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1 files changed, 0 insertions, 170 deletions

diff --git a/5x_cv/logs/cv_am.rb b/5x_cv/logs/cv_am.rb
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index 86b1689..0000000
--- a/5x_cv/logs/cv_am.rb
+++ /dev/null
@@ -1,170 +0,0 @@
-# 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 = OpenTox::Authorization.authenticate("guest","guest") 
-  subjectid = nil
-
-  if args.size != 12 
-    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 pc_type"
-    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 ! args[11] == ""
-    if ! (args[11] == "electronic" || args[11] == "geometrical" || args[11] == "topological" || args[11] == "constitutional")
-      puts "pc_type must be \"electronic\", \"geometrical\", \"topological\" or \"constitutional\""
-      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]==""
-  alg_params = alg_params << ";pc_type=#{args[11]}" 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]==""
-    lazar_single_args[:pc_type] = args[11] 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