diff options
Diffstat (limited to 'lib/ot_predictions.rb')
| -rwxr-xr-x | lib/ot_predictions.rb | 83 |
1 files changed, 42 insertions, 41 deletions
diff --git a/lib/ot_predictions.rb b/lib/ot_predictions.rb index 2e3c238..df1efc3 100755 --- a/lib/ot_predictions.rb +++ b/lib/ot_predictions.rb @@ -16,16 +16,18 @@ module Lib end def initialize( feature_type, test_dataset_uris, test_target_dataset_uris, - prediction_feature, prediction_dataset_uris, predicted_variables, subjectid=nil, task=nil) + 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 prediciton -- test-dataset: "+test_dataset_uris.inspect LOGGER.debug "loading prediciton -- test-target-datset: "+test_target_dataset_uris.inspect LOGGER.debug "loading prediciton -- prediction-dataset: "+prediction_dataset_uris.inspect LOGGER.debug "loading prediciton -- predicted_variable: "+predicted_variables.inspect + LOGGER.debug "loading prediciton -- predicted_confidence: "+predicted_confidences.inspect LOGGER.debug "loading prediciton -- prediction_feature: "+prediction_feature.to_s raise "prediction_feature missing" unless prediction_feature @@ -46,6 +48,7 @@ module Lib 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 @@ -72,7 +75,7 @@ module Lib "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 @@ -92,35 +95,24 @@ module Lib compounds.each do |c| case feature_type when "classification" - actual_values << classification_value(test_target_dataset, c, prediction_feature, accept_values) + actual_values << classification_val(test_target_dataset, c, prediction_feature, accept_values) when "regression" - actual_values << regression_value(test_target_dataset, c, prediction_feature) + 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 - - # TODO: remove LAZAR_PREDICTION_DATASET_HACK - no_prediction_feature = prediction_dataset.features.keys.index(predicted_variable)==nil - if no_prediction_feature - one_entry_per_compound = true - compounds.each do |c| - if prediction_dataset.data_entries[c] and prediction_dataset.data_entries[c].size != 1 - one_entry_per_compound = false - break - end - end - msg = "prediction-feature not found: '"+predicted_variable+"' in prediction-dataset: "+prediction_dataset_uri.to_s+", available features: "+ - prediction_dataset.features.keys.inspect - if one_entry_per_compound - LOGGER.warn msg - else - raise msg - end - end - + 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 + 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 + 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 @@ -141,25 +133,18 @@ module Lib else case feature_type when "classification" - # TODO: remove LAZAR_PREDICTION_DATASET_HACK - predicted_values << classification_value(prediction_dataset, c, no_prediction_feature ? nil : predicted_variable, accept_values) + predicted_values << classification_val(prediction_dataset, c, predicted_variable, accept_values) when "regression" - predicted_values << regression_value(prediction_dataset, c, no_prediction_feature ? nil : predicted_variable) + predicted_values << regression_val(prediction_dataset, c, predicted_variable) end - # TODO confidence_values << prediction_dataset.get_prediction_confidence(c, predicted_variable) - conf = predicted_values[count]!=nil ? 1 : nil - begin - feature = prediction_dataset.data_entries[c].keys[0] - feature_data = prediction_dataset.features[feature] - conf = feature_data[OT.confidence].to_f if feature_data[OT.confidence]!=nil - rescue - LOGGER.warn "could not get confidence" + if predicted_confidence + confidence_values << confidence_val(prediction_dataset, c, predicted_confidence) + else + confidence_values << nil end - confidence_values << conf end count += 1 end - @compounds += compounds all_predicted_values += predicted_values all_actual_values += actual_values @@ -174,7 +159,7 @@ module Lib end private - def regression_value(dataset, compound, feature) + def regression_val(dataset, compound, feature) v = value(dataset, compound, feature) begin v = v.to_f unless v==nil or v.is_a?(Numeric) @@ -185,7 +170,18 @@ module Lib end end - def classification_value(dataset, compound, feature, accept_values) + 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 "+ @@ -239,6 +235,10 @@ module Lib def self.to_array( predictions, add_pic=false, format=false ) + confidence_available = false + predictions.each do |p| + confidence_available |= p.confidence_values_available? + end res = [] conf_column = nil predictions.each do |p| @@ -269,9 +269,9 @@ module Lib a << nil end end - if p.confidence_values_available? + if confidence_available conf_column = a.size if conf_column==nil - a << p.confidence_value(i) #(format ? p.confidence_value(i).to_nice_s : p.confidence_value(i)) + a << p.confidence_value(i) end a << p.identifier(i) res << a @@ -279,6 +279,7 @@ module Lib end if conf_column!=nil + LOGGER.debug "sort via confidence: "+res.collect{|n| n[conf_column]}.inspect res = res.sort_by{ |n| n[conf_column] || 0 }.reverse if format res.each do |a| |