cleanup and reorder code;save prediction object also for single prediction

1 files changed, 97 insertions, 131 deletions

diff --git a/helper.rb b/helper.rb
index 3bd1755..d423285 100644
--- a/helper.rb
+++ b/helper.rb
@@ -1,4 +1,5 @@
 helpers do
+
   def embedded_svg image, options={}
     doc = Nokogiri::HTML::DocumentFragment.parse image
     svg = doc.at_css 'svg'
@@ -14,146 +15,111 @@ helpers do
     doc.to_html.html_safe
   end
 
-  def to_csv(m,predictions,compounds)
-    model = (m != "Cramer" ? Model::Validation.find(m.to_s) : "Cramer")
+  def prediction_to_csv(m,c,p)
+    #model = Model::Validation.find(m.to_s)
+    model = m
+    model_name = "#{model.endpoint.gsub('_', ' ')} (#{model.species})"
+    model_unit = model.regression? ? "(#{model.unit})" : ""
+    converted_model_unit = model.regression? ? "#{model.unit =~ /\b(mmol\/L)\b/ ? "(mg/L)" : "(mg/kg_bw/day)"}" : ""
+
+    #predictions = predictions_ids.collect{|prediction_id| Prediction.find prediction_id}
     csv = ""
-    if model == "Cramer"
-      compounds = compounds.collect{|c| c.smiles}
-      
-      prediction = [Toxtree.predict(compounds, "Cramer rules"), Toxtree.predict(compounds, "Cramer rules with extensions")]
-      output = {}
-      output["model_name"] = "Oral toxicity (Cramer rules)"
-      output["model_type"] = false
-      output["model_unit"] = false
-      ["measurements", "converted_measurements", "prediction_value", "converted_value", "interval", "converted_interval", "probability", "db_hit", "warnings", "info", "toxtree", "sa_prediction", "sa_matches", "confidence"].each do |key|
-        output["#{key}"] = false
+    compound = c#Compound.find prediction_object.compound
+    prediction = p#prediction_object.prediction
+    #prediction.delete_if{|k,v| k =~ /neighbors|prediction_feature_id/}
+    output = {}
+    line = ""
+    output["model_name"] = model_name
+    output["model_unit"] = model_unit
+    output["converted_model_unit"] = converted_model_unit
+
+    if prediction[:value]
+      inApp = (prediction[:warnings].join(" ") =~ /Cannot/ ? "no" : (prediction[:warnings].join(" ") =~ /may|Insufficient/ ? "maybe" : "yes"))
+      if prediction[:info] =~ /\b(identical)\b/i
+        prediction[:info] = "This compound was part of the training dataset. All information "\
+          "from this compound was removed from the training data before the "\
+          "prediction to obtain unbiased results."
       end
-      output["toxtree"] = true
-      output["cramer_rules"] = prediction.collect{|array| array.collect{|hash| hash["Cramer rules"]}}.flatten.compact
-      output["cramer_rules_extensions"] = prediction.collect{|array| array.collect{|hash| hash["Cramer rules, with extensions"]}}.flatten.compact
+      note = "\"#{prediction[:warnings].uniq.join(" ")}\""
+
+      output["prediction_value"] = model.regression? ? "#{prediction[:value].delog10.signif(3)}" : "#{prediction[:value]}"
+      output["converted_value"] = model.regression? ? "#{compound.mmol_to_mg(prediction[:value].delog10).signif(3)}" : nil
+
+      if prediction[:measurements].is_a?(Array)
+        output["measurements"] = model.regression? ? prediction[:measurements].collect{|value| "#{value.delog10.signif(3)}"} : prediction[:measurements].collect{|value| "#{value}"}
+        output["converted_measurements"] = model.regression? ? prediction[:measurements].collect{|value| "#{compound.mmol_to_mg(value.delog10).signif(3)}"} : false
+      else
+        output["measurements"] = model.regression? ? "#{prediction[:measurements].delog10.signif(3)}" : "#{prediction[:measurements]}"
+        output["converted_measurements"] = model.regression? ? "#{compound.mmol_to_mg(prediction[:measurements].delog10).signif(3)}" : false
+
+      end #db_hit
+
+      if model.regression?
+
+        if !prediction[:prediction_interval].blank?
+          interval = prediction[:prediction_interval]
+          output['interval'] = []
+          output['converted_interval'] = []
+          output['interval'] << interval[1].delog10.signif(3)
+          output['interval'] << interval[0].delog10.signif(3)
+          output['converted_interval'] << compound.mmol_to_mg(interval[1].delog10).signif(3)
+          output['converted_interval'] << compound.mmol_to_mg(interval[0].delog10).signif(3)
+        end #prediction interval
+
+        line += "#{output['model_name']},#{compound.smiles},"\
+          "\"#{prediction[:info] ? prediction[:info] : "no"}\",\"#{output['measurements'].join("; ") if prediction[:info]}\","\
+          "#{!output['prediction_value'].blank? ? output['prediction_value'] : ""},"\
+          "#{!output['converted_value'].blank? ? output['converted_value'] : ""},"\
+          "#{!prediction[:prediction_interval].blank? ? output['interval'].first : ""},"\
+          "#{!prediction[:prediction_interval].blank? ? output['interval'].last : ""},"\
+          "#{!prediction[:prediction_interval].blank? ? output['converted_interval'].first : ""},"\
+          "#{!prediction[:prediction_interval].blank? ? output['converted_interval'].last : ""},"\
+          "#{inApp},#{note.nil? ? "" : note.chomp}\n"
+      else # Classification
+
+        if !prediction[:probabilities].blank?
+          output['probabilities'] = []
+          prediction[:probabilities].each{|k,v| output['probabilities'] << v.signif(3)}
+        end
+
+        line += "Consensus mutagenicity,#{compound.smiles},"\
+          "\"#{prediction[:info] ? prediction[:info] : "no"}\",\"#{output['measurements'].join("; ") if prediction[:info]}\","\
+          "#{prediction['Consensus prediction']},"\
+          "#{prediction['Consensus confidence']},"\
+          "#{prediction['Structural alerts for mutagenicity']},"\
+          "#{output['prediction_value']},"\
+          "#{!prediction[:probabilities].blank? ? output['probabilities'].first : ""},"\
+          "#{!prediction[:probabilities].blank? ? output['probabilities'].last : ""},"\
+          "#{inApp},#{note.nil? ? "" : note}\n"
 
-      # header
-      csv = "ID,Endpoint,Unique SMILES,Cramer rules,Cramer rules with extensions\n"
+      end
       
-      compounds.each_with_index do |smiles, idx|
-        csv << "#{idx+1},#{output["model_name"]},#{smiles},"\
-          "#{output["cramer_rules"][idx] != "nil" ? output["cramer_rules"][idx] : "none" },"\
-          "#{output["cramer_rules_extensions"][idx] != "nil" ? output["cramer_rules_extensions"][idx] : "none"}\n"
+      output['warnings'] = prediction[:warnings] if prediction[:warnings]
+
+    else #no prediction value
+      inApp = "no"
+      if prediction[:info] =~ /\b(identical)\b/i
+        prediction[:info] = "This compound was part of the training dataset. All information "\
+          "from this compound was removed from the training data before the "\
+          "prediction to obtain unbiased results."
       end
+      note = "\"#{prediction[:warnings].join(" ")}\""
 
-    else
-      output = {}
-      predictions.each_with_index do |prediction,idx|
-        compound = compounds[idx]
-        line = ""
-        output["model_name"] = "#{model.endpoint.gsub('_', ' ')} (#{model.species})"
-        output["model_type"] = model.model.class.to_s.match("Classification") ? type = "Classification" : type = "Regression"
-        output["model_unit"] = (type == "Regression") ? "(#{model.unit})" : ""
-        output["converted_model_unit"] = (type == "Regression") ? "#{model.unit =~ /\b(mmol\/L)\b/ ? "(mg/L)" : "(mg/kg_bw/day)"}" : ""
-        ["measurements", "converted_measurements", "prediction_value", "converted_value", "interval", "converted_interval", "probability", "db_hit", "warnings", "info", "toxtree", "sa_prediction", "sa_matches", "confidence"].each do |key|
-          output["#{key}"] = false
-        end
-
-        if prediction[:value]
-          inApp = (prediction[:warnings].join(" ") =~ /Cannot/ ? "no" : (prediction[:warnings].join(" ") =~ /may|Insufficient/ ? "maybe" : "yes"))
-          if prediction[:info] =~ /\b(identical)\b/i
-            prediction[:info] = "This compound was part of the training dataset. All information "\
-              "from this compound was removed from the training data before the "\
-              "prediction to obtain unbiased results."
-          end
-          note = "\"#{prediction[:warnings].uniq.join(" ")}\""
-
-          output["prediction_value"] = (type == "Regression") ? "#{prediction[:value].delog10.signif(3)}" : "#{prediction[:value]}"
-          output["converted_value"] = "#{compound.mmol_to_mg(prediction[:value].delog10).signif(3)}" if type == "Regression"
-
-          output["db_hit"] = prediction[:info] if prediction[:info]
-          
-          if prediction[:measurements].is_a?(Array)
-            output["measurements"] = (type == "Regression") ? prediction[:measurements].collect{|value| "#{value.delog10.signif(3)}"} : prediction[:measurements].collect{|value| "#{value}"}
-            output["converted_measurements"] = (type == "Regression") ? prediction[:measurements].collect{|value| "#{compound.mmol_to_mg(value.delog10).signif(3)}"} : false
-          else
-            output["measurements"] = (type == "Regression") ? "#{prediction[:measurements].delog10.signif(3)}" : "#{prediction[:measurements]}"
-            output["converted_measurements"] = (type == "Regression") ? "#{compound.mmol_to_mg(prediction[:measurements].delog10).signif(3)}" : false
-
-          end #db_hit
-
-          if type == "Regression"
-
-            if !prediction[:prediction_interval].nil?
-              interval = prediction[:prediction_interval]
-              output['interval'] = "#{interval[1].delog10.signif(3)} - #{interval[0].delog10.signif(3)}"
-              output['converted_interval'] = "#{compound.mmol_to_mg(interval[1].delog10).signif(3)} - #{compound.mmol_to_mg(interval[0].delog10).signif(3)}"
-            end #prediction interval
-
-            line += "#{idx+1},#{output['model_name']},#{compound.smiles},"\
-              "\"#{prediction[:info] ? prediction[:info] : "no"}\",\"#{output['measurements'].join("; ") if prediction[:info]}\","\
-              "#{output['prediction_value'] != false ? output['prediction_value'] : ""},"\
-              "#{output['converted_value'] != false ? output['converted_value'] : ""},"\
-              "#{output['interval'].split(" - ").first.strip unless output['interval'] == false},"\
-              "#{output['interval'].split(" - ").last.strip unless output['interval'] == false},"\
-              "#{output['converted_interval'].split(" - ").first.strip unless output['converted_interval'] == false},"\
-              "#{output['converted_interval'].split(" - ").last.strip unless output['converted_interval'] == false},"\
-              "#{inApp},#{note.nil? ? "" : note.chomp}\n"
-          else # Classification
-
-            # consensus mutagenicity
-            sa_prediction = KaziusAlerts.predict(compound.smiles)
-            lazar_mutagenicity = prediction
-            confidence = 0
-            lazar_mutagenicity_val = (lazar_mutagenicity[:value] == "non-mutagenic" ? false : true)
-            if sa_prediction[:prediction] == false && lazar_mutagenicity_val == false
-              confidence = 0.85
-            elsif sa_prediction[:prediction] == true && lazar_mutagenicity_val == true
-              confidence = 0.85 * ( 1 - sa_prediction[:error_product] )
-            elsif sa_prediction[:prediction] == false && lazar_mutagenicity_val == true
-              confidence = 0.11
-            elsif sa_prediction[:prediction] == true && lazar_mutagenicity_val == false
-              confidence = ( 1 - sa_prediction[:error_product] ) - 0.57
-            end
-            output['sa_prediction'] = sa_prediction
-            output['sa_matches'] = sa_prediction[:matches].collect{|a| a.first}.join("; ") unless sa_prediction[:matches].blank?
-            output['confidence'] = confidence.signif(3)
-            output['model_name'] = "Lazar #{model.endpoint.gsub('_', ' ').downcase} (#{model.species}):"
-            output['probability'] = prediction[:probabilities] ? prediction[:probabilities].collect{|k,v| "#{k}: #{v.signif(3)}"} : false
-
-            line += "#{idx+1},Consensus mutagenicity,#{compound.smiles},"\
-              "\"#{prediction[:info] ? prediction[:info] : "no"}\",\"#{output['measurements'].join("; ") if prediction[:info]}\","\
-              "#{sa_prediction[:prediction] == false ? "non-mutagenic" : "mutagenic"},"\
-              "#{output['confidence']},#{output['sa_matches'] != false ? "\"#{output['sa_matches']}\"" : "none"},"\
-              "#{output['prediction_value']},"\
-              "#{output['probability'][0] != false ? output['probability'][0].split(":").last : ""},"\
-              "#{output['probability'][1] != false ? output['probability'][1].split(":").last : ""},"\
-              "#{inApp},#{note.nil? ? "" : note}\n"
-
-          end
-          
-          output["warnings"] = prediction[:warnings] if prediction[:warnings]
-
-        else #no prediction value
-          inApp = "no"
-          if prediction[:info] =~ /\b(identical)\b/i
-            prediction[:info] = "This compound was part of the training dataset. All information "\
-              "from this compound was removed from the training data before the "\
-              "prediction to obtain unbiased results."
-          end
-          note = "\"#{prediction[:warnings].join(" ")}\""
-
-          output["warnings"] = prediction[:warnings]
-          output["info"] = prediction[:info] if prediction[:info]
-
-          if type == "Regression"
-            line += "#{idx+1},#{output['model_name']},#{compound.smiles},#{prediction[:info] ? prediction[:info] : "no"},"\
-              "#{prediction[:measurements].collect{|m| m.delog10.signif(3)}.join("; ") if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
-          else
-            line += "#{idx+1},Consensus mutagenicity,#{compound.smiles},#{prediction[:info] ? prediction[:info] : "no"},"\
-              "#{prediction[:measurements].join("; ") if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
-          end
+      output['warnings'] = prediction[:warnings]
+      output['info'] = prediction[:info] if prediction[:info]
 
-        end
-        csv += line
+      if model.regression?
+        line += "#{output['model_name']},#{compound.smiles},#{prediction[:info] ? prediction[:info] : "no"},"\
+          "#{prediction[:measurements].collect{|m| m.delog10.signif(3)}.join("; ") if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
+      else
+        line += "Consensus mutagenicity,#{compound.smiles},#{prediction[:info] ? prediction[:info] : "no"},"\
+          "#{prediction[:measurements].join("; ") if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
       end
-      csv
+
     end
+    csv += line
+    # output
+    csv
   end
 
 end