serial batch prediction with task

8 files changed, 592 insertions, 199 deletions

diff --git a/application.rb b/application.rb
index 380b48a..4f73ad6 100644
--- a/application.rb
+++ b/application.rb
@@ -1,6 +1,5 @@
 include OpenTox
 
-
 configure :production do
   $logger = Logger.new(STDOUT)
   enable :reloader
@@ -39,8 +38,151 @@ helpers do
     end
     doc.to_html.html_safe
   end
-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
+      csv
+    end
+  end
+
+end
+              
 get '/?' do
   redirect to('/predict') 
 end
@@ -53,6 +195,42 @@ get '/predict/?' do
   @models.count <= 0 ? (haml :info) : (haml :predict)
 end
 
+get '/task/?' do
+  if params[:turi]
+    task = Task.find(params[:turi].to_s)
+    return JSON.pretty_generate(:percent => task.percent)
+  elsif params[:predictions]
+    pageSize = params[:pageSize].to_i - 1
+    pageNumber= params[:pageNumber].to_i - 1
+    compound = Compound.find @@compounds_ids[pageNumber]
+    image = compound.svg
+    smiles = compound.smiles
+    task = Task.find(params[:predictions].to_s)
+    unless task.predictions[params[:model]].nil?
+      array = []
+      html = "<table class=\"table table-bordered single-batch\"><tr>"
+      html += "<td>#{image}</br>#{smiles}</br></td>"
+      string = "<td><table class=\"table\">"
+      prediction = task.predictions[params[:model]][pageNumber.to_i]
+      sort = []
+      if prediction[:info]
+        sort << {"info" => prediction[:info]}
+        sort << {"measurements" => prediction[:measurements].join("</br>")}
+        prediction.delete("info")
+        prediction.delete("measurements")
+      end
+      task.predictions[params[:model]][pageNumber.to_i].each do |k,v|
+       string += "<tr><td>#{(k=="value" ? "prediction" : k).capitalize}:</td> "\
+          "<td>#{v.blank? ? "none" : (v.kind_of?(Array) ? v.join("\</br>") : v)}</td></tr>"
+      end
+      string += "</table></td>"
+      html += "#{string}</tr></table>"
+      array << [html]
+    end
+    return JSON.pretty_generate(:predictions => array)
+  end
+end
+
 get '/predict/modeldetails/:model' do
   model = Model::Validation.find params[:model]
   crossvalidations = Validation::RepeatedCrossValidation.find(model.repeated_crossvalidation_id).crossvalidations
@@ -71,175 +249,13 @@ get '/predict/dataset/:name' do
   csv
 end
 
-get '/predict/:tmppath/:model/:filename?' do
+get '/predict/csv/:task/:model/:filename/?' do
   response['Content-Type'] = "text/csv"
-  path = File.join("tmp", params[:tmppath])
-  `sort -gk1 #{path} -o #{path}`
-
-  send_file path, :filename => "#{Time.now.strftime("%Y-%m-%d")}_lazar_batch_prediction_#{params[:model]}_#{params[:filename]}", :type => "text/csv", :disposition => "attachment"
-end
-
-get '/batch/:model/' do
-
-  if params[:model] == "Cramer"
-    dataset = Dataset.find params[:dataset]
-    compounds = dataset.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
-
-    # td paths to insert results in GUI
-    compound_ids = dataset.compounds.collect{|c| c.id}
-    output["tds"] = compound_ids.each_with_index.map{|cid,idx| "prediction_#{cid}_Cramer_#{idx}"}
-    
-    # write to file
-    # 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
-    File.open(File.join("tmp", params[:tmppath]),"a+"){|file| file.write(csv)}
-
-    # cleanup
-    dataset.delete
-
-    # return output
-    response['Content-Type'] = "application/json"
-    return JSON.pretty_generate output
-
-  else
-    idx = params[:idx].to_i
-    compound = Compound.find params[:compound]
-
-    model = Model::Validation.find params[:model]
-    prediction = model.predict(compound)
-    output = {}
-    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
-
-        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},#{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
-
-        csv = "#{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"
-        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},#{prediction[:info] ? prediction[:info] : "no"},"\
-          "#{prediction[:measurements] if prediction[:info]},,,,,,,"+ [inApp,note].join(",")+"\n"
-      end
-
-    end #prediction value
-
-    # write to file
-    File.open(File.join("tmp", params[:tmppath]),"a"){|file| file.write(csv)}
-
-    # return output
-    response['Content-Type'] = "application/json"
-    return JSON.pretty_generate output
-
-  end# if Cramer
+  task = Task.find params[:task].to_s
+  tempfile = Tempfile.new
+  tempfile.write(task.csv)
+  tempfile.rewind
+  send_file tempfile, :filename => "#{Time.now.strftime("%Y-%m-%d")}_lazar_batch_prediction_#{params[:model]}_#{params[:filename]}", :type => "text/csv", :disposition => "attachment"
 end
 
 post '/predict/?' do
@@ -273,33 +289,98 @@ post '/predict/?' do
     end
     
     @models = params[:selection].keys
-    @tmppaths = {}
-    @models.each do |model|
-      m = Model::Validation.find model
-      type = (m.regression? ? "Regression" : "Classification") unless model == "Cramer"
-      # add header for regression
-      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,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,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
+    # for single predictions in batch
+    @@compounds_ids = @compounds.collect{|c| c.id.to_s}
+    @tasks = []
+    @models.each{|m| t = Task.new; t.save; @tasks << t}
+    @predictions = {}
+    task = Task.run do
+      @models.each_with_index do |model,idx|
+        t = @tasks[idx]
+        unless model == "Cramer"
+          m = Model::Validation.find model
+          type = (m.regression? ? "Regression" : "Classification")
+          # add header for regression
+          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,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,inTrainingSet,Measurements,Consensus Prediction,Consensus Confidence,"\
+              "Structural alerts for mutagenicity,Lazar Prediction,"\
+              "Lazar predProbability #{av[0]},Lazar predProbability #{av[1]},inApplicabilityDomain,Note\n"
+          end
+          # predict compounds
+          p = 100.0/@compounds.size
+          counter = 1
+          predictions = []
+          @compounds.each do |compound|
+            prediction = m.predict(compound)
+            if type == "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
+              prediction["Consensus prediction"] = sa_prediction[:prediction] == false ? "non-mutagenic" : "mutagenic"
+              prediction["Consensus confidence"] = confidence.signif(3)
+              prediction["Structural alerts for mutagenicity"] = sa_prediction[:matches] ? sa_prediction[:matches].collect{|a| a.first}.join("; ") : "none"
+            end
+            predictions << prediction.delete_if{|k,v| k =~ /neighbors|prediction_feature_id/i}
+            t.update_percent((counter*p).ceil)
+            counter += 1
+          end
+          # write csv
+          t[:csv] = header + to_csv(model,predictions,@compounds)
+          # write predictions
+          @predictions["#{model}"] = predictions
+        else # Cramer model
+          #t[:csv] = to_csv(model,nil,@compounds)
+          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["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"
+          # content
+          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
+          # write csv
+          t[:csv] = csv
+          # write predictions
+          @predictions["#{model}"] = predictions
+          t.update_percent(100)
+        end
+        # save task 
+        # append predictions as last action otherwise they won't save
+        # mongoid works with shallow copy via #dup
+        t[:predictions] = @predictions
+        t.save
+      end#models
+
+    end#main task
 
     File.delete File.join("tmp", params[:fileselect][:filename])
-    return haml :batch
+    return haml :task
   end
 
   # single compound prediction
@@ -350,4 +431,3 @@ get '/style.css' do
   headers 'Content-Type' => 'text/css; charset=utf-8'
   scss :style
 end
-
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
diff --git a/public/javascripts/pagination.min.js b/public/javascripts/pagination.min.js
new file mode 100644
index 0000000..89faf77
--- /dev/null
+++ b/public/javascripts/pagination.min.js
@@ -0,0 +1,11 @@
+/*
+ * pagination.js 2.0.7
+ * A jQuery plugin to provide simple yet fully customisable pagination
+ * https://github.com/superRaytin/paginationjs
+
+ * Homepage: http://paginationjs.com
+ *
+ * Copyright 2014-2100, superRaytin
+ * Released under the MIT license.
+*/
+!function(a,b){function c(a){throw new Error("Pagination: "+a)}function d(a){a.dataSource||c('"dataSource" is required.'),"string"==typeof a.dataSource?"undefined"==typeof a.totalNumber?c('"totalNumber" is required.'):b.isNumeric(a.totalNumber)||c('"totalNumber" is incorrect. (Number)'):j.isObject(a.dataSource)&&("undefined"==typeof a.locator?c('"dataSource" is an Object, please specify "locator".'):"string"==typeof a.locator||b.isFunction(a.locator)||c(""+a.locator+" is incorrect. (String | Function)"))}function e(a){var c=["go","previous","next","disable","enable","refresh","show","hide","destroy"];b.each(c,function(b,c){a.off(i+c)}),a.data("pagination",{}),b(".paginationjs",a).remove()}function f(a,b){return("object"==(b=typeof a)?null==a&&"null"||Object.prototype.toString.call(a).slice(8,-1):b).toLowerCase()}"undefined"==typeof b&&c("Pagination requires jQuery.");var g="pagination",h="addHook",i="__pagination-";b.fn.pagination&&(g="pagination2"),b.fn[g]=function(f){if("undefined"==typeof f)return this;var g=b(this),h={initialize:function(){var a=this;if(g.data("pagination")||g.data("pagination",{}),a.callHook("beforeInit")!==!1){g.data("pagination").initialized&&b(".paginationjs",g).remove(),a.disabled=!!l.disabled;var c=a.model={pageRange:l.pageRange,pageSize:l.pageSize};a.parseDataSource(l.dataSource,function(b){if(a.sync=j.isArray(b),a.sync&&(c.totalNumber=l.totalNumber=b.length),c.totalPage=a.getTotalPage(),!(l.hideWhenLessThanOnePage&&c.totalPage<=1)){var d=a.render(!0);l.className&&d.addClass(l.className),c.el=d,g["bottom"===l.position?"append":"prepend"](d),a.observer(),g.data("pagination").initialized=!0,a.callHook("afterInit",d)}})}},render:function(a){var c=this,d=c.model,e=d.el||b('<div class="paginationjs"></div>'),f=a!==!0;c.callHook("beforeRender",f);var g=d.pageNumber||l.pageNumber,h=l.pageRange,i=d.totalPage,j=g-h,k=g+h;return k>i&&(k=i,j=i-2*h,j=1>j?1:j),1>=j&&(j=1,k=Math.min(2*h+1,i)),e.html(c.createTemplate({currentPage:g,pageRange:h,totalPage:i,rangeStart:j,rangeEnd:k})),c.callHook("afterRender",f),e},createTemplate:function(a){var c,d,e=this,f=a.currentPage,g=a.totalPage,h=a.rangeStart,i=a.rangeEnd,j=l.totalNumber,k=l.showPrevious,m=l.showNext,n=l.showPageNumbers,o=l.showNavigator,p=l.showGoInput,q=l.showGoButton,r=l.pageLink,s=l.prevText,t=l.nextText,u=l.ellipsisText,v=l.goButtonText,w=l.classPrefix,x=l.activeClassName,y=l.disableClassName,z=l.ulClassName,A=b.isFunction(l.formatNavigator)?l.formatNavigator():l.formatNavigator,B=b.isFunction(l.formatGoInput)?l.formatGoInput():l.formatGoInput,C=b.isFunction(l.formatGoButton)?l.formatGoButton():l.formatGoButton,D=b.isFunction(l.autoHidePrevious)?l.autoHidePrevious():l.autoHidePrevious,E=b.isFunction(l.autoHideNext)?l.autoHideNext():l.autoHideNext,F=b.isFunction(l.header)?l.header():l.header,G=b.isFunction(l.footer)?l.footer():l.footer,H="",I='<input type="text" class="J-paginationjs-go-pagenumber">',J='<input type="button" class="J-paginationjs-go-button" value="'+v+'">';if(F&&(c=e.replaceVariables(F,{currentPage:f,totalPage:g,totalNumber:j}),H+=c),k||n||m){if(H+='<div class="paginationjs-pages">',H+=z?'<ul class="'+z+'">':"<ul>",k&&(1===f?D||(H+='<li class="'+w+"-prev "+y+'"><a>'+s+"</a></li>"):H+='<li class="'+w+'-prev J-paginationjs-previous" data-num="'+(f-1)+'" title="Previous page"><a href="'+r+'">'+s+"</a></li>"),n){if(3>=h)for(d=1;h>d;d++)H+=d==f?'<li class="'+w+"-page J-paginationjs-page "+x+'" data-num="'+d+'"><a>'+d+"</a></li>":'<li class="'+w+'-page J-paginationjs-page" data-num="'+d+'"><a href="'+r+'">'+d+"</a></li>";else l.showFirstOnEllipsisShow&&(H+='<li class="'+w+"-page "+w+'-first J-paginationjs-page" data-num="1"><a href="'+r+'">1</a></li>'),H+='<li class="'+w+"-ellipsis "+y+'"><a>'+u+"</a></li>";for(d=h;i>=d;d++)H+=d==f?'<li class="'+w+"-page J-paginationjs-page "+x+'" data-num="'+d+'"><a>'+d+"</a></li>":'<li class="'+w+'-page J-paginationjs-page" data-num="'+d+'"><a href="'+r+'">'+d+"</a></li>";if(i>=g-2)for(d=i+1;g>=d;d++)H+='<li class="'+w+'-page J-paginationjs-page" data-num="'+d+'"><a href="'+r+'">'+d+"</a></li>";else H+='<li class="'+w+"-ellipsis "+y+'"><a>'+u+"</a></li>",l.showLastOnEllipsisShow&&(H+='<li class="'+w+"-page "+w+'-last J-paginationjs-page" data-num="'+g+'"><a href="'+r+'">'+g+"</a></li>")}m&&(f==g?E||(H+='<li class="'+w+"-next "+y+'"><a>'+t+"</a></li>"):H+='<li class="'+w+'-next J-paginationjs-next" data-num="'+(f+1)+'" title="Next page"><a href="'+r+'">'+t+"</a></li>"),H+="</ul></div>"}return o&&A&&(c=e.replaceVariables(A,{currentPage:f,totalPage:g,totalNumber:j}),H+='<div class="'+w+'-nav J-paginationjs-nav">'+c+"</div>"),p&&B&&(c=e.replaceVariables(B,{currentPage:f,totalPage:g,totalNumber:j,input:I}),H+='<div class="'+w+'-go-input">'+c+"</div>"),q&&C&&(c=e.replaceVariables(C,{currentPage:f,totalPage:g,totalNumber:j,button:J}),H+='<div class="'+w+'-go-button">'+c+"</div>"),G&&(c=e.replaceVariables(G,{currentPage:f,totalPage:g,totalNumber:j}),H+=c),H},go:function(a,c){function d(a){if(e.callHook("beforePaging",h)===!1)return!1;if(f.direction="undefined"==typeof f.pageNumber?0:h>f.pageNumber?1:-1,f.pageNumber=h,e.render(),e.disabled&&!e.sync&&e.enable(),g.data("pagination").model=f,b.isFunction(l.formatResult)){var d=b.extend(!0,[],a);j.isArray(a=l.formatResult(d))||(a=d)}g.data("pagination").currentPageData=a,e.doCallback(a,c),e.callHook("afterPaging",h),1==h&&e.callHook("afterIsFirstPage"),h==f.totalPage&&e.callHook("afterIsLastPage")}var e=this,f=e.model;if(!e.disabled){var h=a,i=l.pageSize,k=f.totalPage;if(h=parseInt(h),!(!h||1>h||h>k)){if(e.sync)return void d(e.getDataSegment(h));var m={},n=l.alias||{};m[n.pageSize?n.pageSize:"pageSize"]=i,m[n.pageNumber?n.pageNumber:"pageNumber"]=h;var o={type:"get",cache:!1,data:{},contentType:"application/x-www-form-urlencoded; charset=UTF-8",dataType:"json",async:!0};b.extend(!0,o,l.ajax),b.extend(o.data||{},m),o.url=l.dataSource,o.success=function(a){d(e.filterDataByLocator(a))},o.error=function(a,b,c){l.formatAjaxError&&l.formatAjaxError(a,b,c),e.enable()},e.disable(),b.ajax(o)}}},doCallback:function(a,c){var d=this,e=d.model;b.isFunction(c)?c(a,e):b.isFunction(l.callback)&&l.callback(a,e)},destroy:function(){this.callHook("beforeDestroy")!==!1&&(this.model.el.remove(),g.off(),b("#paginationjs-style").remove(),this.callHook("afterDestroy"))},previous:function(a){this.go(this.model.pageNumber-1,a)},next:function(a){this.go(this.model.pageNumber+1,a)},disable:function(){var a=this,b=a.sync?"sync":"async";a.callHook("beforeDisable",b)!==!1&&(a.disabled=!0,a.model.disabled=!0,a.callHook("afterDisable",b))},enable:function(){var a=this,b=a.sync?"sync":"async";a.callHook("beforeEnable",b)!==!1&&(a.disabled=!1,a.model.disabled=!1,a.callHook("afterEnable",b))},refresh:function(a){this.go(this.model.pageNumber,a)},show:function(){var a=this;a.model.el.is(":visible")||a.model.el.show()},hide:function(){var a=this;a.model.el.is(":visible")&&a.model.el.hide()},replaceVariables:function(a,b){var c;for(var d in b){var e=b[d],f=new RegExp("<%=\\s*"+d+"\\s*%>","img");c=(c||a).replace(f,e)}return c},getDataSegment:function(a){var b=l.pageSize,c=l.dataSource,d=l.totalNumber,e=b*(a-1)+1,f=Math.min(a*b,d);return c.slice(e-1,f)},getTotalPage:function(){return Math.ceil(l.totalNumber/l.pageSize)},getLocator:function(a){var d;return"string"==typeof a?d=a:b.isFunction(a)?d=a():c('"locator" is incorrect. (String | Function)'),d},filterDataByLocator:function(a){var d,e=this.getLocator(l.locator);if(j.isObject(a)){try{b.each(e.split("."),function(b,c){d=(d?d:a)[c]})}catch(f){}d?j.isArray(d)||c("dataSource."+e+" must be an Array."):c("dataSource."+e+" is undefined.")}return d||a},parseDataSource:function(a,d){var e=this,f=arguments;j.isObject(a)?d(l.dataSource=e.filterDataByLocator(a)):j.isArray(a)?d(l.dataSource=a):b.isFunction(a)?l.dataSource(function(a){b.isFunction(a)&&c('Unexpect parameter of the "done" Function.'),f.callee.call(e,a,d)}):"string"==typeof a?(/^https?|file:/.test(a)&&(l.ajaxDataType="jsonp"),d(a)):c('Unexpect data type of the "dataSource".')},callHook:function(c){var d,e=g.data("pagination"),f=Array.prototype.slice.apply(arguments);return f.shift(),l[c]&&b.isFunction(l[c])&&l[c].apply(a,f)===!1&&(d=!1),e.hooks&&e.hooks[c]&&b.each(e.hooks[c],function(b,c){c.apply(a,f)===!1&&(d=!1)}),d!==!1},observer:function(){var a=this,d=a.model.el;g.on(i+"go",function(d,e,f){e=parseInt(b.trim(e)),e&&(b.isNumeric(e)||c('"pageNumber" is incorrect. (Number)'),a.go(e,f))}),d.delegate(".J-paginationjs-page","click",function(c){var d=b(c.currentTarget),e=b.trim(d.attr("data-num"));return!e||d.hasClass(l.disableClassName)||d.hasClass(l.activeClassName)?void 0:a.callHook("beforePageOnClick",c,e)===!1?!1:(a.go(e),a.callHook("afterPageOnClick",c,e),l.pageLink?void 0:!1)}),d.delegate(".J-paginationjs-previous","click",function(c){var d=b(c.currentTarget),e=b.trim(d.attr("data-num"));return e&&!d.hasClass(l.disableClassName)?a.callHook("beforePreviousOnClick",c,e)===!1?!1:(a.go(e),a.callHook("afterPreviousOnClick",c,e),l.pageLink?void 0:!1):void 0}),d.delegate(".J-paginationjs-next","click",function(c){var d=b(c.currentTarget),e=b.trim(d.attr("data-num"));return e&&!d.hasClass(l.disableClassName)?a.callHook("beforeNextOnClick",c,e)===!1?!1:(a.go(e),a.callHook("afterNextOnClick",c,e),l.pageLink?void 0:!1):void 0}),d.delegate(".J-paginationjs-go-button","click",function(){var c=b(".J-paginationjs-go-pagenumber",d).val();return a.callHook("beforeGoButtonOnClick",event,c)===!1?!1:(g.trigger(i+"go",c),void a.callHook("afterGoButtonOnClick",event,c))}),d.delegate(".J-paginationjs-go-pagenumber","keyup",function(c){if(13===c.which){var e=b(c.currentTarget).val();if(a.callHook("beforeGoInputOnEnter",c,e)===!1)return!1;g.trigger(i+"go",e),b(".J-paginationjs-go-pagenumber",d).focus(),a.callHook("afterGoInputOnEnter",c,e)}}),g.on(i+"previous",function(b,c){a.previous(c)}),g.on(i+"next",function(b,c){a.next(c)}),g.on(i+"disable",function(){a.disable()}),g.on(i+"enable",function(){a.enable()}),g.on(i+"refresh",function(b,c){a.refresh(c)}),g.on(i+"show",function(){a.show()}),g.on(i+"hide",function(){a.hide()}),g.on(i+"destroy",function(){a.destroy()}),l.triggerPagingOnInit&&g.trigger(i+"go",Math.min(l.pageNumber,a.model.totalPage))}};if(g.data("pagination")&&g.data("pagination").initialized===!0){if(b.isNumeric(f))return g.trigger.call(this,i+"go",f,arguments[1]),this;if("string"==typeof f){var k=Array.prototype.slice.apply(arguments);switch(k[0]=i+k[0],f){case"previous":case"next":case"go":case"disable":case"enable":case"refresh":case"show":case"hide":case"destroy":g.trigger.apply(this,k);break;case"getSelectedPageNum":return g.data("pagination").model?g.data("pagination").model.pageNumber:g.data("pagination").attributes.pageNumber;case"getTotalPage":return g.data("pagination").model.totalPage;case"getSelectedPageData":return g.data("pagination").currentPageData;case"isDisabled":return g.data("pagination").model.disabled===!0;default:c("Pagination do not provide action: "+f)}return this}e(g)}else j.isObject(f)||c("Illegal options");var l=b.extend({},arguments.callee.defaults,f);return d(l),h.initialize(),this},b.fn[g].defaults={totalNumber:1,pageNumber:1,pageSize:10,pageRange:2,showPrevious:!0,showNext:!0,showPageNumbers:!0,showNavigator:!1,showGoInput:!1,showGoButton:!1,pageLink:"",prevText:"&laquo;",nextText:"&raquo;",ellipsisText:"...",goButtonText:"Go",classPrefix:"paginationjs",activeClassName:"active",disableClassName:"disabled",inlineStyle:!0,formatNavigator:"<%= currentPage %> / <%= totalPage %>",formatGoInput:"<%= input %>",formatGoButton:"<%= button %>",position:"bottom",autoHidePrevious:!1,autoHideNext:!1,triggerPagingOnInit:!0,hideWhenLessThanOnePage:!1,showFirstOnEllipsisShow:!0,showLastOnEllipsisShow:!0,callback:function(){}},b.fn[h]=function(a,d){arguments.length<2&&c("Missing argument."),b.isFunction(d)||c("callback must be a function.");var e=b(this),f=e.data("pagination");f||(e.data("pagination",{}),f=e.data("pagination")),!f.hooks&&(f.hooks={}),f.hooks[a]=f.hooks[a]||[],f.hooks[a].push(d)},b[g]=function(a,d){arguments.length<2&&c("Requires two parameters.");var e;return e="string"!=typeof a&&a instanceof jQuery?a:b(a),e.length?(e.pagination(d),e):void 0};var j={};b.each(["Object","Array"],function(a,b){j["is"+b]=function(a){return f(a)===b.toLowerCase()}}),"function"==typeof define&&define.amd&&define(function(){return b})}(this,window.jQuery);
\ No newline at end of file
diff --git a/public/stylesheets/pagination.css b/public/stylesheets/pagination.css
new file mode 100644
index 0000000..117bf0b
--- /dev/null
+++ b/public/stylesheets/pagination.css
@@ -0,0 +1 @@
+.paginationjs{line-height:1.6;font-family:Marmelad,"Lucida Grande",Arial,"Hiragino Sans GB",Georgia,sans-serif;font-size:14px;box-sizing:initial}.paginationjs:after{display:table;content:" ";clear:both}.paginationjs .paginationjs-pages{float:left}.paginationjs .paginationjs-pages ul{float:left;margin:0;padding:0}.paginationjs .paginationjs-go-button,.paginationjs .paginationjs-go-input,.paginationjs .paginationjs-nav{float:left;margin-left:10px;font-size:14px}.paginationjs .paginationjs-pages li{float:left;border:1px solid #aaa;border-right:none;list-style:none}.paginationjs .paginationjs-pages li>a{min-width:30px;height:28px;line-height:28px;display:block;background:#fff;font-size:14px;color:#333;text-decoration:none;text-align:center}.paginationjs .paginationjs-pages li>a:hover{background:#eee}.paginationjs .paginationjs-pages li.active{border:none}.paginationjs .paginationjs-pages li.active>a{height:30px;line-height:30px;background:#aaa;color:#fff}.paginationjs .paginationjs-pages li.disabled>a{opacity:.3}.paginationjs .paginationjs-pages li.disabled>a:hover{background:0 0}.paginationjs .paginationjs-pages li:first-child,.paginationjs .paginationjs-pages li:first-child>a{border-radius:3px 0 0 3px}.paginationjs .paginationjs-pages li:last-child{border-right:1px solid #aaa;border-radius:0 3px 3px 0}.paginationjs .paginationjs-pages li:last-child>a{border-radius:0 3px 3px 0}.paginationjs .paginationjs-go-input>input[type=text]{width:30px;height:28px;background:#fff;border-radius:3px;border:1px solid #aaa;padding:0;font-size:14px;text-align:center;vertical-align:baseline;outline:0;box-shadow:none;box-sizing:initial}.paginationjs .paginationjs-go-button>input[type=button]{min-width:40px;height:30px;line-height:28px;background:#fff;border-radius:3px;border:1px solid #aaa;text-align:center;padding:0 8px;font-size:14px;vertical-align:baseline;outline:0;box-shadow:none;color:#333;cursor:pointer;vertical-align:middle\9}.paginationjs.paginationjs-theme-blue .paginationjs-go-input>input[type=text],.paginationjs.paginationjs-theme-blue .paginationjs-pages li{border-color:#289de9}.paginationjs .paginationjs-go-button>input[type=button]:hover{background-color:#f8f8f8}.paginationjs .paginationjs-nav{height:30px;line-height:30px}.paginationjs .paginationjs-go-button,.paginationjs .paginationjs-go-input{margin-left:5px\9}.paginationjs.paginationjs-small{font-size:12px}.paginationjs.paginationjs-small .paginationjs-pages li>a{min-width:26px;height:24px;line-height:24px;font-size:12px}.paginationjs.paginationjs-small .paginationjs-pages li.active>a{height:26px;line-height:26px}.paginationjs.paginationjs-small .paginationjs-go-input{font-size:12px}.paginationjs.paginationjs-small .paginationjs-go-input>input[type=text]{width:26px;height:24px;font-size:12px}.paginationjs.paginationjs-small .paginationjs-go-button{font-size:12px}.paginationjs.paginationjs-small .paginationjs-go-button>input[type=button]{min-width:30px;height:26px;line-height:24px;padding:0 6px;font-size:12px}.paginationjs.paginationjs-small .paginationjs-nav{height:26px;line-height:26px;font-size:12px}.paginationjs.paginationjs-big{font-size:16px}.paginationjs.paginationjs-big .paginationjs-pages li>a{min-width:36px;height:34px;line-height:34px;font-size:16px}.paginationjs.paginationjs-big .paginationjs-pages li.active>a{height:36px;line-height:36px}.paginationjs.paginationjs-big .paginationjs-go-input{font-size:16px}.paginationjs.paginationjs-big .paginationjs-go-input>input[type=text]{width:36px;height:34px;font-size:16px}.paginationjs.paginationjs-big .paginationjs-go-button{font-size:16px}.paginationjs.paginationjs-big .paginationjs-go-button>input[type=button]{min-width:50px;height:36px;line-height:34px;padding:0 12px;font-size:16px}.paginationjs.paginationjs-big .paginationjs-nav{height:36px;line-height:36px;font-size:16px}.paginationjs.paginationjs-theme-blue .paginationjs-pages li>a{color:#289de9}.paginationjs.paginationjs-theme-blue .paginationjs-pages li>a:hover{background:#e9f4fc}.paginationjs.paginationjs-theme-blue .paginationjs-pages li.active>a{background:#289de9;color:#fff}.paginationjs.paginationjs-theme-blue .paginationjs-pages li.disabled>a:hover{background:0 0}.paginationjs.paginationjs-theme-blue .paginationjs-go-button>input[type=button]{background:#289de9;border-color:#289de9;color:#fff}.paginationjs.paginationjs-theme-green .paginationjs-go-input>input[type=text],.paginationjs.paginationjs-theme-green .paginationjs-pages li{border-color:#449d44}.paginationjs.paginationjs-theme-blue .paginationjs-go-button>input[type=button]:hover{background-color:#3ca5ea}.paginationjs.paginationjs-theme-green .paginationjs-pages li>a{color:#449d44}.paginationjs.paginationjs-theme-green .paginationjs-pages li>a:hover{background:#ebf4eb}.paginationjs.paginationjs-theme-green .paginationjs-pages li.active>a{background:#449d44;color:#fff}.paginationjs.paginationjs-theme-green .paginationjs-pages li.disabled>a:hover{background:0 0}.paginationjs.paginationjs-theme-green .paginationjs-go-button>input[type=button]{background:#449d44;border-color:#449d44;color:#fff}.paginationjs.paginationjs-theme-yellow .paginationjs-go-input>input[type=text],.paginationjs.paginationjs-theme-yellow .paginationjs-pages li{border-color:#ec971f}.paginationjs.paginationjs-theme-green .paginationjs-go-button>input[type=button]:hover{background-color:#55a555}.paginationjs.paginationjs-theme-yellow .paginationjs-pages li>a{color:#ec971f}.paginationjs.paginationjs-theme-yellow .paginationjs-pages li>a:hover{background:#fdf5e9}.paginationjs.paginationjs-theme-yellow .paginationjs-pages li.active>a{background:#ec971f;color:#fff}.paginationjs.paginationjs-theme-yellow .paginationjs-pages li.disabled>a:hover{background:0 0}.paginationjs.paginationjs-theme-yellow .paginationjs-go-button>input[type=button]{background:#ec971f;border-color:#ec971f;color:#fff}.paginationjs.paginationjs-theme-red .paginationjs-go-input>input[type=text],.paginationjs.paginationjs-theme-red .paginationjs-pages li{border-color:#c9302c}.paginationjs.paginationjs-theme-yellow .paginationjs-go-button>input[type=button]:hover{background-color:#eea135}.paginationjs.paginationjs-theme-red .paginationjs-pages li>a{color:#c9302c}.paginationjs.paginationjs-theme-red .paginationjs-pages li>a:hover{background:#faeaea}.paginationjs.paginationjs-theme-red .paginationjs-pages li.active>a{background:#c9302c;color:#fff}.paginationjs.paginationjs-theme-red .paginationjs-pages li.disabled>a:hover{background:0 0}.paginationjs.paginationjs-theme-red .paginationjs-go-button>input[type=button]{background:#c9302c;border-color:#c9302c;color:#fff}.paginationjs.paginationjs-theme-red .paginationjs-go-button>input[type=button]:hover{background-color:#ce4541}.paginationjs .paginationjs-pages li.paginationjs-next{border-right:1px solid #aaa\9}.paginationjs .paginationjs-go-input>input[type=text]{line-height:28px\9;vertical-align:middle\9}.paginationjs.paginationjs-big .paginationjs-pages li>a{line-height:36px\9}.paginationjs.paginationjs-big .paginationjs-go-input>input[type=text]{height:36px\9;line-height:36px\9}
\ No newline at end of file
diff --git a/unicorn.rb b/unicorn.rb
index e60b2bd..41f1ef6 100644
--- a/unicorn.rb
+++ b/unicorn.rb
@@ -1,3 +1,3 @@
-worker_processes 4
+#worker_processes 4
 timeout 6000
 listen 8088
diff --git a/views/layout.haml b/views/layout.haml
index 5ed63e8..9d73848 100644
--- a/views/layout.haml
+++ b/views/layout.haml
@@ -9,12 +9,14 @@
     %link{:rel=>'stylesheet', :href=>"#{'/css/bootstrap.min.css'}"}
     %link{:rel=>'stylesheet', :href=>"#{'/css/theme.default.min.css'}"}
     %link{:rel=>'stylesheet', :href=>"#{'/css/theme.bootstrap.min.css'}"}
-    %link{ :href=>"/style.css", :rel=>"stylesheet"}
-    %link{ :href=>"/stylesheets/jquery-ui.css", :rel=>"stylesheet"}
+    %link{:href=>"/style.css", :rel=>"stylesheet"}
+    %link{:href=>"/stylesheets/pagination.css", :rel=>"stylesheet"}
+    %link{:href=>"/stylesheets/jquery-ui.css", :rel=>"stylesheet"}
     %script{:src=>"/javascripts/jquery-1.11.2.min.js"}
     %script{:src=>"/javascripts/bootstrap.min.js"}
     %script{:src=>"/javascripts/jquery.tablesorter.min.js"}
     %script{:src=>"/javascripts/jquery.tablesorter.widgets.js"}
+    %script{:src=>"/javascripts/pagination.min.js"}
     %script{:src=>"/javascripts/lazar-gui.js"}
   %body
     %noscript
diff --git a/views/style.scss b/views/style.scss
index 2a8f9d4..2510864 100644
--- a/views/style.scss
+++ b/views/style.scss
@@ -98,6 +98,13 @@ supporters{
   margin-left: auto;
   margin-right: auto;
 }
+.single-batch{
+  width: 100%;
+}
+.single-batch{
+  table-layout: fixed;
+  width: 100%;
+}
 .footer{
   margin-top:3em;
 }
diff --git a/views/task.haml b/views/task.haml
new file mode 100644
index 0000000..f88bdc2
--- /dev/null
+++ b/views/task.haml
@@ -0,0 +1,131 @@
+:javascript
+
+  function progress(value,id) {
+    var percent = Math.round(value);
+    var bar = document.getElementById("bar_"+id);
+    var prog = document.getElementById("progress_"+id);
+    bar.style.width = value + '%';
+    if (percent == 100){
+      prog.style.display = "none";
+    };
+  }
+
+  var HttpClient = function() {
+    this.get = function(aUrl, aCallback) {
+    var anHttpRequest = new XMLHttpRequest();
+    anHttpRequest.onreadystatechange = function() {
+    if (anHttpRequest.readyState == 4 && anHttpRequest.status == 200)
+      aCallback(anHttpRequest.responseText);
+    }
+      anHttpRequest.open( "GET", aUrl, true );
+      anHttpRequest.send( null );
+    }
+  };  
+
+  var markers = [];
+
+  function renderTask(task_id,model_id,id) {
+    var uri = "#{to("/")}" + 'task/?turi=' + task_id;
+    var aClient = new HttpClient();
+    aClient.get(uri, function(res) {
+      var response = JSON.parse(res);
+      progress(response['percent'],id);
+      if (response['percent'] == 100){
+        window.clearInterval(markers[id]);
+        $("a#downbutton_"+id).show();
+        $("a#detailsbutton_"+id).show();
+        //pagePredictions(task_id,model_id,id);
+      };
+    });
+  };
+  function simpleTemplating(data) {
+    var html = '<ul class=pagination>';
+    $.each(data, function(index, item){
+      html += '<li>'+ item +'</li>'+'</br>';
+    });
+    html += '</ul>';
+    return html;
+  };
+  function pagePredictions(task_id,model_id,id){
+    //var compounds = #{@compounds_ids};
+    //console.log(compounds[id]);
+    //var compound = compounds[id];
+    button = document.getElementById("detailsbutton_"+id);
+    span = button.childNodes[1];
+    if (span.className == "glyphicon glyphicon-menu-right"){
+      span.className = "glyphicon glyphicon-menu-down";
+      $('#data-container_'+id).show();
+      $('#pager_'+id).show();
+      $('#pager_'+id).pagination({
+        dataSource: '#{to("/")}' + 'task/?predictions=' + task_id + '&model=' + model_id ,
+        locator: 'predictions',
+        totalNumber: #{@compounds.size},
+        pageSize: 1,
+        showPageNumbers: true,
+        showGoInput: true,
+        formatGoInput: 'go to <%= input %>',
+        formatAjaxError: function(jqXHR, textStatus, errorThrown) {
+          $('#data-container_'+id).html(errorThrown);
+        },
+        /*ajax: {
+          beforeSend: function() {
+            $('#data-container_'+id).html('Loading content ...');
+          }
+        },*/
+        callback: function(data, pagination) {
+          var html = simpleTemplating(data);
+          $('#data-container_'+id).html(html);
+          //$('#data-container_'+id).height(300);
+        }
+      });
+    } else if (span.className = "glyphicon glyphicon-menu-down"){
+      span.className = "glyphicon glyphicon-menu-right";
+      $('#data-container_'+id).hide();
+      $('#pager_'+id).hide();
+    };
+  };
+  $("a").click(function(event) {
+    event.preventDefault();
+  });
+%div.well
+  %a.btn.btn-warning{:href => to('/predict')}
+    %span.glyphicon.glyphicon-menu-left{:aria=>{:hidden=>"true"}}
+    New Prediction
+
+  / show file name
+  %topline
+    %div.row
+      %div.col-md-4
+        %h3 Batch Prediction Results:
+      %div.col-md-8
+        %h3= @filename
+
+
+  - @models.each_with_index do |model,idx|
+    - m = Model::Validation.find model unless model == "Cramer"
+    - task = @tasks[idx].id
+    - predictions = @tasks[idx].predictions["#{model}"]
+    #result.panel{:id=>idx}
+      %div.row
+        %div.col-md-6
+          %h5= (model == "Cramer") ? "Oral toxicity (Cramer rules)" : (m.endpoint =~ /Mutagenicity/i ? "Consensus mutagenicity" : "#{m.endpoint} (#{m.species})")
+        %div.col-md-6.h5
+          %a.btn.btn-default.btn-xs{:id => "detailsbutton_#{idx}", :data=>{:toggle=>"collapse"}, :href=>"javascript:void(0)", :onclick=>"pagePredictions('#{task}','#{model}','#{idx}')", :style=>"display:none;font-size:small;"}
+            %span.glyphicon.glyphicon-menu-right
+            Details
+          %a.btn.btn-default.btn-xs{:id => "downbutton_#{idx}", :href=>"#{to("/predict/csv/#{task}/#{model}/#{@filename}")}", :title=>"download", :style=>"display:none;font-size:small;"}
+            %span.glyphicon.glyphicon-download-alt
+            CSV
+      %div{:id=>"progress_#{idx}", :style=>"width:100%;height:2px;position:relative;background-color:#ccc;"}
+        %div{:id=>"bar_#{idx}", :style=>"background-color: #4CAF50;width:10px;height:2px;position:absolute;"}
+      - # increase interval timer for large datasets 
+      - ctimer = ((@compounds.size/1000) == 0 ? 1000 : ((@compounds.size/1000)*1000))
+      :javascript
+        var timer = #{ctimer};
+        $(document).ready(function(){
+          markers[#{idx}] = setInterval(function(){
+            renderTask('#{task}','#{model}',#{idx});
+          }, timer );
+        });
+      #data-container{:id=>idx,:style=>"width:100%;"}
+      #pager{:id=>idx}