712972 -0.641179724
## X83 -0.801647282 -0.100309743
## X84 0.758917341 0.603450761
## X85 -1.033167401 -1.055357076
## X86 -1.033167401 -1.055357076
## X87 -1.033167401 -1.055357076
## X88 0.507560737 0.370787486
## X89 2.186010757 2.144221987
## X90 -0.549440542 1.640599114
## X91 2.568288163 2.278259116
## X92 -0.295816911 -0.372843162
## X93 -1.033167401 -1.055357076
## X94 -0.026324091 -0.123392458
## X95 -0.065713683 -0.159852656
## X96 1.596017014 1.378295535
## X97 -1.033167401 -1.055357076
## X98 -1.033167401 -1.055357076
## X99 -0.065713683 -0.159852656
## X100 -1.033167401 -1.055357076
## X101 -1.033167401 -1.055357076
## X102 -0.801647282 -0.100309743
## X103 0.023833878 -0.076964725
## X104 -0.302617991 -0.379138448
## X105 0.026100905 0.588761760
## X106 -0.459892981 0.138911121
## X107 -0.240841509 -0.321956268
## X108 1.826120241 1.591286041
## X109 0.013065500 3.438427849
## X110 0.908824493 0.742209354
## X111 0.457402767 0.324359752
## X112 -1.033167401 -1.055357076
## X113 0.023833878 -0.076964725
## X114 0.589457083 0.446593220
## X115 -1.033167401 -1.055357076
## X116 0.616094648 0.471249757
## X117 -0.459892981 -0.524716935
## X118 -1.033167401 -1.055357076
## X119 -1.033167401 -1.055357076
## X120 -0.295816911 -0.372843162
## X121 -0.678094317 -0.726690691
## X122 -1.033167401 -1.055357076
## X123 0.597108298 2.216355472
## X124 -1.033167401 -1.055357076
## X125 -1.033167401 -1.055357076
## X126 -1.033167401 -1.055357076
## X127 -1.033167401 -1.055357076
## X128 -1.033167401 -1.055357076
## X129 -1.033167401 -1.055357076
## X130 -1.033167401 -1.055357076
## X131 -1.033167401 -1.055357076
## X132 -1.033167401 -1.055357076
## X133 -1.033167401 -1.055357076
## X134 -1.033167401 -1.055357076
## X135 -1.033167401 -1.055357076
## X136 -1.033167401 -1.055357076
## X137 -1.033167401 -1.055357076
## X138 0.063223470 -0.040504527
## X139 -1.033167401 -1.055357076
## X140 -0.585712972 -0.641179724
## X141 -1.033167401 -1.055357076
## X142 -1.033167401 -1.055357076
## X143 -1.033167401 -1.055357076
## X144 -1.033167401 -1.055357076
## X145 -1.033167401 -1.055357076
## X146 -1.033167401 -1.055357076
## X147 -1.033167401 -1.055357076
## X148 -1.033167401 -1.055357076
## X149 -1.033167401 -1.055357076
## X150 -1.033167401 -1.055357076
## X151 -1.033167401 -1.055357076
## X152 -0.162912460 -0.249822784
## X153 -1.033167401 -1.055357076
## X154 -1.033167401 -1.055357076
## X155 -1.033167401 -1.055357076
## X156 -1.033167401 -1.055357076
## X157 -1.033167401 -1.055357076
## X158 -1.033167401 -1.055357076
## X159 -1.033167401 -1.055357076
## X160 -0.771609176 -0.813250873
## X161 -1.033167401 -1.055357076
## X162 0.023833878 -0.076964725
## X163 -1.033167401 -1.055357076
## X164 1.736572680 1.508398110
## X165 -1.033167401 -1.055357076
## X166 -1.033167401 -1.055357076
## X167 -1.033167401 -1.055357076
## X168 0.744465045 1.253701335
## X169 -0.510050950 1.855163443
## X170 0.850165173 0.687912513
## X171 2.571405325 2.281144456
## X172 -1.033167401 -1.055357076
## X173 1.789281054 1.776996976
## X174 0.730012749 0.576695796
## X175 -1.033167401 -1.055357076
## X176 -0.801647282 -0.100309743
## X177 0.679571401 1.193633815
## X178 -0.459892981 -0.524716935
## X179 1.170382718 0.984315558
## X180 0.113381439 0.005923206
## X181 -0.801647282 -0.100309743
## X182 1.603951608 1.385640035
## X183 -1.033167401 -0.314611768
## X184 0.270656429 0.151501693
## X185 0.113381439 0.005923206
## X186 0.115648466 0.008021635
## X187 -1.033167401 -1.055357076
## X188 -0.941352813 -0.970370717
## X189 -0.709832693 -0.015323383
## X190 -0.248492725 1.433641590
## X191 1.826120241 1.591286041
## X192 0.188193326 0.075171351
## X193 -1.033167401 -1.055357076
## X194 0.023833878 -0.076964725
## X195 -1.033167401 -1.055357076
## X196 0.195844542 0.082253548
## X197 0.116781980 1.108122848
## X198 -0.457625954 0.141009550
## X199 -1.033167401 -1.055357076
## X200 -1.033167401 -1.055357076
## X201 -1.033167401 -1.055357076
## X202 0.023833878 -0.076964725
## X203 -0.026324091 -0.123392458
## X204 0.607593298 1.562432648
## X205 -0.459892981 -0.524716935
## X206 0.315146831 0.192683355
## X207 -0.510050950 1.855163443
## X208 -1.033167401 -1.055357076
## X209 -1.033167401 -1.055357076
## X210 -1.033167401 -1.055357076
## X211 -1.033167401 -1.055357076
## X212 -0.678094317 -0.726690691
## X213 -1.033167401 -1.055357076
## X214 -0.026324091 -0.123392458
## X215 -1.033167401 -1.055357076
## X216 -1.033167401 -1.055357076
## X217 -1.033167401 -1.055357076
## X218 1.955057394 1.967953982
## X219 0.023833878 -0.076964725
## X220 -1.033167401 -1.055357076
## X221 -0.459892981 -0.524716935
## X222 -1.033167401 -1.055357076
## X223 -1.033167401 -1.055357076
## X224 -1.033167401 -1.055357076
## X225 -1.033167401 -1.055357076
## X226 -1.033167401 -1.055357076
## X227 -1.033167401 -1.055357076
## X228 -1.033167401 -1.055357076
## X229 -1.033167401 -1.055357076
## X230 -1.033167401 -1.055357076
## X231 -1.033167401 -1.055357076
## X232 -1.033167401 -1.055357076
## X233 0.616094648 0.471249757
## X234 0.023833878 -0.076964725
## X235 -1.033167401 -1.055357076
## X236 0.116781980 1.108122848
## X237 -1.033167401 -1.055357076
## X238 -1.033167401 -1.055357076
## X239 0.285392103 0.165141479
## X240 4.113550354 3.708600536
## X241 -1.033167401 -1.055357076
## X242 -1.033167401 -1.055357076
## X243 -0.094618276 -0.186607621
## X244 2.004648607 1.976347696
## X245 0.285392103 0.165141479
## X246 0.053021849 -0.049947456
## X247 2.004648607 1.976347696
## X248 -0.549440542 -0.607604866
## X249 -1.033167401 -1.055357076
## X250 0.023833878 -0.076964725
## X251 -1.033167401 -0.314611768
## X252 -0.250192995 -0.330612286
## X253 -1.033167401 -1.055357076
## X254 0.532214654 0.393607897
## X255 0.647266268 1.240848459
## X256 0.449468173 0.317015252
## X257 0.187909948 0.074909048
## X258 -1.033167401 -1.055357076
## X259 -1.033167401 -1.055357076
## X260 0.023833878 -0.076964725
## X261 0.850731929 0.908247520
## X262 -1.033167401 -1.055357076
## X263 -1.033167401 -1.055357076
## X264 -0.302617991 -0.379138448
## X265 -1.033167401 -1.055357076
## X266 -1.033167401 -1.055357076
## X267 0.441533579 0.309670752
## X268 -0.287882317 -0.365498662
## X269 0.065490497 -0.038406098
## X270 0.285392103 0.165141479
## X271 0.023833878 -0.076964725
## X272 -0.196067728 -0.280512302
## X273 -1.033167401 -1.055357076
## X274 0.850731929 0.688437121
## X275 0.023833878 -0.076964725
## X276 1.126459073 0.943658503
## X277 0.258754538 0.140484943
## X278 0.510111142 1.214880405
## X279 -0.667892696 -0.717247762
## X280 -0.459892981 -0.524716935
## X281 -1.033167401 -1.055357076
## X282 0.586056542 0.443445577
## X283 -1.033167401 -1.055357076
## X284 0.297010616 0.175895926
## X285 -0.208536376 -0.292053660
## X286 1.743090382 1.734241492
## X287 1.956757664 1.712207992
## X288 1.334458788 1.136189331
## X289 4.113550354 3.708600536
## X290 0.692890184 0.542334027
## X291 -1.033167401 -1.055357076
## X292 1.750174841 1.740799082
## X293 0.113381439 0.005923206
## X294 -0.771609176 -0.813250873
## X295 0.969467462 0.798342320
## X296 2.266206832 2.218453900
## X297 -0.287882317 -0.365498662
## X298 -0.208536376 -0.292053660
## X299 1.099821507 0.919001967
## X300 -0.459892981 -0.524716935
## X301 -0.941352813 -0.970370717
## X302 0.364738044 0.238586482
## X303 0.744465045 1.253701335
## X304 2.330250342 2.497544909
## X305 1.099821507 1.138812367
## X306 -1.033167401 -1.055357076
## X307 -0.002803688 -0.101621261
## X308 2.689290722 2.390262745
## X309 -0.002803688 -0.101621261
## X310 1.564562016 1.349179838
## X311 -1.033167401 -1.055357076
## X312 4.113550354 3.708600536
## X313 -0.941352813 -0.970370717
## X314 -1.033167401 -1.055357076
## X315 -0.771609176 -0.813250873
## X316 -1.033167401 -1.055357076
## X317 -1.033167401 -1.055357076
## X318 1.111723398 0.930018717
## X319 0.053021849 0.613680600
## X320 1.418622161 1.214093494
## X321 0.285392103 0.165141479
## X322 0.882186927 0.717552818
## X323 -0.667892696 1.041235435
## X324 -1.033167401 -1.055357076
## X325 -1.033167401 -1.055357076
## X326 -1.033167401 -1.055357076
## X327 -1.033167401 -1.055357076
## X328 0.023833878 -0.076964725
## X329 -1.033167401 -1.055357076
## X330 -0.295816911 -0.372843162
## X331 1.099821507 1.138812367
## X332 -0.208536376 -0.292053660
## X333 -0.196067728 -0.280512302
## X334 0.449468173 0.317015252
## X335 0.790372339 0.632566458
## X336 -1.033167401 -1.055357076
## X337 2.004648607 1.976347696
## X338 0.053021849 -0.049947456
## X339 0.163822787 0.052613244
## X340 0.597108298 0.453675417
## X341 -0.549440542 -0.607604866
## X342 -1.033167401 -1.055357076
## X343 -0.104253140 -0.195525943
## X344 0.597108298 1.552727415
## X345 -0.667892696 -0.717247762
## X346 0.616094648 1.312981944
## X347 1.743657139 1.514955700
## X348 0.258754538 0.140484943
## X349 -1.033167401 -1.055357076
## X350 0.410361960 0.280817358
## X351 -0.287882317 -0.365498662
## X352 -0.941352813 0.534989527
## X353 1.099821507 1.138812367
## X354 -0.679794587 -0.728264513
## X355 0.023833878 -0.076964725
## X356 -1.033167401 -1.055357076
## X357 0.718960993 0.786276356
## X358 0.023833878 -0.076964725
## X359 0.616094648 1.312981944
## X360 0.418013175 0.287899555
## X361 -0.287882317 -0.365498662
## X362 -1.033167401 -1.055357076
## X363 1.743090382 1.734241492
## X364 -1.033167401 -1.055357076
## X365 0.144836437 0.035038904
## X366 -1.033167401 -1.055357076
## X367 -1.033167401 -1.055357076
## X368 -1.033167401 -1.055357076
## X369 -0.196067728 -0.280512302
## X370 2.320898856 2.488888891
## X371 -1.033167401 -1.055357076
## X372 0.364738044 0.238586482
## X373 -1.033167401 -1.055357076
## X374 0.714993696 0.562793706
## X375 0.582372624 0.440035631
## X376 1.654109577 1.432067769
## X377 1.170382718 0.984315558
## X378 -0.600448647 -0.654819510
## X379 -1.033167401 -1.055357076
## X380 -1.033167401 -1.055357076
## X381 0.285392103 0.165141479
## X382 1.191636095 1.223798726
## X383 2.227383997 1.962707910
## X384 -0.065713683 -0.159852656
## X385 0.507560737 0.370787486
## X386 1.743090382 1.734241492
## X387 0.691189913 0.540760205
## X388 2.069542251 2.036415216
## X389 1.298469737 2.063432485
## X390 0.117915493 0.010120064
## X391 1.170382718 0.984315558
## X392 0.065490497 -0.038406098
## X393 -1.033167401 -1.055357076
## X394 -1.033167401 -1.055357076
## X395 0.449468173 0.317015252
## X396 -1.033167401 -1.055357076
## X397 -0.459892981 -0.524716935
## X398 -0.459892981 -0.524716935
## X399 -1.033167401 -1.055357076
## X400 0.144836437 0.035038904
## X401 0.151637518 0.041334190
## X402 1.334458788 1.136189331
## X403 0.113381439 0.005923206
## X404 -0.549440542 -0.607604866
## X405 0.117915493 0.010120064
## X406 0.023833878 -0.076964725
## X407 0.381740745 0.254324696
## X408 -1.033167401 -1.055357076
## X409 1.099821507 0.919001967
## X410 2.320898856 2.488888891
## X411 2.005215364 1.757061904
## X412 1.377815677 1.396132178
## X413 0.510111142 1.214880405
## X414 -0.295816911 -0.372843162
## X415 -1.033167401 -1.055357076
## X416 -1.033167401 -1.055357076
## X417 1.743090382 1.734241492
## X418 0.113381439 0.005923206
## X419 0.023833878 -0.076964725
## X420 -0.591097161 -0.646163492
## X421 0.364738044 0.238586482
## X422 0.285392103 0.165141479
## X423 1.654109577 1.432067769
## X424 1.810534431 1.576859345
## X425 1.654109577 1.432067769
## X426 -0.065713683 -0.159852656
## X427 -1.033167401 -1.055357076
## X428 -1.033167401 -1.055357076
## X429 -1.033167401 -1.055357076
## X430 -0.208536376 -0.292053660
## X431 -1.033167401 -1.055357076
## X432 0.023833878 -0.076964725
## X433 -1.033167401 -1.055357076
## X434 0.692890184 0.542334027
## X435 -0.549440542 -0.607604866
## X436 -1.033167401 -1.055357076
## X437 5.512589313 5.003593308
## X438 1.654109577 1.432067769
## X439 -1.033167401 -1.055357076
## X440 -1.033167401 -1.055357076
## X441 0.601642352 0.457872274
## X442 0.466754253 0.333015770
## X443 1.837171997 1.821326281
## X444 0.449468173 0.317015252
## X445 -0.457625954 0.141009550
## X446 0.053021849 -0.049947456
## X447 -0.287882317 -0.365498662
## X448 -0.457625954 0.141009550
## X449 0.065490497 -0.038406098
## X450 -0.585712972 -0.641179724
## X451 0.023833878 -0.076964725
## X452 2.005215364 1.757061904
## X453 0.456836011 0.323835145
## X454 2.570838568 2.280619849
## [ reached 'max' / getOption("max.print") -- omitted 497 rows ]
##
## $yData
## [1] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [16] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [31] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [46] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [61] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [76] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [91] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [106] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [121] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [136] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [151] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [166] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [181] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [196] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [211] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [226] Low Low Low Low Low Low Low Low Low Low Low Low Low Mid Mid
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## [271] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [286] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [301] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [316] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [331] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [346] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [361] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [376] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [391] Low Low Low Low Low Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [406] Mid Mid Mid Mid Mid Mid Mid Mid Low Low Low Low Low Low Low
## [421] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [436] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [451] Low Low Low Low Low Low Low Low Low Low Low Low Low Low Low
## [466] Low Low Low Low Low Low Low Low Low Low Low High High Mid Mid
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## [496] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [511] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [526] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [541] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [556] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [571] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [586] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [601] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [616] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [631] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid High High Mid Mid Mid
## [646] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [661] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [676] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [691] Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid Mid
## [706] Mid Mid Mid Mid Mid Mid Mid Mid Mid High High High High High High
## [721] High High High High High High High High High High High High High High High
## [736] High High High High High High High High High High High High High High High
## [751] High High High High High High High High High High High High High High High
## [766] High High High High High High High High High High High High High High High
## [781] High High High High High High High High High High High High High High High
## [796] High High High High High High High High High High High High High High High
## [811] High High High High High High High High High High High High High High High
## [826] High High High High High High High High High High High High High High High
## [841] High High High High High High High High High High High High High High High
## [856] High High High High High High High High High High High High High High High
## [871] High High High High High High High High High High High High High High High
## [886] High High High High High High High High High High High High High High High
## [901] High High High High High High High High High High High High High High High
## [916] High High High High High High High High High High High High High High High
## [931] High High High High High High High High High High High High High High High
## [946] High High High High High High
## Levels: Low Mid High
##
## $xNames
## [1] "FP001" "FP002" "FP003"
## [4] "FP004" "FP005" "FP006"
## [7] "FP007" "FP008" "FP009"
## [10] "FP010" "FP011" "FP012"
## [13] "FP013" "FP014" "FP015"
## [16] "FP016" "FP017" "FP018"
## [19] "FP019" "FP020" "FP021"
## [22] "FP022" "FP023" "FP024"
## [25] "FP025" "FP026" "FP027"
## [28] "FP028" "FP029" "FP030"
## [31] "FP031" "FP032" "FP033"
## [34] "FP034" "FP035" "FP036"
## [37] "FP037" "FP038" "FP039"
## [40] "FP040" "FP041" "FP042"
## [43] "FP043" "FP044" "FP045"
## [46] "FP046" "FP047" "FP048"
## [49] "FP049" "FP050" "FP051"
## [52] "FP052" "FP053" "FP054"
## [55] "FP055" "FP056" "FP057"
## [58] "FP058" "FP059" "FP060"
## [61] "FP061" "FP062" "FP063"
## [64] "FP064" "FP065" "FP066"
## [67] "FP067" "FP068" "FP069"
## [70] "FP070" "FP071" "FP072"
## [73] "FP073" "FP074" "FP075"
## [76] "FP076" "FP077" "FP078"
## [79] "FP079" "FP080" "FP081"
## [82] "FP082" "FP083" "FP084"
## [85] "FP085" "FP086" "FP087"
## [88] "FP088" "FP089" "FP090"
## [91] "FP091" "FP092" "FP093"
## [94] "FP094" "FP095" "FP096"
## [97] "FP097" "FP098" "FP099"
## [100] "FP100" "FP101" "FP102"
## [103] "FP103" "FP104" "FP105"
## [106] "FP106" "FP107" "FP108"
## [109] "FP109" "FP110" "FP111"
## [112] "FP112" "FP113" "FP114"
## [115] "FP115" "FP116" "FP117"
## [118] "FP118" "FP119" "FP120"
## [121] "FP121" "FP122" "FP123"
## [124] "FP124" "FP125" "FP126"
## [127] "FP127" "FP128" "FP129"
## [130] "FP130" "FP131" "FP132"
## [133] "FP133" "FP134" "FP135"
## [136] "FP136" "FP137" "FP138"
## [139] "FP139" "FP140" "FP141"
## [142] "FP142" "FP143" "FP144"
## [145] "FP145" "FP146" "FP147"
## [148] "FP148" "FP149" "FP150"
## [151] "FP151" "FP152" "FP153"
## [154] "FP155" "FP156" "FP157"
## [157] "FP158" "FP159" "FP160"
## [160] "FP161" "FP162" "FP163"
## [163] "FP164" "FP165" "FP166"
## [166] "FP167" "FP168" "FP169"
## [169] "FP170" "FP171" "FP172"
## [172] "FP173" "FP174" "FP175"
## [175] "FP176" "FP177" "FP178"
## [178] "FP179" "FP180" "FP181"
## [181] "FP182" "FP183" "FP184"
## [184] "FP185" "FP186" "FP187"
## [187] "FP188" "FP189" "FP190"
## [190] "FP191" "FP192" "FP193"
## [193] "FP194" "FP195" "FP196"
## [196] "FP197" "FP198" "FP201"
## [199] "FP202" "FP203" "FP204"
## [202] "FP205" "FP206" "FP207"
## [205] "FP208" "MolWeight" "NumBonds"
## [208] "NumMultBonds" "NumRotBonds" "NumDblBonds"
## [211] "NumCarbon" "NumNitrogen" "NumOxygen"
## [214] "NumSulfer" "NumChlorine" "NumHalogen"
## [217] "NumRings" "HydrophilicFactor" "SurfaceArea1"
## [220] "SurfaceArea2"
##
## $problemType
## [1] "Classification"
##
## $tuneValue
## threshold
## 2 1
##
## $obsLevels
## [1] "Low" "Mid" "High"
## attr(,"ordered")
## [1] FALSE
##
## $param
## list()
##
## attr(,"class")
## [1] "pamrtrained"NSC_Tune$results## threshold logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 0 1.0053088 0.7986117 0.6383621 0.5918682 0.377933196 0.5705143
## 2 1 0.8852013 0.7986907 0.6435073 0.6045224 0.390689052 0.5629779
## 3 2 0.8572315 0.7867513 0.6204747 0.5855622 0.354489788 0.5226695
## 4 3 0.8440090 0.7831023 0.6072123 0.5772620 0.331334495 0.4932871
## 5 4 0.8836407 0.7798191 0.5959490 0.5815176 0.320109872 0.4547332
## 6 5 0.9439966 0.7682432 0.5830754 0.5393650 0.211538787 NaN
## 7 6 0.9879275 0.7701367 0.5881594 0.4710398 0.048665101 NaN
## 8 7 1.0214083 0.7734845 0.5897285 0.4500637 0.002282919 NaN
## 9 8 1.0464494 0.7756318 0.5918340 0.4489999 0.000000000 NaN
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.5802349 0.7979792 0.5740786 0.7964560
## 2 0.5835158 0.8016081 0.5677051 0.8084817
## 3 0.5582769 0.7882126 0.5367218 0.8032933
## 4 0.5417570 0.7782304 0.4902777 0.8054533
## 5 0.5339216 0.7706006 0.4265496 0.8183140
## 6 0.4605736 0.7316940 NaN 0.8164331
## 7 0.3623889 0.6806491 NaN 0.8229237
## 8 0.3347222 0.6673077 NaN 0.8182719
## 9 0.3333333 0.6666667 NaN NaN
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.5740786 0.5802349 0.1972894 0.6891071
## 2 0.5677051 0.5835158 0.2015075 0.6925619
## 3 0.5367218 0.5582769 0.1951874 0.6732448
## 4 0.4902777 0.5417570 0.1924207 0.6599937
## 5 0.4265496 0.5339216 0.1938392 0.6522611
## 6 NaN 0.4605736 0.1797883 0.5961338
## 7 NaN 0.3623889 0.1570133 0.5215190
## 8 NaN 0.3347222 0.1500212 0.5010150
## 9 NaN 0.3333333 0.1496666 0.5000000
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 0.207410713 0.04290616 0.04831082 0.062898945 0.091107862 0.06225442
## 2 0.160335415 0.04468868 0.04816844 0.064720949 0.093096077 0.06389466
## 3 0.118359061 0.04923520 0.05411279 0.047645975 0.070128289 0.05208052
## 4 0.078031415 0.05194093 0.06036538 0.052120079 0.076003967 0.05758974
## 5 0.041695972 0.05181450 0.06214396 0.045984727 0.068208081 NA
## 6 0.019107473 0.04162677 0.05106245 0.015787366 0.026066562 NA
## 7 0.009566838 0.03703778 0.03915760 0.016053493 0.033424310 NA
## 8 0.004578527 0.03677434 0.03719562 0.004328825 0.007219223 NA
## 9 0.001852537 0.03673222 0.03689563 0.003549913 0.000000000 NA
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.060730826 0.029931070 0.06030153
## 2 0.062306543 0.030007758 0.06403451
## 3 0.047085461 0.022639261 0.06377230
## 4 0.050369597 0.023883501 0.09473380
## 5 0.044777490 0.021528870 0.10469447
## 6 0.016122287 0.008886446 NA
## 7 0.020138495 0.009648278 NA
## 8 0.004392052 0.002027101 NA
## 9 0.000000000 0.000000000 NA
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.031847546 0.06030153 0.060730826 0.020966315
## 2 0.033986775 0.06403451 0.062306543 0.021573650
## 3 0.026874143 0.06377230 0.047085461 0.015881992
## 4 0.031500874 0.09473380 0.050369597 0.017373360
## 5 0.034130618 0.10469447 0.044777490 0.015328242
## 6 0.025491242 NA 0.016122287 0.005262455
## 7 0.003801667 NA 0.020138495 0.005351164
## 8 NA NA 0.004392052 0.001442942
## 9 NA NA 0.000000000 0.001183304
## Mean_Balanced_AccuracySD
## 1 0.045195187
## 2 0.046063039
## 3 0.034689195
## 4 0.036866243
## 5 0.032857538
## 6 0.012108669
## 7 0.014867820
## 8 0.003209577
## 9 0.000000000(NSC_Train_Accuracy <- NSC_Tune$results[NSC_Tune$results$threshold==NSC_Tune$bestTune$threshold,
c("Accuracy")])## [1] 0.6045224##################################
# Identifying and plotting the
# best model predictors
##################################
NSC_VarImp <- varImp(NSC_Tune, scale = TRUE)
plot(NSC_VarImp,
top=25,
scales=list(y=list(cex = .95)),
main="Ranked Variable Importance : Nearest Shrunken Centroids",
xlab="Scaled Variable Importance Metrics",
ylab="Predictors",
cex=2,
origin=0,
alpha=0.45)
##################################
# Independently evaluating the model
# on the test set
##################################
NSC_Test <- data.frame(NSC_Observed = PMA_PreModelling_Test_NSC$Log_Solubility_Class,
NSC_Predicted = predict(NSC_Tune,
PMA_PreModelling_Test_NSC[,!names(PMA_PreModelling_Test_NSC) %in% c("Log_Solubility_Class")],
type = "raw"))
NSC_Test## NSC_Observed NSC_Predicted
## 1 High High
## 2 High High
## 3 High Mid
## 4 High High
## 5 High Mid
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High Mid
## 11 High Mid
## 12 High Low
## 13 High High
## 14 High High
## 15 High Mid
## 16 High Mid
## 17 High High
## 18 High High
## 19 High High
## 20 High Mid
## 21 High High
## 22 High High
## 23 High High
## 24 High Mid
## 25 High High
## 26 High Mid
## 27 High High
## 28 High High
## 29 High Low
## 30 High High
## 31 High Low
## 32 High High
## 33 High High
## 34 High Mid
## 35 High Mid
## 36 High High
## 37 High High
## 38 High High
## 39 High Mid
## 40 High High
## 41 High High
## 42 High Low
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High High
## 50 High Mid
## 51 High High
## 52 High High
## 53 High Mid
## 54 High High
## 55 High High
## 56 High Mid
## 57 High High
## 58 Mid High
## 59 Mid Mid
## 60 Mid Low
## 61 Mid High
## 62 Mid High
## 63 Mid High
## 64 Mid High
## 65 Mid Mid
## 66 Mid Low
## 67 Mid Mid
## 68 Mid Low
## 69 Mid Mid
## 70 Mid Low
## 71 Mid High
## 72 Mid Mid
## 73 Mid High
## 74 Mid Low
## 75 Mid Mid
## 76 Mid High
## 77 Mid Mid
## 78 Mid High
## 79 Mid Mid
## 80 Mid Mid
## 81 Mid Mid
## 82 Mid High
## 83 Mid High
## 84 Mid High
## 85 Mid Mid
## 86 Mid High
## 87 Mid Low
## 88 Mid Low
## 89 Mid High
## 90 Mid High
## 91 Mid Mid
## 92 Mid Mid
## 93 Mid Low
## 94 Mid Mid
## 95 Mid Mid
## 96 Mid Mid
## 97 Mid Mid
## 98 Mid Mid
## 99 Mid Mid
## 100 Mid High
## 101 Mid High
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid Mid
## 105 Mid High
## 106 Mid High
## 107 Mid Low
## 108 Mid Low
## 109 Mid Mid
## 110 Mid Low
## 111 Mid Mid
## 112 Mid Low
## 113 Mid Mid
## 114 Mid Low
## 115 Mid Low
## 116 Mid Low
## 117 Mid Low
## 118 Mid High
## 119 Low Low
## 120 Low Low
## 121 Low Low
## 122 Low Mid
## 123 Low Low
## 124 Low High
## 125 Low Low
## 126 Low Mid
## 127 Low High
## 128 Low Mid
## 129 Low High
## 130 Low Low
## 131 Low Mid
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low High
## 136 Low Mid
## 137 Low Low
## 138 Low Mid
## 139 Low High
## 140 Low Low
## 141 Low Low
## 142 Low Low
## 143 Low Low
## 144 Low Low
## 145 Low Low
## 146 Low Low
## 147 Low Low
## 148 Low Low
## 149 Low High
## 150 Low Low
## 151 Low Low
## 152 Low Low
## 153 Low High
## 154 Low Mid
## 155 Low Low
## 156 Low Low
## 157 Low Low
## 158 Low Low
## 159 Low High
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Mid
## 164 Low Low
## 165 Low Low
## 166 Low Mid
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Mid
## 172 Low High
## 173 Low Low
## 174 Low High
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low High
## 181 Low Low
## 182 Low Low
## 183 Low Mid
## 184 Low High
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Low
## 226 High Mid
## 227 High High
## 228 High Mid
## 229 High High
## 230 High Mid
## 231 High High
## 232 High High
## 233 High High
## 234 High Mid
## 235 High High
## 236 High Mid
## 237 High Mid
## 238 Mid Mid
## 239 Mid Mid
## 240 Mid Mid
## 241 Mid High
## 242 Mid High
## 243 Mid High
## 244 Mid Low
## 245 Mid Low
## 246 Mid Mid
## 247 Mid High
## 248 Mid Mid
## 249 Mid High
## 250 Mid High
## 251 Mid Mid
## 252 Mid Mid
## 253 Mid Mid
## 254 Mid Low
## 255 Mid Mid
## 256 Mid Mid
## 257 Mid Mid
## 258 Mid Mid
## 259 Mid Low
## 260 Mid High
## 261 Mid High
## 262 Mid Mid
## 263 Mid High
## 264 Mid Low
## 265 Mid Low
## 266 Mid Low
## 267 Mid Mid
## 268 Mid High
## 269 Low Mid
## 270 Low Low
## 271 Low Mid
## 272 Low Low
## 273 Low Low
## 274 Low Low
## 275 Low Mid
## 276 Low Low
## 277 Low Low
## 278 Low Mid
## 279 Low Low
## 280 Low Mid
## 281 Low High
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low High
## 286 Low Low
## 287 Low High
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low High
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(NSC_Test_Accuracy <- Accuracy(y_pred = NSC_Test$NSC_Predicted,
y_true = NSC_Test$NSC_Observed))## [1] 0.63607591.5.7 Averaged Neural Network (AVNN)
Averaged Neural Networks implement fitting of the same neural network model using different random number seeds. All the resulting models are used for prediction by averaging the model scores and translating to predicted classes. Neural networks are comprised of node layers, containing an input layer, one or more hidden layers, and an output layer. Each node, or artificial neuron, connects to another and has an associated weight and threshold. If the output of any individual node is above the specified threshold value, that node is activated, sending data to the next layer of the network. Otherwise, no data is passed along to the next layer of the network.
[A] The averaged neural network model from the nnet package was implemented through the caret package.
[B] The model contains 3 hyperparameters:
[B.1] size = number of hidden units made to vary across a range of values equal to 1 to 13
[B.2] decay = weight decay made to vary across a range of values equal to 0.00 to 0.10
[B.3] bag = bagging held constant at a value of FALSE
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves size=5, decay=0 and bag=FALSE
[C.2] Accuracy = 0.67296
[D] The model does not allow for ranking of predictors in terms of variable importance.
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.65822
Code Chunk | Output
##################################
# Transforming factor predictors
# as required by the nature of the model
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_AVNN <- as.data.frame(lapply(PMA_PreModelling_Train[,!names(PMA_PreModelling_Train) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Train_AVNN$Log_Solubility_Class <- PMA_PreModelling_Train$Log_Solubility_Class
dim(PMA_PreModelling_Train_AVNN)## [1] 951 221PMA_PreModelling_Test_AVNN <- as.data.frame(lapply(PMA_PreModelling_Test[,!names(PMA_PreModelling_Test) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Test_AVNN$Log_Solubility_Class <- PMA_PreModelling_Test$Log_Solubility_Class
dim(PMA_PreModelling_Test_AVNN)## [1] 316 221##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_AVNN$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
AVNN_Grid = expand.grid(decay = c(0.00, 0.01, 0.10),
size = c(1, 5, 9, 13),
bag = FALSE)
maxSize <- max(AVNN_Grid$size)
##################################
# Running the averaged neural network model
# by setting the caret method to 'avNNet'
##################################
set.seed(12345678)
AVNN_Tune <- train(x = PMA_PreModelling_Train_AVNN[,!names(PMA_PreModelling_Train_AVNN) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_AVNN$Log_Solubility_Class,
method = "avNNet",
tuneGrid = AVNN_Grid,
metric = "Accuracy",
preProc = c("center", "scale"),
trControl = KFold_Control,
maxit = 5,
repeats = 10,
allowParallel = FALSE,
MaxNWts = 10*(maxSize * (length(PMA_PreModelling_Train_AVNN) + 1) + maxSize + 1),
trace = FALSE)
##################################
# Reporting the cross-validation results
# for the train set
##################################
AVNN_Tune## Model Averaged Neural Network
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## Pre-processing: centered (220), scaled (220)
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## decay size logLoss AUC prAUC Accuracy Kappa Mean_F1
## 0.00 1 0.8743301 0.7916644 0.6159023 0.6184602 0.3870841 NaN
## 0.00 5 0.7296976 0.8246721 0.6642682 0.6729680 0.4811186 0.5957249
## 0.00 9 0.7529018 0.8196216 0.6686448 0.6581196 0.4520066 0.5653505
## 0.00 13 0.7713276 0.8160298 0.6630645 0.6403240 0.4194198 0.5494161
## 0.01 1 0.8527143 0.7921062 0.6217329 0.6255424 0.3935409 0.4754874
## 0.01 5 0.7546137 0.8202957 0.6619866 0.6551059 0.4540184 0.5539830
## 0.01 9 0.7637712 0.8188823 0.6628303 0.6613331 0.4559582 0.5782255
## 0.01 13 0.7597509 0.8313850 0.6804986 0.6645472 0.4593961 0.5736998
## 0.10 1 0.8636663 0.7955220 0.6182132 0.5982479 0.3494394 0.5284185
## 0.10 5 0.7576092 0.8131087 0.6477432 0.6666739 0.4682212 0.5909508
## 0.10 9 0.7475943 0.8236217 0.6693355 0.6393055 0.4189232 0.5470570
## 0.10 13 0.7959497 0.8081472 0.6494537 0.6288116 0.3956828 0.5342739
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.5736665 0.7964324 0.4406714 0.8461139
## 0.6386059 0.8271879 0.6341100 0.8674043
## 0.6185619 0.8158697 0.6496467 0.8585254
## 0.5911098 0.8058184 0.6177253 0.8514954
## 0.5794171 0.7983556 0.6090909 0.8536804
## 0.6203362 0.8193767 0.6884385 0.8644528
## 0.6193824 0.8173641 0.5730730 0.8658935
## 0.6204659 0.8182370 0.6284561 0.8693794
## 0.5414457 0.7853702 0.6390245 0.8311334
## 0.6299002 0.8218824 0.6521677 0.8580581
## 0.5838415 0.8083322 0.6361331 0.8519042
## 0.5751526 0.7971639 0.5875691 0.8491083
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.4406714 0.5736665 0.2061534 0.6850495
## 0.6341100 0.6386059 0.2243227 0.7328969
## 0.6496467 0.6185619 0.2193732 0.7172158
## 0.6177253 0.5911098 0.2134413 0.6984641
## 0.6090909 0.5794171 0.2085141 0.6888864
## 0.6884385 0.6203362 0.2183686 0.7198564
## 0.5730730 0.6193824 0.2204444 0.7183733
## 0.6284561 0.6204659 0.2215157 0.7193514
## 0.6390245 0.5414457 0.1994160 0.6634079
## 0.6521677 0.6299002 0.2222246 0.7258913
## 0.6361331 0.5838415 0.2131018 0.6960868
## 0.5875691 0.5751526 0.2096039 0.6861582
##
## Tuning parameter 'bag' was held constant at a value of FALSE
## Accuracy was used to select the optimal model using the largest value.
## The final values used for the model were size = 5, decay = 0 and bag = FALSE.AVNN_Tune$finalModel## Model Averaged Neural Network with 10 Repeats
##
## a 220-5-3 network with 1123 weights
## options were -AVNN_Tune$results## decay size bag logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 0.00 1 FALSE 0.8743301 0.7916644 0.6159023 0.6184602 0.3870841 NaN
## 5 0.01 1 FALSE 0.8527143 0.7921062 0.6217329 0.6255424 0.3935409 0.4754874
## 9 0.10 1 FALSE 0.8636663 0.7955220 0.6182132 0.5982479 0.3494394 0.5284185
## 2 0.00 5 FALSE 0.7296976 0.8246721 0.6642682 0.6729680 0.4811186 0.5957249
## 6 0.01 5 FALSE 0.7546137 0.8202957 0.6619866 0.6551059 0.4540184 0.5539830
## 10 0.10 5 FALSE 0.7576092 0.8131087 0.6477432 0.6666739 0.4682212 0.5909508
## 3 0.00 9 FALSE 0.7529018 0.8196216 0.6686448 0.6581196 0.4520066 0.5653505
## 7 0.01 9 FALSE 0.7637712 0.8188823 0.6628303 0.6613331 0.4559582 0.5782255
## 11 0.10 9 FALSE 0.7475943 0.8236217 0.6693355 0.6393055 0.4189232 0.5470570
## 4 0.00 13 FALSE 0.7713276 0.8160298 0.6630645 0.6403240 0.4194198 0.5494161
## 8 0.01 13 FALSE 0.7597509 0.8313850 0.6804986 0.6645472 0.4593961 0.5736998
## 12 0.10 13 FALSE 0.7959497 0.8081472 0.6494537 0.6288116 0.3956828 0.5342739
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.5736665 0.7964324 0.4406714 0.8461139
## 5 0.5794171 0.7983556 0.6090909 0.8536804
## 9 0.5414457 0.7853702 0.6390245 0.8311334
## 2 0.6386059 0.8271879 0.6341100 0.8674043
## 6 0.6203362 0.8193767 0.6884385 0.8644528
## 10 0.6299002 0.8218824 0.6521677 0.8580581
## 3 0.6185619 0.8158697 0.6496467 0.8585254
## 7 0.6193824 0.8173641 0.5730730 0.8658935
## 11 0.5838415 0.8083322 0.6361331 0.8519042
## 4 0.5911098 0.8058184 0.6177253 0.8514954
## 8 0.6204659 0.8182370 0.6284561 0.8693794
## 12 0.5751526 0.7971639 0.5875691 0.8491083
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.4406714 0.5736665 0.2061534 0.6850495
## 5 0.6090909 0.5794171 0.2085141 0.6888864
## 9 0.6390245 0.5414457 0.1994160 0.6634079
## 2 0.6341100 0.6386059 0.2243227 0.7328969
## 6 0.6884385 0.6203362 0.2183686 0.7198564
## 10 0.6521677 0.6299002 0.2222246 0.7258913
## 3 0.6496467 0.6185619 0.2193732 0.7172158
## 7 0.5730730 0.6193824 0.2204444 0.7183733
## 11 0.6361331 0.5838415 0.2131018 0.6960868
## 4 0.6177253 0.5911098 0.2134413 0.6984641
## 8 0.6284561 0.6204659 0.2215157 0.7193514
## 12 0.5875691 0.5751526 0.2096039 0.6861582
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 0.06182060 0.03818877 0.05330993 0.04715826 0.08542407 NA
## 5 0.05796163 0.03523217 0.04786735 0.06254090 0.12554122 NA
## 9 0.04738598 0.03519045 0.04714663 0.06949372 0.12503326 0.07296465
## 2 0.05194405 0.02829588 0.04855106 0.04252893 0.06283645 0.05825960
## 6 0.05208844 0.02895720 0.03681862 0.03381334 0.04977224 0.03527784
## 10 0.04294212 0.02402278 0.03643602 0.03161813 0.04938901 0.03548599
## 3 0.04755711 0.02898232 0.03321211 0.03176787 0.04924431 0.05328903
## 7 0.05487524 0.03705808 0.05632455 0.02928235 0.04713396 0.04310652
## 11 0.04420828 0.02997049 0.04128367 0.04625483 0.07993394 0.06612313
## 4 0.06075696 0.03041349 0.04355976 0.04751680 0.07886839 0.05342062
## 8 0.05268121 0.02324128 0.04527397 0.02751443 0.04653444 0.03975306
## 12 0.05354993 0.02549944 0.03480287 0.04296635 0.07646580 0.05941717
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.06601282 0.02727416 0.01262238
## 5 0.08707831 0.04157705 NA
## 9 0.09291523 0.03917346 0.06879317
## 2 0.04243563 0.01901505 0.11646707
## 6 0.03246272 0.01592494 0.10715731
## 10 0.03271050 0.01646549 0.06796995
## 3 0.03406656 0.01544643 0.07992946
## 7 0.03109855 0.01602722 0.11369947
## 11 0.06397997 0.02540251 0.12982590
## 4 0.06168335 0.02325369 0.09749658
## 8 0.03455672 0.01565608 0.10240891
## 12 0.05171240 0.02565866 0.09043070
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.02634704 0.01262238 0.06601282 0.015719418
## 5 0.02880085 NA 0.08707831 0.020846966
## 9 0.03919715 0.06879317 0.09291523 0.023164574
## 2 0.02335260 0.11646707 0.04243563 0.014176309
## 6 0.02224323 0.10715731 0.03246272 0.011271115
## 10 0.02844367 0.06796995 0.03271050 0.010539376
## 3 0.01951320 0.07992946 0.03406656 0.010589289
## 7 0.01849106 0.11369947 0.03109855 0.009760783
## 11 0.02716153 0.12982590 0.06397997 0.015418278
## 4 0.02867818 0.09749658 0.06168335 0.015838932
## 8 0.01788874 0.10240891 0.03455672 0.009171477
## 12 0.02256365 0.09043070 0.05171240 0.014322115
## Mean_Balanced_AccuracySD
## 1 0.04632515
## 5 0.06415712
## 9 0.06580491
## 2 0.03064781
## 6 0.02397790
## 10 0.02417231
## 3 0.02459656
## 7 0.02314419
## 11 0.04422533
## 4 0.04218772
## 8 0.02497062
## 12 0.03844077(AVNN_Train_Accuracy <- AVNN_Tune$results[AVNN_Tune$results$decay==AVNN_Tune$bestTune$decay &
AVNN_Tune$results$size==AVNN_Tune$bestTune$size,
c("Accuracy")])## [1] 0.672968##################################
# Identifying and plotting the
# best model predictors
##################################
# model does not support variable importance measurement
##################################
# Independently evaluating the model
# on the test set
##################################
AVNN_Test <- data.frame(AVNN_Observed = PMA_PreModelling_Test_AVNN$Log_Solubility_Class,
AVNN_Predicted = predict(AVNN_Tune,
PMA_PreModelling_Test_AVNN[,!names(PMA_PreModelling_Test_AVNN) %in% c("Log_Solubility_Class")],
type = "raw"))
AVNN_Test## AVNN_Observed AVNN_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Low
## 13 High High
## 14 High High
## 15 High High
## 16 High High
## 17 High High
## 18 High High
## 19 High High
## 20 High High
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High High
## 27 High High
## 28 High High
## 29 High Low
## 30 High High
## 31 High Low
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High Low
## 43 High High
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High High
## 50 High High
## 51 High High
## 52 High High
## 53 High High
## 54 High High
## 55 High High
## 56 High High
## 57 High High
## 58 Mid High
## 59 Mid High
## 60 Mid High
## 61 Mid High
## 62 Mid High
## 63 Mid High
## 64 Mid High
## 65 Mid High
## 66 Mid Low
## 67 Mid High
## 68 Mid Low
## 69 Mid High
## 70 Mid Low
## 71 Mid High
## 72 Mid Low
## 73 Mid Low
## 74 Mid Low
## 75 Mid High
## 76 Mid High
## 77 Mid High
## 78 Mid High
## 79 Mid High
## 80 Mid High
## 81 Mid High
## 82 Mid Low
## 83 Mid High
## 84 Mid High
## 85 Mid Low
## 86 Mid High
## 87 Mid Low
## 88 Mid Low
## 89 Mid High
## 90 Mid Low
## 91 Mid High
## 92 Mid High
## 93 Mid Low
## 94 Mid High
## 95 Mid High
## 96 Mid High
## 97 Mid Mid
## 98 Mid Low
## 99 Mid High
## 100 Mid High
## 101 Mid High
## 102 Mid Mid
## 103 Mid Low
## 104 Mid High
## 105 Mid High
## 106 Mid Low
## 107 Mid Low
## 108 Mid Low
## 109 Mid Low
## 110 Mid Low
## 111 Mid Low
## 112 Mid Low
## 113 Mid Low
## 114 Mid Low
## 115 Mid Low
## 116 Mid Low
## 117 Mid Low
## 118 Mid High
## 119 Low Low
## 120 Low Low
## 121 Low Low
## 122 Low High
## 123 Low Low
## 124 Low High
## 125 Low Low
## 126 Low Low
## 127 Low Low
## 128 Low Low
## 129 Low Low
## 130 Low Low
## 131 Low Low
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low High
## 136 Low Low
## 137 Low Low
## 138 Low Low
## 139 Low Low
## 140 Low Low
## 141 Low Low
## 142 Low Low
## 143 Low Low
## 144 Low Low
## 145 Low Low
## 146 Low Low
## 147 Low Low
## 148 Low Low
## 149 Low Low
## 150 Low Low
## 151 Low Low
## 152 Low Low
## 153 Low High
## 154 Low Low
## 155 Low Low
## 156 Low Low
## 157 Low Low
## 158 Low Low
## 159 Low Low
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low High
## 181 Low Low
## 182 Low Low
## 183 Low Low
## 184 Low Low
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High High
## 222 High High
## 223 High High
## 224 High High
## 225 High Low
## 226 High Low
## 227 High High
## 228 High High
## 229 High High
## 230 High Low
## 231 High Low
## 232 High High
## 233 High High
## 234 High High
## 235 High High
## 236 High High
## 237 High High
## 238 Mid Low
## 239 Mid High
## 240 Mid High
## 241 Mid High
## 242 Mid High
## 243 Mid High
## 244 Mid Low
## 245 Mid Low
## 246 Mid High
## 247 Mid High
## 248 Mid High
## 249 Mid High
## 250 Mid Low
## 251 Mid High
## 252 Mid High
## 253 Mid High
## 254 Mid Low
## 255 Mid High
## 256 Mid Low
## 257 Mid High
## 258 Mid Low
## 259 Mid Low
## 260 Mid High
## 261 Mid Low
## 262 Mid Low
## 263 Mid High
## 264 Mid Low
## 265 Mid Low
## 266 Mid Low
## 267 Mid Low
## 268 Mid High
## 269 Low Low
## 270 Low Low
## 271 Low High
## 272 Low Low
## 273 Low Low
## 274 Low Low
## 275 Low Low
## 276 Low Low
## 277 Low Low
## 278 Low Low
## 279 Low Low
## 280 Low Low
## 281 Low High
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Low
## 287 Low Low
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid High
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(AVNN_Test_Accuracy <- Accuracy(y_pred = AVNN_Test$AVNN_Predicted,
y_true = AVNN_Test$AVNN_Observed))## [1] 0.65822781.5.8 Support Vector Machine - Radial Basis Function Kernel (SVM_R)
Support Vector Machine plots each observation in an N-dimensional space corresponding to the number of features in the data set and finds a hyperplane that maximally separates the different classes by a maximally large margin (which is defined as the distance between the hyperplane and the closest data points from each class). The algorithm applies kernel transformation by mapping non-linearly separable data using the similarities between the points in a high-dimensional feature space for improved discrimination.
[A] The support vector machine (radial basis function kernel) model from the kernlab package was implemented through the caret package.
[B] The model contains 2 hyperparameters:
[B.1] sigma = sigma held constant at a value of 0.00285
[B.2] C = cost made to vary across a range of 14 default values
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves sigma=0.00285 and C=8
[C.2] Accuracy = 0.79802
[D] The model does not allow for ranking of predictors in terms of variable importance.
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.79114
Code Chunk | Output
##################################
# Transforming factor predictors
# as required by the nature of the model
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_SVM_R <- as.data.frame(lapply(PMA_PreModelling_Train[,!names(PMA_PreModelling_Train) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Train_SVM_R$Log_Solubility_Class <- PMA_PreModelling_Train$Log_Solubility_Class
dim(PMA_PreModelling_Train_SVM_R)## [1] 951 221PMA_PreModelling_Test_SVM_R <- as.data.frame(lapply(PMA_PreModelling_Test[,!names(PMA_PreModelling_Test) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Test_SVM_R$Log_Solubility_Class <- PMA_PreModelling_Test$Log_Solubility_Class
dim(PMA_PreModelling_Test_SVM_R)## [1] 316 221##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_SVM_R$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
# used a range of default values
##################################
# Running the support vector machine (radial basis function kernel) model
# by setting the caret method to 'svmRadial'
##################################
set.seed(12345678)
SVM_R_Tune <- train(x = PMA_PreModelling_Train_SVM_R[,!names(PMA_PreModelling_Train_SVM_R) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_SVM_R$Log_Solubility_Class,
method = "svmRadial",
tuneLength = 14,
metric = "Accuracy",
preProc = c("center", "scale"),
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
SVM_R_Tune## Support Vector Machines with Radial Basis Function Kernel
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## Pre-processing: centered (220), scaled (220)
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## C logLoss AUC prAUC Accuracy Kappa Mean_F1
## 0.25 0.6334423 0.8689748 0.7194482 0.7023115 0.5371923 0.6886849
## 0.50 0.5725928 0.8907098 0.7600585 0.7212379 0.5660314 0.7089492
## 1.00 0.5331090 0.9035696 0.7838100 0.7518216 0.6139046 0.7411611
## 2.00 0.5118222 0.9091475 0.7937931 0.7633569 0.6320557 0.7535229
## 4.00 0.4951963 0.9144035 0.8006117 0.7864376 0.6678594 0.7767546
## 8.00 0.4791068 0.9221485 0.8115407 0.7980168 0.6856740 0.7881976
## 16.00 0.4805208 0.9215547 0.8125939 0.7928644 0.6782327 0.7815636
## 32.00 0.4821513 0.9207821 0.8071511 0.7834344 0.6637563 0.7717154
## 64.00 0.4798816 0.9213063 0.8099530 0.7813072 0.6604966 0.7704117
## 128.00 0.4738832 0.9240360 0.8150784 0.7728856 0.6476486 0.7611360
## 256.00 0.4680732 0.9256462 0.8176965 0.7812626 0.6605779 0.7683309
## 512.00 0.4670243 0.9275979 0.8204870 0.7854736 0.6669789 0.7717478
## 1024.00 0.4668307 0.9274744 0.8191998 0.7886093 0.6720220 0.7753791
## 2048.00 0.4660341 0.9276946 0.8196551 0.7886203 0.6720784 0.7755116
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.6841728 0.8477694 0.7014227 0.8493309
## 0.7030356 0.8568140 0.7237266 0.8589960
## 0.7368545 0.8724838 0.7536193 0.8749749
## 0.7508730 0.8782335 0.7623762 0.8804365
## 0.7763841 0.8897518 0.7833933 0.8927348
## 0.7878551 0.8955247 0.7930046 0.8987511
## 0.7813813 0.8942936 0.7859441 0.8959220
## 0.7707860 0.8896925 0.7770926 0.8911737
## 0.7679817 0.8886472 0.7768166 0.8897177
## 0.7600439 0.8843750 0.7671500 0.8858450
## 0.7675481 0.8887752 0.7744510 0.8905710
## 0.7702521 0.8910541 0.7788597 0.8932930
## 0.7747190 0.8926772 0.7819394 0.8947361
## 0.7744188 0.8927925 0.7829020 0.8947657
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.7014227 0.6841728 0.2341038 0.7659711
## 0.7237266 0.7030356 0.2404126 0.7799248
## 0.7536193 0.7368545 0.2506072 0.8046692
## 0.7623762 0.7508730 0.2544523 0.8145533
## 0.7833933 0.7763841 0.2621459 0.8330679
## 0.7930046 0.7878551 0.2660056 0.8416899
## 0.7859441 0.7813813 0.2642881 0.8378374
## 0.7770926 0.7707860 0.2611448 0.8302393
## 0.7768166 0.7679817 0.2604357 0.8283145
## 0.7671500 0.7600439 0.2576285 0.8222095
## 0.7744510 0.7675481 0.2604209 0.8281617
## 0.7788597 0.7702521 0.2618245 0.8306531
## 0.7819394 0.7747190 0.2628698 0.8336981
## 0.7829020 0.7744188 0.2628734 0.8336056
##
## Tuning parameter 'sigma' was held constant at a value of 0.002858301
## Accuracy was used to select the optimal model using the largest value.
## The final values used for the model were sigma = 0.002858301 and C = 8.SVM_R_Tune$finalModel## Support Vector Machine object of class "ksvm"
##
## SV type: C-svc (classification)
## parameter : cost C = 8
##
## Gaussian Radial Basis kernel function.
## Hyperparameter : sigma = 0.00285830098890164
##
## Number of Support Vectors : 612
##
## Objective Function Value : -941.4835 -179.1601 -709.4411
## Training error : 0.030494
## Probability model included.SVM_R_Tune$results## sigma C logLoss AUC prAUC Accuracy Kappa
## 1 0.002858301 0.25 0.6334423 0.8689748 0.7194482 0.7023115 0.5371923
## 2 0.002858301 0.50 0.5725928 0.8907098 0.7600585 0.7212379 0.5660314
## 3 0.002858301 1.00 0.5331090 0.9035696 0.7838100 0.7518216 0.6139046
## 4 0.002858301 2.00 0.5118222 0.9091475 0.7937931 0.7633569 0.6320557
## 5 0.002858301 4.00 0.4951963 0.9144035 0.8006117 0.7864376 0.6678594
## 6 0.002858301 8.00 0.4791068 0.9221485 0.8115407 0.7980168 0.6856740
## 7 0.002858301 16.00 0.4805208 0.9215547 0.8125939 0.7928644 0.6782327
## 8 0.002858301 32.00 0.4821513 0.9207821 0.8071511 0.7834344 0.6637563
## 9 0.002858301 64.00 0.4798816 0.9213063 0.8099530 0.7813072 0.6604966
## 10 0.002858301 128.00 0.4738832 0.9240360 0.8150784 0.7728856 0.6476486
## 11 0.002858301 256.00 0.4680732 0.9256462 0.8176965 0.7812626 0.6605779
## 12 0.002858301 512.00 0.4670243 0.9275979 0.8204870 0.7854736 0.6669789
## 13 0.002858301 1024.00 0.4668307 0.9274744 0.8191998 0.7886093 0.6720220
## 14 0.002858301 2048.00 0.4660341 0.9276946 0.8196551 0.7886203 0.6720784
## Mean_F1 Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value
## 1 0.6886849 0.6841728 0.8477694 0.7014227
## 2 0.7089492 0.7030356 0.8568140 0.7237266
## 3 0.7411611 0.7368545 0.8724838 0.7536193
## 4 0.7535229 0.7508730 0.8782335 0.7623762
## 5 0.7767546 0.7763841 0.8897518 0.7833933
## 6 0.7881976 0.7878551 0.8955247 0.7930046
## 7 0.7815636 0.7813813 0.8942936 0.7859441
## 8 0.7717154 0.7707860 0.8896925 0.7770926
## 9 0.7704117 0.7679817 0.8886472 0.7768166
## 10 0.7611360 0.7600439 0.8843750 0.7671500
## 11 0.7683309 0.7675481 0.8887752 0.7744510
## 12 0.7717478 0.7702521 0.8910541 0.7788597
## 13 0.7753791 0.7747190 0.8926772 0.7819394
## 14 0.7755116 0.7744188 0.8927925 0.7829020
## Mean_Neg_Pred_Value Mean_Precision Mean_Recall Mean_Detection_Rate
## 1 0.8493309 0.7014227 0.6841728 0.2341038
## 2 0.8589960 0.7237266 0.7030356 0.2404126
## 3 0.8749749 0.7536193 0.7368545 0.2506072
## 4 0.8804365 0.7623762 0.7508730 0.2544523
## 5 0.8927348 0.7833933 0.7763841 0.2621459
## 6 0.8987511 0.7930046 0.7878551 0.2660056
## 7 0.8959220 0.7859441 0.7813813 0.2642881
## 8 0.8911737 0.7770926 0.7707860 0.2611448
## 9 0.8897177 0.7768166 0.7679817 0.2604357
## 10 0.8858450 0.7671500 0.7600439 0.2576285
## 11 0.8905710 0.7744510 0.7675481 0.2604209
## 12 0.8932930 0.7788597 0.7702521 0.2618245
## 13 0.8947361 0.7819394 0.7747190 0.2628698
## 14 0.8947657 0.7829020 0.7744188 0.2628734
## Mean_Balanced_Accuracy logLossSD AUCSD prAUCSD AccuracySD
## 1 0.7659711 0.09339648 0.03468015 0.04633665 0.05447632
## 2 0.7799248 0.07984859 0.02883467 0.03856222 0.06064653
## 3 0.8046692 0.07213086 0.02504415 0.03649587 0.04456283
## 4 0.8145533 0.06624518 0.02353704 0.03813585 0.04235807
## 5 0.8330679 0.05959703 0.02132218 0.03310646 0.04170888
## 6 0.8416899 0.05510115 0.02002718 0.02903684 0.03773073
## 7 0.8378374 0.05420583 0.02034707 0.03249035 0.03445460
## 8 0.8302393 0.05770925 0.02060820 0.03455509 0.03048716
## 9 0.8283145 0.05720643 0.01891486 0.03079520 0.03249443
## 10 0.8222095 0.05414976 0.01708929 0.02985041 0.02791027
## 11 0.8281617 0.05299575 0.01628181 0.03036527 0.03244138
## 12 0.8306531 0.05420690 0.01706101 0.03131832 0.03613351
## 13 0.8336981 0.05285324 0.01668703 0.03160307 0.03096756
## 14 0.8336056 0.05415747 0.01712255 0.03249465 0.03168511
## KappaSD Mean_F1SD Mean_SensitivitySD Mean_SpecificitySD
## 1 0.08409044 0.05337911 0.05426422 0.02840416
## 2 0.09315091 0.06124440 0.06221827 0.03020477
## 3 0.06880439 0.04601586 0.04779523 0.02243608
## 4 0.06585164 0.04455160 0.04548224 0.02186434
## 5 0.06572357 0.04810153 0.04847195 0.02169854
## 6 0.05983365 0.04362341 0.04322383 0.01986295
## 7 0.05564077 0.03886324 0.04102731 0.01924360
## 8 0.04852055 0.03491912 0.03553032 0.01632531
## 9 0.05087227 0.03556612 0.03664403 0.01653544
## 10 0.04328130 0.03145730 0.03272197 0.01321027
## 11 0.04965883 0.03425632 0.03539463 0.01535187
## 12 0.05490551 0.03780197 0.03838928 0.01677832
## 13 0.04707027 0.03247373 0.03400901 0.01430045
## 14 0.04796210 0.03342970 0.03470549 0.01457028
## Mean_Pos_Pred_ValueSD Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD
## 1 0.04764490 0.02928670 0.04764490 0.05426422
## 2 0.05384587 0.03176220 0.05384587 0.06221827
## 3 0.04144067 0.02343898 0.04144067 0.04779523
## 4 0.04201510 0.02129843 0.04201510 0.04548224
## 5 0.04439903 0.01986004 0.04439903 0.04847195
## 6 0.04356920 0.01784381 0.04356920 0.04322383
## 7 0.03687719 0.01646975 0.03687719 0.04102731
## 8 0.03568480 0.01472081 0.03568480 0.03553032
## 9 0.03574066 0.01642710 0.03574066 0.03664403
## 10 0.03082723 0.01410300 0.03082723 0.03272197
## 11 0.03372772 0.01717814 0.03372772 0.03539463
## 12 0.03789028 0.01921067 0.03789028 0.03838928
## 13 0.03078889 0.01647518 0.03078889 0.03400901
## 14 0.03350426 0.01665767 0.03350426 0.03470549
## Mean_Detection_RateSD Mean_Balanced_AccuracySD
## 1 0.018158775 0.04122482
## 2 0.020215509 0.04611720
## 3 0.014854278 0.03499167
## 4 0.014119357 0.03359874
## 5 0.013902961 0.03504914
## 6 0.012576909 0.03149055
## 7 0.011484866 0.03003873
## 8 0.010162386 0.02579808
## 9 0.010831476 0.02653767
## 10 0.009303424 0.02291174
## 11 0.010813793 0.02531002
## 12 0.012044505 0.02754040
## 13 0.010322521 0.02410125
## 14 0.010561702 0.02459817(SVM_R_Train_Accuracy <- SVM_R_Tune$results[SVM_R_Tune$results$C==SVM_R_Tune$bestTune$C,
c("Accuracy")])## [1] 0.7980168##################################
# Identifying and plotting the
# best model predictors
##################################
# model does not support variable importance measurement
##################################
# Independently evaluating the model
# on the test set
##################################
SVM_R_Test <- data.frame(SVM_R_Observed = PMA_PreModelling_Test_SVM_R$Log_Solubility_Class,
SVM_R_Predicted = predict(SVM_R_Tune,
PMA_PreModelling_Test_SVM_R[,!names(PMA_PreModelling_Test_SVM_R) %in% c("Log_Solubility_Class")],
type = "raw"))
SVM_R_Test## SVM_R_Observed SVM_R_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Mid
## 13 High High
## 14 High High
## 15 High High
## 16 High High
## 17 High High
## 18 High High
## 19 High High
## 20 High High
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High High
## 27 High High
## 28 High High
## 29 High Mid
## 30 High High
## 31 High Low
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High Low
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High Mid
## 50 High High
## 51 High High
## 52 High Mid
## 53 High Mid
## 54 High High
## 55 High High
## 56 High High
## 57 High High
## 58 Mid High
## 59 Mid Mid
## 60 Mid Mid
## 61 Mid Mid
## 62 Mid Mid
## 63 Mid High
## 64 Mid High
## 65 Mid Mid
## 66 Mid Mid
## 67 Mid Low
## 68 Mid High
## 69 Mid High
## 70 Mid Mid
## 71 Mid High
## 72 Mid Mid
## 73 Mid Mid
## 74 Mid Low
## 75 Mid High
## 76 Mid Low
## 77 Mid Mid
## 78 Mid Mid
## 79 Mid Mid
## 80 Mid High
## 81 Mid Mid
## 82 Mid High
## 83 Mid Low
## 84 Mid Mid
## 85 Mid Mid
## 86 Mid High
## 87 Mid Low
## 88 Mid Mid
## 89 Mid Mid
## 90 Mid Mid
## 91 Mid Mid
## 92 Mid Mid
## 93 Mid Mid
## 94 Mid Mid
## 95 Mid High
## 96 Mid Mid
## 97 Mid Low
## 98 Mid Mid
## 99 Mid High
## 100 Mid Mid
## 101 Mid Mid
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid Mid
## 105 Mid Low
## 106 Mid Mid
## 107 Mid Mid
## 108 Mid Mid
## 109 Mid Low
## 110 Mid Low
## 111 Mid Mid
## 112 Mid Low
## 113 Mid Mid
## 114 Mid Mid
## 115 Mid Mid
## 116 Mid Low
## 117 Mid Low
## 118 Mid Low
## 119 Low Mid
## 120 Low Mid
## 121 Low Low
## 122 Low Mid
## 123 Low Low
## 124 Low Mid
## 125 Low Low
## 126 Low Mid
## 127 Low Low
## 128 Low Low
## 129 Low Low
## 130 Low Mid
## 131 Low Low
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low Mid
## 136 Low Low
## 137 Low Mid
## 138 Low Low
## 139 Low Low
## 140 Low Mid
## 141 Low Mid
## 142 Low Low
## 143 Low Low
## 144 Low Low
## 145 Low Mid
## 146 Low Low
## 147 Low Low
## 148 Low Mid
## 149 Low Low
## 150 Low Low
## 151 Low Mid
## 152 Low Low
## 153 Low Low
## 154 Low Low
## 155 Low Low
## 156 Low Low
## 157 Low Low
## 158 Low Low
## 159 Low Low
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Low
## 183 Low Low
## 184 Low Low
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Low
## 226 High High
## 227 High High
## 228 High High
## 229 High High
## 230 High Mid
## 231 High Mid
## 232 High High
## 233 High High
## 234 High High
## 235 High High
## 236 High Mid
## 237 High Mid
## 238 Mid Mid
## 239 Mid Mid
## 240 Mid Mid
## 241 Mid High
## 242 Mid Mid
## 243 Mid Mid
## 244 Mid Low
## 245 Mid Mid
## 246 Mid High
## 247 Mid Mid
## 248 Mid High
## 249 Mid High
## 250 Mid Mid
## 251 Mid Mid
## 252 Mid Mid
## 253 Mid Mid
## 254 Mid Low
## 255 Mid Mid
## 256 Mid High
## 257 Mid Mid
## 258 Mid Mid
## 259 Mid Low
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid Mid
## 263 Mid Mid
## 264 Mid Mid
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Low
## 268 Mid Mid
## 269 Low Low
## 270 Low Low
## 271 Low Mid
## 272 Low Low
## 273 Low Low
## 274 Low Low
## 275 Low Low
## 276 Low Low
## 277 Low Low
## 278 Low Mid
## 279 Low Low
## 280 Low Low
## 281 Low Low
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Low
## 287 Low Low
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(SVM_R_Test_Accuracy <- Accuracy(y_pred = SVM_R_Test$SVM_R_Predicted,
y_true = SVM_R_Test$SVM_R_Observed))## [1] 0.79113921.5.9 Support Vector Machine - Polynomial Kernel (SVM_P)
Support Vector Machine plots each observation in an N-dimensional space corresponding to the number of features in the data set and finds a hyperplane that maximally separates the different classes by a maximally large margin (which is defined as the distance between the hyperplane and the closest data points from each class). The algorithm applies kernel transformation by mapping non-linearly separable data using the similarities between the points in a high-dimensional feature space for improved discrimination.
[A] The support vector machine (polynomial kernel) model from the kernlab package was implemented through the caret package.
[B] The model contains 3 hyperparameters:
[B.1] degree = polynomial degree made to vary across a range of values equal to 1 to 2
[B.2] scale = scale made to vary across a range of values equal to 0.001 to 0.010
[B.3] C = cost made to vary across a range of values equal to 0.25 to 32.00
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves degree=2, scale=0.010 and C=1
[C.2] Accuracy = 0.79597
[D] The model does not allow for ranking of predictors in terms of variable importance.
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.78797
Code Chunk | Output
##################################
# Transforming factor predictors
# as required by the nature of the model
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_SVM_P <- as.data.frame(lapply(PMA_PreModelling_Train[,!names(PMA_PreModelling_Train) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Train_SVM_P$Log_Solubility_Class <- PMA_PreModelling_Train$Log_Solubility_Class
dim(PMA_PreModelling_Train_SVM_P)## [1] 951 221PMA_PreModelling_Test_SVM_P <- as.data.frame(lapply(PMA_PreModelling_Test[,!names(PMA_PreModelling_Test) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Test_SVM_P$Log_Solubility_Class <- PMA_PreModelling_Test$Log_Solubility_Class
dim(PMA_PreModelling_Test_SVM_P)## [1] 316 221##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_SVM_P$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
SVM_P_Grid = expand.grid(degree = 1:2,
scale = c(0.01, 0.005, 0.001),
C = 2^(-2:5))
##################################
# Running the support vector machine (polynomial kernel) model
# by setting the caret method to 'svmPoly'
##################################
set.seed(12345678)
SVM_P_Tune <- train(x = PMA_PreModelling_Train_SVM_P[,!names(PMA_PreModelling_Train_SVM_P) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_SVM_P$Log_Solubility_Class,
method = "svmPoly",
tuneGrid = SVM_P_Grid,
metric = "Accuracy",
preProc = c("center", "scale"),
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
SVM_P_Tune## Support Vector Machines with Polynomial Kernel
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## Pre-processing: centered (220), scaled (220)
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## degree scale C logLoss AUC prAUC Accuracy Kappa
## 1 0.001 0.25 0.7425358 0.8362126 0.6805526 0.6361131 0.4493588
## 1 0.001 0.50 0.6790601 0.8472631 0.6892398 0.6476043 0.4620013
## 1 0.001 1.00 0.6074072 0.8719809 0.7220562 0.7002506 0.5348414
## 1 0.001 2.00 0.5638024 0.8895648 0.7511967 0.7212596 0.5671169
## 1 0.001 4.00 0.5404136 0.8983201 0.7653866 0.7265118 0.5741199
## 1 0.001 8.00 0.5213522 0.9052265 0.7766254 0.7549900 0.6180651
## 1 0.001 16.00 0.5206046 0.9067964 0.7752507 0.7613394 0.6290659
## 1 0.001 32.00 0.5280919 0.9045401 0.7732186 0.7603642 0.6274367
## 1 0.005 0.25 0.5887799 0.8799167 0.7344352 0.7170598 0.5595619
## 1 0.005 0.50 0.5551921 0.8947722 0.7595126 0.7244172 0.5711617
## 1 0.005 1.00 0.5368922 0.9003932 0.7684109 0.7370276 0.5905210
## 1 0.005 2.00 0.5185553 0.9061931 0.7766261 0.7571505 0.6218207
## 1 0.005 4.00 0.5235077 0.9061557 0.7744450 0.7582587 0.6246277
## 1 0.005 8.00 0.5261044 0.9044746 0.7729243 0.7550894 0.6189175
## 1 0.005 16.00 0.5314598 0.9032831 0.7740152 0.7486952 0.6110584
## 1 0.005 32.00 0.5249288 0.9081205 0.7811437 0.7707358 0.6443087
## 1 0.010 0.25 0.5546393 0.8944241 0.7590873 0.7212817 0.5662198
## 1 0.010 0.50 0.5357205 0.9003240 0.7694477 0.7391552 0.5939715
## 1 0.010 1.00 0.5184350 0.9064958 0.7772667 0.7550233 0.6185161
## 1 0.010 2.00 0.5218201 0.9063104 0.7750827 0.7593115 0.6262870
## 1 0.010 4.00 0.5305254 0.9041721 0.7728925 0.7635221 0.6321139
## 1 0.010 8.00 0.5294425 0.9044233 0.7746450 0.7507783 0.6142788
## 1 0.010 16.00 0.5231705 0.9081176 0.7822007 0.7707139 0.6446323
## 1 0.010 32.00 0.5402305 0.9010681 0.7675077 0.7634222 0.6329205
## 2 0.001 0.25 0.6708145 0.8509589 0.6936269 0.6529010 0.4692013
## 2 0.001 0.50 0.6028213 0.8749020 0.7275914 0.7023334 0.5373749
## 2 0.001 1.00 0.5528551 0.8941762 0.7609881 0.7212708 0.5667906
## 2 0.001 2.00 0.5357778 0.9001432 0.7693027 0.7444520 0.6019296
## 2 0.001 4.00 0.5146052 0.9072263 0.7824361 0.7623591 0.6304446
## 2 0.001 8.00 0.5070388 0.9109772 0.7854211 0.7718549 0.6462392
## 2 0.001 16.00 0.5003080 0.9133160 0.7906196 0.7833459 0.6634169
## 2 0.001 32.00 0.4989230 0.9168384 0.8010330 0.7844427 0.6657529
## 2 0.005 0.25 0.5435039 0.8993897 0.7721435 0.7476220 0.6074272
## 2 0.005 0.50 0.5212181 0.9063795 0.7831133 0.7633898 0.6322581
## 2 0.005 1.00 0.5070836 0.9128024 0.7937546 0.7717889 0.6459466
## 2 0.005 2.00 0.4921505 0.9180085 0.8024260 0.7938832 0.6797238
## 2 0.005 4.00 0.4860238 0.9200755 0.8045043 0.7938946 0.6800484
## 2 0.005 8.00 0.4965847 0.9162563 0.7976748 0.7876013 0.6705312
## 2 0.005 16.00 0.4954733 0.9148149 0.7945286 0.7844763 0.6661521
## 2 0.005 32.00 0.4891914 0.9176457 0.7988817 0.7749799 0.6513036
## 2 0.010 0.25 0.5229100 0.9051278 0.7801677 0.7601764 0.6277482
## 2 0.010 0.50 0.5051421 0.9133305 0.7930368 0.7875236 0.6694848
## 2 0.010 1.00 0.4925652 0.9188195 0.8029170 0.7959670 0.6833765
## 2 0.010 2.00 0.4960478 0.9174846 0.8035097 0.7854848 0.6669011
## 2 0.010 4.00 0.4980684 0.9156226 0.7970502 0.7823262 0.6625245
## 2 0.010 8.00 0.4955305 0.9162287 0.7970276 0.7781266 0.6560209
## 2 0.010 16.00 0.4885723 0.9195064 0.8028522 0.7802541 0.6594150
## 2 0.010 32.00 0.4871701 0.9202634 0.8052654 0.7854846 0.6677958
## Mean_F1 Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value
## 0.6190158 0.6332736 0.8229397 0.6219501
## 0.6334887 0.6373437 0.8261137 0.6362706
## 0.6823725 0.6806229 0.8477132 0.6914818
## 0.7088966 0.7046823 0.8578552 0.7186652
## 0.7133931 0.7080915 0.8597870 0.7251696
## 0.7409558 0.7382863 0.8740976 0.7472157
## 0.7460150 0.7452266 0.8786879 0.7513209
## 0.7478188 0.7459778 0.8776105 0.7547906
## 0.7004053 0.6964683 0.8554155 0.7090943
## 0.7103820 0.7057052 0.8590559 0.7213368
## 0.7233435 0.7194052 0.8652580 0.7335939
## 0.7419863 0.7395774 0.8757621 0.7479651
## 0.7436928 0.7432268 0.8771803 0.7514185
## 0.7426587 0.7394076 0.8746624 0.7501237
## 0.7395223 0.7375711 0.8725188 0.7473544
## 0.7608432 0.7583548 0.8831014 0.7685075
## 0.7072083 0.7021522 0.8574052 0.7195617
## 0.7259649 0.7221828 0.8664405 0.7344094
## 0.7399236 0.7375522 0.8747556 0.7459336
## 0.7446456 0.7439794 0.8778428 0.7510897
## 0.7510732 0.7480782 0.8791840 0.7590235
## 0.7411606 0.7392973 0.8737871 0.7475077
## 0.7613747 0.7597066 0.8831640 0.7682054
## 0.7508179 0.7486921 0.8799351 0.7585597
## 0.6385967 0.6414221 0.8283276 0.6414030
## 0.6867832 0.6833688 0.8479230 0.6971314
## 0.7090174 0.7041322 0.8575365 0.7208983
## 0.7315480 0.7272411 0.8687400 0.7412446
## 0.7502264 0.7475626 0.8783424 0.7568466
## 0.7616240 0.7601642 0.8839516 0.7682715
## 0.7726163 0.7712056 0.8891871 0.7795315
## 0.7761365 0.7764421 0.8896868 0.7818337
## 0.7380429 0.7323240 0.8704357 0.7511184
## 0.7548104 0.7504577 0.8785584 0.7657603
## 0.7627776 0.7628599 0.8827217 0.7690667
## 0.7866682 0.7862027 0.8934553 0.7908440
## 0.7843056 0.7846380 0.8943604 0.7884124
## 0.7763498 0.7758442 0.8921344 0.7806474
## 0.7718833 0.7714791 0.8914351 0.7758663
## 0.7622841 0.7610597 0.8864001 0.7671518
## 0.7523773 0.7493000 0.8769521 0.7613541
## 0.7774189 0.7774172 0.8901691 0.7826842
## 0.7856146 0.7860837 0.8956675 0.7884064
## 0.7748329 0.7741325 0.8903693 0.7804796
## 0.7703455 0.7689738 0.8897980 0.7752653
## 0.7658243 0.7644513 0.8877132 0.7711418
## 0.7688450 0.7677080 0.8886923 0.7746540
## 0.7749172 0.7734593 0.8915191 0.7811386
## Mean_Neg_Pred_Value Mean_Precision Mean_Recall Mean_Detection_Rate
## 0.8197082 0.6219501 0.6332736 0.2120377
## 0.8219626 0.6362706 0.6373437 0.2158681
## 0.8495213 0.6914818 0.6806229 0.2334169
## 0.8586745 0.7186652 0.7046823 0.2404199
## 0.8621211 0.7251696 0.7080915 0.2421706
## 0.8771376 0.7472157 0.7382863 0.2516633
## 0.8805829 0.7513209 0.7452266 0.2537798
## 0.8794252 0.7547906 0.7459778 0.2534547
## 0.8578335 0.7090943 0.6964683 0.2390199
## 0.8609942 0.7213368 0.7057052 0.2414724
## 0.8677792 0.7335939 0.7194052 0.2456759
## 0.8784552 0.7479651 0.7395774 0.2523835
## 0.8793537 0.7514185 0.7432268 0.2527529
## 0.8764167 0.7501237 0.7394076 0.2516965
## 0.8722246 0.7473544 0.7375711 0.2495651
## 0.8842522 0.7685075 0.7583548 0.2569119
## 0.8594827 0.7195617 0.7021522 0.2404272
## 0.8683551 0.7344094 0.7221828 0.2463851
## 0.8773719 0.7459336 0.7375522 0.2516744
## 0.8797295 0.7510897 0.7439794 0.2531038
## 0.8809587 0.7590235 0.7480782 0.2545074
## 0.8732368 0.7475077 0.7392973 0.2502594
## 0.8841539 0.7682054 0.7597066 0.2569046
## 0.8811924 0.7585597 0.7486921 0.2544741
## 0.8245001 0.6414030 0.6414221 0.2176337
## 0.8500846 0.6971314 0.6833688 0.2341111
## 0.8587832 0.7208983 0.7041322 0.2404236
## 0.8714169 0.7412446 0.7272411 0.2481507
## 0.8803486 0.7568466 0.7475626 0.2541197
## 0.8847508 0.7682715 0.7601642 0.2572850
## 0.8912327 0.7795315 0.7712056 0.2611153
## 0.8910789 0.7818337 0.7764421 0.2614809
## 0.8721360 0.7511184 0.7323240 0.2492073
## 0.8801517 0.7657603 0.7504577 0.2544633
## 0.8847371 0.7690667 0.7628599 0.2572630
## 0.8955905 0.7908440 0.7862027 0.2646277
## 0.8963814 0.7884124 0.7846380 0.2646315
## 0.8930943 0.7806474 0.7758442 0.2625338
## 0.8916326 0.7758663 0.7714791 0.2614921
## 0.8868220 0.7671518 0.7610597 0.2583266
## 0.8781346 0.7613541 0.7493000 0.2533921
## 0.8934054 0.7826842 0.7774172 0.2625079
## 0.8974927 0.7884064 0.7860837 0.2653223
## 0.8921558 0.7804796 0.7741325 0.2618283
## 0.8903869 0.7752653 0.7689738 0.2607754
## 0.8883907 0.7711418 0.7644513 0.2593755
## 0.8893625 0.7746540 0.7677080 0.2600847
## 0.8918068 0.7811386 0.7734593 0.2618282
## Mean_Balanced_Accuracy
## 0.7281066
## 0.7317287
## 0.7641680
## 0.7812687
## 0.7839393
## 0.8061920
## 0.8119573
## 0.8117942
## 0.7759419
## 0.7823805
## 0.7923316
## 0.8076697
## 0.8102035
## 0.8070350
## 0.8050450
## 0.8207281
## 0.7797787
## 0.7943116
## 0.8061539
## 0.8109111
## 0.8136311
## 0.8065422
## 0.8214353
## 0.8143136
## 0.7348748
## 0.7656459
## 0.7808343
## 0.7979906
## 0.8129525
## 0.8220579
## 0.8301964
## 0.8330645
## 0.8013799
## 0.8145081
## 0.8227908
## 0.8398290
## 0.8394992
## 0.8339893
## 0.8314571
## 0.8237299
## 0.8131260
## 0.8337932
## 0.8408756
## 0.8322509
## 0.8293859
## 0.8260823
## 0.8282002
## 0.8324892
##
## Accuracy was used to select the optimal model using the largest value.
## The final values used for the model were degree = 2, scale = 0.01 and C = 1.SVM_P_Tune$finalModel## Support Vector Machine object of class "ksvm"
##
## SV type: C-svc (classification)
## parameter : cost C = 1
##
## Polynomial kernel function.
## Hyperparameters : degree = 2 scale = 0.01 offset = 1
##
## Number of Support Vectors : 590
##
## Objective Function Value : -100.055 -18.6953 -79.9307
## Training error : 0.02734
## Probability model included.SVM_P_Tune$results## degree scale C logLoss AUC prAUC Accuracy Kappa
## 1 1 0.001 0.25 0.7425358 0.8362126 0.6805526 0.6361131 0.4493588
## 2 1 0.001 0.50 0.6790601 0.8472631 0.6892398 0.6476043 0.4620013
## 3 1 0.001 1.00 0.6074072 0.8719809 0.7220562 0.7002506 0.5348414
## 4 1 0.001 2.00 0.5638024 0.8895648 0.7511967 0.7212596 0.5671169
## 5 1 0.001 4.00 0.5404136 0.8983201 0.7653866 0.7265118 0.5741199
## 6 1 0.001 8.00 0.5213522 0.9052265 0.7766254 0.7549900 0.6180651
## 7 1 0.001 16.00 0.5206046 0.9067964 0.7752507 0.7613394 0.6290659
## 8 1 0.001 32.00 0.5280919 0.9045401 0.7732186 0.7603642 0.6274367
## 9 1 0.005 0.25 0.5887799 0.8799167 0.7344352 0.7170598 0.5595619
## 10 1 0.005 0.50 0.5551921 0.8947722 0.7595126 0.7244172 0.5711617
## 11 1 0.005 1.00 0.5368922 0.9003932 0.7684109 0.7370276 0.5905210
## 12 1 0.005 2.00 0.5185553 0.9061931 0.7766261 0.7571505 0.6218207
## 13 1 0.005 4.00 0.5235077 0.9061557 0.7744450 0.7582587 0.6246277
## 14 1 0.005 8.00 0.5261044 0.9044746 0.7729243 0.7550894 0.6189175
## 15 1 0.005 16.00 0.5314598 0.9032831 0.7740152 0.7486952 0.6110584
## 16 1 0.005 32.00 0.5249288 0.9081205 0.7811437 0.7707358 0.6443087
## 17 1 0.010 0.25 0.5546393 0.8944241 0.7590873 0.7212817 0.5662198
## 18 1 0.010 0.50 0.5357205 0.9003240 0.7694477 0.7391552 0.5939715
## 19 1 0.010 1.00 0.5184350 0.9064958 0.7772667 0.7550233 0.6185161
## 20 1 0.010 2.00 0.5218201 0.9063104 0.7750827 0.7593115 0.6262870
## 21 1 0.010 4.00 0.5305254 0.9041721 0.7728925 0.7635221 0.6321139
## 22 1 0.010 8.00 0.5294425 0.9044233 0.7746450 0.7507783 0.6142788
## 23 1 0.010 16.00 0.5231705 0.9081176 0.7822007 0.7707139 0.6446323
## 24 1 0.010 32.00 0.5402305 0.9010681 0.7675077 0.7634222 0.6329205
## 25 2 0.001 0.25 0.6708145 0.8509589 0.6936269 0.6529010 0.4692013
## 26 2 0.001 0.50 0.6028213 0.8749020 0.7275914 0.7023334 0.5373749
## 27 2 0.001 1.00 0.5528551 0.8941762 0.7609881 0.7212708 0.5667906
## 28 2 0.001 2.00 0.5357778 0.9001432 0.7693027 0.7444520 0.6019296
## 29 2 0.001 4.00 0.5146052 0.9072263 0.7824361 0.7623591 0.6304446
## 30 2 0.001 8.00 0.5070388 0.9109772 0.7854211 0.7718549 0.6462392
## 31 2 0.001 16.00 0.5003080 0.9133160 0.7906196 0.7833459 0.6634169
## 32 2 0.001 32.00 0.4989230 0.9168384 0.8010330 0.7844427 0.6657529
## 33 2 0.005 0.25 0.5435039 0.8993897 0.7721435 0.7476220 0.6074272
## 34 2 0.005 0.50 0.5212181 0.9063795 0.7831133 0.7633898 0.6322581
## 35 2 0.005 1.00 0.5070836 0.9128024 0.7937546 0.7717889 0.6459466
## 36 2 0.005 2.00 0.4921505 0.9180085 0.8024260 0.7938832 0.6797238
## 37 2 0.005 4.00 0.4860238 0.9200755 0.8045043 0.7938946 0.6800484
## 38 2 0.005 8.00 0.4965847 0.9162563 0.7976748 0.7876013 0.6705312
## 39 2 0.005 16.00 0.4954733 0.9148149 0.7945286 0.7844763 0.6661521
## 40 2 0.005 32.00 0.4891914 0.9176457 0.7988817 0.7749799 0.6513036
## 41 2 0.010 0.25 0.5229100 0.9051278 0.7801677 0.7601764 0.6277482
## 42 2 0.010 0.50 0.5051421 0.9133305 0.7930368 0.7875236 0.6694848
## 43 2 0.010 1.00 0.4925652 0.9188195 0.8029170 0.7959670 0.6833765
## 44 2 0.010 2.00 0.4960478 0.9174846 0.8035097 0.7854848 0.6669011
## 45 2 0.010 4.00 0.4980684 0.9156226 0.7970502 0.7823262 0.6625245
## 46 2 0.010 8.00 0.4955305 0.9162287 0.7970276 0.7781266 0.6560209
## 47 2 0.010 16.00 0.4885723 0.9195064 0.8028522 0.7802541 0.6594150
## 48 2 0.010 32.00 0.4871701 0.9202634 0.8052654 0.7854846 0.6677958
## Mean_F1 Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value
## 1 0.6190158 0.6332736 0.8229397 0.6219501
## 2 0.6334887 0.6373437 0.8261137 0.6362706
## 3 0.6823725 0.6806229 0.8477132 0.6914818
## 4 0.7088966 0.7046823 0.8578552 0.7186652
## 5 0.7133931 0.7080915 0.8597870 0.7251696
## 6 0.7409558 0.7382863 0.8740976 0.7472157
## 7 0.7460150 0.7452266 0.8786879 0.7513209
## 8 0.7478188 0.7459778 0.8776105 0.7547906
## 9 0.7004053 0.6964683 0.8554155 0.7090943
## 10 0.7103820 0.7057052 0.8590559 0.7213368
## 11 0.7233435 0.7194052 0.8652580 0.7335939
## 12 0.7419863 0.7395774 0.8757621 0.7479651
## 13 0.7436928 0.7432268 0.8771803 0.7514185
## 14 0.7426587 0.7394076 0.8746624 0.7501237
## 15 0.7395223 0.7375711 0.8725188 0.7473544
## 16 0.7608432 0.7583548 0.8831014 0.7685075
## 17 0.7072083 0.7021522 0.8574052 0.7195617
## 18 0.7259649 0.7221828 0.8664405 0.7344094
## 19 0.7399236 0.7375522 0.8747556 0.7459336
## 20 0.7446456 0.7439794 0.8778428 0.7510897
## 21 0.7510732 0.7480782 0.8791840 0.7590235
## 22 0.7411606 0.7392973 0.8737871 0.7475077
## 23 0.7613747 0.7597066 0.8831640 0.7682054
## 24 0.7508179 0.7486921 0.8799351 0.7585597
## 25 0.6385967 0.6414221 0.8283276 0.6414030
## 26 0.6867832 0.6833688 0.8479230 0.6971314
## 27 0.7090174 0.7041322 0.8575365 0.7208983
## 28 0.7315480 0.7272411 0.8687400 0.7412446
## 29 0.7502264 0.7475626 0.8783424 0.7568466
## 30 0.7616240 0.7601642 0.8839516 0.7682715
## 31 0.7726163 0.7712056 0.8891871 0.7795315
## 32 0.7761365 0.7764421 0.8896868 0.7818337
## 33 0.7380429 0.7323240 0.8704357 0.7511184
## 34 0.7548104 0.7504577 0.8785584 0.7657603
## 35 0.7627776 0.7628599 0.8827217 0.7690667
## 36 0.7866682 0.7862027 0.8934553 0.7908440
## 37 0.7843056 0.7846380 0.8943604 0.7884124
## 38 0.7763498 0.7758442 0.8921344 0.7806474
## 39 0.7718833 0.7714791 0.8914351 0.7758663
## 40 0.7622841 0.7610597 0.8864001 0.7671518
## 41 0.7523773 0.7493000 0.8769521 0.7613541
## 42 0.7774189 0.7774172 0.8901691 0.7826842
## 43 0.7856146 0.7860837 0.8956675 0.7884064
## 44 0.7748329 0.7741325 0.8903693 0.7804796
## 45 0.7703455 0.7689738 0.8897980 0.7752653
## 46 0.7658243 0.7644513 0.8877132 0.7711418
## 47 0.7688450 0.7677080 0.8886923 0.7746540
## 48 0.7749172 0.7734593 0.8915191 0.7811386
## Mean_Neg_Pred_Value Mean_Precision Mean_Recall Mean_Detection_Rate
## 1 0.8197082 0.6219501 0.6332736 0.2120377
## 2 0.8219626 0.6362706 0.6373437 0.2158681
## 3 0.8495213 0.6914818 0.6806229 0.2334169
## 4 0.8586745 0.7186652 0.7046823 0.2404199
## 5 0.8621211 0.7251696 0.7080915 0.2421706
## 6 0.8771376 0.7472157 0.7382863 0.2516633
## 7 0.8805829 0.7513209 0.7452266 0.2537798
## 8 0.8794252 0.7547906 0.7459778 0.2534547
## 9 0.8578335 0.7090943 0.6964683 0.2390199
## 10 0.8609942 0.7213368 0.7057052 0.2414724
## 11 0.8677792 0.7335939 0.7194052 0.2456759
## 12 0.8784552 0.7479651 0.7395774 0.2523835
## 13 0.8793537 0.7514185 0.7432268 0.2527529
## 14 0.8764167 0.7501237 0.7394076 0.2516965
## 15 0.8722246 0.7473544 0.7375711 0.2495651
## 16 0.8842522 0.7685075 0.7583548 0.2569119
## 17 0.8594827 0.7195617 0.7021522 0.2404272
## 18 0.8683551 0.7344094 0.7221828 0.2463851
## 19 0.8773719 0.7459336 0.7375522 0.2516744
## 20 0.8797295 0.7510897 0.7439794 0.2531038
## 21 0.8809587 0.7590235 0.7480782 0.2545074
## 22 0.8732368 0.7475077 0.7392973 0.2502594
## 23 0.8841539 0.7682054 0.7597066 0.2569046
## 24 0.8811924 0.7585597 0.7486921 0.2544741
## 25 0.8245001 0.6414030 0.6414221 0.2176337
## 26 0.8500846 0.6971314 0.6833688 0.2341111
## 27 0.8587832 0.7208983 0.7041322 0.2404236
## 28 0.8714169 0.7412446 0.7272411 0.2481507
## 29 0.8803486 0.7568466 0.7475626 0.2541197
## 30 0.8847508 0.7682715 0.7601642 0.2572850
## 31 0.8912327 0.7795315 0.7712056 0.2611153
## 32 0.8910789 0.7818337 0.7764421 0.2614809
## 33 0.8721360 0.7511184 0.7323240 0.2492073
## 34 0.8801517 0.7657603 0.7504577 0.2544633
## 35 0.8847371 0.7690667 0.7628599 0.2572630
## 36 0.8955905 0.7908440 0.7862027 0.2646277
## 37 0.8963814 0.7884124 0.7846380 0.2646315
## 38 0.8930943 0.7806474 0.7758442 0.2625338
## 39 0.8916326 0.7758663 0.7714791 0.2614921
## 40 0.8868220 0.7671518 0.7610597 0.2583266
## 41 0.8781346 0.7613541 0.7493000 0.2533921
## 42 0.8934054 0.7826842 0.7774172 0.2625079
## 43 0.8974927 0.7884064 0.7860837 0.2653223
## 44 0.8921558 0.7804796 0.7741325 0.2618283
## 45 0.8903869 0.7752653 0.7689738 0.2607754
## 46 0.8883907 0.7711418 0.7644513 0.2593755
## 47 0.8893625 0.7746540 0.7677080 0.2600847
## 48 0.8918068 0.7811386 0.7734593 0.2618282
## Mean_Balanced_Accuracy logLossSD AUCSD prAUCSD AccuracySD
## 1 0.7281066 0.11203738 0.03159725 0.03363159 0.04756966
## 2 0.7317287 0.09170327 0.03246884 0.03905730 0.05604862
## 3 0.7641680 0.07077823 0.02896322 0.03548006 0.04939319
## 4 0.7812687 0.06718182 0.02578268 0.03519441 0.04510048
## 5 0.7839393 0.06173775 0.02304760 0.02916857 0.05030513
## 6 0.8061920 0.06299235 0.02377123 0.03167562 0.04129201
## 7 0.8119573 0.06004884 0.02079446 0.02828920 0.02498795
## 8 0.8117942 0.06083120 0.02142383 0.03097518 0.03485542
## 9 0.7759419 0.06992890 0.02719634 0.03503258 0.04994670
## 10 0.7823805 0.06464405 0.02373698 0.03038672 0.04214880
## 11 0.7923316 0.06002189 0.02269008 0.02898261 0.04853983
## 12 0.8076697 0.05914432 0.02147841 0.02846344 0.03153359
## 13 0.8102035 0.05929851 0.02090097 0.02998032 0.02881504
## 14 0.8070350 0.06180020 0.02130408 0.02998603 0.03893205
## 15 0.8050450 0.06166499 0.02367902 0.03126658 0.03915183
## 16 0.8207281 0.05961107 0.02586995 0.04182988 0.04643554
## 17 0.7797787 0.06636716 0.02409976 0.03163091 0.04419462
## 18 0.7943116 0.05993194 0.02262492 0.02954995 0.04531006
## 19 0.8061539 0.05989286 0.02154595 0.02869937 0.03633519
## 20 0.8109111 0.06066658 0.02101719 0.03008695 0.02902439
## 21 0.8136311 0.06109132 0.02095346 0.02978613 0.03603258
## 22 0.8065422 0.06181175 0.02404170 0.03308943 0.04155930
## 23 0.8214353 0.06284607 0.02625529 0.04243295 0.05208644
## 24 0.8143136 0.06190866 0.02707084 0.04166313 0.03507656
## 25 0.7348748 0.09444896 0.03381130 0.04112873 0.05389647
## 26 0.7656459 0.07233227 0.02886136 0.03662107 0.03944701
## 27 0.7808343 0.06682785 0.02568283 0.03726046 0.04451356
## 28 0.7979906 0.06521996 0.02315212 0.03144387 0.03960056
## 29 0.8129525 0.06413662 0.02303732 0.03065523 0.03482007
## 30 0.8220579 0.06364747 0.02243233 0.03175675 0.03145995
## 31 0.8301964 0.06018744 0.02246488 0.03482926 0.03603469
## 32 0.8330645 0.05887333 0.01965952 0.02949126 0.04017956
## 33 0.8013799 0.06937193 0.02462615 0.03573916 0.04713319
## 34 0.8145081 0.06882613 0.02434751 0.03825952 0.03732159
## 35 0.8227908 0.06169660 0.02312955 0.03760458 0.04476669
## 36 0.8398290 0.05904747 0.02072440 0.02854056 0.04219298
## 37 0.8394992 0.05235123 0.01925323 0.02582048 0.03183334
## 38 0.8339893 0.04978836 0.01982786 0.02815681 0.03263686
## 39 0.8314571 0.05510444 0.01930415 0.03030358 0.02867393
## 40 0.8237299 0.05363204 0.01893952 0.02850532 0.03286777
## 41 0.8131260 0.06001501 0.02369771 0.03592135 0.03843723
## 42 0.8337932 0.05570737 0.02168253 0.03080143 0.03780976
## 43 0.8408756 0.05349713 0.02106130 0.02909710 0.03428818
## 44 0.8322509 0.05040863 0.02115380 0.02995862 0.03208969
## 45 0.8293859 0.05062179 0.02046420 0.03062647 0.02704053
## 46 0.8260823 0.05140931 0.01862226 0.02834773 0.02930213
## 47 0.8282002 0.05298321 0.01824371 0.02655759 0.03002569
## 48 0.8324892 0.05464176 0.01681435 0.02618757 0.02982383
## KappaSD Mean_F1SD Mean_SensitivitySD Mean_SpecificitySD
## 1 0.06713840 0.04924902 0.04889938 0.02131838
## 2 0.08052394 0.05410488 0.05734557 0.02563990
## 3 0.07258124 0.04670572 0.04872986 0.02279265
## 4 0.06943577 0.04311920 0.04704110 0.02295396
## 5 0.07793674 0.05079642 0.05286966 0.02560929
## 6 0.06627568 0.04335030 0.04696194 0.02249393
## 7 0.04105966 0.02425001 0.02796966 0.01519852
## 8 0.05609072 0.03689666 0.03919916 0.01961988
## 9 0.07624502 0.05124561 0.05248159 0.02428110
## 10 0.06474086 0.04075972 0.04415903 0.02113157
## 11 0.07581025 0.04929428 0.05285777 0.02504795
## 12 0.05008363 0.03145923 0.03456208 0.01703259
## 13 0.04583353 0.02749620 0.02969385 0.01657791
## 14 0.06183235 0.03967509 0.04212588 0.02112656
## 15 0.06036889 0.03720484 0.03986864 0.02021339
## 16 0.07198785 0.04661118 0.04689059 0.02411376
## 17 0.06784464 0.04196409 0.04501298 0.02217260
## 18 0.07151526 0.04547932 0.04946004 0.02385480
## 19 0.05811002 0.03610832 0.03972918 0.02007204
## 20 0.04609126 0.02678352 0.03005923 0.01655740
## 21 0.05793078 0.03740218 0.04049491 0.02008933
## 22 0.06469313 0.04145417 0.04378894 0.02165525
## 23 0.08047311 0.05190361 0.05270628 0.02664515
## 24 0.05479826 0.03407617 0.03550924 0.01870176
## 25 0.07707566 0.05136516 0.05398904 0.02445426
## 26 0.05739063 0.03917950 0.03989507 0.01733810
## 27 0.06800761 0.04177914 0.04559070 0.02238668
## 28 0.06176729 0.03889292 0.04180155 0.02068392
## 29 0.05460124 0.03512348 0.03800816 0.01827443
## 30 0.04969829 0.03208632 0.03402048 0.01713731
## 31 0.05689965 0.03952996 0.03969747 0.01914245
## 32 0.06372303 0.04308429 0.04495287 0.02148215
## 33 0.07268974 0.04771433 0.05032509 0.02382511
## 34 0.05814158 0.03783524 0.03903950 0.01979393
## 35 0.06892386 0.04835596 0.04622343 0.02270695
## 36 0.06646599 0.04624995 0.04662680 0.02241891
## 37 0.05047028 0.03357232 0.03519402 0.01746133
## 38 0.05194108 0.03625313 0.03713244 0.01771763
## 39 0.04516475 0.03085405 0.03179159 0.01534250
## 40 0.05108864 0.03445427 0.03561056 0.01657163
## 41 0.05951370 0.04053915 0.03985838 0.02006602
## 42 0.05947871 0.04370039 0.04267770 0.01958177
## 43 0.05359589 0.03600022 0.03612086 0.01818240
## 44 0.05098948 0.03453106 0.03594599 0.01748561
## 45 0.04188207 0.02772156 0.02723265 0.01402455
## 46 0.04545975 0.03113288 0.03189860 0.01462027
## 47 0.04666991 0.03035173 0.03263908 0.01527392
## 48 0.04553172 0.03011769 0.03186441 0.01423882
## Mean_Pos_Pred_ValueSD Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD
## 1 0.04393771 0.02271913 0.04393771 0.04889938
## 2 0.04687656 0.02878184 0.04687656 0.05734557
## 3 0.04193029 0.02739505 0.04193029 0.04872986
## 4 0.03453651 0.02470730 0.03453651 0.04704110
## 5 0.04373199 0.02629015 0.04373199 0.05286966
## 6 0.03792046 0.02144670 0.03792046 0.04696194
## 7 0.02121717 0.01402806 0.02121717 0.02796966
## 8 0.03612888 0.01811871 0.03612888 0.03919916
## 9 0.04848427 0.02658025 0.04848427 0.05248159
## 10 0.03269214 0.02308580 0.03269214 0.04415903
## 11 0.04082948 0.02529125 0.04082948 0.05285777
## 12 0.02755761 0.01714574 0.02755761 0.03456208
## 13 0.02891446 0.01694895 0.02891446 0.02969385
## 14 0.03836089 0.02080556 0.03836089 0.04212588
## 15 0.03422169 0.02126567 0.03422169 0.03986864
## 16 0.04566633 0.02425741 0.04566633 0.04689059
## 17 0.03504069 0.02464169 0.03504069 0.04501298
## 18 0.03915199 0.02421925 0.03915199 0.04946004
## 19 0.03145720 0.01977395 0.03145720 0.03972918
## 20 0.02720257 0.01714314 0.02720257 0.03005923
## 21 0.03527073 0.01928942 0.03527073 0.04049491
## 22 0.03782536 0.02187290 0.03782536 0.04378894
## 23 0.05047465 0.02745587 0.05047465 0.05270628
## 24 0.03323774 0.01912312 0.03323774 0.03550924
## 25 0.04442154 0.02764838 0.04442154 0.05398904
## 26 0.03754248 0.02161952 0.03754248 0.03989507
## 27 0.03230636 0.02422449 0.03230636 0.04559070
## 28 0.03433824 0.02132121 0.03433824 0.04180155
## 29 0.02985580 0.01829318 0.02985580 0.03800816
## 30 0.03030130 0.01651486 0.03030130 0.03402048
## 31 0.03934189 0.01798786 0.03934189 0.03969747
## 32 0.04010872 0.01995044 0.04010872 0.04495287
## 33 0.04201258 0.02473946 0.04201258 0.05032509
## 34 0.03582966 0.01899962 0.03582966 0.03903950
## 35 0.04794865 0.02199566 0.04794865 0.04622343
## 36 0.04523386 0.02067656 0.04523386 0.04662680
## 37 0.03195678 0.01622477 0.03195678 0.03519402
## 38 0.03695144 0.01589624 0.03695144 0.03713244
## 39 0.03090573 0.01433311 0.03090573 0.03179159
## 40 0.03298102 0.01699123 0.03298102 0.03561056
## 41 0.04006822 0.01914242 0.04006822 0.03985838
## 42 0.04250912 0.01818273 0.04250912 0.04267770
## 43 0.03608676 0.01762340 0.03608676 0.03612086
## 44 0.03406100 0.01628540 0.03406100 0.03594599
## 45 0.03125222 0.01428522 0.03125222 0.02723265
## 46 0.03242301 0.01512473 0.03242301 0.03189860
## 47 0.02970765 0.01622939 0.02970765 0.03263908
## 48 0.02928603 0.01610761 0.02928603 0.03186441
## Mean_Detection_RateSD Mean_Balanced_AccuracySD
## 1 0.015856553 0.03479562
## 2 0.018682873 0.04122375
## 3 0.016464398 0.03555559
## 4 0.015033494 0.03483441
## 5 0.016768376 0.03911531
## 6 0.013764002 0.03458068
## 7 0.008329318 0.02138733
## 8 0.011618472 0.02928719
## 9 0.016648899 0.03814813
## 10 0.014049599 0.03248328
## 11 0.016179944 0.03881310
## 12 0.010511198 0.02565941
## 13 0.009605013 0.02297742
## 14 0.012977350 0.03150216
## 15 0.013050609 0.02992589
## 16 0.015478513 0.03539326
## 17 0.014731540 0.03345409
## 18 0.015103353 0.03651004
## 19 0.012111729 0.02975154
## 20 0.009674795 0.02314951
## 21 0.012010861 0.03014258
## 22 0.013853099 0.03259111
## 23 0.017362146 0.03959276
## 24 0.011692186 0.02691402
## 25 0.017965489 0.03902765
## 26 0.013149005 0.02840638
## 27 0.014837854 0.03386316
## 28 0.013200187 0.03112120
## 29 0.011606689 0.02796863
## 30 0.010486649 0.02543323
## 31 0.012011565 0.02932902
## 32 0.013393185 0.03315921
## 33 0.015711064 0.03693143
## 34 0.012440529 0.02936411
## 35 0.014922231 0.03443098
## 36 0.014064328 0.03442881
## 37 0.010611114 0.02621934
## 38 0.010878954 0.02734570
## 39 0.009557976 0.02345554
## 40 0.010955922 0.02601269
## 41 0.012812412 0.02987678
## 42 0.012603254 0.03105748
## 43 0.011429394 0.02705262
## 44 0.010696563 0.02660245
## 45 0.009013509 0.02049623
## 46 0.009767377 0.02318021
## 47 0.010008565 0.02382181
## 48 0.009941278 0.02297285(SVM_P_Train_Accuracy <- SVM_P_Tune$results[SVM_P_Tune$results$degree==SVM_P_Tune$bestTune$degree &
SVM_P_Tune$results$scale==SVM_P_Tune$bestTune$scale &
SVM_P_Tune$results$C==SVM_P_Tune$bestTune$C,
c("Accuracy")])## [1] 0.795967##################################
# Identifying and plotting the
# best model predictors
##################################
# model does not support variable importance measurement
##################################
# Independently evaluating the model
# on the test set
##################################
SVM_P_Test <- data.frame(SVM_P_Observed = PMA_PreModelling_Test_SVM_P$Log_Solubility_Class,
SVM_P_Predicted = predict(SVM_P_Tune,
PMA_PreModelling_Test_SVM_P[,!names(PMA_PreModelling_Test_SVM_P) %in% c("Log_Solubility_Class")],
type = "raw"))
SVM_P_Test## SVM_P_Observed SVM_P_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Mid
## 13 High High
## 14 High High
## 15 High High
## 16 High High
## 17 High High
## 18 High High
## 19 High High
## 20 High High
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High High
## 27 High High
## 28 High High
## 29 High Low
## 30 High High
## 31 High Mid
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High Low
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High High
## 50 High High
## 51 High High
## 52 High Mid
## 53 High Mid
## 54 High High
## 55 High High
## 56 High High
## 57 High High
## 58 Mid High
## 59 Mid Mid
## 60 Mid Mid
## 61 Mid Mid
## 62 Mid Mid
## 63 Mid High
## 64 Mid High
## 65 Mid Mid
## 66 Mid Mid
## 67 Mid Low
## 68 Mid High
## 69 Mid High
## 70 Mid Mid
## 71 Mid High
## 72 Mid Mid
## 73 Mid Mid
## 74 Mid Low
## 75 Mid High
## 76 Mid Low
## 77 Mid Mid
## 78 Mid Mid
## 79 Mid Mid
## 80 Mid High
## 81 Mid Mid
## 82 Mid High
## 83 Mid Low
## 84 Mid Mid
## 85 Mid Mid
## 86 Mid High
## 87 Mid Low
## 88 Mid Mid
## 89 Mid Mid
## 90 Mid Mid
## 91 Mid Mid
## 92 Mid Mid
## 93 Mid Mid
## 94 Mid Mid
## 95 Mid High
## 96 Mid Mid
## 97 Mid Low
## 98 Mid Mid
## 99 Mid High
## 100 Mid Mid
## 101 Mid Mid
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid High
## 105 Mid Low
## 106 Mid Mid
## 107 Mid Mid
## 108 Mid Low
## 109 Mid Low
## 110 Mid Mid
## 111 Mid Mid
## 112 Mid Low
## 113 Mid Mid
## 114 Mid Mid
## 115 Mid Mid
## 116 Mid Low
## 117 Mid Low
## 118 Mid Low
## 119 Low Mid
## 120 Low Low
## 121 Low Low
## 122 Low Mid
## 123 Low Low
## 124 Low Mid
## 125 Low Low
## 126 Low Mid
## 127 Low Low
## 128 Low Mid
## 129 Low Low
## 130 Low Mid
## 131 Low Low
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low Mid
## 136 Low Low
## 137 Low Mid
## 138 Low Low
## 139 Low Low
## 140 Low Mid
## 141 Low Mid
## 142 Low Mid
## 143 Low Low
## 144 Low Low
## 145 Low Mid
## 146 Low Low
## 147 Low Low
## 148 Low Mid
## 149 Low Low
## 150 Low Low
## 151 Low Mid
## 152 Low Low
## 153 Low Low
## 154 Low Low
## 155 Low Low
## 156 Low Low
## 157 Low Low
## 158 Low Mid
## 159 Low Low
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Low
## 183 Low Low
## 184 Low Low
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Mid
## 226 High High
## 227 High High
## 228 High High
## 229 High High
## 230 High Mid
## 231 High Mid
## 232 High High
## 233 High High
## 234 High High
## 235 High High
## 236 High Mid
## 237 High Mid
## 238 Mid Mid
## 239 Mid Mid
## 240 Mid Mid
## 241 Mid High
## 242 Mid Mid
## 243 Mid Mid
## 244 Mid Low
## 245 Mid Mid
## 246 Mid High
## 247 Mid Mid
## 248 Mid High
## 249 Mid High
## 250 Mid Mid
## 251 Mid Mid
## 252 Mid Mid
## 253 Mid Mid
## 254 Mid Low
## 255 Mid Mid
## 256 Mid High
## 257 Mid Mid
## 258 Mid Mid
## 259 Mid Low
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid Mid
## 263 Mid Mid
## 264 Mid Mid
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Low
## 268 Mid Mid
## 269 Low Low
## 270 Low Low
## 271 Low Mid
## 272 Low Low
## 273 Low Low
## 274 Low Low
## 275 Low Low
## 276 Low Low
## 277 Low Low
## 278 Low Low
## 279 Low Low
## 280 Low Low
## 281 Low Low
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Low
## 287 Low Low
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(SVM_P_Test_Accuracy <- Accuracy(y_pred = SVM_P_Test$SVM_P_Predicted,
y_true = SVM_P_Test$SVM_P_Observed))## [1] 0.78797471.5.10 K-Nearest Neighbors (KNN)
K-Nearest Neighbors use proximity to make predictions about the class grouping of an individual data point. The algorithm examines the labels of a chosen number of data points surrounding a target data point given a distance-based similarity metric, in order to make a prediction about the class that the data point falls into. The process involves setting a value for the chosen number of neighbors, calculating the distance between the target point across all instances, sorting the calculated distances, obtaining the labels of the top entries and returning the prediction for the target point.
[A] The k-nearest neighbors model was implemented through the caret package.
[B] The model contains 1 hyperparameter:
[B.1] k = number of neighbors made to vary across a range of values equal to 1 to 15
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves k=1
[C.2] Accuracy = 0.69096
[D] The model does not allow for ranking of predictors in terms of variable importance.
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.66772
Code Chunk | Output
##################################
# Transforming factor predictors
# as required by the nature of the model
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_KNN <- as.data.frame(lapply(PMA_PreModelling_Train[,!names(PMA_PreModelling_Train) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Train_KNN$Log_Solubility_Class <- PMA_PreModelling_Train$Log_Solubility_Class
dim(PMA_PreModelling_Train_KNN)## [1] 951 221PMA_PreModelling_Test_KNN <- as.data.frame(lapply(PMA_PreModelling_Test[,!names(PMA_PreModelling_Test) %in%
c("Log_Solubility_Class")],
function(x) as.numeric(as.character(x))))
PMA_PreModelling_Test_KNN$Log_Solubility_Class <- PMA_PreModelling_Test$Log_Solubility_Class
dim(PMA_PreModelling_Test_KNN)## [1] 316 221##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_KNN$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
KNN_Grid = data.frame(k = 1:15)
##################################
# Running the k-nearest neighbors model
# by setting the caret method to 'knn'
##################################
set.seed(12345678)
KNN_Tune <- train(x = PMA_PreModelling_Train_KNN[,!names(PMA_PreModelling_Train_KNN) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_KNN$Log_Solubility_Class,
method = "knn",
tuneGrid = KNN_Grid,
metric = "Accuracy",
preProc = c("center", "scale"),
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
KNN_Tune## k-Nearest Neighbors
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## Pre-processing: centered (220), scaled (220)
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## k logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 10.6737099 0.7627248 0.1523593 0.6909644 0.5248443 0.6763654
## 2 6.2928497 0.8097714 0.2987438 0.6687911 0.4915505 0.6567407
## 3 4.1839502 0.8265499 0.3974905 0.6740440 0.5012030 0.6623557
## 4 2.8594322 0.8384589 0.4527443 0.6803257 0.5095334 0.6655584
## 5 2.0527741 0.8426648 0.4961141 0.6728024 0.4992849 0.6578326
## 6 1.6635028 0.8414875 0.5242414 0.6665976 0.4895226 0.6530404
## 7 1.5021258 0.8419778 0.5486772 0.6591839 0.4798950 0.6467301
## 8 1.2420356 0.8423114 0.5581320 0.6475826 0.4624104 0.6333724
## 9 1.0754032 0.8446039 0.5839178 0.6653784 0.4893441 0.6518878
## 10 0.9844257 0.8424898 0.5936362 0.6549069 0.4727168 0.6429190
## 11 0.9569513 0.8410814 0.6044349 0.6496986 0.4657898 0.6390634
## 12 0.9311503 0.8384058 0.6030785 0.6486240 0.4632526 0.6350665
## 13 0.8988341 0.8400084 0.6143793 0.6496657 0.4644401 0.6353063
## 14 0.9010341 0.8398405 0.6178245 0.6580541 0.4775989 0.6432050
## 15 0.9058148 0.8372564 0.6196570 0.6559593 0.4735149 0.6416489
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.6796973 0.8457523 0.6774015 0.8437005
## 0.6610423 0.8337863 0.6571927 0.8318572
## 0.6709135 0.8368506 0.6610606 0.8352393
## 0.6737182 0.8397940 0.6640249 0.8388702
## 0.6676559 0.8368113 0.6565718 0.8356550
## 0.6616797 0.8332811 0.6536380 0.8320344
## 0.6557045 0.8306276 0.6461644 0.8281643
## 0.6424980 0.8253458 0.6321612 0.8225189
## 0.6610590 0.8341057 0.6514759 0.8315761
## 0.6509016 0.8277650 0.6445294 0.8259942
## 0.6469238 0.8257566 0.6413118 0.8230785
## 0.6442150 0.8247755 0.6365916 0.8235268
## 0.6437033 0.8253088 0.6373804 0.8240103
## 0.6514827 0.8301041 0.6455826 0.8283774
## 0.6483081 0.8282646 0.6451923 0.8270225
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.6774015 0.6796973 0.2303215 0.7627248
## 0.6571927 0.6610423 0.2229304 0.7474143
## 0.6610606 0.6709135 0.2246813 0.7538820
## 0.6640249 0.6737182 0.2267752 0.7567561
## 0.6565718 0.6676559 0.2242675 0.7522336
## 0.6536380 0.6616797 0.2221992 0.7474804
## 0.6461644 0.6557045 0.2197280 0.7431661
## 0.6321612 0.6424980 0.2158609 0.7339219
## 0.6514759 0.6610590 0.2217928 0.7475823
## 0.6445294 0.6509016 0.2183023 0.7393333
## 0.6413118 0.6469238 0.2165662 0.7363402
## 0.6365916 0.6442150 0.2162080 0.7344953
## 0.6373804 0.6437033 0.2165552 0.7345061
## 0.6455826 0.6514827 0.2193514 0.7407934
## 0.6451923 0.6483081 0.2186531 0.7382863
##
## Accuracy was used to select the optimal model using the largest value.
## The final value used for the model was k = 1.KNN_Tune$finalModel## 1-nearest neighbor model
## Training set outcome distribution:
##
## Low Mid High
## 427 283 241KNN_Tune$results## k logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 1 10.6737099 0.7627248 0.1523593 0.6909644 0.5248443 0.6763654
## 2 2 6.2928497 0.8097714 0.2987438 0.6687911 0.4915505 0.6567407
## 3 3 4.1839502 0.8265499 0.3974905 0.6740440 0.5012030 0.6623557
## 4 4 2.8594322 0.8384589 0.4527443 0.6803257 0.5095334 0.6655584
## 5 5 2.0527741 0.8426648 0.4961141 0.6728024 0.4992849 0.6578326
## 6 6 1.6635028 0.8414875 0.5242414 0.6665976 0.4895226 0.6530404
## 7 7 1.5021258 0.8419778 0.5486772 0.6591839 0.4798950 0.6467301
## 8 8 1.2420356 0.8423114 0.5581320 0.6475826 0.4624104 0.6333724
## 9 9 1.0754032 0.8446039 0.5839178 0.6653784 0.4893441 0.6518878
## 10 10 0.9844257 0.8424898 0.5936362 0.6549069 0.4727168 0.6429190
## 11 11 0.9569513 0.8410814 0.6044349 0.6496986 0.4657898 0.6390634
## 12 12 0.9311503 0.8384058 0.6030785 0.6486240 0.4632526 0.6350665
## 13 13 0.8988341 0.8400084 0.6143793 0.6496657 0.4644401 0.6353063
## 14 14 0.9010341 0.8398405 0.6178245 0.6580541 0.4775989 0.6432050
## 15 15 0.9058148 0.8372564 0.6196570 0.6559593 0.4735149 0.6416489
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.6796973 0.8457523 0.6774015 0.8437005
## 2 0.6610423 0.8337863 0.6571927 0.8318572
## 3 0.6709135 0.8368506 0.6610606 0.8352393
## 4 0.6737182 0.8397940 0.6640249 0.8388702
## 5 0.6676559 0.8368113 0.6565718 0.8356550
## 6 0.6616797 0.8332811 0.6536380 0.8320344
## 7 0.6557045 0.8306276 0.6461644 0.8281643
## 8 0.6424980 0.8253458 0.6321612 0.8225189
## 9 0.6610590 0.8341057 0.6514759 0.8315761
## 10 0.6509016 0.8277650 0.6445294 0.8259942
## 11 0.6469238 0.8257566 0.6413118 0.8230785
## 12 0.6442150 0.8247755 0.6365916 0.8235268
## 13 0.6437033 0.8253088 0.6373804 0.8240103
## 14 0.6514827 0.8301041 0.6455826 0.8283774
## 15 0.6483081 0.8282646 0.6451923 0.8270225
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.6774015 0.6796973 0.2303215 0.7627248
## 2 0.6571927 0.6610423 0.2229304 0.7474143
## 3 0.6610606 0.6709135 0.2246813 0.7538820
## 4 0.6640249 0.6737182 0.2267752 0.7567561
## 5 0.6565718 0.6676559 0.2242675 0.7522336
## 6 0.6536380 0.6616797 0.2221992 0.7474804
## 7 0.6461644 0.6557045 0.2197280 0.7431661
## 8 0.6321612 0.6424980 0.2158609 0.7339219
## 9 0.6514759 0.6610590 0.2217928 0.7475823
## 10 0.6445294 0.6509016 0.2183023 0.7393333
## 11 0.6413118 0.6469238 0.2165662 0.7363402
## 12 0.6365916 0.6442150 0.2162080 0.7344953
## 13 0.6373804 0.6437033 0.2165552 0.7345061
## 14 0.6455826 0.6514827 0.2193514 0.7407934
## 15 0.6451923 0.6483081 0.2186531 0.7382863
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 1.4961915 0.03432577 0.01597257 0.04331918 0.06604091 0.04370119
## 2 1.4006746 0.03735790 0.01578613 0.04531882 0.06822881 0.04341126
## 3 0.9243300 0.03436191 0.03448663 0.05370407 0.08035512 0.05286920
## 4 1.1054249 0.03477873 0.02800168 0.03614390 0.05304843 0.03531431
## 5 0.6858583 0.03118997 0.04057520 0.04762937 0.07125187 0.04802260
## 6 0.5986646 0.02458701 0.02209462 0.04051384 0.06046828 0.03947920
## 7 0.5259159 0.02425272 0.02324487 0.03418856 0.04871695 0.03292711
## 8 0.4929138 0.02660966 0.03509589 0.03951216 0.05834668 0.03896802
## 9 0.3952281 0.02820862 0.03682023 0.05120634 0.07593751 0.05001877
## 10 0.3909030 0.03030350 0.05129978 0.04309240 0.06190314 0.03953886
## 11 0.3180238 0.03039304 0.04821833 0.03746356 0.05413363 0.03609534
## 12 0.3267534 0.03068468 0.04497559 0.05024105 0.07435455 0.04941595
## 13 0.2764924 0.03198023 0.04433573 0.05018315 0.07378559 0.04942128
## 14 0.2778600 0.03471338 0.04815878 0.05180801 0.07585442 0.05043523
## 15 0.2704995 0.03296372 0.04502635 0.05658539 0.08289007 0.05420621
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.04765761 0.02134400 0.04135296
## 2 0.04740568 0.02222685 0.04118442
## 3 0.05364060 0.02637412 0.05308741
## 4 0.03513614 0.01704800 0.03678329
## 5 0.04802770 0.02328897 0.04957638
## 6 0.04295661 0.01934655 0.03921750
## 7 0.03084609 0.01613415 0.03143797
## 8 0.04074256 0.01899430 0.03613987
## 9 0.04941343 0.02554215 0.04960760
## 10 0.03831481 0.02038562 0.03981215
## 11 0.03536315 0.01735382 0.03568248
## 12 0.04901883 0.02424114 0.05069786
## 13 0.04736192 0.02405194 0.05077322
## 14 0.04904318 0.02430644 0.05149403
## 15 0.05264087 0.02666672 0.05710902
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.02260072 0.04135296 0.04765761 0.01443973
## 2 0.02445799 0.04118442 0.04740568 0.01510627
## 3 0.02799472 0.05308741 0.05364060 0.01790136
## 4 0.01903050 0.03678329 0.03513614 0.01204797
## 5 0.02521781 0.04957638 0.04802770 0.01587646
## 6 0.02216083 0.03921750 0.04295661 0.01350461
## 7 0.01725220 0.03143797 0.03084609 0.01139619
## 8 0.02051145 0.03613987 0.04074256 0.01317072
## 9 0.02616908 0.04960760 0.04941343 0.01706878
## 10 0.02260778 0.03981215 0.03831481 0.01436413
## 11 0.01922152 0.03568248 0.03536315 0.01248785
## 12 0.02656742 0.05069786 0.04901883 0.01674702
## 13 0.02599543 0.05077322 0.04736192 0.01672772
## 14 0.02705760 0.05149403 0.04904318 0.01726934
## 15 0.02984155 0.05710902 0.05264087 0.01886180
## Mean_Balanced_AccuracySD
## 1 0.03432577
## 2 0.03472169
## 3 0.03987352
## 4 0.02597765
## 5 0.03546604
## 6 0.03099549
## 7 0.02315893
## 8 0.02959851
## 9 0.03730545
## 10 0.02928290
## 11 0.02623552
## 12 0.03655520
## 13 0.03563522
## 14 0.03657283
## 15 0.03958705(KNN_Train_Accuracy <- KNN_Tune$results[KNN_Tune$results$k==KNN_Tune$bestTune$k,
c("Accuracy")])## [1] 0.6909644##################################
# Identifying and plotting the
# best model predictors
##################################
# model does not support variable importance measurement
##################################
# Independently evaluating the model
# on the test set
##################################
KNN_Test <- data.frame(KNN_Observed = PMA_PreModelling_Test_KNN$Log_Solubility_Class,
KNN_Predicted = predict(KNN_Tune,
PMA_PreModelling_Test_KNN[,!names(PMA_PreModelling_Test_KNN) %in% c("Log_Solubility_Class")],
type = "raw"))
KNN_Test## KNN_Observed KNN_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High High
## 13 High Mid
## 14 High High
## 15 High High
## 16 High High
## 17 High High
## 18 High High
## 19 High Mid
## 20 High High
## 21 High High
## 22 High High
## 23 High High
## 24 High Mid
## 25 High High
## 26 High High
## 27 High High
## 28 High High
## 29 High Mid
## 30 High Low
## 31 High Low
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High Mid
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High High
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High Mid
## 50 High High
## 51 High Mid
## 52 High Mid
## 53 High High
## 54 High High
## 55 High High
## 56 High Mid
## 57 High High
## 58 Mid High
## 59 Mid Mid
## 60 Mid Mid
## 61 Mid High
## 62 Mid Mid
## 63 Mid High
## 64 Mid High
## 65 Mid Mid
## 66 Mid Mid
## 67 Mid Mid
## 68 Mid Low
## 69 Mid High
## 70 Mid Low
## 71 Mid Low
## 72 Mid Mid
## 73 Mid Mid
## 74 Mid Mid
## 75 Mid High
## 76 Mid Mid
## 77 Mid Mid
## 78 Mid Mid
## 79 Mid Mid
## 80 Mid High
## 81 Mid High
## 82 Mid High
## 83 Mid High
## 84 Mid Mid
## 85 Mid Low
## 86 Mid High
## 87 Mid Mid
## 88 Mid High
## 89 Mid Low
## 90 Mid Mid
## 91 Mid Mid
## 92 Mid Mid
## 93 Mid Low
## 94 Mid Mid
## 95 Mid High
## 96 Mid Mid
## 97 Mid Low
## 98 Mid Mid
## 99 Mid High
## 100 Mid Mid
## 101 Mid Low
## 102 Mid Low
## 103 Mid High
## 104 Mid Low
## 105 Mid Low
## 106 Mid High
## 107 Mid Mid
## 108 Mid Mid
## 109 Mid Low
## 110 Mid Low
## 111 Mid Mid
## 112 Mid Mid
## 113 Mid Mid
## 114 Mid Mid
## 115 Mid Mid
## 116 Mid Low
## 117 Mid Low
## 118 Mid Low
## 119 Low High
## 120 Low Mid
## 121 Low Low
## 122 Low High
## 123 Low Low
## 124 Low Mid
## 125 Low High
## 126 Low High
## 127 Low Low
## 128 Low Low
## 129 Low Low
## 130 Low Low
## 131 Low Low
## 132 Low Mid
## 133 Low Low
## 134 Low High
## 135 Low High
## 136 Low Low
## 137 Low Mid
## 138 Low Low
## 139 Low Low
## 140 Low Mid
## 141 Low Mid
## 142 Low Low
## 143 Low Low
## 144 Low Mid
## 145 Low Mid
## 146 Low High
## 147 Low Low
## 148 Low Mid
## 149 Low Low
## 150 Low Low
## 151 Low High
## 152 Low Mid
## 153 Low Low
## 154 Low Low
## 155 Low Low
## 156 Low Low
## 157 Low Low
## 158 Low Low
## 159 Low Low
## 160 Low Mid
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low High
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Low
## 183 Low Low
## 184 Low Low
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low High
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low High
## 197 Low Low
## 198 Low Low
## 199 Low Mid
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Low
## 226 High High
## 227 High Mid
## 228 High Low
## 229 High High
## 230 High Mid
## 231 High Mid
## 232 High Mid
## 233 High High
## 234 High High
## 235 High High
## 236 High Mid
## 237 High High
## 238 Mid Low
## 239 Mid High
## 240 Mid High
## 241 Mid High
## 242 Mid High
## 243 Mid High
## 244 Mid Low
## 245 Mid Low
## 246 Mid High
## 247 Mid Mid
## 248 Mid High
## 249 Mid Mid
## 250 Mid Mid
## 251 Mid Mid
## 252 Mid Mid
## 253 Mid Mid
## 254 Mid Mid
## 255 Mid Mid
## 256 Mid High
## 257 Mid High
## 258 Mid Mid
## 259 Mid Mid
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid High
## 263 Mid Mid
## 264 Mid High
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Low
## 268 Mid High
## 269 Low Low
## 270 Low High
## 271 Low High
## 272 Low High
## 273 Low Low
## 274 Low Mid
## 275 Low Mid
## 276 Low Low
## 277 Low Mid
## 278 Low Mid
## 279 Low Low
## 280 Low Low
## 281 Low Low
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Mid
## 287 Low Low
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Mid
## 294 Low Low
## 295 Low Low
## 296 Low Mid
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Mid
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(KNN_Test_Accuracy <- Accuracy(y_pred = KNN_Test$KNN_Predicted,
y_true = KNN_Test$KNN_Observed))## [1] 0.66772151.5.11 Classification and Regression Trees (CART)
Classification and Regression Trees construct binary trees for both both nominal and continuous input attributes using Gini Index as its splitting criteria. The algorithm handles missing values by surrogating tests to approximate outcomes. In the pruning phase, CART uses pre-pruning technique called Cost-Complexity pruning to remove redundant branches from the decision tree to improve the accuracy. In the first stage, a sequence of increasingly smaller trees are built on the training data. In the second stage, one of these tree is chosen as the pruned tree, based on its classification accuracy on a pruning set, adopting a cross-validated method in its pruning technique.
[A] The classification and regression trees model from the rpart package was implemented through the caret package.
[B] The model contains 1 hyperparameter:
[B.1] cp = complexity parameter threshold made to vary across a range of values equal to 0.001 to 0.020
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves cp=0.010
[C.2] Accuracy = 0.74878
[D] The model allows for ranking of predictors in terms of variable importance. The top-performing predictors in the model are as follows:
[D.1] MolWeight variable (numeric)
[D.2] NumCarbon variable (numeric)
[D.3] NumBonds variable (numeric)
[D.4] SurfaceArea1 variable (numeric)
[D.5] SurfaceArea2 variable (numeric)
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.79746
Code Chunk | Output
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_CART <- PMA_PreModelling_Train
PMA_PreModelling_Test_CART <- PMA_PreModelling_Test
##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_CART$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
CART_Grid = data.frame(cp = c(0.001, 0.005, 0.010, 0.015, 0.020))
##################################
# Running the classification and regression trees model
# by setting the caret method to 'rpart'
##################################
set.seed(12345678)
CART_Tune <- train(x = PMA_PreModelling_Train_CART[,!names(PMA_PreModelling_Train_CART) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_CART$Log_Solubility_Class,
method = "rpart",
tuneGrid = CART_Grid,
metric = "Accuracy",
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
CART_Tune## CART
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## No pre-processing
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## cp logLoss AUC prAUC Accuracy Kappa Mean_F1
## 0.001 1.1931473 0.8769405 0.5963782 0.7422466 0.6006186 0.7269625
## 0.005 1.0020605 0.8671585 0.5598576 0.7465792 0.6044978 0.7290207
## 0.010 0.7870737 0.8494554 0.5583493 0.7487843 0.6056158 0.7306626
## 0.015 0.7790256 0.8271679 0.5247305 0.7319637 0.5771922 0.7127630
## 0.020 0.7959575 0.8190378 0.4606715 0.7182790 0.5550326 0.6972130
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.7271813 0.8695811 0.7310609 0.8706938
## 0.7268683 0.8696300 0.7423965 0.8752360
## 0.7255223 0.8688406 0.7469902 0.8762166
## 0.7050844 0.8583185 0.7371771 0.8685147
## 0.6893675 0.8511574 0.7240875 0.8616398
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.7310609 0.7271813 0.2474155 0.7983812
## 0.7423965 0.7268683 0.2488597 0.7982491
## 0.7469902 0.7255223 0.2495948 0.7971815
## 0.7371771 0.7050844 0.2439879 0.7817014
## 0.7240875 0.6893675 0.2394263 0.7702624
##
## Accuracy was used to select the optimal model using the largest value.
## The final value used for the model was cp = 0.01.CART_Tune$finalModel## n= 951
##
## node), split, n, loss, yval, (yprob)
## * denotes terminal node
##
## 1) root 951 524 Low (0.44900105 0.29758149 0.25341746)
## 2) NumCarbon>=0.08489128 424 102 Low (0.75943396 0.20754717 0.03301887)
## 4) SurfaceArea1< -0.5808955 119 3 Low (0.97478992 0.02521008 0.00000000) *
## 5) SurfaceArea1>=-0.5808955 305 99 Low (0.67540984 0.27868852 0.04590164)
## 10) MolWeight>=0.6824776 188 35 Low (0.81382979 0.15425532 0.03191489) *
## 11) MolWeight< 0.6824776 117 61 Mid (0.45299145 0.47863248 0.06837607)
## 22) FP178=1 19 1 Low (0.94736842 0.05263158 0.00000000) *
## 23) FP178=0 98 43 Mid (0.35714286 0.56122449 0.08163265)
## 46) MolWeight>=-0.2744138 84 43 Mid (0.41666667 0.48809524 0.09523810)
## 92) SurfaceArea1< 0.4297734 53 23 Low (0.56603774 0.33962264 0.09433962) *
## 93) SurfaceArea1>=0.4297734 31 8 Mid (0.16129032 0.74193548 0.09677419) *
## 47) MolWeight< -0.2744138 14 0 Mid (0.00000000 1.00000000 0.00000000) *
## 3) NumCarbon< 0.08489128 527 300 High (0.19924099 0.37001898 0.43074004)
## 6) MolWeight>=-0.738762 281 140 Mid (0.26690391 0.50177936 0.23131673)
## 12) MolWeight>=0.3719905 59 17 Low (0.71186441 0.23728814 0.05084746)
## 24) SurfaceArea1< 1.444976 50 9 Low (0.82000000 0.14000000 0.04000000) *
## 25) SurfaceArea1>=1.444976 9 2 Mid (0.11111111 0.77777778 0.11111111) *
## 13) MolWeight< 0.3719905 222 95 Mid (0.14864865 0.57207207 0.27927928)
## 26) NumOxygen< 1.113753 205 81 Mid (0.16097561 0.60487805 0.23414634)
## 52) FP072=0 71 31 Mid (0.33802817 0.56338028 0.09859155)
## 104) FP172=1 13 2 Low (0.84615385 0.15384615 0.00000000) *
## 105) FP172=0 58 20 Mid (0.22413793 0.65517241 0.12068966) *
## 53) FP072=1 134 50 Mid (0.06716418 0.62686567 0.30597015)
## 106) FP028=0 121 40 Mid (0.07438017 0.66942149 0.25619835) *
## 107) FP028=1 13 3 High (0.00000000 0.23076923 0.76923077) *
## 27) NumOxygen>=1.113753 17 3 High (0.00000000 0.17647059 0.82352941) *
## 7) MolWeight< -0.738762 246 84 High (0.12195122 0.21951220 0.65853659)
## 14) SurfaceArea1< -0.9872601 67 35 Mid (0.44776119 0.47761194 0.07462687)
## 28) NumBonds>=-0.6650861 28 0 Low (1.00000000 0.00000000 0.00000000) *
## 29) NumBonds< -0.6650861 39 7 Mid (0.05128205 0.82051282 0.12820513) *
## 15) SurfaceArea1>=-0.9872601 179 22 High (0.00000000 0.12290503 0.87709497) *CART_Tune$results## cp logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 0.001 1.1931473 0.8769405 0.5963782 0.7422466 0.6006186 0.7269625
## 2 0.005 1.0020605 0.8671585 0.5598576 0.7465792 0.6044978 0.7290207
## 3 0.010 0.7870737 0.8494554 0.5583493 0.7487843 0.6056158 0.7306626
## 4 0.015 0.7790256 0.8271679 0.5247305 0.7319637 0.5771922 0.7127630
## 5 0.020 0.7959575 0.8190378 0.4606715 0.7182790 0.5550326 0.6972130
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.7271813 0.8695811 0.7310609 0.8706938
## 2 0.7268683 0.8696300 0.7423965 0.8752360
## 3 0.7255223 0.8688406 0.7469902 0.8762166
## 4 0.7050844 0.8583185 0.7371771 0.8685147
## 5 0.6893675 0.8511574 0.7240875 0.8616398
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.7310609 0.7271813 0.2474155 0.7983812
## 2 0.7423965 0.7268683 0.2488597 0.7982491
## 3 0.7469902 0.7255223 0.2495948 0.7971815
## 4 0.7371771 0.7050844 0.2439879 0.7817014
## 5 0.7240875 0.6893675 0.2394263 0.7702624
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 0.3926889 0.02582871 0.06647314 0.03753312 0.05828855 0.04459024
## 2 0.3131879 0.02965215 0.12221479 0.03219736 0.05090059 0.03761941
## 3 0.2784351 0.03408637 0.11088151 0.03307568 0.05359542 0.04073305
## 4 0.1940552 0.03330220 0.09615239 0.04535231 0.07158641 0.04958019
## 5 0.1951355 0.03313475 0.07615704 0.04711549 0.07514746 0.05418514
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.04229818 0.01840686 0.04823586
## 2 0.03910158 0.01704983 0.03841794
## 3 0.04333930 0.01760820 0.03175899
## 4 0.05052005 0.02289770 0.04634280
## 5 0.05588823 0.02337378 0.04926607
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.01814324 0.04823586 0.04229818 0.01251104
## 2 0.01591432 0.03841794 0.03910158 0.01073245
## 3 0.01527999 0.03175899 0.04333930 0.01102523
## 4 0.02414552 0.04634280 0.05052005 0.01511744
## 5 0.02448534 0.04926607 0.05588823 0.01570516
## Mean_Balanced_AccuracySD
## 1 0.03027497
## 2 0.02798101
## 3 0.03033345
## 4 0.03662156
## 5 0.03956813(CART_Train_Accuracy <- CART_Tune$results[CART_Tune$results$cp==CART_Tune$bestTune$cp,
c("Accuracy")])## [1] 0.7487843##################################
# Identifying and plotting the
# best model predictors
##################################
CART_VarImp <- varImp(CART_Tune, scale = TRUE)
plot(CART_VarImp,
top=25,
scales=list(y=list(cex = .95)),
main="Ranked Variable Importance : Classification and Regression Trees",
xlab="Scaled Variable Importance Metrics",
ylab="Predictors",
cex=2,
origin=0,
alpha=0.45)
##################################
# Independently evaluating the model
# on the test set
##################################
CART_Test <- data.frame(CART_Observed = PMA_PreModelling_Test_CART$Log_Solubility_Class,
CART_Predicted = predict(CART_Tune,
PMA_PreModelling_Test_CART[,!names(PMA_PreModelling_Test_CART) %in% c("Log_Solubility_Class")],
type = "raw"))
CART_Test## CART_Observed CART_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Low
## 13 High High
## 14 High High
## 15 High High
## 16 High Mid
## 17 High High
## 18 High High
## 19 High High
## 20 High Mid
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High High
## 27 High High
## 28 High High
## 29 High Low
## 30 High High
## 31 High Low
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High Mid
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High Low
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High Mid
## 50 High Mid
## 51 High High
## 52 High Mid
## 53 High High
## 54 High High
## 55 High Mid
## 56 High High
## 57 High Mid
## 58 Mid Mid
## 59 Mid Mid
## 60 Mid Low
## 61 Mid Mid
## 62 Mid Mid
## 63 Mid Mid
## 64 Mid High
## 65 Mid High
## 66 Mid Low
## 67 Mid Low
## 68 Mid Mid
## 69 Mid High
## 70 Mid Mid
## 71 Mid Low
## 72 Mid Low
## 73 Mid Mid
## 74 Mid Low
## 75 Mid High
## 76 Mid Mid
## 77 Mid Mid
## 78 Mid Mid
## 79 Mid Mid
## 80 Mid Mid
## 81 Mid Mid
## 82 Mid High
## 83 Mid High
## 84 Mid Mid
## 85 Mid High
## 86 Mid Mid
## 87 Mid Low
## 88 Mid Mid
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## 90 Mid Mid
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## 94 Mid High
## 95 Mid Mid
## 96 Mid Mid
## 97 Mid Mid
## 98 Mid Low
## 99 Mid Mid
## 100 Mid Mid
## 101 Mid Mid
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid Mid
## 105 Mid Mid
## 106 Mid Low
## 107 Mid Mid
## 108 Mid Mid
## 109 Mid Mid
## 110 Mid Low
## 111 Mid Mid
## 112 Mid Mid
## 113 Mid Mid
## 114 Mid Low
## 115 Mid Mid
## 116 Mid Low
## 117 Mid Low
## 118 Mid Low
## 119 Low Low
## 120 Low Low
## 121 Low Mid
## 122 Low Mid
## 123 Low Low
## 124 Low Mid
## 125 Low Low
## 126 Low Low
## 127 Low Low
## 128 Low Low
## 129 Low Mid
## 130 Low Low
## 131 Low Low
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low Low
## 136 Low Low
## 137 Low Low
## 138 Low Low
## 139 Low Low
## 140 Low Mid
## 141 Low Low
## 142 Low Mid
## 143 Low Low
## 144 Low Low
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## 146 Low Low
## 147 Low Low
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## 149 Low Low
## 150 Low Low
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## 155 Low Low
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## 157 Low Low
## 158 Low Low
## 159 Low Mid
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
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## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Low
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## 185 Low Low
## 186 Low Low
## 187 Low Low
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## 190 Low Low
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## 194 Low Low
## 195 Low Low
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## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
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## 224 High High
## 225 High Mid
## 226 High High
## 227 High High
## 228 High Mid
## 229 High High
## 230 High Mid
## 231 High High
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## 234 High High
## 235 High Mid
## 236 High High
## 237 High Low
## 238 Mid Mid
## 239 Mid High
## 240 Mid Mid
## 241 Mid High
## 242 Mid Mid
## 243 Mid Mid
## 244 Mid Mid
## 245 Mid Low
## 246 Mid Mid
## 247 Mid Mid
## 248 Mid Mid
## 249 Mid Mid
## 250 Mid Mid
## 251 Mid Mid
## 252 Mid High
## 253 Mid Mid
## 254 Mid Mid
## 255 Mid Mid
## 256 Mid High
## 257 Mid Mid
## 258 Mid Low
## 259 Mid Mid
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid Low
## 263 Mid Mid
## 264 Mid Low
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Low
## 268 Mid Low
## 269 Low Low
## 270 Low Low
## 271 Low Mid
## 272 Low Low
## 273 Low Low
## 274 Low Low
## 275 Low Mid
## 276 Low Low
## 277 Low Low
## 278 Low Low
## 279 Low Low
## 280 Low Low
## 281 Low Low
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Low
## 287 Low Low
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(CART_Test_Accuracy <- Accuracy(y_pred = CART_Test$CART_Predicted,
y_true = CART_Test$CART_Observed))## [1] 0.79746841.5.12 Conditional Inference Trees (CTREE)
Conditional Inference Trees use recursive partitioning of features based on the value of correlations in conditional inference framework - compensating against overfitting and a selection bias towards features with many possible splits or missing values thus avoiding biasing and vulnerability to the errors making the method more flexible for the problems in the data. The algorithm applies a significance test which is a permutation test that selects input features to split and recurse, calculating the p-value in the process. The distribution of the test statistic under the null hypothesis is obtained by calculating all possible values of the test statistic under rearrangements of the classes on the observed data points.
[A] The conditional inference trees model from the party package was implemented through the caret package.
[B] The model contains 1 hyperparameter:
[B.1] mincriterion = 1-p-value threshold made to vary across a range of values equal to 0.75 to 0.99
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves mincriterion=0.75
[C.2] Accuracy = 0.73185
[D] The model allows for ranking of predictors in terms of variable importance. The top-performing predictors in the model are as follows:
[D.1] NumCarbon variable (numeric)
[D.2] MolWeight variable (numeric)
[D.3] NumBonds variable (numeric)
[D.4] NumRings variable (numeric)
[D.5] NumMultBonds variable (numeric)
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.79430
Code Chunk | Output
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_CTREE <- PMA_PreModelling_Train
PMA_PreModelling_Test_CTREE <- PMA_PreModelling_Test
##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_CTREE$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
CTREE_Grid = data.frame(mincriterion = sort(c(0.95, seq(0.75, 0.99, length = 2))))
##################################
# Running the conditional inference trees model
# by setting the caret method to 'ctree'
##################################
set.seed(12345678)
CTREE_Tune <- train(x = PMA_PreModelling_Train_CTREE[,!names(PMA_PreModelling_Train_CTREE) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_CTREE$Log_Solubility_Class,
method = "ctree",
tuneGrid = CTREE_Grid,
metric = "Accuracy",
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
CTREE_Tune## Conditional Inference Tree
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## No pre-processing
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## mincriterion logLoss AUC prAUC Accuracy Kappa
## 0.75 0.9299039 0.8782359 0.6305546 0.7318519 0.5816893
## 0.95 0.8082372 0.8739128 0.6346791 0.7224113 0.5657826
## 0.99 0.7949996 0.8667851 0.6256556 0.7192308 0.5592964
## Mean_F1 Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value
## 0.7061496 0.7107353 0.8624620 0.7179074
## 0.6941214 0.6966903 0.8572185 0.7141345
## 0.6924343 0.6886095 0.8547227 0.7174026
## Mean_Neg_Pred_Value Mean_Precision Mean_Recall Mean_Detection_Rate
## 0.8698998 0.7179074 0.7107353 0.2439506
## 0.8657959 0.7141345 0.6966903 0.2408038
## 0.8640532 0.7174026 0.6886095 0.2397436
## Mean_Balanced_Accuracy
## 0.7865987
## 0.7769544
## 0.7716661
##
## Accuracy was used to select the optimal model using the largest value.
## The final value used for the model was mincriterion = 0.75.CTREE_Tune$finalModel##
## Conditional inference tree with 28 terminal nodes
##
## Response: .outcome
## Inputs: FP001, FP002, FP003, FP004, FP005, FP006, FP007, FP008, FP009, FP010, FP011, FP012, FP013, FP014, FP015, FP016, FP017, FP018, FP019, FP020, FP021, FP022, FP023, FP024, FP025, FP026, FP027, FP028, FP029, FP030, FP031, FP032, FP033, FP034, FP035, FP036, FP037, FP038, FP039, FP040, FP041, FP042, FP043, FP044, FP045, FP046, FP047, FP048, FP049, FP050, FP051, FP052, FP053, FP054, FP055, FP056, FP057, FP058, FP059, FP060, FP061, FP062, FP063, FP064, FP065, FP066, FP067, FP068, FP069, FP070, FP071, FP072, FP073, FP074, FP075, FP076, FP077, FP078, FP079, FP080, FP081, FP082, FP083, FP084, FP085, FP086, FP087, FP088, FP089, FP090, FP091, FP092, FP093, FP094, FP095, FP096, FP097, FP098, FP099, FP100, FP101, FP102, FP103, FP104, FP105, FP106, FP107, FP108, FP109, FP110, FP111, FP112, FP113, FP114, FP115, FP116, FP117, FP118, FP119, FP120, FP121, FP122, FP123, FP124, FP125, FP126, FP127, FP128, FP129, FP130, FP131, FP132, FP133, FP134, FP135, FP136, FP137, FP138, FP139, FP140, FP141, FP142, FP143, FP144, FP145, FP146, FP147, FP148, FP149, FP150, FP151, FP152, FP153, FP155, FP156, FP157, FP158, FP159, FP160, FP161, FP162, FP163, FP164, FP165, FP166, FP167, FP168, FP169, FP170, FP171, FP172, FP173, FP174, FP175, FP176, FP177, FP178, FP179, FP180, FP181, FP182, FP183, FP184, FP185, FP186, FP187, FP188, FP189, FP190, FP191, FP192, FP193, FP194, FP195, FP196, FP197, FP198, FP201, FP202, FP203, FP204, FP205, FP206, FP207, FP208, MolWeight, NumBonds, NumMultBonds, NumRotBonds, NumDblBonds, NumCarbon, NumNitrogen, NumOxygen, NumSulfer, NumChlorine, NumHalogen, NumRings, HydrophilicFactor, SurfaceArea1, SurfaceArea2
## Number of observations: 951
##
## 1) MolWeight <= 0.2222905; criterion = 1, statistic = 385.056
## 2) NumCarbon <= 0.1817764; criterion = 1, statistic = 133.298
## 3) FP072 == {0}; criterion = 1, statistic = 99.39
## 4) FP063 == {0}; criterion = 1, statistic = 49.64
## 5) NumCarbon <= -0.9551655; criterion = 1, statistic = 64.15
## 6) NumCarbon <= -2.047084; criterion = 0.958, statistic = 17.099
## 7)* weights = 18
## 6) NumCarbon > -2.047084
## 8)* weights = 32
## 5) NumCarbon > -0.9551655
## 9) NumBonds <= -0.7205854; criterion = 0.998, statistic = 20.067
## 10) FP172 == {0}; criterion = 0.992, statistic = 16.941
## 11)* weights = 17
## 10) FP172 == {1}
## 12)* weights = 8
## 9) NumBonds > -0.7205854
## 13)* weights = 40
## 4) FP063 == {1}
## 14) MolWeight <= -0.946357; criterion = 1, statistic = 28.548
## 15)* weights = 27
## 14) MolWeight > -0.946357
## 16)* weights = 33
## 3) FP072 == {1}
## 17) NumCarbon <= -0.685958; criterion = 1, statistic = 97.13
## 18) FP104 == {1}; criterion = 1, statistic = 31.286
## 19)* weights = 25
## 18) FP104 == {0}
## 20)* weights = 126
## 17) NumCarbon > -0.685958
## 21) FP059 == {1}; criterion = 1, statistic = 38.172
## 22)* weights = 18
## 21) FP059 == {0}
## 23) NumCarbon <= -0.2191597; criterion = 0.998, statistic = 22.847
## 24) NumChlorine <= -0.3972472; criterion = 0.993, statistic = 20.745
## 25) FP178 == {0}; criterion = 0.838, statistic = 14.258
## 26)* weights = 79
## 25) FP178 == {1}
## 27)* weights = 14
## 24) NumChlorine > -0.3972472
## 28)* weights = 7
## 23) NumCarbon > -0.2191597
## 29)* weights = 51
## 2) NumCarbon > 0.1817764
## 30) HydrophilicFactor <= -0.7783308; criterion = 0.991, statistic = 18.067
## 31)* weights = 25
## 30) HydrophilicFactor > -0.7783308
## 32)* weights = 22
## 1) MolWeight > 0.2222905
## 33) HydrophilicFactor <= 1.849533; criterion = 1, statistic = 56.391
## 34) MolWeight <= 0.6620108; criterion = 1, statistic = 43.012
## 35) NumOxygen <= 0.2462845; criterion = 1, statistic = 45.056
## 36) FP075 == {0}; criterion = 0.966, statistic = 14.284
## 37) FP171 == {1}; criterion = 0.987, statistic = 16.099
## 38)* weights = 10
## 37) FP171 == {0}
## 39)* weights = 48
## 36) FP075 == {1}
## 40) FP008 == {0}; criterion = 0.833, statistic = 11.176
## 41)* weights = 28
## 40) FP008 == {1}
## 42)* weights = 8
## 35) NumOxygen > 0.2462845
## 43)* weights = 32
## 34) MolWeight > 0.6620108
## 44) FP042 == {0}; criterion = 0.999, statistic = 25.325
## 45) FP140 == {1}; criterion = 0.992, statistic = 20.479
## 46)* weights = 44
## 45) FP140 == {0}
## 47) FP036 == {1}; criterion = 0.859, statistic = 14.553
## 48)* weights = 10
## 47) FP036 == {0}
## 49) FP186 == {0}; criterion = 0.926, statistic = 15.913
## 50) FP029 == {0}; criterion = 0.918, statistic = 12.581
## 51)* weights = 154
## 50) FP029 == {1}
## 52)* weights = 19
## 49) FP186 == {1}
## 53)* weights = 15
## 44) FP042 == {1}
## 54)* weights = 20
## 33) HydrophilicFactor > 1.849533
## 55)* weights = 21CTREE_Tune$results## mincriterion logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 0.75 0.9299039 0.8782359 0.6305546 0.7318519 0.5816893 0.7061496
## 2 0.95 0.8082372 0.8739128 0.6346791 0.7224113 0.5657826 0.6941214
## 3 0.99 0.7949996 0.8667851 0.6256556 0.7192308 0.5592964 0.6924343
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.7107353 0.8624620 0.7179074 0.8698998
## 2 0.6966903 0.8572185 0.7141345 0.8657959
## 3 0.6886095 0.8547227 0.7174026 0.8640532
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.7179074 0.7107353 0.2439506 0.7865987
## 2 0.7141345 0.6966903 0.2408038 0.7769544
## 3 0.7174026 0.6886095 0.2397436 0.7716661
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 0.3415735 0.02500537 0.08304812 0.05478428 0.08461822 0.05842740
## 2 0.2488583 0.02548413 0.09593237 0.05749373 0.08853568 0.05781397
## 3 0.1928018 0.02262195 0.09394902 0.05115262 0.07730964 0.05334228
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.06329530 0.02641177 0.05867052
## 2 0.06478196 0.02748015 0.06438939
## 3 0.05274447 0.02362171 0.06370703
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.02950585 0.05867052 0.06329530 0.01826143
## 2 0.03266375 0.06438939 0.06478196 0.01916458
## 3 0.02886486 0.06370703 0.05274447 0.01705087
## Mean_Balanced_AccuracySD
## 1 0.04478143
## 2 0.04600230
## 3 0.03803450(CTREE_Train_Accuracy <- CTREE_Tune$results[CTREE_Tune$results$mincriterion==CTREE_Tune$bestTune$mincriterion,
c("Accuracy")])## [1] 0.7318519##################################
# Identifying and plotting the
# best model predictors
##################################
CTREE_VarImp <- varImp(CTREE_Tune, scale = TRUE)
plot(CTREE_VarImp,
top=25,
scales=list(y=list(cex = .95)),
main="Ranked Variable Importance : Conditional Inference Trees",
xlab="Scaled Variable Importance Metrics",
ylab="Predictors",
cex=2,
origin=0,
alpha=0.45)
##################################
# Independently evaluating the model
# on the test set
##################################
CTREE_Test <- data.frame(CTREE_Observed = PMA_PreModelling_Test_CTREE$Log_Solubility_Class,
CTREE_Predicted = predict(CTREE_Tune,
PMA_PreModelling_Test_CTREE[,!names(PMA_PreModelling_Test_CTREE) %in% c("Log_Solubility_Class")],
type = "raw"))
CTREE_Test## CTREE_Observed CTREE_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Low
## 13 High High
## 14 High High
## 15 High High
## 16 High Mid
## 17 High High
## 18 High High
## 19 High High
## 20 High Mid
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High High
## 27 High High
## 28 High High
## 29 High Low
## 30 High High
## 31 High Low
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High Mid
## 43 High Mid
## 44 High High
## 45 High Mid
## 46 High High
## 47 High High
## 48 High High
## 49 High Mid
## 50 High Mid
## 51 High High
## 52 High Mid
## 53 High Mid
## 54 High Mid
## 55 High Mid
## 56 High Mid
## 57 High Mid
## 58 Mid Mid
## 59 Mid Mid
## 60 Mid Low
## 61 Mid High
## 62 Mid Mid
## 63 Mid High
## 64 Mid Mid
## 65 Mid Mid
## 66 Mid Low
## 67 Mid Low
## 68 Mid Mid
## 69 Mid Mid
## 70 Mid Mid
## 71 Mid Low
## 72 Mid Mid
## 73 Mid Mid
## 74 Mid Mid
## 75 Mid Mid
## 76 Mid Low
## 77 Mid Mid
## 78 Mid Mid
## 79 Mid Mid
## 80 Mid Mid
## 81 Mid Mid
## 82 Mid Mid
## 83 Mid Mid
## 84 Mid Mid
## 85 Mid Mid
## 86 Mid Mid
## 87 Mid Low
## 88 Mid Low
## 89 Mid Mid
## 90 Mid Mid
## 91 Mid Mid
## 92 Mid Low
## 93 Mid Mid
## 94 Mid Mid
## 95 Mid Mid
## 96 Mid Mid
## 97 Mid Mid
## 98 Mid Mid
## 99 Mid Mid
## 100 Mid Mid
## 101 Mid Mid
## 102 Mid Mid
## 103 Mid Low
## 104 Mid Mid
## 105 Mid Mid
## 106 Mid Low
## 107 Mid Low
## 108 Mid Mid
## 109 Mid Low
## 110 Mid Low
## 111 Mid Mid
## 112 Mid Mid
## 113 Mid Mid
## 114 Mid Low
## 115 Mid Low
## 116 Mid Low
## 117 Mid Low
## 118 Mid Mid
## 119 Low Low
## 120 Low Low
## 121 Low Low
## 122 Low Mid
## 123 Low Low
## 124 Low Mid
## 125 Low Low
## 126 Low Low
## 127 Low Low
## 128 Low Mid
## 129 Low Mid
## 130 Low Low
## 131 Low Low
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low Low
## 136 Low Mid
## 137 Low Low
## 138 Low Low
## 139 Low Low
## 140 Low Mid
## 141 Low Low
## 142 Low Mid
## 143 Low Low
## 144 Low Mid
## 145 Low Low
## 146 Low Low
## 147 Low Low
## 148 Low Low
## 149 Low Low
## 150 Low Low
## 151 Low Low
## 152 Low Low
## 153 Low Low
## 154 Low Low
## 155 Low Low
## 156 Low Mid
## 157 Low Low
## 158 Low Low
## 159 Low Low
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Low
## 183 Low Low
## 184 Low Mid
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Low
## 226 High High
## 227 High High
## 228 High Mid
## 229 High High
## 230 High Mid
## 231 High High
## 232 High High
## 233 High Mid
## 234 High Mid
## 235 High Mid
## 236 High Mid
## 237 High Low
## 238 Mid Mid
## 239 Mid Mid
## 240 Mid Mid
## 241 Mid High
## 242 Mid Mid
## 243 Mid Mid
## 244 Mid Mid
## 245 Mid Mid
## 246 Mid High
## 247 Mid Mid
## 248 Mid Mid
## 249 Mid Mid
## 250 Mid Mid
## 251 Mid Mid
## 252 Mid Mid
## 253 Mid Mid
## 254 Mid Mid
## 255 Mid Mid
## 256 Mid Mid
## 257 Mid Low
## 258 Mid Mid
## 259 Mid Mid
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid Low
## 263 Mid Mid
## 264 Mid Low
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Low
## 268 Mid Mid
## 269 Low Low
## 270 Low Low
## 271 Low Low
## 272 Low Low
## 273 Low Low
## 274 Low Low
## 275 Low Mid
## 276 Low Low
## 277 Low Low
## 278 Low Mid
## 279 Low Low
## 280 Low Low
## 281 Low Low
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Low
## 287 Low Low
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(CTREE_Test_Accuracy <- Accuracy(y_pred = CTREE_Test$CTREE_Predicted,
y_true = CTREE_Test$CTREE_Observed))## [1] 0.79430381.5.13 C5.0 Decision Trees (C50)
C5.0 Decision Trees generate multi-branch trees in a situation where one or more nominal inputs are given, using an information-based criterion (Entropy and Information Gain) as an attribute selection measure to build decision trees. For overfitting avoidance, the algorithm applies a pessimistic pruning approach called Rule-post pruning, to remove unreliable branches from the decision tree to reduce the size of the tree without any loss of its predictive accuracy. The Rule-post pruning starts off by converting a decision tree to an equivalent set of rules, then based on statistical confidence estimations for error rate it evaluates the rules with the aim of simplifying them without affecting the accuracy, adopting the Binomial Confidence Limit method. In a case of handling missing values, the algorithm allows to whether estimate missing values as a function of other attributes or apportions the case probabilistically among the results.
[A] The C5.0 decision trees model from the C50 and plyr packages was implemented through the caret package.
[B] The model contains 3 hyperparameters:
[B.1] trials = number of boosting iterations made to vary across a range of values equal to 1 to 100
[B.2] model = model type made to vary across a range of levels equal to TREE and RULES
[B.3] winnow = winnow made to vary across a range of levels equal to TRUE and FALSE
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves trials=100, method=TREE and winnow=TRUE
[C.2] Accuracy = 0.80650
[D] The model allows for ranking of predictors in terms of variable importance. The top-performing predictors in the model are as follows:
[D.1] NumOxygen variable (numeric)
[D.2] HydrophilicFactor variable (numeric)
[D.3] NumHalogen variable (numeric)
[D.4] NumUltBonds variable (numeric)
[D.5] FP059 variable (factor)
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.79746
Code Chunk | Output
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_C50 <- PMA_PreModelling_Train
PMA_PreModelling_Test_C50 <- PMA_PreModelling_Test
##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_C50$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
C50_Grid = expand.grid(trials = c(1:9, (1:10)*10),
model = c("tree", "rules"),
winnow = c(TRUE, FALSE))
##################################
# Running the C5.0 decision trees model
# by setting the caret method to 'C5.0'
##################################
set.seed(12345678)
C50_Tune <- train(x = PMA_PreModelling_Train_C50[,!names(PMA_PreModelling_Train_C50) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_C50$Log_Solubility_Class,
method = "C5.0",
tuneGrid = C50_Grid,
metric = "Accuracy",
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
C50_Tune## C5.0
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## No pre-processing
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## model winnow trials logLoss AUC prAUC Accuracy Kappa
## rules FALSE 1 4.3998216 0.8408083 0.5156719 0.7381915 0.5947229
## rules FALSE 2 4.4180247 0.8634563 0.2667234 0.7433987 0.5991622
## rules FALSE 3 3.0815338 0.8835409 0.3741605 0.7613615 0.6264783
## rules FALSE 4 2.3265626 0.8984500 0.4398827 0.7812514 0.6574573
## rules FALSE 5 1.8862805 0.9043791 0.4875171 0.7781488 0.6530764
## rules FALSE 6 1.4758932 0.9117815 0.5293323 0.7781488 0.6524744
## rules FALSE 7 1.3129158 0.9131539 0.5546080 0.7760762 0.6488931
## rules FALSE 8 1.1476519 0.9136152 0.5831336 0.7707685 0.6401249
## rules FALSE 9 1.0102236 0.9163227 0.6027160 0.7749797 0.6468697
## rules FALSE 10 0.9796198 0.9159229 0.6197572 0.7802212 0.6548122
## rules FALSE 20 0.6737258 0.9247341 0.7281327 0.7845091 0.6609854
## rules FALSE 30 0.5654788 0.9296457 0.7613622 0.7950028 0.6782596
## rules FALSE 40 0.5621567 0.9303461 0.7860606 0.7950142 0.6778542
## rules FALSE 50 0.5606451 0.9315716 0.7940533 0.8002557 0.6861108
## rules FALSE 60 0.4633390 0.9328656 0.8009159 0.7960559 0.6798741
## rules FALSE 70 0.4630926 0.9332206 0.8086730 0.7992250 0.6848068
## rules FALSE 80 0.4631011 0.9333377 0.8109600 0.8023386 0.6895699
## rules FALSE 90 0.4635094 0.9333083 0.8128360 0.8023722 0.6893981
## rules FALSE 100 0.4638961 0.9336327 0.8177924 0.8045108 0.6928865
## rules TRUE 1 4.5949501 0.8413849 0.5298497 0.7476110 0.6082290
## rules TRUE 2 4.8098674 0.8566663 0.2560095 0.7381364 0.5884582
## rules TRUE 3 3.5992989 0.8745340 0.3351453 0.7622823 0.6287036
## rules TRUE 4 2.7092183 0.8897535 0.3883074 0.7685533 0.6380081
## rules TRUE 5 2.1942160 0.8964537 0.4317708 0.7676339 0.6359801
## rules TRUE 6 1.7167324 0.9050112 0.4744267 0.7791692 0.6549972
## rules TRUE 7 1.5182003 0.9080220 0.4938592 0.7727977 0.6453724
## rules TRUE 8 1.3485439 0.9108548 0.5283318 0.7844660 0.6636506
## rules TRUE 9 1.2197820 0.9107392 0.5442087 0.7781388 0.6529197
## rules TRUE 10 1.1547306 0.9112995 0.5704581 0.7854185 0.6644813
## rules TRUE 20 0.7120869 0.9228715 0.6836373 0.7833903 0.6608088
## rules TRUE 30 0.5768641 0.9252306 0.7386287 0.7939506 0.6774290
## rules TRUE 40 0.5452365 0.9252018 0.7587722 0.7897284 0.6713428
## rules TRUE 50 0.5451507 0.9256279 0.7723910 0.7897177 0.6705840
## rules TRUE 60 0.5444175 0.9270822 0.7837442 0.7928649 0.6755764
## rules TRUE 70 0.5457853 0.9265074 0.7859145 0.7918454 0.6739786
## rules TRUE 80 0.5466714 0.9260918 0.7894437 0.7970644 0.6822153
## rules TRUE 90 0.5497657 0.9255103 0.7892020 0.7981392 0.6838235
## rules TRUE 100 0.5498533 0.9260822 0.7938398 0.7981171 0.6836508
## tree FALSE 1 0.7612018 0.8580351 0.5288793 0.7339152 0.5870632
## tree FALSE 2 5.2014199 0.8494950 0.2814721 0.7518099 0.6123568
## tree FALSE 3 3.4814254 0.8724411 0.3721631 0.7529738 0.6162606
## tree FALSE 4 2.4881127 0.8870553 0.4376884 0.7644641 0.6331428
## tree FALSE 5 1.8707244 0.8977838 0.4913879 0.7612619 0.6297120
## tree FALSE 6 1.5303403 0.9022829 0.5379048 0.7769860 0.6528794
## tree FALSE 7 1.4253875 0.9050179 0.5722072 0.7717339 0.6459715
## tree FALSE 8 1.0424061 0.9139393 0.6067340 0.7823379 0.6610352
## tree FALSE 9 0.9417560 0.9147496 0.6339689 0.7876239 0.6695055
## tree FALSE 10 0.9063859 0.9161953 0.6527033 0.7791690 0.6557818
## tree FALSE 20 0.6989894 0.9216524 0.7457930 0.7907596 0.6746213
## tree FALSE 30 0.5631850 0.9254035 0.7815907 0.7970759 0.6837073
## tree FALSE 40 0.4945231 0.9271021 0.7926199 0.7980954 0.6858351
## tree FALSE 50 0.4934000 0.9284288 0.8058008 0.8001897 0.6887982
## tree FALSE 60 0.4603809 0.9291503 0.8140329 0.7991811 0.6874140
## tree FALSE 70 0.4587198 0.9299012 0.8177462 0.8044336 0.6951426
## tree FALSE 80 0.4583668 0.9301982 0.8197170 0.8044336 0.6952564
## tree FALSE 90 0.4587226 0.9299374 0.8215848 0.8023173 0.6920721
## tree FALSE 100 0.4579943 0.9301044 0.8223640 0.8023061 0.6920681
## tree TRUE 1 0.7165793 0.8699032 0.5773924 0.7444860 0.6035460
## tree TRUE 2 4.9776117 0.8570899 0.2739288 0.7643757 0.6313036
## tree TRUE 3 3.5283332 0.8775094 0.3342130 0.7549790 0.6188641
## tree TRUE 4 2.4300910 0.8937930 0.4063116 0.7707477 0.6431457
## tree TRUE 5 1.8553249 0.8994602 0.4501029 0.7613510 0.6289163
## tree TRUE 6 1.5176863 0.9050496 0.4863684 0.7749475 0.6493903
## tree TRUE 7 1.3827044 0.9065018 0.5236694 0.7781495 0.6547263
## tree TRUE 8 1.2785617 0.9103441 0.5552439 0.7896962 0.6722063
## tree TRUE 9 1.1479034 0.9115481 0.5947708 0.7823386 0.6612019
## tree TRUE 10 1.0829792 0.9120167 0.6207333 0.7875796 0.6697041
## tree TRUE 20 0.7791523 0.9189332 0.7212392 0.7949818 0.6805427
## tree TRUE 30 0.5806222 0.9227834 0.7622756 0.7959460 0.6821497
## tree TRUE 40 0.5116859 0.9241585 0.7804611 0.8001789 0.6888465
## tree TRUE 50 0.5090894 0.9240593 0.7911353 0.8044228 0.6948172
## tree TRUE 60 0.4752511 0.9254364 0.8036675 0.8043561 0.6950834
## tree TRUE 70 0.4754358 0.9256619 0.8060710 0.8043673 0.6954467
## tree TRUE 80 0.4768183 0.9254681 0.8072215 0.8043451 0.6950472
## tree TRUE 90 0.4778953 0.9252003 0.8067785 0.8054087 0.6966916
## tree TRUE 100 0.4775511 0.9248092 0.8087300 0.8065057 0.6984037
## Mean_F1 Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value
## 0.7188424 0.7214393 0.8687339 0.7203882
## 0.7090655 0.7242612 0.8677124 0.7230738
## 0.7302637 0.7428591 0.8766258 0.7477161
## 0.7541111 0.7614754 0.8865482 0.7672533
## 0.7486633 0.7595351 0.8854277 0.7622445
## 0.7454670 0.7587167 0.8847086 0.7679882
## 0.7452348 0.7559019 0.8833580 0.7600896
## 0.7372250 0.7483993 0.8804983 0.7547927
## 0.7401911 0.7516943 0.8833135 0.7594778
## 0.7477664 0.7571904 0.8853735 0.7670104
## 0.7502744 0.7608254 0.8873458 0.7720503
## 0.7617496 0.7729525 0.8935281 0.7844215
## 0.7612514 0.7726297 0.8930333 0.7845901
## 0.7687550 0.7778862 0.8957174 0.7910687
## 0.7650901 0.7740144 0.8939344 0.7855420
## 0.7677491 0.7769947 0.8957019 0.7888818
## 0.7717573 0.7801706 0.8969807 0.7923013
## 0.7715202 0.7802301 0.8968301 0.7923813
## 0.7739996 0.7830079 0.8980171 0.7948244
## 0.7330151 0.7342882 0.8716971 0.7384755
## 0.7011406 0.7136512 0.8635145 0.7163039
## 0.7384643 0.7454747 0.8773243 0.7470665
## 0.7427568 0.7499286 0.8803161 0.7523172
## 0.7393418 0.7474752 0.8794501 0.7512590
## 0.7567587 0.7618785 0.8858145 0.7652025
## 0.7481535 0.7553904 0.8830292 0.7554946
## 0.7598361 0.7671112 0.8894069 0.7681894
## 0.7511560 0.7588127 0.8853224 0.7626148
## 0.7602687 0.7666261 0.8892511 0.7711765
## 0.7553661 0.7630853 0.8880986 0.7666583
## 0.7656344 0.7734862 0.8938739 0.7774451
## 0.7601058 0.7693790 0.8923107 0.7721930
## 0.7607054 0.7684056 0.8915919 0.7733129
## 0.7636601 0.7717375 0.8933773 0.7768433
## 0.7633156 0.7717744 0.8924521 0.7763256
## 0.7688645 0.7768142 0.8953182 0.7816894
## 0.7714522 0.7784610 0.8955948 0.7838052
## 0.7699093 0.7776120 0.8956587 0.7848725
## 0.7154348 0.7195978 0.8642325 0.7179639
## 0.7299613 0.7330113 0.8718755 0.7348175
## 0.7380388 0.7384485 0.8738620 0.7408057
## 0.7461220 0.7480311 0.8793593 0.7498875
## 0.7485117 0.7484156 0.8783481 0.7537901
## 0.7631329 0.7625242 0.8854308 0.7693010
## 0.7593001 0.7584048 0.8839338 0.7639114
## 0.7663096 0.7669054 0.8884837 0.7697555
## 0.7733934 0.7733247 0.8911952 0.7774483
## 0.7630225 0.7623790 0.8868278 0.7670768
## 0.7736599 0.7738698 0.8940395 0.7787467
## 0.7817821 0.7802971 0.8962296 0.7895580
## 0.7835157 0.7817797 0.8973943 0.7905321
## 0.7841804 0.7825591 0.8982879 0.7918669
## 0.7831516 0.7820273 0.8979750 0.7900428
## 0.7879936 0.7864944 0.9001727 0.7955738
## 0.7880524 0.7868727 0.9003108 0.7948079
## 0.7865102 0.7855207 0.8991656 0.7937685
## 0.7875018 0.7854756 0.8990609 0.7951182
## 0.7338431 0.7332680 0.8695933 0.7407179
## 0.7442697 0.7439494 0.8784015 0.7535392
## 0.7402033 0.7403878 0.8745296 0.7477666
## 0.7561681 0.7551551 0.8826139 0.7632724
## 0.7461051 0.7454499 0.8785112 0.7525808
## 0.7580654 0.7585219 0.8850253 0.7639635
## 0.7633805 0.7634924 0.8867043 0.7691997
## 0.7749586 0.7738115 0.8921545 0.7823281
## 0.7685066 0.7672597 0.8886616 0.7745327
## 0.7731251 0.7721831 0.8918562 0.7789794
## 0.7789619 0.7788408 0.8954313 0.7852555
## 0.7802228 0.7805548 0.8958470 0.7856744
## 0.7856427 0.7857361 0.8979090 0.7923134
## 0.7884630 0.7888025 0.8994876 0.7945402
## 0.7882304 0.7892416 0.8998804 0.7925585
## 0.7884690 0.7896754 0.9002030 0.7920092
## 0.7884395 0.7890206 0.8998804 0.7922908
## 0.7896140 0.7899942 0.9003612 0.7939276
## 0.7905062 0.7908474 0.9010173 0.7951369
## Mean_Neg_Pred_Value Mean_Precision Mean_Recall Mean_Detection_Rate
## 0.8693989 0.7203882 0.7214393 0.2460638
## 0.8811055 0.7230738 0.7242612 0.2477996
## 0.8892817 0.7477161 0.7428591 0.2537872
## 0.8980195 0.7672533 0.7614754 0.2604171
## 0.8972404 0.7622445 0.7595351 0.2593829
## 0.8995631 0.7679882 0.7587167 0.2593829
## 0.8972547 0.7600896 0.7559019 0.2586921
## 0.8958753 0.7547927 0.7483993 0.2569228
## 0.8986540 0.7594778 0.7516943 0.2583266
## 0.9008506 0.7670104 0.7571904 0.2600737
## 0.9040818 0.7720503 0.7608254 0.2615030
## 0.9091187 0.7844215 0.7729525 0.2650009
## 0.9093315 0.7845901 0.7726297 0.2650047
## 0.9112929 0.7910687 0.7778862 0.2667519
## 0.9084173 0.7855420 0.7740144 0.2653520
## 0.9104146 0.7888818 0.7769947 0.2664083
## 0.9120000 0.7923013 0.7801706 0.2674462
## 0.9120312 0.7923813 0.7802301 0.2674574
## 0.9130942 0.7948244 0.7830079 0.2681703
## 0.8735208 0.7384755 0.7342882 0.2492037
## 0.8787375 0.7163039 0.7136512 0.2460455
## 0.8857836 0.7470665 0.7454747 0.2540941
## 0.8899802 0.7523172 0.7499286 0.2561844
## 0.8908735 0.7512590 0.7474752 0.2558780
## 0.8946273 0.7652025 0.7618785 0.2597231
## 0.8917583 0.7554946 0.7553904 0.2575992
## 0.8980060 0.7681894 0.7671112 0.2614887
## 0.8962528 0.7626148 0.7588127 0.2593796
## 0.8991277 0.7711765 0.7666261 0.2618062
## 0.8993577 0.7666583 0.7630853 0.2611301
## 0.9050358 0.7774451 0.7734862 0.2646502
## 0.9033862 0.7721930 0.7693790 0.2632428
## 0.9034367 0.7733129 0.7684056 0.2632392
## 0.9050674 0.7768433 0.7717375 0.2642883
## 0.9042940 0.7763256 0.7717744 0.2639485
## 0.9068977 0.7816894 0.7768142 0.2656881
## 0.9068596 0.7838052 0.7784610 0.2660464
## 0.9079962 0.7848725 0.7776120 0.2660390
## 0.8678523 0.7179639 0.7195978 0.2446384
## 0.8790552 0.7348175 0.7330113 0.2506033
## 0.8761280 0.7408057 0.7384485 0.2509913
## 0.8837889 0.7498875 0.7480311 0.2548214
## 0.8802015 0.7537901 0.7484156 0.2537540
## 0.8887356 0.7693010 0.7625242 0.2589953
## 0.8850949 0.7639114 0.7584048 0.2572446
## 0.8921189 0.7697555 0.7669054 0.2607793
## 0.8942573 0.7774483 0.7733247 0.2625413
## 0.8905381 0.7670768 0.7623790 0.2597230
## 0.8967414 0.7787467 0.7738698 0.2635865
## 0.8997388 0.7895580 0.7802971 0.2656920
## 0.8997383 0.7905321 0.7817797 0.2660318
## 0.9015820 0.7918669 0.7825591 0.2667299
## 0.9008834 0.7900428 0.7820273 0.2663937
## 0.9040457 0.7955738 0.7864944 0.2681445
## 0.9040138 0.7948079 0.7868727 0.2681445
## 0.9026830 0.7937685 0.7855207 0.2674391
## 0.9022665 0.7951182 0.7854756 0.2674354
## 0.8702088 0.7407179 0.7332680 0.2481620
## 0.8849721 0.7535392 0.7439494 0.2547919
## 0.8770798 0.7477666 0.7403878 0.2516597
## 0.8855146 0.7632724 0.7551551 0.2569159
## 0.8804118 0.7525808 0.7454499 0.2537837
## 0.8884618 0.7639635 0.7585219 0.2583158
## 0.8892814 0.7691997 0.7634924 0.2593832
## 0.8957470 0.7823281 0.7738115 0.2632321
## 0.8913391 0.7745327 0.7672597 0.2607795
## 0.8943265 0.7789794 0.7721831 0.2625265
## 0.8990249 0.7852555 0.7788408 0.2649939
## 0.8994597 0.7856744 0.7805548 0.2653153
## 0.9014763 0.7923134 0.7857361 0.2667263
## 0.9041016 0.7945402 0.7888025 0.2681409
## 0.9040420 0.7925585 0.7892416 0.2681187
## 0.9037795 0.7920092 0.7896754 0.2681224
## 0.9037091 0.7922908 0.7890206 0.2681150
## 0.9043179 0.7939276 0.7899942 0.2684696
## 0.9049415 0.7951369 0.7908474 0.2688352
## Mean_Balanced_Accuracy
## 0.7950866
## 0.7959868
## 0.8097425
## 0.8240118
## 0.8224814
## 0.8217127
## 0.8196299
## 0.8144488
## 0.8175039
## 0.8212819
## 0.8240856
## 0.8332403
## 0.8328315
## 0.8368018
## 0.8339744
## 0.8363483
## 0.8385756
## 0.8385301
## 0.8405125
## 0.8029927
## 0.7885829
## 0.8113995
## 0.8151223
## 0.8134626
## 0.8238465
## 0.8192098
## 0.8282591
## 0.8220675
## 0.8279386
## 0.8255920
## 0.8336800
## 0.8308448
## 0.8299987
## 0.8325574
## 0.8321133
## 0.8360662
## 0.8370279
## 0.8366353
## 0.7919152
## 0.8024434
## 0.8061552
## 0.8136952
## 0.8133818
## 0.8239775
## 0.8211693
## 0.8276946
## 0.8322599
## 0.8246034
## 0.8339547
## 0.8382633
## 0.8395870
## 0.8404235
## 0.8400011
## 0.8433335
## 0.8435918
## 0.8423432
## 0.8422682
## 0.8014307
## 0.8111755
## 0.8074587
## 0.8188845
## 0.8119806
## 0.8217736
## 0.8250984
## 0.8329830
## 0.8279607
## 0.8320196
## 0.8371361
## 0.8382009
## 0.8418226
## 0.8441450
## 0.8445610
## 0.8449392
## 0.8444505
## 0.8451777
## 0.8459323
##
## Accuracy was used to select the optimal model using the largest value.
## The final values used for the model were trials = 100, model = tree and
## winnow = TRUE.C50_Tune$finalModel##
## Call:
## (function (x, y, trials = 1, rules = FALSE, weights = NULL, control
## 1.23060333905164, -0.309270049682714, -1.07920674404989,
## 2.00054003341881, 2.00054
##
## Classification Tree
## Number of samples: 951
## Number of predictors: 220
##
## Number of boosting iterations: 100
## Average tree size: 80.2
##
## Non-standard options: attempt to group attributes, winnowingC50_Tune$results## model winnow trials logLoss AUC prAUC Accuracy Kappa
## 39 rules FALSE 1 4.3998216 0.8408083 0.5156719 0.7381915 0.5947229
## 58 rules TRUE 1 4.5949501 0.8413849 0.5298497 0.7476110 0.6082290
## 1 tree FALSE 1 0.7612018 0.8580351 0.5288793 0.7339152 0.5870632
## 20 tree TRUE 1 0.7165793 0.8699032 0.5773924 0.7444860 0.6035460
## 40 rules FALSE 2 4.4180247 0.8634563 0.2667234 0.7433987 0.5991622
## 59 rules TRUE 2 4.8098674 0.8566663 0.2560095 0.7381364 0.5884582
## 2 tree FALSE 2 5.2014199 0.8494950 0.2814721 0.7518099 0.6123568
## 21 tree TRUE 2 4.9776117 0.8570899 0.2739288 0.7643757 0.6313036
## 41 rules FALSE 3 3.0815338 0.8835409 0.3741605 0.7613615 0.6264783
## 60 rules TRUE 3 3.5992989 0.8745340 0.3351453 0.7622823 0.6287036
## 3 tree FALSE 3 3.4814254 0.8724411 0.3721631 0.7529738 0.6162606
## 22 tree TRUE 3 3.5283332 0.8775094 0.3342130 0.7549790 0.6188641
## 42 rules FALSE 4 2.3265626 0.8984500 0.4398827 0.7812514 0.6574573
## 61 rules TRUE 4 2.7092183 0.8897535 0.3883074 0.7685533 0.6380081
## 4 tree FALSE 4 2.4881127 0.8870553 0.4376884 0.7644641 0.6331428
## 23 tree TRUE 4 2.4300910 0.8937930 0.4063116 0.7707477 0.6431457
## 43 rules FALSE 5 1.8862805 0.9043791 0.4875171 0.7781488 0.6530764
## 62 rules TRUE 5 2.1942160 0.8964537 0.4317708 0.7676339 0.6359801
## 5 tree FALSE 5 1.8707244 0.8977838 0.4913879 0.7612619 0.6297120
## 24 tree TRUE 5 1.8553249 0.8994602 0.4501029 0.7613510 0.6289163
## 44 rules FALSE 6 1.4758932 0.9117815 0.5293323 0.7781488 0.6524744
## 63 rules TRUE 6 1.7167324 0.9050112 0.4744267 0.7791692 0.6549972
## 6 tree FALSE 6 1.5303403 0.9022829 0.5379048 0.7769860 0.6528794
## 25 tree TRUE 6 1.5176863 0.9050496 0.4863684 0.7749475 0.6493903
## 45 rules FALSE 7 1.3129158 0.9131539 0.5546080 0.7760762 0.6488931
## 64 rules TRUE 7 1.5182003 0.9080220 0.4938592 0.7727977 0.6453724
## 7 tree FALSE 7 1.4253875 0.9050179 0.5722072 0.7717339 0.6459715
## 26 tree TRUE 7 1.3827044 0.9065018 0.5236694 0.7781495 0.6547263
## 46 rules FALSE 8 1.1476519 0.9136152 0.5831336 0.7707685 0.6401249
## 65 rules TRUE 8 1.3485439 0.9108548 0.5283318 0.7844660 0.6636506
## 8 tree FALSE 8 1.0424061 0.9139393 0.6067340 0.7823379 0.6610352
## 27 tree TRUE 8 1.2785617 0.9103441 0.5552439 0.7896962 0.6722063
## 47 rules FALSE 9 1.0102236 0.9163227 0.6027160 0.7749797 0.6468697
## 66 rules TRUE 9 1.2197820 0.9107392 0.5442087 0.7781388 0.6529197
## 9 tree FALSE 9 0.9417560 0.9147496 0.6339689 0.7876239 0.6695055
## 28 tree TRUE 9 1.1479034 0.9115481 0.5947708 0.7823386 0.6612019
## 48 rules FALSE 10 0.9796198 0.9159229 0.6197572 0.7802212 0.6548122
## 67 rules TRUE 10 1.1547306 0.9112995 0.5704581 0.7854185 0.6644813
## 10 tree FALSE 10 0.9063859 0.9161953 0.6527033 0.7791690 0.6557818
## 29 tree TRUE 10 1.0829792 0.9120167 0.6207333 0.7875796 0.6697041
## 49 rules FALSE 20 0.6737258 0.9247341 0.7281327 0.7845091 0.6609854
## 68 rules TRUE 20 0.7120869 0.9228715 0.6836373 0.7833903 0.6608088
## 11 tree FALSE 20 0.6989894 0.9216524 0.7457930 0.7907596 0.6746213
## 30 tree TRUE 20 0.7791523 0.9189332 0.7212392 0.7949818 0.6805427
## 50 rules FALSE 30 0.5654788 0.9296457 0.7613622 0.7950028 0.6782596
## 69 rules TRUE 30 0.5768641 0.9252306 0.7386287 0.7939506 0.6774290
## 12 tree FALSE 30 0.5631850 0.9254035 0.7815907 0.7970759 0.6837073
## 31 tree TRUE 30 0.5806222 0.9227834 0.7622756 0.7959460 0.6821497
## 51 rules FALSE 40 0.5621567 0.9303461 0.7860606 0.7950142 0.6778542
## 70 rules TRUE 40 0.5452365 0.9252018 0.7587722 0.7897284 0.6713428
## 13 tree FALSE 40 0.4945231 0.9271021 0.7926199 0.7980954 0.6858351
## 32 tree TRUE 40 0.5116859 0.9241585 0.7804611 0.8001789 0.6888465
## 52 rules FALSE 50 0.5606451 0.9315716 0.7940533 0.8002557 0.6861108
## 71 rules TRUE 50 0.5451507 0.9256279 0.7723910 0.7897177 0.6705840
## 14 tree FALSE 50 0.4934000 0.9284288 0.8058008 0.8001897 0.6887982
## 33 tree TRUE 50 0.5090894 0.9240593 0.7911353 0.8044228 0.6948172
## 53 rules FALSE 60 0.4633390 0.9328656 0.8009159 0.7960559 0.6798741
## 72 rules TRUE 60 0.5444175 0.9270822 0.7837442 0.7928649 0.6755764
## 15 tree FALSE 60 0.4603809 0.9291503 0.8140329 0.7991811 0.6874140
## 34 tree TRUE 60 0.4752511 0.9254364 0.8036675 0.8043561 0.6950834
## 54 rules FALSE 70 0.4630926 0.9332206 0.8086730 0.7992250 0.6848068
## 73 rules TRUE 70 0.5457853 0.9265074 0.7859145 0.7918454 0.6739786
## 16 tree FALSE 70 0.4587198 0.9299012 0.8177462 0.8044336 0.6951426
## 35 tree TRUE 70 0.4754358 0.9256619 0.8060710 0.8043673 0.6954467
## 55 rules FALSE 80 0.4631011 0.9333377 0.8109600 0.8023386 0.6895699
## 74 rules TRUE 80 0.5466714 0.9260918 0.7894437 0.7970644 0.6822153
## 17 tree FALSE 80 0.4583668 0.9301982 0.8197170 0.8044336 0.6952564
## 36 tree TRUE 80 0.4768183 0.9254681 0.8072215 0.8043451 0.6950472
## 56 rules FALSE 90 0.4635094 0.9333083 0.8128360 0.8023722 0.6893981
## 75 rules TRUE 90 0.5497657 0.9255103 0.7892020 0.7981392 0.6838235
## 18 tree FALSE 90 0.4587226 0.9299374 0.8215848 0.8023173 0.6920721
## 37 tree TRUE 90 0.4778953 0.9252003 0.8067785 0.8054087 0.6966916
## 57 rules FALSE 100 0.4638961 0.9336327 0.8177924 0.8045108 0.6928865
## 76 rules TRUE 100 0.5498533 0.9260822 0.7938398 0.7981171 0.6836508
## 19 tree FALSE 100 0.4579943 0.9301044 0.8223640 0.8023061 0.6920681
## 38 tree TRUE 100 0.4775511 0.9248092 0.8087300 0.8065057 0.6984037
## Mean_F1 Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value
## 39 0.7188424 0.7214393 0.8687339 0.7203882
## 58 0.7330151 0.7342882 0.8716971 0.7384755
## 1 0.7154348 0.7195978 0.8642325 0.7179639
## 20 0.7338431 0.7332680 0.8695933 0.7407179
## 40 0.7090655 0.7242612 0.8677124 0.7230738
## 59 0.7011406 0.7136512 0.8635145 0.7163039
## 2 0.7299613 0.7330113 0.8718755 0.7348175
## 21 0.7442697 0.7439494 0.8784015 0.7535392
## 41 0.7302637 0.7428591 0.8766258 0.7477161
## 60 0.7384643 0.7454747 0.8773243 0.7470665
## 3 0.7380388 0.7384485 0.8738620 0.7408057
## 22 0.7402033 0.7403878 0.8745296 0.7477666
## 42 0.7541111 0.7614754 0.8865482 0.7672533
## 61 0.7427568 0.7499286 0.8803161 0.7523172
## 4 0.7461220 0.7480311 0.8793593 0.7498875
## 23 0.7561681 0.7551551 0.8826139 0.7632724
## 43 0.7486633 0.7595351 0.8854277 0.7622445
## 62 0.7393418 0.7474752 0.8794501 0.7512590
## 5 0.7485117 0.7484156 0.8783481 0.7537901
## 24 0.7461051 0.7454499 0.8785112 0.7525808
## 44 0.7454670 0.7587167 0.8847086 0.7679882
## 63 0.7567587 0.7618785 0.8858145 0.7652025
## 6 0.7631329 0.7625242 0.8854308 0.7693010
## 25 0.7580654 0.7585219 0.8850253 0.7639635
## 45 0.7452348 0.7559019 0.8833580 0.7600896
## 64 0.7481535 0.7553904 0.8830292 0.7554946
## 7 0.7593001 0.7584048 0.8839338 0.7639114
## 26 0.7633805 0.7634924 0.8867043 0.7691997
## 46 0.7372250 0.7483993 0.8804983 0.7547927
## 65 0.7598361 0.7671112 0.8894069 0.7681894
## 8 0.7663096 0.7669054 0.8884837 0.7697555
## 27 0.7749586 0.7738115 0.8921545 0.7823281
## 47 0.7401911 0.7516943 0.8833135 0.7594778
## 66 0.7511560 0.7588127 0.8853224 0.7626148
## 9 0.7733934 0.7733247 0.8911952 0.7774483
## 28 0.7685066 0.7672597 0.8886616 0.7745327
## 48 0.7477664 0.7571904 0.8853735 0.7670104
## 67 0.7602687 0.7666261 0.8892511 0.7711765
## 10 0.7630225 0.7623790 0.8868278 0.7670768
## 29 0.7731251 0.7721831 0.8918562 0.7789794
## 49 0.7502744 0.7608254 0.8873458 0.7720503
## 68 0.7553661 0.7630853 0.8880986 0.7666583
## 11 0.7736599 0.7738698 0.8940395 0.7787467
## 30 0.7789619 0.7788408 0.8954313 0.7852555
## 50 0.7617496 0.7729525 0.8935281 0.7844215
## 69 0.7656344 0.7734862 0.8938739 0.7774451
## 12 0.7817821 0.7802971 0.8962296 0.7895580
## 31 0.7802228 0.7805548 0.8958470 0.7856744
## 51 0.7612514 0.7726297 0.8930333 0.7845901
## 70 0.7601058 0.7693790 0.8923107 0.7721930
## 13 0.7835157 0.7817797 0.8973943 0.7905321
## 32 0.7856427 0.7857361 0.8979090 0.7923134
## 52 0.7687550 0.7778862 0.8957174 0.7910687
## 71 0.7607054 0.7684056 0.8915919 0.7733129
## 14 0.7841804 0.7825591 0.8982879 0.7918669
## 33 0.7884630 0.7888025 0.8994876 0.7945402
## 53 0.7650901 0.7740144 0.8939344 0.7855420
## 72 0.7636601 0.7717375 0.8933773 0.7768433
## 15 0.7831516 0.7820273 0.8979750 0.7900428
## 34 0.7882304 0.7892416 0.8998804 0.7925585
## 54 0.7677491 0.7769947 0.8957019 0.7888818
## 73 0.7633156 0.7717744 0.8924521 0.7763256
## 16 0.7879936 0.7864944 0.9001727 0.7955738
## 35 0.7884690 0.7896754 0.9002030 0.7920092
## 55 0.7717573 0.7801706 0.8969807 0.7923013
## 74 0.7688645 0.7768142 0.8953182 0.7816894
## 17 0.7880524 0.7868727 0.9003108 0.7948079
## 36 0.7884395 0.7890206 0.8998804 0.7922908
## 56 0.7715202 0.7802301 0.8968301 0.7923813
## 75 0.7714522 0.7784610 0.8955948 0.7838052
## 18 0.7865102 0.7855207 0.8991656 0.7937685
## 37 0.7896140 0.7899942 0.9003612 0.7939276
## 57 0.7739996 0.7830079 0.8980171 0.7948244
## 76 0.7699093 0.7776120 0.8956587 0.7848725
## 19 0.7875018 0.7854756 0.8990609 0.7951182
## 38 0.7905062 0.7908474 0.9010173 0.7951369
## Mean_Neg_Pred_Value Mean_Precision Mean_Recall Mean_Detection_Rate
## 39 0.8693989 0.7203882 0.7214393 0.2460638
## 58 0.8735208 0.7384755 0.7342882 0.2492037
## 1 0.8678523 0.7179639 0.7195978 0.2446384
## 20 0.8702088 0.7407179 0.7332680 0.2481620
## 40 0.8811055 0.7230738 0.7242612 0.2477996
## 59 0.8787375 0.7163039 0.7136512 0.2460455
## 2 0.8790552 0.7348175 0.7330113 0.2506033
## 21 0.8849721 0.7535392 0.7439494 0.2547919
## 41 0.8892817 0.7477161 0.7428591 0.2537872
## 60 0.8857836 0.7470665 0.7454747 0.2540941
## 3 0.8761280 0.7408057 0.7384485 0.2509913
## 22 0.8770798 0.7477666 0.7403878 0.2516597
## 42 0.8980195 0.7672533 0.7614754 0.2604171
## 61 0.8899802 0.7523172 0.7499286 0.2561844
## 4 0.8837889 0.7498875 0.7480311 0.2548214
## 23 0.8855146 0.7632724 0.7551551 0.2569159
## 43 0.8972404 0.7622445 0.7595351 0.2593829
## 62 0.8908735 0.7512590 0.7474752 0.2558780
## 5 0.8802015 0.7537901 0.7484156 0.2537540
## 24 0.8804118 0.7525808 0.7454499 0.2537837
## 44 0.8995631 0.7679882 0.7587167 0.2593829
## 63 0.8946273 0.7652025 0.7618785 0.2597231
## 6 0.8887356 0.7693010 0.7625242 0.2589953
## 25 0.8884618 0.7639635 0.7585219 0.2583158
## 45 0.8972547 0.7600896 0.7559019 0.2586921
## 64 0.8917583 0.7554946 0.7553904 0.2575992
## 7 0.8850949 0.7639114 0.7584048 0.2572446
## 26 0.8892814 0.7691997 0.7634924 0.2593832
## 46 0.8958753 0.7547927 0.7483993 0.2569228
## 65 0.8980060 0.7681894 0.7671112 0.2614887
## 8 0.8921189 0.7697555 0.7669054 0.2607793
## 27 0.8957470 0.7823281 0.7738115 0.2632321
## 47 0.8986540 0.7594778 0.7516943 0.2583266
## 66 0.8962528 0.7626148 0.7588127 0.2593796
## 9 0.8942573 0.7774483 0.7733247 0.2625413
## 28 0.8913391 0.7745327 0.7672597 0.2607795
## 48 0.9008506 0.7670104 0.7571904 0.2600737
## 67 0.8991277 0.7711765 0.7666261 0.2618062
## 10 0.8905381 0.7670768 0.7623790 0.2597230
## 29 0.8943265 0.7789794 0.7721831 0.2625265
## 49 0.9040818 0.7720503 0.7608254 0.2615030
## 68 0.8993577 0.7666583 0.7630853 0.2611301
## 11 0.8967414 0.7787467 0.7738698 0.2635865
## 30 0.8990249 0.7852555 0.7788408 0.2649939
## 50 0.9091187 0.7844215 0.7729525 0.2650009
## 69 0.9050358 0.7774451 0.7734862 0.2646502
## 12 0.8997388 0.7895580 0.7802971 0.2656920
## 31 0.8994597 0.7856744 0.7805548 0.2653153
## 51 0.9093315 0.7845901 0.7726297 0.2650047
## 70 0.9033862 0.7721930 0.7693790 0.2632428
## 13 0.8997383 0.7905321 0.7817797 0.2660318
## 32 0.9014763 0.7923134 0.7857361 0.2667263
## 52 0.9112929 0.7910687 0.7778862 0.2667519
## 71 0.9034367 0.7733129 0.7684056 0.2632392
## 14 0.9015820 0.7918669 0.7825591 0.2667299
## 33 0.9041016 0.7945402 0.7888025 0.2681409
## 53 0.9084173 0.7855420 0.7740144 0.2653520
## 72 0.9050674 0.7768433 0.7717375 0.2642883
## 15 0.9008834 0.7900428 0.7820273 0.2663937
## 34 0.9040420 0.7925585 0.7892416 0.2681187
## 54 0.9104146 0.7888818 0.7769947 0.2664083
## 73 0.9042940 0.7763256 0.7717744 0.2639485
## 16 0.9040457 0.7955738 0.7864944 0.2681445
## 35 0.9037795 0.7920092 0.7896754 0.2681224
## 55 0.9120000 0.7923013 0.7801706 0.2674462
## 74 0.9068977 0.7816894 0.7768142 0.2656881
## 17 0.9040138 0.7948079 0.7868727 0.2681445
## 36 0.9037091 0.7922908 0.7890206 0.2681150
## 56 0.9120312 0.7923813 0.7802301 0.2674574
## 75 0.9068596 0.7838052 0.7784610 0.2660464
## 18 0.9026830 0.7937685 0.7855207 0.2674391
## 37 0.9043179 0.7939276 0.7899942 0.2684696
## 57 0.9130942 0.7948244 0.7830079 0.2681703
## 76 0.9079962 0.7848725 0.7776120 0.2660390
## 19 0.9022665 0.7951182 0.7854756 0.2674354
## 38 0.9049415 0.7951369 0.7908474 0.2688352
## Mean_Balanced_Accuracy logLossSD AUCSD prAUCSD AccuracySD
## 39 0.7950866 1.26197292 0.02669086 0.09802544 0.03601103
## 58 0.8029927 1.42608709 0.03859823 0.09759662 0.04788411
## 1 0.7919152 0.11298617 0.02319332 0.06391725 0.04703561
## 20 0.8014307 0.12378294 0.03124258 0.08747079 0.04510927
## 40 0.7959868 0.79123527 0.03095378 0.02873823 0.03790043
## 59 0.7885829 1.60850325 0.04764474 0.02176659 0.04641712
## 2 0.8024434 1.14224005 0.02841643 0.02395132 0.02611790
## 21 0.8111755 1.21361607 0.03075393 0.02761228 0.04314238
## 41 0.8097425 0.84725158 0.03169843 0.03880580 0.04292380
## 60 0.8113995 0.92456808 0.03873293 0.02244063 0.05748607
## 3 0.8061552 0.91393923 0.02419156 0.03577088 0.03900525
## 22 0.8074587 0.86795870 0.02616879 0.02755225 0.03218430
## 42 0.8240118 0.67823542 0.02484804 0.04041327 0.03911873
## 61 0.8151223 0.88467750 0.03756622 0.02366588 0.05025326
## 4 0.8136952 1.07636245 0.02652924 0.04696199 0.03348309
## 23 0.8188845 1.02892289 0.03234949 0.03394537 0.03179387
## 43 0.8224814 0.71032458 0.02929515 0.03767629 0.04457132
## 62 0.8134626 0.95573818 0.03696961 0.02507496 0.05118487
## 5 0.8133818 0.81233673 0.02271256 0.04472605 0.02881786
## 24 0.8119806 0.83323784 0.02796773 0.03933952 0.03808827
## 44 0.8217127 0.81123557 0.03076724 0.03411326 0.03653517
## 63 0.8238465 0.78699215 0.03190682 0.03110031 0.05358059
## 6 0.8239775 0.53103294 0.02324888 0.04311010 0.03326740
## 25 0.8217736 0.55146716 0.02142596 0.03575684 0.04391405
## 45 0.8196299 0.74317410 0.02960763 0.04738621 0.04015206
## 64 0.8192098 0.77447976 0.03328976 0.02843041 0.05174070
## 7 0.8211693 0.53648250 0.02304708 0.04414994 0.03694958
## 26 0.8250984 0.51399150 0.02196270 0.04115841 0.03932364
## 46 0.8144488 0.64032969 0.02986305 0.03767369 0.04293496
## 65 0.8282591 0.75735530 0.02920705 0.04512639 0.05158321
## 8 0.8276946 0.41620745 0.01957757 0.03645547 0.02956640
## 27 0.8329830 0.37231302 0.01937400 0.04947941 0.04143746
## 47 0.8175039 0.56445215 0.02621782 0.04087433 0.04149547
## 66 0.8220675 0.65434929 0.02936644 0.05130687 0.04671978
## 9 0.8322599 0.42568041 0.02176166 0.04983952 0.03292870
## 28 0.8279607 0.27674193 0.01634298 0.05463534 0.04083135
## 48 0.8212819 0.53956070 0.02695111 0.04451928 0.04240813
## 67 0.8279386 0.62139226 0.02712088 0.05678654 0.04053112
## 10 0.8246034 0.34536482 0.02046931 0.05467356 0.03096991
## 29 0.8320196 0.27355919 0.01836861 0.05939741 0.03394859
## 49 0.8240856 0.19126673 0.02267987 0.04145159 0.03283956
## 68 0.8255920 0.34092223 0.02390603 0.04359462 0.03934078
## 11 0.8339547 0.23870358 0.01820133 0.04038751 0.03361482
## 30 0.8371361 0.28610752 0.02176013 0.05348774 0.03984109
## 50 0.8332403 0.16930340 0.02119816 0.04415982 0.02822802
## 69 0.8336800 0.24547200 0.02257303 0.04101625 0.03407537
## 12 0.8382633 0.17440513 0.02117677 0.04024213 0.03387861
## 31 0.8382009 0.19440650 0.02329260 0.05031692 0.03898263
## 51 0.8328315 0.16979768 0.02034757 0.04623790 0.02941640
## 70 0.8308448 0.16656247 0.02204785 0.04486236 0.03064868
## 13 0.8395870 0.10666364 0.02087640 0.04045236 0.03431305
## 32 0.8418226 0.15859947 0.02473230 0.04889511 0.03882464
## 52 0.8368018 0.16850286 0.02000001 0.04458278 0.03104739
## 71 0.8299987 0.16604304 0.02174263 0.04724990 0.03524275
## 14 0.8404235 0.10598279 0.02112343 0.03616615 0.03297653
## 33 0.8441450 0.15394959 0.02236615 0.04204374 0.04086161
## 53 0.8339744 0.05355855 0.02075354 0.04387413 0.02644225
## 72 0.8325574 0.16485136 0.02110227 0.04750782 0.03765784
## 15 0.8400011 0.05691464 0.02085727 0.03909196 0.03362917
## 34 0.8445610 0.06235584 0.02121055 0.03953007 0.03499119
## 54 0.8363483 0.05280377 0.01984033 0.03796261 0.02683736
## 73 0.8321133 0.16318648 0.02083087 0.04743096 0.03837482
## 16 0.8433335 0.05688378 0.02028938 0.03795597 0.03434247
## 35 0.8449392 0.06479120 0.02251565 0.04070193 0.03496574
## 55 0.8385756 0.05361756 0.02025390 0.03917335 0.02388150
## 74 0.8360662 0.16357333 0.02143230 0.04760397 0.03828301
## 17 0.8435918 0.05553278 0.02013439 0.03862265 0.03676637
## 36 0.8444505 0.06402896 0.02213748 0.03993299 0.03809449
## 56 0.8385301 0.05421114 0.02055659 0.03813419 0.03386591
## 75 0.8370279 0.16351521 0.02071554 0.04596348 0.03472007
## 18 0.8423432 0.05452993 0.01944429 0.03680870 0.03766831
## 37 0.8451777 0.06229369 0.02157639 0.03943625 0.03570780
## 57 0.8405125 0.05645153 0.02128895 0.03637219 0.03312976
## 76 0.8366353 0.16413906 0.02023852 0.04497487 0.03416900
## 19 0.8422682 0.05519652 0.01928457 0.03581795 0.03801585
## 38 0.8459323 0.06219288 0.02172015 0.03904607 0.03186940
## KappaSD Mean_F1SD Mean_SensitivitySD Mean_SpecificitySD
## 39 0.05681019 0.03231878 0.03553743 0.02043570
## 58 0.07741820 0.05301456 0.05747477 0.02608765
## 1 0.07259861 0.04215800 0.04422135 0.02471356
## 20 0.07325270 0.04587470 0.05118658 0.02575565
## 40 0.05897585 0.04143273 0.03892247 0.01994807
## 59 0.07420306 0.05091137 0.04966577 0.02538739
## 2 0.04197639 0.02783233 0.02767560 0.01450477
## 21 0.07137913 0.04434360 0.04906163 0.02539443
## 41 0.07150787 0.05766053 0.05151418 0.02513552
## 60 0.09158259 0.06309030 0.06559085 0.03056202
## 3 0.06091862 0.04216714 0.04345022 0.01968626
## 22 0.05240311 0.03423822 0.03949676 0.01840562
## 42 0.06292152 0.04695760 0.04253062 0.02146795
## 61 0.08019233 0.05562762 0.05576423 0.02736503
## 4 0.05389728 0.03689599 0.03744603 0.01841025
## 23 0.05148164 0.03357490 0.03864443 0.01806187
## 43 0.07063384 0.05376721 0.04872523 0.02404839
## 62 0.08117403 0.05895070 0.05832880 0.02728834
## 5 0.04356640 0.02870308 0.02930024 0.01407153
## 24 0.06144942 0.04153050 0.04590405 0.02110094
## 44 0.05808361 0.04365785 0.03878096 0.02002653
## 63 0.08419551 0.05772150 0.05903101 0.02786987
## 6 0.05230480 0.03495291 0.03615650 0.01738068
## 25 0.07080877 0.04756108 0.05284732 0.02429335
## 45 0.06358966 0.04721183 0.04259365 0.02183474
## 64 0.08115259 0.05864413 0.05842842 0.02649490
## 7 0.05669116 0.04140594 0.03981165 0.01777890
## 26 0.06400060 0.04112696 0.04580184 0.02301963
## 46 0.06782447 0.05085826 0.04583890 0.02263279
## 65 0.08135553 0.05865305 0.05987012 0.02688737
## 8 0.04758259 0.03345913 0.03332935 0.01666064
## 27 0.06623226 0.04635240 0.04983387 0.02273009
## 47 0.06659430 0.04937063 0.04567289 0.02250221
## 66 0.07394266 0.05216378 0.05349885 0.02447847
## 9 0.05244165 0.03694905 0.03746286 0.01779907
## 28 0.06487480 0.04453446 0.04680196 0.02253662
## 48 0.06720153 0.04795510 0.04538641 0.02240869
## 67 0.06486168 0.04697991 0.04837299 0.02142834
## 10 0.05063378 0.03652414 0.03843379 0.01732146
## 29 0.05343940 0.03704541 0.03846528 0.01842703
## 49 0.05434132 0.04035819 0.03750883 0.01951654
## 68 0.06368415 0.04714171 0.04658493 0.02209463
## 11 0.05374641 0.03709858 0.03985227 0.01817060
## 30 0.06457622 0.04568555 0.04891991 0.02273416
## 50 0.04674867 0.03567855 0.03244568 0.01712072
## 69 0.05590175 0.03966224 0.03971091 0.02029143
## 12 0.05472849 0.03602606 0.04012441 0.01907227
## 31 0.06318344 0.04399889 0.04637035 0.02263779
## 51 0.04886837 0.03917129 0.03403019 0.01790093
## 70 0.05017704 0.03481374 0.03608776 0.01786600
## 13 0.05503915 0.03620261 0.03949596 0.01907581
## 32 0.06270098 0.04232729 0.04651123 0.02207138
## 52 0.05090403 0.03800110 0.03622761 0.01812598
## 71 0.05803373 0.04102427 0.04352206 0.02041654
## 14 0.05265098 0.03509411 0.03800652 0.01787709
## 33 0.06619306 0.04363211 0.04766010 0.02324298
## 53 0.04376784 0.03078488 0.03125676 0.01602651
## 72 0.06198902 0.04421170 0.04610647 0.02172040
## 15 0.05367297 0.03433603 0.03769064 0.01856734
## 34 0.05707647 0.03936320 0.04228419 0.02020516
## 54 0.04487682 0.03214675 0.03178551 0.01676148
## 73 0.06266156 0.04545189 0.04548052 0.02188426
## 16 0.05470377 0.03577270 0.03924258 0.01857432
## 35 0.05650342 0.03827086 0.04068216 0.01983203
## 55 0.03997911 0.02917812 0.02923586 0.01472537
## 74 0.06242672 0.04452347 0.04509391 0.02179653
## 17 0.05865926 0.03910252 0.04206211 0.01993961
## 36 0.06179229 0.04169803 0.04409802 0.02180000
## 56 0.05579638 0.04175139 0.03973470 0.01980127
## 75 0.05710499 0.04036985 0.04179570 0.02021548
## 18 0.05994552 0.04024507 0.04363568 0.02012205
## 37 0.05792360 0.04034217 0.04232331 0.02039560
## 57 0.05453309 0.04028715 0.03959932 0.01950015
## 76 0.05652595 0.04087210 0.04222306 0.02014606
## 19 0.06018135 0.03949784 0.04245921 0.02017025
## 38 0.05214303 0.03684885 0.03937103 0.01847994
## Mean_Pos_Pred_ValueSD Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD
## 39 0.02998882 0.02037896 0.02998882 0.03553743
## 58 0.04621281 0.02389567 0.04621281 0.05747477
## 1 0.04421817 0.02761719 0.04421817 0.04422135
## 20 0.03707760 0.02375484 0.03707760 0.05118658
## 40 0.04872877 0.02163241 0.04872877 0.03892247
## 59 0.05285215 0.02442831 0.05285215 0.04966577
## 2 0.02884807 0.01474110 0.02884807 0.02767560
## 21 0.03366092 0.02331849 0.03366092 0.04906163
## 41 0.06346844 0.02000355 0.06346844 0.05151418
## 60 0.06564681 0.02948169 0.06564681 0.06559085
## 3 0.04114222 0.02025977 0.04114222 0.04345022
## 22 0.02567741 0.01661003 0.02567741 0.03949676
## 42 0.04921213 0.01873079 0.04921213 0.04253062
## 61 0.05575595 0.02523662 0.05575595 0.05576423
## 4 0.03637348 0.01674801 0.03637348 0.03744603
## 23 0.02687098 0.01665253 0.02687098 0.03864443
## 43 0.05720195 0.02076561 0.05720195 0.04872523
## 62 0.05796352 0.02486537 0.05796352 0.05832880
## 5 0.02806396 0.01560642 0.02806396 0.02930024
## 24 0.03682452 0.01896888 0.03682452 0.04590405
## 44 0.05058806 0.01885442 0.05058806 0.03878096
## 63 0.05767832 0.02770519 0.05767832 0.05903101
## 6 0.03178277 0.01722287 0.03178277 0.03615650
## 25 0.04109856 0.02195430 0.04109856 0.05284732
## 45 0.04895866 0.01905854 0.04895866 0.04259365
## 64 0.05905129 0.02548676 0.05905129 0.05842842
## 7 0.04232212 0.01833095 0.04232212 0.03981165
## 26 0.03554257 0.02007458 0.03554257 0.04580184
## 46 0.05813749 0.02122548 0.05813749 0.04583890
## 65 0.05659038 0.02514076 0.05659038 0.05987012
## 8 0.03173899 0.01406662 0.03173899 0.03332935
## 27 0.04023332 0.02002117 0.04023332 0.04983387
## 47 0.05495988 0.02065135 0.05495988 0.04567289
## 66 0.05251775 0.02370868 0.05251775 0.05349885
## 9 0.03599456 0.01616990 0.03599456 0.03746286
## 28 0.04029730 0.02019486 0.04029730 0.04680196
## 48 0.05412289 0.02171586 0.05412289 0.04538641
## 67 0.04761735 0.02027254 0.04761735 0.04837299
## 10 0.03354942 0.01431345 0.03354942 0.03843379
## 29 0.03485871 0.01688737 0.03485871 0.03846528
## 49 0.04097016 0.01497465 0.04097016 0.03750883
## 68 0.04347144 0.01774646 0.04347144 0.04658493
## 11 0.03245246 0.01653287 0.03245246 0.03985227
## 30 0.03940775 0.01825548 0.03940775 0.04891991
## 50 0.03297852 0.01256155 0.03297852 0.03244568
## 69 0.03621938 0.01510933 0.03621938 0.03971091
## 12 0.02795957 0.01682372 0.02795957 0.04012441
## 31 0.03912607 0.01838976 0.03912607 0.04637035
## 51 0.03697999 0.01222440 0.03697999 0.03403019
## 70 0.03474357 0.01436200 0.03474357 0.03608776
## 13 0.03129475 0.01760070 0.03129475 0.03949596
## 32 0.03533804 0.01920214 0.03533804 0.04651123
## 52 0.04032433 0.01422718 0.04032433 0.03622761
## 71 0.03942945 0.01629676 0.03942945 0.04352206
## 14 0.03068234 0.01692120 0.03068234 0.03800652
## 33 0.03717437 0.02022177 0.03717437 0.04766010
## 53 0.03326150 0.01282258 0.03326150 0.03125676
## 72 0.04315935 0.01707980 0.04315935 0.04610647
## 15 0.02863923 0.01745733 0.02863923 0.03769064
## 34 0.03387076 0.01649211 0.03387076 0.04228419
## 54 0.03312521 0.01209076 0.03312521 0.03178551
## 73 0.04381869 0.01726375 0.04381869 0.04548052
## 16 0.02999139 0.01766678 0.02999139 0.03924258
## 35 0.03432975 0.01734009 0.03432975 0.04068216
## 55 0.02903226 0.01068754 0.02903226 0.02923586
## 74 0.04341918 0.01778236 0.04341918 0.04509391
## 17 0.03278455 0.01869577 0.03278455 0.04206211
## 36 0.03694346 0.01835932 0.03694346 0.04409802
## 56 0.04183194 0.01490998 0.04183194 0.03973470
## 75 0.03882325 0.01582891 0.03882325 0.04179570
## 18 0.03412265 0.01915699 0.03412265 0.04363568
## 37 0.03578768 0.01681694 0.03578768 0.04232331
## 57 0.03930587 0.01421304 0.03930587 0.03959932
## 76 0.03816803 0.01513668 0.03816803 0.04222306
## 19 0.03323493 0.01972288 0.03323493 0.04245921
## 38 0.03126924 0.01475714 0.03126924 0.03937103
## Mean_Detection_RateSD Mean_Balanced_AccuracySD
## 39 0.012003678 0.02787560
## 58 0.015961369 0.04162310
## 1 0.015678538 0.03441792
## 20 0.015036422 0.03833590
## 40 0.012633475 0.02932242
## 59 0.015472372 0.03738377
## 2 0.008705966 0.02105694
## 21 0.014380794 0.03712823
## 41 0.014307935 0.03820438
## 60 0.019162025 0.04798675
## 3 0.013001750 0.03148697
## 22 0.010728100 0.02878821
## 42 0.013039576 0.03190957
## 61 0.016751086 0.04145610
## 4 0.011161028 0.02787689
## 23 0.010597957 0.02811383
## 43 0.014857106 0.03629726
## 62 0.017061623 0.04269599
## 5 0.009605952 0.02152923
## 24 0.012696089 0.03342150
## 44 0.012178389 0.02929842
## 63 0.017860196 0.04338575
## 6 0.011089134 0.02666623
## 25 0.014638016 0.03844684
## 45 0.013384019 0.03212669
## 64 0.017246901 0.04235836
## 7 0.012316528 0.02871649
## 26 0.013107879 0.03423313
## 46 0.014311654 0.03417123
## 65 0.017194403 0.04319774
## 8 0.009855465 0.02490594
## 27 0.013812488 0.03606707
## 47 0.013831823 0.03402589
## 66 0.015573260 0.03882129
## 9 0.010976234 0.02756638
## 28 0.013610449 0.03435514
## 48 0.014136045 0.03384677
## 67 0.013510372 0.03468727
## 10 0.010323305 0.02779532
## 29 0.011316196 0.02821434
## 49 0.010946521 0.02841790
## 68 0.013113592 0.03413647
## 11 0.011204942 0.02892509
## 30 0.013280363 0.03573198
## 50 0.009409341 0.02470851
## 69 0.011358458 0.02982153
## 12 0.011292869 0.02948154
## 31 0.012994211 0.03432725
## 51 0.009805466 0.02585427
## 70 0.010216228 0.02681321
## 13 0.011437682 0.02914796
## 32 0.012941546 0.03415708
## 52 0.010349130 0.02702831
## 71 0.011747583 0.03174223
## 14 0.010992176 0.02781760
## 33 0.013620538 0.03537388
## 53 0.008814084 0.02353351
## 72 0.012552612 0.03374083
## 15 0.011209723 0.02803043
## 34 0.011663730 0.03111150
## 54 0.008945785 0.02415665
## 73 0.012791607 0.03350722
## 16 0.011447490 0.02880981
## 35 0.011655246 0.03009497
## 55 0.007960499 0.02177688
## 74 0.012761005 0.03328343
## 17 0.012255457 0.03089021
## 36 0.012698163 0.03282599
## 56 0.011288635 0.02965750
## 75 0.011573356 0.03084121
## 18 0.012556103 0.03176118
## 37 0.011902598 0.03118768
## 57 0.011043255 0.02943416
## 76 0.011389665 0.03103702
## 19 0.012671950 0.03117779
## 38 0.010623134 0.02876715(C50_Train_Accuracy <- C50_Tune$results[C50_Tune$results$trials==C50_Tune$bestTune$trials &
C50_Tune$results$model==C50_Tune$bestTune$model &
C50_Tune$results$winnow==C50_Tune$bestTune$winnow,
c("Accuracy")])## [1] 0.8065057##################################
# Identifying and plotting the
# best model predictors
##################################
C50_VarImp <- varImp(C50_Tune, scale = TRUE)
plot(C50_VarImp,
top=25,
scales=list(y=list(cex = .95)),
main="Ranked Variable Importance : C5.0 Decision Trees",
xlab="Scaled Variable Importance Metrics",
ylab="Predictors",
cex=2,
origin=0,
alpha=0.45)
##################################
# Independently evaluating the model
# on the test set
##################################
C50_Test <- data.frame(C50_Observed = PMA_PreModelling_Test_C50$Log_Solubility_Class,
C50_Predicted = predict(C50_Tune,
PMA_PreModelling_Test_C50[,!names(PMA_PreModelling_Test_C50) %in% c("Log_Solubility_Class")],
type = "raw"))
C50_Test## C50_Observed C50_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Mid
## 13 High High
## 14 High High
## 15 High High
## 16 High High
## 17 High High
## 18 High High
## 19 High High
## 20 High High
## 21 High High
## 22 High Mid
## 23 High High
## 24 High High
## 25 High High
## 26 High High
## 27 High Mid
## 28 High High
## 29 High Mid
## 30 High Mid
## 31 High Low
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High Low
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High High
## 50 High High
## 51 High Mid
## 52 High Mid
## 53 High Mid
## 54 High High
## 55 High Mid
## 56 High Low
## 57 High Mid
## 58 Mid High
## 59 Mid Mid
## 60 Mid Mid
## 61 Mid High
## 62 Mid Mid
## 63 Mid High
## 64 Mid Mid
## 65 Mid Mid
## 66 Mid Mid
## 67 Mid Mid
## 68 Mid High
## 69 Mid Low
## 70 Mid Mid
## 71 Mid Mid
## 72 Mid Low
## 73 Mid Mid
## 74 Mid Mid
## 75 Mid High
## 76 Mid Mid
## 77 Mid Mid
## 78 Mid Mid
## 79 Mid Mid
## 80 Mid Mid
## 81 Mid High
## 82 Mid High
## 83 Mid Low
## 84 Mid Mid
## 85 Mid Low
## 86 Mid Mid
## 87 Mid Mid
## 88 Mid Mid
## 89 Mid Mid
## 90 Mid Mid
## 91 Mid Mid
## 92 Mid Mid
## 93 Mid Mid
## 94 Mid High
## 95 Mid Mid
## 96 Mid Mid
## 97 Mid Low
## 98 Mid Low
## 99 Mid High
## 100 Mid Mid
## 101 Mid Mid
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid Mid
## 105 Mid Low
## 106 Mid Low
## 107 Mid Low
## 108 Mid Mid
## 109 Mid Low
## 110 Mid Mid
## 111 Mid Low
## 112 Mid Mid
## 113 Mid Low
## 114 Mid Low
## 115 Mid Mid
## 116 Mid Low
## 117 Mid Mid
## 118 Mid Low
## 119 Low Low
## 120 Low Mid
## 121 Low Low
## 122 Low Mid
## 123 Low Low
## 124 Low Low
## 125 Low Low
## 126 Low Mid
## 127 Low Low
## 128 Low Low
## 129 Low Low
## 130 Low Low
## 131 Low Low
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low Low
## 136 Low Low
## 137 Low Low
## 138 Low Low
## 139 Low Low
## 140 Low Mid
## 141 Low Low
## 142 Low Mid
## 143 Low Low
## 144 Low Low
## 145 Low Mid
## 146 Low Mid
## 147 Low Low
## 148 Low Low
## 149 Low Low
## 150 Low Low
## 151 Low High
## 152 Low Low
## 153 Low Low
## 154 Low Low
## 155 Low Low
## 156 Low Low
## 157 Low Low
## 158 Low Low
## 159 Low Low
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Low
## 183 Low Low
## 184 Low Low
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High High
## 222 High High
## 223 High High
## 224 High High
## 225 High Mid
## 226 High High
## 227 High High
## 228 High High
## 229 High High
## 230 High Mid
## 231 High High
## 232 High Mid
## 233 High High
## 234 High High
## 235 High High
## 236 High Mid
## 237 High Mid
## 238 Mid Mid
## 239 Mid Mid
## 240 Mid High
## 241 Mid High
## 242 Mid Mid
## 243 Mid Mid
## 244 Mid High
## 245 Mid Mid
## 246 Mid High
## 247 Mid Mid
## 248 Mid High
## 249 Mid Mid
## 250 Mid Mid
## 251 Mid Mid
## 252 Mid High
## 253 Mid Mid
## 254 Mid Low
## 255 Mid Mid
## 256 Mid Mid
## 257 Mid Mid
## 258 Mid Mid
## 259 Mid Mid
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid Mid
## 263 Mid Mid
## 264 Mid Mid
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Low
## 268 Mid Mid
## 269 Low Low
## 270 Low Low
## 271 Low Low
## 272 Low Mid
## 273 Low Low
## 274 Low Low
## 275 Low Low
## 276 Low Low
## 277 Low Low
## 278 Low Mid
## 279 Low Low
## 280 Low Low
## 281 Low Low
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Low
## 287 Low Low
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(C50_Test_Accuracy <- Accuracy(y_pred = C50_Test$C50_Predicted,
y_true = C50_Test$C50_Observed))## [1] 0.79746841.5.14 Random Forest (RF)
Random Forest is an ensemble learning method made up of a large set of small decision trees called estimators, with each producing its own prediction. The random forest model aggregates the predictions of the estimators to produce a more accurate prediction. The algorithm involves bootstrap aggregating (where smaller subsets of the training data are repeatedly subsampled with replacement), random subspacing (where a subset of features are sampled and used to train each individual estimator), estimator training (where unpruned decision trees are formulated for each estimator) and inference by aggregating the predictions of all estimators.
[A] The random forest model from the randomForest package was implemented through the caret package.
[B] The model contains 1 hyperparameter:
[B.1] mtry = number of randomly selected predictors made to vary across a range of values equal to 25 to 125
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration involves mtry=125
[C.2] Accuracy = 0.82131
[D] The model allows for ranking of predictors in terms of variable importance. The top-performing predictors in the model are as follows:
[D.1] MolWeight variable (numeric)
[D.2] NumCarbon variable (numeric)
[D.3] HydroPhilicFactor variable (numeric)
[D.4] NumBonds variable (numeric)
[D.5] SurfaceArea1 variable (numeric)
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.83861
Code Chunk | Output
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_RF <- PMA_PreModelling_Train
PMA_PreModelling_Test_RF <- PMA_PreModelling_Test
##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_RF$Log_Solubility_Class,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
RF_Grid = data.frame(mtry = c(25,75,125))
##################################
# Running the random forest model
# by setting the caret method to 'rf'
##################################
set.seed(12345678)
RF_Tune <- train(x = PMA_PreModelling_Train_RF[,!names(PMA_PreModelling_Train_RF) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_RF$Log_Solubility_Class,
method = "rf",
tuneGrid = RF_Grid,
metric = "Accuracy",
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
RF_Tune## Random Forest
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## No pre-processing
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results across tuning parameters:
##
## mtry logLoss AUC prAUC Accuracy Kappa Mean_F1
## 25 0.4462239 0.9380318 0.8130727 0.8191933 0.7174161 0.8056486
## 75 0.4360232 0.9400867 0.8104672 0.8192042 0.7169067 0.8045893
## 125 0.4366238 0.9399228 0.7952400 0.8213097 0.7204875 0.8077254
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.8026215 0.9064782 0.8132709 0.9113003
## 0.8008399 0.9058877 0.8151338 0.9123177
## 0.8035951 0.9070571 0.8162022 0.9126181
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.8132709 0.8026215 0.2730644 0.8545499
## 0.8151338 0.8008399 0.2730681 0.8533638
## 0.8162022 0.8035951 0.2737699 0.8553261
##
## Accuracy was used to select the optimal model using the largest value.
## The final value used for the model was mtry = 125.RF_Tune$finalModel##
## Call:
## randomForest(x = x, y = y, mtry = param$mtry)
## Type of random forest: classification
## Number of trees: 500
## No. of variables tried at each split: 125
##
## OOB estimate of error rate: 18.51%
## Confusion matrix:
## Low Mid High class.error
## Low 395 32 0 0.07494145
## Mid 67 186 30 0.34275618
## High 4 43 194 0.19502075RF_Tune$results## mtry logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 25 0.4462239 0.9380318 0.8130727 0.8191933 0.7174161 0.8056486
## 2 75 0.4360232 0.9400867 0.8104672 0.8192042 0.7169067 0.8045893
## 3 125 0.4366238 0.9399228 0.7952400 0.8213097 0.7204875 0.8077254
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.8026215 0.9064782 0.8132709 0.9113003
## 2 0.8008399 0.9058877 0.8151338 0.9123177
## 3 0.8035951 0.9070571 0.8162022 0.9126181
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.8132709 0.8026215 0.2730644 0.8545499
## 2 0.8151338 0.8008399 0.2730681 0.8533638
## 3 0.8162022 0.8035951 0.2737699 0.8553261
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 0.06222865 0.02113626 0.04061799 0.04214814 0.06770662 0.04558738
## 2 0.06639577 0.02070023 0.04274670 0.04277842 0.06845144 0.04760295
## 3 0.06832290 0.02130083 0.04130356 0.04102100 0.06495421 0.04549251
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.04846113 0.02303450 0.04169781
## 2 0.04886793 0.02293834 0.04370933
## 3 0.04612283 0.02135576 0.04288773
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.02082675 0.04169781 0.04846113 0.01404938
## 2 0.02082426 0.04370933 0.04886793 0.01425947
## 3 0.02006362 0.04288773 0.04612283 0.01367367
## Mean_Balanced_AccuracySD
## 1 0.03567161
## 2 0.03584598
## 3 0.03367716(RF_Train_Accuracy <- RF_Tune$results[RF_Tune$results$mtry==RF_Tune$bestTune$mtry,
c("Accuracy")])## [1] 0.8213097##################################
# Identifying and plotting the
# best model predictors
##################################
RF_VarImp <- varImp(RF_Tune, scale = TRUE)
plot(RF_VarImp,
top=25,
scales=list(y=list(cex = .95)),
main="Ranked Variable Importance : Random Forest",
xlab="Scaled Variable Importance Metrics",
ylab="Predictors",
cex=2,
origin=0,
alpha=0.45)
##################################
# Independently evaluating the model
# on the test set
##################################
RF_Test <- data.frame(RF_Observed = PMA_PreModelling_Test_RF$Log_Solubility_Class,
RF_Predicted = predict(RF_Tune,
PMA_PreModelling_Test_RF[,!names(PMA_PreModelling_Test_RF) %in% c("Log_Solubility_Class")],
type = "raw"))
RF_Test## RF_Observed RF_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Mid
## 13 High High
## 14 High High
## 15 High High
## 16 High High
## 17 High High
## 18 High High
## 19 High High
## 20 High High
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High High
## 27 High High
## 28 High High
## 29 High Mid
## 30 High High
## 31 High Low
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High Low
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High High
## 50 High High
## 51 High Mid
## 52 High Mid
## 53 High Mid
## 54 High High
## 55 High Mid
## 56 High High
## 57 High Mid
## 58 Mid Mid
## 59 Mid Mid
## 60 Mid Mid
## 61 Mid Mid
## 62 Mid Mid
## 63 Mid High
## 64 Mid Mid
## 65 Mid Mid
## 66 Mid Mid
## 67 Mid Mid
## 68 Mid Mid
## 69 Mid High
## 70 Mid Mid
## 71 Mid Low
## 72 Mid Mid
## 73 Mid Mid
## 74 Mid Low
## 75 Mid High
## 76 Mid Mid
## 77 Mid Mid
## 78 Mid Mid
## 79 Mid Mid
## 80 Mid Mid
## 81 Mid Mid
## 82 Mid High
## 83 Mid Low
## 84 Mid Mid
## 85 Mid Mid
## 86 Mid Mid
## 87 Mid Low
## 88 Mid Mid
## 89 Mid Mid
## 90 Mid Mid
## 91 Mid Mid
## 92 Mid Mid
## 93 Mid Mid
## 94 Mid Mid
## 95 Mid Mid
## 96 Mid Mid
## 97 Mid Mid
## 98 Mid Low
## 99 Mid High
## 100 Mid Mid
## 101 Mid Mid
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid Mid
## 105 Mid Mid
## 106 Mid Low
## 107 Mid Mid
## 108 Mid Mid
## 109 Mid Mid
## 110 Mid Mid
## 111 Mid Low
## 112 Mid Mid
## 113 Mid Low
## 114 Mid Mid
## 115 Mid Low
## 116 Mid Low
## 117 Mid Low
## 118 Mid Low
## 119 Low Low
## 120 Low Mid
## 121 Low Low
## 122 Low Mid
## 123 Low Low
## 124 Low Mid
## 125 Low Low
## 126 Low Low
## 127 Low Low
## 128 Low Low
## 129 Low Low
## 130 Low Low
## 131 Low Low
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low Low
## 136 Low Low
## 137 Low Low
## 138 Low Low
## 139 Low Low
## 140 Low Mid
## 141 Low Low
## 142 Low Mid
## 143 Low Low
## 144 Low Low
## 145 Low Mid
## 146 Low Low
## 147 Low Low
## 148 Low Low
## 149 Low Low
## 150 Low Low
## 151 Low Low
## 152 Low Low
## 153 Low Low
## 154 Low Low
## 155 Low Low
## 156 Low Low
## 157 Low Low
## 158 Low Low
## 159 Low Low
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Low
## 183 Low Low
## 184 Low Low
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Mid
## 226 High High
## 227 High High
## 228 High Mid
## 229 High High
## 230 High Mid
## 231 High High
## 232 High High
## 233 High High
## 234 High High
## 235 High High
## 236 High Mid
## 237 High Low
## 238 Mid Mid
## 239 Mid Mid
## 240 Mid Mid
## 241 Mid High
## 242 Mid High
## 243 Mid Mid
## 244 Mid Mid
## 245 Mid Mid
## 246 Mid High
## 247 Mid Mid
## 248 Mid High
## 249 Mid Mid
## 250 Mid Mid
## 251 Mid Mid
## 252 Mid High
## 253 Mid Mid
## 254 Mid Low
## 255 Mid Mid
## 256 Mid High
## 257 Mid Mid
## 258 Mid Mid
## 259 Mid Mid
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid Mid
## 263 Mid Mid
## 264 Mid Mid
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Low
## 268 Mid Low
## 269 Low Low
## 270 Low Low
## 271 Low Low
## 272 Low Low
## 273 Low Low
## 274 Low Low
## 275 Low Low
## 276 Low Low
## 277 Low Low
## 278 Low Low
## 279 Low Low
## 280 Low Low
## 281 Low Low
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Low
## 287 Low Low
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(RF_Test_Accuracy <- Accuracy(y_pred = RF_Test$RF_Predicted,
y_true = RF_Test$RF_Observed))## [1] 0.83860761.5.15 Bagged Trees (BTREE)
Bagged Trees combine bootstrapping and decision trees to construct an ensemble. The modeling process involves generating bootstrap samples of the original data, training an unpruned decision tree for each bootstrap subset of the data and implementing an ensemble voting for all the individual decision tree predictions to formulate the final prediction. The bootstrap aggregation (bagging) mechanism improves the model performance by reducing variance. Although the individual decision trees in the model are identically distributed, they are not necessarily independent and share similar structure. This similarity, known as tree correlation, is an essential factor that prevents further reduction of variance.
[A] The bagged trees model from the ipred, plyr and e1071 packages was implemented through the caret package.
[B] The model does not contain any hyperparameter.
[C] The cross-validated model performance of the final model is summarized as follows:
[C.1] Final model configuration is fixed due to the absence of a hyperparameter
[C.2] Accuracy = 0.81078
[D] The model allows for ranking of predictors in terms of variable importance. The top-performing predictors in the model are as follows:
[D.1] MolWeight variable (numeric)
[D.2] NumCarbon variable (numeric)
[D.3] NumBonds variable (numeric)
[D.4] SurfaceArea1 variable (numeric)
[D.5] HydrophilicFactor variable (numeric)
[E] The independent test model performance of the final model is summarized as follows:
[E.1] Accuracy = 0.81329
Code Chunk | Output
##################################
# Creating a local object
# for the train and test sets
##################################
PMA_PreModelling_Train_BTREE <- PMA_PreModelling_Train
PMA_PreModelling_Test_BTREE <- PMA_PreModelling_Test
##################################
# Creating consistent fold assignments
# for the 10-Fold Cross Validation process
##################################
set.seed(12345678)
KFold_Indices <- createFolds(PMA_PreModelling_Train_BTREE$Log_Solubility,
k = 10,
returnTrain=TRUE)
KFold_Control <- trainControl(method="cv",
index=KFold_Indices,
summaryFunction = multiClassSummary,
classProbs = TRUE)
##################################
# Setting the conditions
# for hyperparameter tuning
##################################
# No hyperparameter tuning process conducted
##################################
# Running the bagged trees model
# by setting the caret method to 'treebag'
##################################
set.seed(12345678)
BTREE_Tune <- train(x = PMA_PreModelling_Train_BTREE[,!names(PMA_PreModelling_Train_BTREE) %in% c("Log_Solubility_Class")],
y = PMA_PreModelling_Train_BTREE$Log_Solubility_Class,
method = "treebag",
nbagg = 50,
metric = "Accuracy",
trControl = KFold_Control)
##################################
# Reporting the cross-validation results
# for the train set
##################################
BTREE_Tune## Bagged CART
##
## 951 samples
## 220 predictors
## 3 classes: 'Low', 'Mid', 'High'
##
## No pre-processing
## Resampling: Cross-Validated (10 fold)
## Summary of sample sizes: 856, 855, 856, 855, 857, 856, ...
## Resampling results:
##
## logLoss AUC prAUC Accuracy Kappa Mean_F1
## 0.6081849 0.9326071 0.7041064 0.8107827 0.7035657 0.7971691
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 0.7925209 0.9012913 0.8079533 0.9070897
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 0.8079533 0.7925209 0.2702609 0.8469061BTREE_Tune$finalModel##
## Bagging classification trees with 50 bootstrap replicationsBTREE_Tune$results## parameter logLoss AUC prAUC Accuracy Kappa Mean_F1
## 1 none 0.6081849 0.9326071 0.7041064 0.8107827 0.7035657 0.7971691
## Mean_Sensitivity Mean_Specificity Mean_Pos_Pred_Value Mean_Neg_Pred_Value
## 1 0.7925209 0.9012913 0.8079533 0.9070897
## Mean_Precision Mean_Recall Mean_Detection_Rate Mean_Balanced_Accuracy
## 1 0.8079533 0.7925209 0.2702609 0.8469061
## logLossSD AUCSD prAUCSD AccuracySD KappaSD Mean_F1SD
## 1 0.2935258 0.02255702 0.0409326 0.05142226 0.08239393 0.05664061
## Mean_SensitivitySD Mean_SpecificitySD Mean_Pos_Pred_ValueSD
## 1 0.0597361 0.02729944 0.04719834
## Mean_Neg_Pred_ValueSD Mean_PrecisionSD Mean_RecallSD Mean_Detection_RateSD
## 1 0.02549526 0.04719834 0.0597361 0.01714075
## Mean_Balanced_AccuracySD
## 1 0.04345743(BTREE_Train_Accuracy <- BTREE_Tune$results$Accuracy)## [1] 0.8107827##################################
# Identifying and plotting the
# best model predictors
##################################
BTREE_VarImp <- varImp(BTREE_Tune, scale = TRUE)
plot(BTREE_VarImp,
top=25,
scales=list(y=list(cex = .95)),
main="Ranked Variable Importance : Bagged Trees",
xlab="Scaled Variable Importance Metrics",
ylab="Predictors",
cex=2,
origin=0,
alpha=0.45)
##################################
# Independently evaluating the model
# on the test set
##################################
BTREE_Test <- data.frame(BTREE_Observed = PMA_PreModelling_Test_BTREE$Log_Solubility_Class,
BTREE_Predicted = predict(BTREE_Tune,
PMA_PreModelling_Test_BTREE[,!names(PMA_PreModelling_Test_BTREE) %in% c("Log_Solubility_Class")],
type = "raw"))
BTREE_Test## BTREE_Observed BTREE_Predicted
## 1 High High
## 2 High High
## 3 High High
## 4 High High
## 5 High High
## 6 High High
## 7 High High
## 8 High High
## 9 High High
## 10 High High
## 11 High High
## 12 High Mid
## 13 High High
## 14 High High
## 15 High High
## 16 High High
## 17 High High
## 18 High High
## 19 High High
## 20 High High
## 21 High High
## 22 High High
## 23 High High
## 24 High High
## 25 High High
## 26 High High
## 27 High High
## 28 High High
## 29 High Mid
## 30 High High
## 31 High Low
## 32 High High
## 33 High High
## 34 High High
## 35 High High
## 36 High High
## 37 High High
## 38 High High
## 39 High High
## 40 High High
## 41 High High
## 42 High High
## 43 High Mid
## 44 High High
## 45 High High
## 46 High High
## 47 High High
## 48 High High
## 49 High High
## 50 High High
## 51 High High
## 52 High Mid
## 53 High Mid
## 54 High Mid
## 55 High Mid
## 56 High High
## 57 High Mid
## 58 Mid Mid
## 59 Mid Mid
## 60 Mid Mid
## 61 Mid Mid
## 62 Mid Mid
## 63 Mid High
## 64 Mid Mid
## 65 Mid Mid
## 66 Mid Mid
## 67 Mid Mid
## 68 Mid Mid
## 69 Mid High
## 70 Mid Mid
## 71 Mid Low
## 72 Mid Low
## 73 Mid Mid
## 74 Mid Mid
## 75 Mid High
## 76 Mid Mid
## 77 Mid Mid
## 78 Mid Mid
## 79 Mid Mid
## 80 Mid High
## 81 Mid Mid
## 82 Mid High
## 83 Mid High
## 84 Mid Mid
## 85 Mid Mid
## 86 Mid Mid
## 87 Mid Low
## 88 Mid Mid
## 89 Mid Mid
## 90 Mid Mid
## 91 Mid Mid
## 92 Mid Mid
## 93 Mid Low
## 94 Mid High
## 95 Mid Mid
## 96 Mid Mid
## 97 Mid Mid
## 98 Mid Low
## 99 Mid High
## 100 Mid Mid
## 101 Mid Mid
## 102 Mid Mid
## 103 Mid Mid
## 104 Mid Mid
## 105 Mid Mid
## 106 Mid Low
## 107 Mid Mid
## 108 Mid Mid
## 109 Mid Low
## 110 Mid Low
## 111 Mid Low
## 112 Mid Mid
## 113 Mid Low
## 114 Mid Mid
## 115 Mid Mid
## 116 Mid Low
## 117 Mid Low
## 118 Mid Low
## 119 Low Low
## 120 Low Mid
## 121 Low Mid
## 122 Low Mid
## 123 Low Low
## 124 Low Mid
## 125 Low Low
## 126 Low Low
## 127 Low Low
## 128 Low Low
## 129 Low Low
## 130 Low Low
## 131 Low Low
## 132 Low Low
## 133 Low Low
## 134 Low Low
## 135 Low Low
## 136 Low Low
## 137 Low Low
## 138 Low Low
## 139 Low Low
## 140 Low Mid
## 141 Low Low
## 142 Low Mid
## 143 Low Low
## 144 Low Low
## 145 Low Mid
## 146 Low Mid
## 147 Low Low
## 148 Low Low
## 149 Low Low
## 150 Low Low
## 151 Low Low
## 152 Low Low
## 153 Low Low
## 154 Low Low
## 155 Low Low
## 156 Low Low
## 157 Low Low
## 158 Low Low
## 159 Low Low
## 160 Low Low
## 161 Low Low
## 162 Low Low
## 163 Low Low
## 164 Low Low
## 165 Low Low
## 166 Low Low
## 167 Low Low
## 168 Low Low
## 169 Low Low
## 170 Low Low
## 171 Low Low
## 172 Low Low
## 173 Low Low
## 174 Low Low
## 175 Low Low
## 176 Low Low
## 177 Low Low
## 178 Low Low
## 179 Low Low
## 180 Low Low
## 181 Low Low
## 182 Low Low
## 183 Low Low
## 184 Low Low
## 185 Low Low
## 186 Low Low
## 187 Low Low
## 188 Low Low
## 189 Low Low
## 190 Low Low
## 191 Low Low
## 192 Low Low
## 193 Low Low
## 194 Low Low
## 195 Low Low
## 196 Low Low
## 197 Low Low
## 198 Low Low
## 199 Low Low
## 200 Low Low
## 201 Low Low
## 202 Low Low
## 203 Low Low
## 204 Low Low
## 205 Low Low
## 206 Low Low
## 207 Low Low
## 208 Low Low
## 209 Low Low
## 210 Low Low
## 211 Low Low
## 212 Low Low
## 213 Low Low
## 214 Low Low
## 215 Low Low
## 216 Low Low
## 217 High High
## 218 High High
## 219 High High
## 220 High High
## 221 High Mid
## 222 High High
## 223 High High
## 224 High High
## 225 High Mid
## 226 High High
## 227 High High
## 228 High Mid
## 229 High High
## 230 High Mid
## 231 High High
## 232 High Mid
## 233 High High
## 234 High High
## 235 High High
## 236 High Mid
## 237 High Low
## 238 Mid Mid
## 239 Mid Mid
## 240 Mid Mid
## 241 Mid High
## 242 Mid Mid
## 243 Mid Mid
## 244 Mid Mid
## 245 Mid Mid
## 246 Mid High
## 247 Mid Mid
## 248 Mid High
## 249 Mid Mid
## 250 Mid Mid
## 251 Mid Low
## 252 Mid High
## 253 Mid Mid
## 254 Mid Low
## 255 Mid Mid
## 256 Mid High
## 257 Mid Low
## 258 Mid Mid
## 259 Mid Mid
## 260 Mid Mid
## 261 Mid Mid
## 262 Mid Mid
## 263 Mid Mid
## 264 Mid Mid
## 265 Mid Low
## 266 Mid Mid
## 267 Mid Low
## 268 Mid Mid
## 269 Low Low
## 270 Low Low
## 271 Low Low
## 272 Low Mid
## 273 Low Low
## 274 Low Low
## 275 Low Mid
## 276 Low Low
## 277 Low Low
## 278 Low Low
## 279 Low Low
## 280 Low Low
## 281 Low Low
## 282 Low Low
## 283 Low Low
## 284 Low Low
## 285 Low Low
## 286 Low Low
## 287 Low Low
## 288 Low Low
## 289 Low Low
## 290 Low Low
## 291 Low Low
## 292 Low Low
## 293 Low Low
## 294 Low Low
## 295 Low Low
## 296 Low Low
## 297 Low Low
## 298 Low Low
## 299 Low Low
## 300 Low Low
## 301 Low Low
## 302 Low Low
## 303 Low Low
## 304 Low Low
## 305 Low Low
## 306 Low Low
## 307 Low Low
## 308 Low Low
## 309 Low Low
## 310 Low Low
## 311 Low Low
## 312 Low Low
## 313 Mid Mid
## 314 High Low
## 315 Low Low
## 316 Mid Low##################################
# Reporting the independent evaluation results
# for the test set
##################################
(BTREE_Test_Accuracy <- Accuracy(y_pred = BTREE_Test$BTREE_Predicted,
y_true = BTREE_Test$BTREE_Observed))## [1] 0.81329111.6 Consolidated Findings
[A] The models which demonstrated the best and most consistent Accuracy metrics are as follows:
[A.1] RF: Random Forest (randomForest package)
[A.2.1] Cross-Validation Accuracy = 0.82131
[A.2.2] Test Accuracy = 0.83861
[A.2] BTREE: Bagged Trees (ipred, plyr and e1071 packages)
[A.2.1] Cross-Validation Accuracy = 0.81078
[A.2.2] Test Accuracy = 0.81329
[A.3] C50: C5.0 Decision Trees (C50 and plyr packages)
[A.3.1] Cross-Validation Accuracy = 0.80650
[A.3.2] Test Accuracy = 0.79746
Code Chunk | Output
##################################
# Consolidating all evaluation results
# for the train and test sets
# using the ROC Curve AUC metric
##################################
Model <- c('PMR','LDA','FDA','MDA','NB','NSC','AVNN','SVM_R','SVM_P','KNN','CART','CTREE','C50','RF','BTREE',
'PMR','LDA','FDA','MDA','NB','NSC','AVNN','SVM_R','SVM_P','KNN','CART','CTREE','C50','RF','BTREE')
Set <- c(rep('Cross-Validation',15),rep('Test',15))
Accuracy <- c(PMR_Train_Accuracy,LDA_Train_Accuracy,FDA_Train_Accuracy,MDA_Train_Accuracy,NB_Train_Accuracy,
NSC_Train_Accuracy,AVNN_Train_Accuracy,SVM_R_Train_Accuracy,SVM_P_Train_Accuracy,KNN_Train_Accuracy,
CART_Train_Accuracy,CTREE_Train_Accuracy,C50_Train_Accuracy,RF_Train_Accuracy,BTREE_Train_Accuracy,
PMR_Test_Accuracy,LDA_Test_Accuracy,FDA_Test_Accuracy,MDA_Test_Accuracy,NB_Test_Accuracy,
NSC_Test_Accuracy,AVNN_Test_Accuracy,SVM_R_Test_Accuracy,SVM_P_Test_Accuracy,KNN_Test_Accuracy,
CART_Test_Accuracy,CTREE_Test_Accuracy,C50_Test_Accuracy,RF_Test_Accuracy,BTREE_Test_Accuracy)
Accuracy_Summary <- as.data.frame(cbind(Model,Set,Accuracy))
Accuracy_Summary$Accuracy <- as.numeric(as.character(Accuracy_Summary$Accuracy))
Accuracy_Summary$Set <- factor(Accuracy_Summary$Set,
levels = c("Cross-Validation",
"Test"))
Accuracy_Summary$Model <- factor(Accuracy_Summary$Model,
levels = c("PMR",
"LDA",
"FDA",
"MDA",
"NB",
"NSC",
"AVNN",
"SVM_R",
"SVM_P",
"KNN",
"CART",
"CTREE",
"C50",
"RF",
"BTREE"))
print(Accuracy_Summary, row.names=FALSE)## Model Set Accuracy
## PMR Cross-Validation 0.7433879
## LDA Cross-Validation 0.7286501
## FDA Cross-Validation 0.7750012
## MDA Cross-Validation 0.7434488
## NB Cross-Validation 0.6434612
## NSC Cross-Validation 0.6045224
## AVNN Cross-Validation 0.6729680
## SVM_R Cross-Validation 0.7980168
## SVM_P Cross-Validation 0.7959670
## KNN Cross-Validation 0.6909644
## CART Cross-Validation 0.7487843
## CTREE Cross-Validation 0.7318519
## C50 Cross-Validation 0.8065057
## RF Cross-Validation 0.8213097
## BTREE Cross-Validation 0.8107827
## PMR Test 0.7658228
## LDA Test 0.7689873
## FDA Test 0.8196203
## MDA Test 0.7151899
## NB Test 0.6550633
## NSC Test 0.6360759
## AVNN Test 0.6582278
## SVM_R Test 0.7911392
## SVM_P Test 0.7879747
## KNN Test 0.6677215
## CART Test 0.7974684
## CTREE Test 0.7943038
## C50 Test 0.7974684
## RF Test 0.8386076
## BTREE Test 0.8132911(Accuracy_Plot <- dotplot(Model ~ Accuracy,
data = Accuracy_Summary,
groups = Set,
main = "Classification Model Performance Comparison",
ylab = "Model",
xlab = "Accuracy",
auto.key = list(adj=1, space="top", columns=2),
type=c("p", "h"),
origin = 0,
alpha = 0.45,
pch = 16,
cex = 2))
3. References
[Book] Applied Predictive Modeling by Max Kuhn and Kjell Johnson
[Book] An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie and Rob Tibshirani
[Book] An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie and Rob Tibshirani
[Book] Multivariate Data Visualization with R by Deepayan Sarkar
[Book] Machine Learning by Samuel Jackson
[Book] Data Modeling Methods by Jacob Larget
[Book] Regression Modeling Strategies by Frank Harrel
[Book] Pattern Recognition and Neural Networks by Brian Ripley
[Book] Modern Applied Statistics with S by William Venables and Brian Ripley
[R Package] AppliedPredictiveModeling by Max Kuhn
[R Package] caret by Max Kuhn
[R Package] rpart by Terry Therneau and Beth Atkinson
[R Package] lattice by Deepayan Sarkar
[R Package] dplyr by Hadley Wickham
[R Package] moments by Lukasz Komsta and Frederick
[R Package] skimr by Elin Waring
[R Package] RANN by Sunil Arya, David Mount, Samuel Kemp and Gregory Jefferis
[R Package] corrplot by Taiyun Wei
[R Package] tidyverse by Hadley Wickham
[R Package] lares by Bernardo Lares
[R Package] DMwR2 by Luis Torgo
[R Package] gridExtra by Baptiste Auguie and Anton Antonov
[R Package] rattle by Graham Williams
[R Package] rpart.plot by Stephen Milborrow
[R Package] RColorBrewer by Erich Neuwirth
[R Package] stats by R Core Team
[R Package] pls by Kristian Hovde Liland
[R Package] nnet by Brian Ripley
[R Package] elasticnet by Hui Zou
[R Package] earth by Stephen Milborrow
[R Package] party by Torsten Hothorn
[R Package] kernlab by Alexandros Karatzoglou
[R Package] randomForest by Andy Liaw
[R Package] pROC by Xavier Robin
[R Package] mda by Trevor Hastie
[R Package] klaR by Christian Roever, Nils Raabe, Karsten Luebke, Uwe Ligges, Gero Szepannek, Marc Zentgraf and David Meyer
[R Package] pamr by Trevor Hastie, Rob Tibshirani, Balasubramanian Narasimhan and Gil Chu
[R Package] C50 by Max Kuhn
[R Package] MLmetrics by Yachen Yan
[R Package] ordinalNet by Michael Wurm, Paul Rathouz and Bret Hanlon
[Article] The caret Package by Max Kuhn
[Article] A Short Introduction to the caret Package by Max Kuhn
[Article] Caret Package – A Practical Guide to Machine Learning in R by Selva Prabhakaran
[Article] Tuning Machine Learning Models Using the Caret R Package by Jason Brownlee
[Article] Lattice Graphs by Alboukadel Kassambara
[Article] A Tour of Machine Learning Algorithms by Jason Brownlee
[Article] Decision Tree Algorithm Examples In Data Mining by Software Testing Help Team
[Article] 4 Types of Classification Tasks in Machine Learning by Jason Brownlee
[Article] Spot-Check Classification Machine Learning Algorithms in Python with scikit-learn by Jason Brownlee
[Article] Feature Engineering and Selection: A Practical Approach for Predictive Models by Max Kuhn and Kjell Johnson
[Article] An Introduction to Naive Bayes Algorithm for Beginners by Turing Team
[Article] Machine Learning Tutorial: A Step-by-Step Guide for Beginners by Mayank Banoula
[Article] Nearest Shrunken Centroids With Python by Jason Brownlee
[Article] Discriminant Analysis Essentials in R by Alboukadel Kassambara
[Article] Linear Discriminant Analysis, Explained by Xiaozhou Yang
[Article] Flexible Discriminant Analysis by BCCVL Team
[Article] Classification Tree by BCCVL Team
[Article] Random Forest by BCCVL Team
[Article] Boosted Regression Tree by BCCVL Team
[Article] Artificial Neural Network by BCCVL Team
[Article] Generalized Linear Model by BCCVL Team
[Article] Generalized Boosting Model by BCCVL Team
[Article] Conditional Inference Trees in R Programming by Geeks for Geeks Team
[Article] C5.0: An Informal Tutorial by RuleQuest Team
[Article] What is Nearest Shrunken Centroid Classification? by Rob Tibshirani
[Article] K-Nearest Neighbors Algorithm by IBM Team
[Publication] The Origins of Logistic Regression by JS Cramer (Econometrics eJournal)
[Publication] The Use of Multiple Measurements in Taxonomic Problems by Ronald Fisher (Annals of Human Genetics)
[Publication] Flexible Discriminant Analysis by Optimal Scoring by Trevor Hastie, Robert Tibshirani and Andreas Buja (Journal of the American Statistical Association)
[Publication] Discriminant Analysis by Gaussian Mixtures by Trevor Hastie and Robert Tibshirani (Journal of the Royal Statistical Society)
[Publication] Who Discovered Bayes’s Theorem? by Stephen Stigler (The American Statistician)
[Publication] Diagnosis of Multiple Cancer Types by Shrunken Centroids of Gene Expression by Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan and Gilbert Chu (Proceedings of the National Academy of Sciences of the United States of America)
[Publication] A Training Algorithm for Optimal Margin Classifiers by Bernhard Boser, Isabelle Guyon and Vladimir Vapnik (Proceedings of the Fifth Annual Workshop on Computational Learning Theory)
[Publication] Nearest Neighbor Pattern Classification Thomas Cover and Peter Hart (IEEE Transactions on Information Theory)
[Publication] Classification and Regression Trees by Leo Breiman, Jerome Friedman, Richard Olshen, and Charles Stone (Computer Science)
[Publication] Unbiased Recursive Partitioning: A Conditional Inference Framework by Torsten Hothorn, Kurt Hornik and Achim Zeileis (Journal of Computational and Graphical Statistics)
[Publication] C4.5: Programs for Machine Learning by Ross Quinlan (Machine Learning)
[Publication] Random Forest by Leo Breiman (Machine Learning)
[Publication] Bagging Predictors by Leo Breiman (Machine Learning)
[Course] Applied Data Mining and Statistical Learning by Penn State Eberly College of Science
[Course] Regression Methods by Penn State Eberly College of Science
[Course] Applied Regression Analysis by Penn State Eberly College of Science
[Course] Applied Data Mining and Statistical Learning by Penn State Eberly College of Science