adjust to new wrapper, replace activerecord with datamapper (remove activerecord code), is_classification to feature_type

1 files changed, 94 insertions, 42 deletions

diff --git a/lib/ot_predictions.rb b/lib/ot_predictions.rb
index 0175a0c..52683a6 100644..100755
--- a/lib/ot_predictions.rb
+++ b/lib/ot_predictions.rb
@@ -15,7 +15,7 @@ module Lib
       return @compounds[instance_index]
     end
   
-    def initialize(is_classification, test_dataset_uri, test_target_dataset_uri, 
+    def initialize(feature_type, test_dataset_uri, test_target_dataset_uri, 
       prediction_feature, prediction_dataset_uri, predicted_variable, task=nil)
       
         LOGGER.debug("loading prediciton via test-dataset:'"+test_dataset_uri.to_s+
@@ -53,38 +53,47 @@ module Lib
           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.index(prediction_feature)==nil
+                "available features are: "+test_target_dataset.features.inspect if test_target_dataset.features.keys.index(prediction_feature)==nil
         end
         
+        test_dataset.load_all
         @compounds = test_dataset.compounds
         LOGGER.debug "test dataset size: "+@compounds.size.to_s
         raise "test dataset is empty" unless @compounds.size>0
-        class_values = is_classification ? OpenTox::Feature.domain(prediction_feature) : nil
+        class_values = feature_type=="classification" ? OpenTox::Feature.new(prediction_feature).domain : nil
         
         actual_values = []
         @compounds.each do |c|
-          value = test_target_dataset.get_value(c, prediction_feature)
-          
-          if is_classification
-            value = value.to_s unless value==nil
-            raise "illegal class_value of actual value "+value.to_s+" class: "+
-              value.class.to_s unless value==nil or class_values.index(value)!=nil
-            actual_values.push class_values.index(value) 
-          else
-            begin
-              value = value.to_f unless value==nil or value.is_a?(Numeric)
-            rescue
-              LOGGER.warn "no numeric value for regression: '"+value.to_s+"'"
-              value = nil
-            end
-            actual_values.push value
+          case feature_type
+          when "classification"
+            actual_values << classification_value(test_target_dataset, c, prediction_feature, class_values)
+          when "regression"
+            actual_values << regression_value(test_target_dataset, c, prediction_feature)
           end
         end
         task.progress(40) if task # loaded actual values
         
         prediction_dataset = OpenTox::Dataset.find prediction_dataset_uri
         raise "prediction dataset not found: '"+prediction_dataset_uri.to_s+"'" unless prediction_dataset
-        raise "prediction-feature not found: '"+predicted_variable+"' in prediction-dataset: "+prediction_dataset_uri.to_s+", available features: "+prediction_dataset.features.inspect if prediction_dataset.features.index(predicted_variable)==nil
+        
+        # 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 = prediction_dataset.data_entries.keys.size == @compounds.size
+          @compounds.each do |c|
+            if 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 "more predicted than test compounds test:"+@compounds.size.to_s+" < prediction:"+
           prediction_dataset.compounds.size.to_s if @compounds.size < prediction_dataset.compounds.size
@@ -102,38 +111,79 @@ module Lib
             predicted_values << nil
             confidence_values << nil
           else
-            if is_classification
-              value = prediction_dataset.get_predicted_class(c, predicted_variable)
-              value = value.to_s unless value==nil
-              raise "illegal class_value of predicted value "+value.to_s+" class: "+value.class.to_s unless value==nil or class_values.index(value)!=nil
-              predicted_values << class_values.index(value)
-            else
-              value = prediction_dataset.get_predicted_regression(c, predicted_variable)
-              begin
-                value = value.to_f unless value==nil or value.is_a?(Numeric)
-              rescue
-                LOGGER.warn "no numeric value for regression: '"+value.to_s+"'"
-                value = nil
-              end
-              predicted_values << value
+            case feature_type
+            when "classification"
+              # TODO: remove LAZAR_PREDICTION_DATASET_HACK
+              predicted_values << classification_value(prediction_dataset, c, no_prediction_feature ? nil : predicted_variable, class_values)
+            when "regression"
+              predicted_values << regression_value(prediction_dataset, c, no_prediction_feature ? nil : predicted_variable)
+            end
+            # TODO confidence_values << prediction_dataset.get_prediction_confidence(c, predicted_variable)
+            conf = 1
+            begin
+              feature = prediction_dataset.data_entries[c].keys[0]
+              feature_data = prediction_dataset.features[feature]
+              conf = feature_data[OT.confidence] if feature_data[OT.confidence]!=nil 
+            rescue
+              LOGGER.warn "could not get confidence"
             end
-            confidence_values << prediction_dataset.get_prediction_confidence(c, predicted_variable)
+            confidence_values << conf
           end
         end
         task.progress(80) if task # loaded predicted values and confidence
         
-        super(predicted_values, actual_values, confidence_values, is_classification, class_values)
+        super(predicted_values, actual_values, confidence_values, feature_type, class_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_value(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 classification_value(dataset, compound, feature, class_values)
+      v = value(dataset, compound, feature)
+      i = class_values.index(v)
+      raise "illegal class_value of predicted value "+v.to_s+" class: "+v.class.to_s unless v==nil or i!=nil
+      i
+    end
+    
+    def value(dataset, compound, feature)
+      
+      if feature==nil
+        v = dataset.data_entries[compound].values[0]
+      else
+        v = dataset.data_entries[compound][feature]
+      end
+      raise "no array" unless v.is_a?(Array)
+      if v.size>1
+        raise "multiple values"
+      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
     
       res = {}
-      if @is_classification
+      case @feature_type
+      when "classification"
         (Lib::VAL_CLASS_PROPS).each{ |s| res[s] = send(s)}  
-      else
+      when "regression"
         (Lib::VAL_REGR_PROPS).each{ |s| res[s] = send(s) }  
       end
       return res
@@ -152,16 +202,18 @@ module Lib
           
           #PENDING!
           begin
-            a.push( "http://ambit.uni-plovdiv.bg:8080/ambit2/depict/cdk?search="+
-              URI.encode(OpenTox::Compound.new(:uri=>p.identifier(i)).smiles) ) if add_pic
+            #a.push( "http://ambit.uni-plovdiv.bg:8080/ambit2/depict/cdk?search="+
+            #  URI.encode(OpenTox::Compound.new(:uri=>p.identifier(i)).smiles) ) if add_pic
+            a << p.identifier(i)+"/image"
           rescue => ex
+            raise ex
             #a.push("Could not add pic: "+ex.message)
-            a.push(p.identifier(i))
+            #a.push(p.identifier(i))
           end
           
           a << (format ? p.actual_value(i).to_nice_s : p.actual_value(i))
           a << (format ? p.predicted_value(i).to_nice_s : p.predicted_value(i))
-          if p.classification?
+          if p.feature_type=="classification"
             if (p.predicted_value(i)!=nil and p.actual_value(i)!=nil)
               a << (p.classification_miss?(i) ? 1 : 0)
             else
@@ -180,7 +232,7 @@ module Lib
       header << "compound" if add_pic
       header << "actual value"
       header << "predicted value"
-      header << "missclassified" if predictions[0].classification?
+      header << "missclassified" if predictions[0].feature_type=="classification"
       header << "confidence value" if predictions[0].confidence_values_available?
       header << "compound-uri"
       res.insert(0, header)