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#!/usr/bin/env ruby
require_relative '../../lazar/lib/lazar'
include OpenTox
id = File.open(ARGV[0]).readlines.sample.chomp # random cv
csv_file = "data/training_log10-cv.csv"
cv = Validation::RegressionCrossValidation.find id
data = []
cv.predictions.each do |cid,p|
smi = Compound.find(cid).smiles
warnings = "F"
warnings = "T" if p["warnings"] and !p["warnings"].empty?
if p["prediction_interval"]
data << [smi,p["value"],p["measurements"].median,p["prediction_interval"][0],p["prediction_interval"][1],warnings]
else
data << [smi,p["value"],p["measurements"].median,nil,nil,warnings]
end
end
data.sort!{|a,b| a[1] <=> b[1]}
CSV.open(csv_file,"w+") do |csv|
csv << ["SMILES","LOAEL_measured_median","LOAEL_predicted","Prediction_interval_low","Prediction_interval_high","Warnings"]
data.each{|r| csv << r}
end
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