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# Do a 10-fold crossvalidation with mutiple datasets
# Author: Andreas Maunz, David Vorgrimmler
# @params: CSV-File, Method (LAST, BBRC), Minimum Frequency
def cv (args)
subjectid = nil#OpenTox::Authorization.authenticate(guest,guest)
if args.size != 11
puts
puts "Error! Arguments: file_or_dataset_uri feature_generation min_frequency min_chisq_significance backbone stratified random_seed prediction_algorithm local_svm_kernel nr_hits conf_stdev"
exit 1
end
reg=/^(http|https):\/\/[a-z0-9]+([\-\.]{1}[a-z0-9]+)*\.[a-z]{2,5}(:[0-9]{1,5})?(\/.*)?$/ix
file=args[0]
# dataset_is_uri=false
# if reg.match(file)? true : false
# #file.include? "http"
# puts "Uri is valid"
dataset_is_uri=true
# files = [ file ]
# elsif ! File.exists? file
# puts "File #{file} missing"
# exit 1
# end
# if args[1].to_s != "last" && args[1].to_s != "bbrc"
if !(args[1].to_s.include? "/algorithm/fminer/bbrc") && !(args[1].to_s.include? "/algorithm/fminer/last")
puts "feature_generation_uri must contain '/algorithm/fminer/last' or '/algorithm/fminer/bbrc'"
# puts "feature_generation must be 'last' or 'bbrc'"
exit 1
end
if ! args[2] == ""
if args[2].to_i < 2
puts "min_frequency must be at least 2 or \"\""
exit 1
end
end
if ! args[3] == ""
if ! (args[3].to_f <= 1.0 && args[3].to_f >= 0.0)
puts "min_chisq_significance must be between 0 and 1 or \"\""
exit 1
end
end
if ! args[4] == ""
if args[4].to_s != "true" && args[4].to_s != "false"
puts "backbone must be 'true' or 'false'."
exit 1
end
end
if args[5].to_s != "true" && args[5].to_s != "false"
puts "stratified must be 'true' or 'false'"
exit 1
end
if ! args[6] == ""
if ! (args[6].to_i <= 1)
puts "random_seed must be a natural number or \"\""
exit 1
end
end
if ! args[7] == ""
if ! (args[7] == "local_svm_classification")
puts "lazar_prediction_method must be \"local_svm_classification\""
exit 1
end
end
if ! args[8] == ""
if ! (args[8] == "weighted_tanimoto" || args[8] == "propositionalized")
puts "local_svm_kernel must be \"weighted_tanimoto\" or \"propositionalized\""
exit 1
end
end
if ! args[9] == ""
if ! (args[9] == "true")
puts "nr_hits must be \"true\""
exit 1
end
end
if ! args[10] == ""
if ! (args[10] == "true")
puts "conf_stdev must be \"true\""
exit 1
end
end
#if !dataset_is_uri
# # Upload a dataset
# training_dataset = OpenTox::Dataset.create_from_csv_file(file, subjectid)
# prediction_feature = training_dataset.features.keys[0]
# training_dataset_uri=training_dataset.uri
# puts prediction_feature
#else
training_dataset_uri=file
puts training_dataset_uri
prediction_feature = OpenTox::Dataset.find(training_dataset_uri).features.keys.first
puts prediction_feature
# end
puts training_dataset_uri
# Crossvalidation
# @param [Hash] params (required:algorithm_uri,dataset_uri,prediction_feature, optional:algorithm_params,num_folds(10),random_seed(1),stratified(false))
alg_params = "feature_generation_uri=#{args[1]}";
alg_params = alg_params << ";min_frequency=#{args[2]}" unless args[2]==""
alg_params = alg_params << ";min_chisq_significance=#{args[3]}" unless args[3]==""
alg_params = alg_params << ";backbone=#{args[4]}" unless args[4]==""
alg_params = alg_params << ";prediction_algorithm=#{args[7]}" unless args[7]==""
alg_params = alg_params << ";local_svm_kernel=#{args[8]}" unless args[8]==""
alg_params = alg_params << ";nr_hits=#{args[9]}" unless args[9]==""
alg_params = alg_params << ";conf_stdev=#{args[10]}" unless args[10]==""
stratified_param = args[5]
random_seed_param = args[6]
cv_args = {:dataset_uri => training_dataset_uri, :prediction_feature => prediction_feature, :algorithm_uri => args[1].split('fminer')[0] + "lazar", :algorithm_params => alg_params, :stratified => stratified_param }
cv_args[:random_seed] = random_seed_param unless random_seed_param == ""
puts file
puts cv_args.to_yaml
puts
begin
lazar_single_args = {}
lazar_single_args[:feature_generation_uri] = "#{args[1]}";
lazar_single_args[:min_frequency] = args[2] unless args[2]==""
lazar_single_args[:min_chisq_significance] = args[3] unless args[3]==""
lazar_single_args[:backbone] = args[4] unless args[4]==""
lazar_single_args[:prediction_algorithm] = args[7] unless args[7]==""
lazar_single_args[:local_svm_kernel] = args[8] unless args[8]==""
lazar_single_args[:nr_hits] = args[9] unless args[9]==""
lazar_single_args[:conf_stdev] = args[10] unless args[10]==""
#m = OpenTox::Algorithm::Lazar.new.run({:dataset_uri => training_dataset_uri, :subjectid => subjectid}.merge lazar_single_args ).to_s
#puts m
cv = OpenTox::Crossvalidation.create(cv_args).uri
puts cv
cvr = OpenTox::CrossvalidationReport.create( cv , subjectid).uri
puts cvr
#qmrfr = OpenTox::QMRFReport.create(m).uri
#puts qmrfr
#cv_stat = OpenTox::Validation.from_cv_statistics( cv, subjectid )
#puts cv_stat.metadata.to_yaml
#[ cv_stat, training_dataset_uri ]
rescue Exception => e
puts "cv failed: #{e.message} #{e.backtrace}"
end
end
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