diff options
Diffstat (limited to 'lib/ot_predictions.rb')
| -rwxr-xr-x | lib/ot_predictions.rb | 222 |
1 files changed, 11 insertions, 211 deletions
diff --git a/lib/ot_predictions.rb b/lib/ot_predictions.rb index 335fe84..3be845b 100755 --- a/lib/ot_predictions.rb +++ b/lib/ot_predictions.rb @@ -1,228 +1,28 @@ +require "lib/prediction_data.rb" require "lib/predictions.rb" module Lib class OTPredictions < Predictions - CHECK_VALUES = ENV['RACK_ENV'] =~ /debug|test/ - + def initialize(data, compounds=nil) + raise unless data.is_a?(Hash) + super(data) + @compounds = compounds + end + def identifier(instance_index) - return compound(instance_index) + compound(instance_index) end def compound(instance_index) - return @compounds[instance_index] - end - - def initialize( feature_type, test_dataset_uris, test_target_dataset_uris, - prediction_feature, prediction_dataset_uris, predicted_variables, predicted_confidences, subjectid=nil, task=nil) - - test_dataset_uris = [test_dataset_uris] unless test_dataset_uris.is_a?(Array) - test_target_dataset_uris = [test_target_dataset_uris] unless test_target_dataset_uris.is_a?(Array) - prediction_dataset_uris = [prediction_dataset_uris] unless prediction_dataset_uris.is_a?(Array) - predicted_variables = [predicted_variables] unless predicted_variables.is_a?(Array) - predicted_confidences = [predicted_confidences] unless predicted_confidences.is_a?(Array) - LOGGER.debug "loading prediction -- test-dataset: "+test_dataset_uris.inspect - LOGGER.debug "loading prediction -- test-target-datset: "+test_target_dataset_uris.inspect - LOGGER.debug "loading prediction -- prediction-dataset: "+prediction_dataset_uris.inspect - LOGGER.debug "loading prediction -- predicted_variable: "+predicted_variables.inspect - LOGGER.debug "loading prediction -- predicted_confidence: "+predicted_confidences.inspect - LOGGER.debug "loading prediction -- prediction_feature: "+prediction_feature.to_s - raise "prediction_feature missing" unless prediction_feature - - @compounds = [] - all_predicted_values = [] - all_actual_values = [] - all_confidence_values = [] - accept_values = nil - - if task - task_step = 100 / (test_dataset_uris.size*2 + 1) - task_status = 0 - end - - test_dataset_uris.size.times do |i| - - test_dataset_uri = test_dataset_uris[i] - test_target_dataset_uri = test_target_dataset_uris[i] - prediction_dataset_uri = prediction_dataset_uris[i] - predicted_variable = predicted_variables[i] - predicted_confidence = predicted_confidences[i] - - predicted_variable=prediction_feature if predicted_variable==nil - - test_dataset = Lib::DatasetCache.find test_dataset_uri,subjectid - raise "test dataset not found: '"+test_dataset_uri.to_s+"'" unless test_dataset - - if test_target_dataset_uri == nil || test_target_dataset_uri.strip.size==0 || test_target_dataset_uri==test_dataset_uri - test_target_dataset_uri = test_dataset_uri - test_target_dataset = test_dataset - raise "prediction_feature not found in test_dataset, specify a test_target_dataset\n"+ - "prediction_feature: '"+prediction_feature.to_s+"'\n"+ - "test_dataset: '"+test_target_dataset_uri.to_s+"'\n"+ - "available features are: "+test_target_dataset.features.inspect if test_target_dataset.features.keys.index(prediction_feature)==nil - else - test_target_dataset = Lib::DatasetCache.find test_target_dataset_uri,subjectid - raise "test target datset not found: '"+test_target_dataset_uri.to_s+"'" unless test_target_dataset - if CHECK_VALUES - test_dataset.compounds.each do |c| - raise "test compound not found on test class dataset "+c.to_s unless test_target_dataset.compounds.include?(c) - end - end - raise "prediction_feature not found in test_target_dataset\n"+ - "prediction_feature: '"+prediction_feature.to_s+"'\n"+ - "test_target_dataset: '"+test_target_dataset_uri.to_s+"'\n"+ - "available features are: "+test_target_dataset.features.inspect if test_target_dataset.features.keys.index(prediction_feature)==nil - end - - compounds = test_dataset.compounds - LOGGER.debug "test dataset size: "+compounds.size.to_s - raise "test dataset is empty "+test_dataset_uri.to_s unless compounds.size>0 - - if feature_type=="classification" - av = test_target_dataset.accept_values(prediction_feature) - raise "'"+OT.acceptValue.to_s+"' missing/invalid for feature '"+prediction_feature.to_s+"' in dataset '"+ - test_target_dataset_uri.to_s+"', acceptValues are: '"+av.inspect+"'" if av==nil or av.length<2 - if accept_values==nil - accept_values=av - else - raise "accept values (in folds) differ "+av.inspect+" != "+accept_values.inspect if av!=accept_values - end - end - - actual_values = [] - compounds.each do |c| - case feature_type - when "classification" - actual_values << classification_val(test_target_dataset, c, prediction_feature, accept_values) - when "regression" - actual_values << regression_val(test_target_dataset, c, prediction_feature) - end - end - task.progress( task_status += task_step ) if task # loaded actual values - - prediction_dataset = Lib::DatasetCache.find prediction_dataset_uri,subjectid - raise "prediction dataset not found: '"+prediction_dataset_uri.to_s+"'" unless prediction_dataset - - # allow missing prediction feature if there are no compounds in the prediction dataset - raise "predicted_variable not found in prediction_dataset\n"+ - "predicted_variable '"+predicted_variable.to_s+"'\n"+ - "prediction_dataset: '"+prediction_dataset_uri.to_s+"'\n"+ - "available features are: "+prediction_dataset.features.inspect if prediction_dataset.features.keys.index(predicted_variable)==nil and prediction_dataset.compounds.size>0 - raise "predicted_confidence not found in prediction_dataset\n"+ - "predicted_confidence '"+predicted_confidence.to_s+"'\n"+ - "prediction_dataset: '"+prediction_dataset_uri.to_s+"'\n"+ - "available features are: "+prediction_dataset.features.inspect if predicted_confidence and prediction_dataset.features.keys.index(predicted_confidence)==nil and prediction_dataset.compounds.size>0 - - raise "more predicted than test compounds, #test: "+compounds.size.to_s+" < #prediction: "+ - prediction_dataset.compounds.size.to_s+", test-dataset: "+test_dataset_uri.to_s+", prediction-dataset: "+ - prediction_dataset_uri if compounds.size < prediction_dataset.compounds.size - if CHECK_VALUES - prediction_dataset.compounds.each do |c| - raise "predicted compound not found in test dataset:\n"+c+"\ntest-compounds:\n"+ - compounds.collect{|c| c.to_s}.join("\n") if compounds.index(c)==nil - end - end - - predicted_values = [] - confidence_values = [] - count = 0 - compounds.each do |c| - if prediction_dataset.compounds.index(c)==nil - predicted_values << nil - confidence_values << nil - else - case feature_type - when "classification" - predicted_values << classification_val(prediction_dataset, c, predicted_variable, accept_values) - when "regression" - predicted_values << regression_val(prediction_dataset, c, predicted_variable) - end - if predicted_confidence - confidence_values << confidence_val(prediction_dataset, c, predicted_confidence) - else - confidence_values << nil - end - end - count += 1 - end - @compounds += compounds - all_predicted_values += predicted_values - all_actual_values += actual_values - all_confidence_values += confidence_values - - task.progress( task_status += task_step ) if task # loaded predicted values and confidence - end - - super(all_predicted_values, all_actual_values, all_confidence_values, feature_type, accept_values) - raise "illegal num compounds "+num_info if @compounds.size != @predicted_values.size - task.progress(100) if task # done with the mathmatics - end - - private - def regression_val(dataset, compound, feature) - v = value(dataset, compound, feature) - begin - v = v.to_f unless v==nil or v.is_a?(Numeric) - v - rescue - LOGGER.warn "no numeric value for regression: '"+v.to_s+"'" - nil - end - end - - def confidence_val(dataset, compound, confidence) - v = value(dataset, compound, confidence) - begin - v = v.to_f unless v==nil or v.is_a?(Numeric) - v - rescue - LOGGER.warn "no numeric value for confidence '"+v.to_s+"'" - nil - end - end - - def classification_val(dataset, compound, feature, accept_values) - v = value(dataset, compound, feature) - i = accept_values.index(v.to_s) - raise "illegal class_value of prediction (value is '"+v.to_s+"'), accept values are "+ - accept_values.inspect unless v==nil or i!=nil - i + @compounds[instance_index] end - def value(dataset, compound, feature) - return nil if dataset.data_entries[compound]==nil - if feature==nil - v = dataset.data_entries[compound].values[0] - else - v = dataset.data_entries[compound][feature] - end - return nil if v==nil - raise "no array "+v.class.to_s+" : '"+v.to_s+"'" unless v.is_a?(Array) - if v.size>1 - v.uniq! - if v.size>1 - v = nil - LOGGER.warn "not yet implemented: multiple non-equal values "+compound.to_s+" "+v.inspect - else - v = v[0] - end - elsif v.size==1 - v = v[0] - else - v = nil - end - raise "array" if v.is_a?(Array) - v = nil if v.to_s.size==0 - v - end - - public - def compute_stats - + def compute_stats() res = {} - case @feature_type + case feature_type when "classification" (Validation::VAL_CLASS_PROPS).each{ |s| res[s] = send(s)} when "regression" |