serial batch prediction with task

1 files changed, 161 insertions, 0 deletions

diff --git a/helper.rb b/helper.rb
new file mode 100644
index 0000000..8837161
--- /dev/null
+++ b/helper.rb
@@ -0,0 +1,161 @@
+helpers do
+  def embedded_svg image, options={}
+    doc = Nokogiri::HTML::DocumentFragment.parse image
+    svg = doc.at_css 'svg'
+    title = doc.at_css 'title'
+    if options[:class].present?
+      svg['class'] = options[:class]
+    end
+    if options[:title].present?
+      title.children.remove
+      text_node = Nokogiri::XML::Text.new(options[:title], doc)
+      title.add_child(text_node)
+    end
+    doc.to_html.html_safe
+  end
+
+  def to_csv(m,predictions,compounds)
+    model = (m != "Cramer" ? Model::Validation.find(m.to_s) : "Cramer")
+    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
+      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
+
+      # header
+      csv = "ID,Endpoint,Unique SMILES,Cramer rules,Cramer rules with extensions\n"
+      
+      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"
+      end
+
+    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)} (#{model.unit})"} : prediction[:measurements].collect{|value| "#{value}"}
+            output["converted_measurements"] = (type == "Regression") ? prediction[:measurements].collect{|value| "#{compound.mmol_to_mg(value.delog10).signif(3)} #{model.unit =~ /mmol\/L/ ? "(mg/L)" : "(mg/kg_bw/day)"}"} : false
+          else
+            output["measurements"] = (type == "Regression") ? "#{prediction[:measurements].delog10.signif(3)} (#{model.unit})}" : "#{prediction[:measurements]}"
+            output["converted_measurements"] = (type == "Regression") ? "#{compound.mmol_to_mg(prediction[:measurements].delog10).signif(3)} #{(model.unit =~ /\b(mmol\/L)\b/) ? "(mg/L)" : "(mg/kg_bw/day)"}" : 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"}\",\"#{prediction[: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"}\",\"#{prediction[: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] if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
+          else
+            line += "#{idx+1},Consensus mutagenicity,#{compound.smiles},#{prediction[:info] ? prediction[:info] : "no"},"\
+              "#{prediction[:measurements] if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
+          end
+
+        end
+        csv += line
+      end
+      $logger.debug csv
+      csv
+    end
+  end
+
+end