adjusted order of elements

4 files changed, 71 insertions, 66 deletions

diff --git a/application.rb b/application.rb
index a4f632a..dc46bf7 100644
--- a/application.rb
+++ b/application.rb
@@ -135,14 +135,13 @@ get '/batch/:model/' do
     end
 
     if prediction[:value]
-      inApp = prediction[:neighbors] ? "yes" : "no"
-      inT = prediction[:info] =~ /\b(identical)\b/i ? "yes" : "no"
+      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(" ")}" + ( prediction[:info] ? "#{prediction[:info]}\"" : "\"" )
+      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"
@@ -166,14 +165,15 @@ get '/batch/:model/' do
           output['converted_interval'] = "#{compound.mmol_to_mg(interval[1].delog10).signif(3)} - #{compound.mmol_to_mg(interval[0].delog10).signif(3)}"
         end #prediction interval
 
-        csv = "#{idx+1},#{output['model_name']},#{output['model_type']},#{compound.smiles},"\
-          "#{output['prediction_value'] != false ? output['prediction_value'] : "-"},"\
-          "#{output['converted_value'] != false ? output['converted_value'] : "-"},"\
+        csv = "#{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},#{inT},#{note.nil? ? "" : note.chomp}\n"
+          "#{inApp},#{note.nil? ? "" : note.chomp}\n"
       else # Classification
 
         # consensus mutagenicity
@@ -191,19 +191,20 @@ get '/batch/:model/' do
         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].flatten.first 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
+        output['sa_prediction'] = sa_prediction
+        output['sa_matches'] = sa_prediction[:matches].flatten 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
 
         csv = "#{idx+1},Consensus mutagenicity,#{compound.smiles},"\
-          "#{output['sa_prediction']['prediction'] == false ? "non-mutagenic" : "mutagenic"},"\
-          "#{output['confidence']},#{output['sa_matches'] != false ? "\"#{output['sa_matches']}\"" : "none"}, ,"\
-          "#{output['model_type']},#{output['prediction_value']},"\
+          "\"#{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'].join("; ")}\"" : "none"},"\
+          "#{output['prediction_value']},"\
           "#{output['probability'][0] != false ? output['probability'][0].split(":").last : ""},"\
           "#{output['probability'][1] != false ? output['probability'][1].split(":").last : ""},"\
-          "#{inApp},#{inT},#{note.nil? ? "" : note}\n"
+          "#{inApp},#{note.nil? ? "" : note}\n"
 
       end
       
@@ -211,21 +212,22 @@ get '/batch/:model/' do
 
     else #no prediction value
       inApp = "no"
-      inT = prediction[:info] =~ /\b(identical)\b/i ? "yes" : "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(" ")}\"" + ( prediction[:info] ? "\"#{prediction[:info]}\"" : "" )
+      note = "\"#{prediction[:warnings].join(" ")}\""
 
       output["warnings"] = prediction[:warnings]
       output["info"] = prediction[:info] if prediction[:info]
 
       if type == "Regression"
-        csv = "#{idx+1},#{output['model_name']},#{output['model_type']},#{compound.smiles},,,,,,,"+ [inApp,inT,note].join(",")+"\n"
+        csv = "#{idx+1},#{output['model_name']},#{compound.smiles},#{prediction[:info] ? prediction[:info] : "no"},"\
+          "#{prediction[:measurements] if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
       else
-        csv = "#{idx+1},Consensus mutagenicity,#{compound.smiles},,,,,#{output['model_type']},,,,"+ [inApp,inT,note].join(",")+"\n"
+        csv = "#{idx+1},Consensus mutagenicity,#{compound.smiles},#{prediction[:info] ? prediction[:info] : "no"},"\
+          "#{prediction[:measurements] if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
       end
 
     end #prediction value
@@ -256,7 +258,9 @@ post '/predict/?' do
       $logger.debug "save dataset #{params[:fileselect][:filename]}"
       if input.class == OpenTox::Dataset
         @dataset = Dataset.find input
+        $logger.debug "get compounds"
         @compounds = @dataset.compounds
+        $logger.debug "get compounds finish"
       else
         bad_request_error "Could not serialize file '#{@filename}'."
       end
@@ -272,6 +276,7 @@ post '/predict/?' do
     
     @models = params[:selection].keys
     @tmppaths = {}
+    $logger.debug "get endpoint"
     @models.each do |model|
       m = Model::Validation.find model
       type = (m.regression? ? "Regression" : "Classification") unless model == "Cramer"
@@ -279,21 +284,23 @@ post '/predict/?' do
       if type == "Regression"
         unit = (type == "Regression") ? "(#{m.unit})" : ""
         converted_unit = (type == "Regression") ? "#{m.unit =~ /\b(mmol\/L)\b/ ? "(mg/L)" : "(mg/kg_bw/day)"}" : ""
-        header = "ID,Endpoint,Type,Unique SMILES,Prediction #{unit},Prediction #{converted_unit},"\
-          "Interval Low #{unit},Interval High #{unit},Interval Low #{converted_unit},Interval High #{converted_unit},"\
-          "inApplicabilityDomain,inTrainningSet,Note\n"
+        header = "ID,Endpoint,Unique SMILES,inTrainingSet,Measurements,Prediction #{unit},Prediction #{converted_unit},"\
+          "Prediction Interval Low #{unit},Prediction Interval High #{unit},"\
+          "Prediction Interval Low #{converted_unit},Prediction Interval High #{converted_unit},"\
+          "inApplicabilityDomain,Note\n"
       end
       # add header for classification
       if type == "Classification"
         av = m.prediction_feature.accept_values
-        header = "ID,Endpoint,Unique SMILES,Structural alerts prediction,Structural alerts confidence,"\
-          "Structural alerts for mutagenicity,Lazar mutagenicity (Salmonella typhimurium),Type,Prediction,"\
-          "predProbability #{av[0]},predProbability #{av[1]},inApplicabilityDomain,inTrainningSet,Note\n"
+        header = "ID,Endpoint,Unique SMILES,inTrainingSet,Measurements,Consensus Prediction,Consensus Confidence,"\
+          "Structural alerts for mutagenicity,Lazar Prediction,"\
+          "Lazar predProbability #{av[0]},Lazar predProbability #{av[1]},inApplicabilityDomain,Note\n"
       end
       path = File.join("tmp", "#{Time.now.strftime("%Y-%m-%d")}_#{SecureRandom.urlsafe_base64(5)}")
       File.open(path, "w"){|f| f.write(header) if header}
       @tmppaths[model] = path.split("/").last
     end
+    $logger.debug "get endpoint finished"
 
     File.delete File.join("tmp", params[:fileselect][:filename])
     return haml :batch
diff --git a/views/batch.haml b/views/batch.haml
index aaa09bf..fccd88c 100644
--- a/views/batch.haml
+++ b/views/batch.haml
@@ -26,10 +26,10 @@
     // create request
     if (model == "Cramer"){
       var dataset = '#{@dataset.id}';
-      var uri = "#{to("/batch/")}" + model + '/?dataset=' + escape(dataset) + '&tmppath=' + tmppath + '&last=' + last;
+      var uri = "#{to("/batch/")}" + model + '/?dataset=' + escape(dataset) + '&tmppath=' + tmppath;
     } else {
       var dataset = '#{@dataset.id}';
-      var uri = "#{to("/batch/")}" + model + '/?compound=' + escape(compound) + '&dataset=' + dataset + '&idx=' + idx + '&tmppath=' + tmppath + '&last=' + last;
+      var uri = "#{to("/batch/")}" + model + '/?compound=' + escape(compound) + '&dataset=' + dataset + '&idx=' + idx + '&tmppath=' + tmppath;
     };
     var aClient = new HttpClient();
     aClient.get(uri, function(res) {
@@ -56,15 +56,20 @@
           if (response['db_hit'] != false){
             var value = document.createTextNode(response['db_hit']);
             p.appendChild(value);
+            var h2 = document.createElement("h5");
+            var t = document.createTextNode("Measurements:");
+            h2.appendChild(t);
+            p.appendChild(h2);
+            for (var i=0; i<response['measurements'].length; i++){
+              var value = document.createTextNode(response['measurements'][i]);
+              var br = document.createElement("br");
+              p.appendChild(value);
+              p.appendChild(br);
+            };
           };
-          // Structural alerts
-          var h2 = document.createElement("h5");
-          var t = document.createTextNode("Structural alerts:");
-          h2.appendChild(t);
-          p.appendChild(h2);
-          // prediction
+          // Consensus prediction
           var h3 = document.createElement("h5");
-          var t = document.createTextNode("Prediction:");
+          var t = document.createTextNode("Consensus prediction:");
           if (response['sa_prediction']['prediction'] == false){
             var value = document.createTextNode("non-mutagenic");
           };
@@ -74,9 +79,9 @@
           h3.appendChild(t);
           p.appendChild(h3);
           p.appendChild(value);
-          // confidence
+          // Consensus confidence
           var h4 = document.createElement("h5");
-          var t = document.createTextNode("Confidence:");
+          var t = document.createTextNode("Consensus confidence:");
           var value = document.createTextNode(response['confidence']);
           h4.appendChild(t);
           p.appendChild(h4);
@@ -110,13 +115,6 @@
             var value = document.createTextNode(response['model_name']);
             h.appendChild(value);
             p.appendChild(h);
-          } else if (val == "type") {
-            var t = document.createTextNode("Type: ");
-            var value = document.createTextNode(response['model_type']);
-            h.appendChild(t);
-            p.appendChild(h);
-            p.appendChild(value);
-            h.style.display = "inline";
           } else if (val == "db_hit" && response['db_hit'] != false && response['sa_prediction'] == false) {
             var value = document.createTextNode(response['db_hit']);
             p.appendChild(value);
diff --git a/views/predict.haml b/views/predict.haml
index eb9047b..6b1c462 100644
--- a/views/predict.haml
+++ b/views/predict.haml
@@ -130,7 +130,7 @@
       %a.btn.glyphicon.glyphicon-info-sign{:href=>"javascript:void(0)", :title=>"File format", :tabindex=>"0", data: {trigger:"focus", toggle:"popover", placement:"auto", html:"true", content:"One column with compounds and keyword SMILES or InChI in the first row."}}
       %br
       %span.btn.btn-default.btn-file
-        %input{:type=>"file", :name=> "fileselect", :id=>"fileselect", :accept=>"text/csv"}
+        %input{:type=>"file", :name=> "fileselect", :id=>"fileselect", :autocomplete=>"off", :accept=>"text/csv"}
 
   %fieldset#middle.well
     %h2 2. Select one or more endpoints
diff --git a/views/prediction.haml b/views/prediction.haml
index b5a7e82..872ee1e 100644
--- a/views/prediction.haml
+++ b/views/prediction.haml
@@ -38,39 +38,34 @@
                 - if sa_prediction
                   - hash = sa_prediction[:prediction]
                   - confidence = sa_prediction[:confidence]
-                  %p
-                  %b Structural alerts:
-                  %p
                   / check for database hit
                   - if prediction[:info] =~ /\b(identical)\b/i
                     - @dbhit[i] = true
-                    / show message about dbhit and measurements
                     %p
                       :plain
                         This compound was part of the training dataset. <i>All</i> information </br>
                         from this compound was removed from the training data before the </br>
                         prediction, to obtain unbiased results.
                       %p
-                  %b Prediction:
+                      %b Measured activity:
+                      %br
+                      = prediction[:measurements].join("; ")
+                  %b Consensus prediction:
                   %br
                   =(hash[:prediction] == true ? "mutagenic" : "non-mutagenic")
                   %p
-                  %b Confidence:
+                  %b Consensus confidence:
                   %br
                   =confidence.to_f.signif(3)
                   %p
                   %b Structural alerts for mutagenicity:
                   %br
-                  =hash[:matches].flatten.first
-                  %p
+                  =hash[:matches].blank? ? "none" : hash[:matches].join("; ")
                 / check for prediction
+                %p
                 - if prediction[:neighbors] and !prediction[:value].nil?
                   %b.title= ("Lazar #{@models[i].endpoint.gsub('_', ' ').downcase} (#{@models[i].species}):" if sa_prediction)
                   %p
-                  / show model type (classification|regression)
-                  %b Type:
-                  = type
-                  %p 
                   / check for database hit
                   - if prediction[:info] =~ /\b(identical)\b/i
                     - @dbhit[i] = true
@@ -81,14 +76,14 @@
                           This compound was part of the training dataset. <i>All</i> information </br>
                           from this compound was removed from the training data before the </br>
                           prediction, to obtain unbiased results.
-                        %p
+                      %p
                         %b Measured activity:
                         %br
                         - if prediction[:measurements].is_a?(Array)
                           = (type == "Regression") ? prediction[:measurements].collect{|value| "#{value.delog10.signif(3)} (#{unit})</br>#{@compound.mmol_to_mg(value.delog10).signif(3)} #{unit =~ /mmol\/L/ ? "(mg/L)" : "(mg/kg_bw/day)"}"}.join("</br>") : prediction[:measurements].join(", ")
                         - else
                           = (type == "Regression") ? "#{prediction[:measurements].delog10.signif(3)} (#{unit})</br>#{@compound.mmol_to_mg(prediction[:measurements].delog10).signif(3)} #{(unit =~ /\b(mmol\/L)\b/) ? "(mg/L)" : "(mg/kg_bw/day)"}" : prediction[:measurements]
-                    
+                  
                   - else
                     - @dbhit[i] = false
                   
@@ -116,16 +111,23 @@
                           %br
                           = "#{prediction[:probabilities].keys[1]}: #{prediction[:probabilities].values[1].signif(3)}"
                   
+                    %p
+                    - if !prediction[:warnings].blank?
+                      %b Warnings:
+                      %br
+                      =prediction[:warnings].join("</br>")
+
                 - else
                   %p
                   - if !prediction[:info].blank?
-                    %b Info:
-                    %br
-                    %p=prediction[:info].sub(/\'.*\'/,"").sub(/,/, ",<br>")
+                    :plain
+                      This compound was part of the training dataset. <i>All</i> information </br>
+                      from this compound was removed from the training data before the </br>
+                      prediction, to obtain unbiased results.
                   - if !prediction[:warnings].blank?
                     %b Warnings:
-                    - prediction[:warnings].uniq.each do |warning|
-                      %p=warning.sub(/,/, ",<br>")
+                    %br
+                    =prediction[:warnings].join("</br>")
 
           / show Cramer rules if checked
           - if @toxtree == true
@@ -143,5 +145,3 @@
   / always show the neighbors table, message is given there. Except only Cramer is selected.
   - unless @predictions.blank?
     = haml :neighbors, :layout => false
-    
-