1 files changed, 161 insertions, 0 deletions
diff --git a/5x_cv/lib/cv_am.rb b/5x_cv/lib/cv_am.rb
new file mode 100644
index 0000000..965cd5b
--- /dev/null
+++ b/5x_cv/lib/cv_am.rb
@@ -0,0 +1,161 @@
+# 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