added prediction objects;re-ordered code and cleanup

6 files changed, 173 insertions, 754 deletions

diff --git a/application.rb b/application.rb
index e4b9e38..0957d71 100644
--- a/application.rb
+++ b/application.rb
@@ -1,3 +1,6 @@
+require_relative 'task.rb'
+require_relative 'prediction.rb'
+require_relative 'helper.rb'
 include OpenTox
 
 configure :production do
@@ -23,171 +26,15 @@ error do
   haml :error
 end
 
-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
-      csv
-    end
-  end
-
-end
-              
 get '/?' do
   redirect to('/predict') 
 end
 
 get '/predict/?' do
+  if params[:tpid] && !params[:tpid].blank?
+    pid = params[:tpid].to_i
+    Process.kill(9,pid) #if (Process.getpgid(pid) rescue nil).present?
+  end
   @models = Model::Validation.all
   @models = @models.delete_if{|m| m.model.name =~ /\b(Net cell association)\b/}
   @endpoints = @models.collect{|m| m.endpoint}.sort.uniq
@@ -222,7 +69,6 @@ get '/task/?' do
         string = "<td><table class=\"table\">"
         prediction = task.predictions[params[:model]][pageNumber.to_i]
         sorter = []
-        $logger.debug prediction
         if prediction[:info]
           sorter << {"Info" => prediction[:info]}
           if prediction[:measurements_string].kind_of?(Array)
@@ -357,7 +203,18 @@ post '/predict/?' do
           counter = 1
           predictions = []
           @compounds.each do |compound|
-            prediction = m.predict(compound)
+            if Prediction.where(compound: compound.id, model: m.id).exists?
+              $logger.debug "prediction already exists !"
+              prediction = Prediction.find_by(compound: compound.id, model: m.id).prediction
+            else
+              prediction = m.predict(compound)
+              # save prediction object
+              prediction_object = Prediction.new
+              prediction_object[:compound] = compound.id
+              prediction_object[:model] = m.id
+              prediction_object[:prediction] = prediction
+              prediction_object.save
+            end
             if type == "Classification"# consensus mutagenicity
               sa_prediction = KaziusAlerts.predict(compound.smiles)
               lazar_mutagenicity = prediction
@@ -421,9 +278,6 @@ post '/predict/?' do
               "#{output["cramer_rules"][idx] != "nil" ? output["cramer_rules"][idx] : "none" },"\
               "#{output["cramer_rules_extensions"][idx] != "nil" ? output["cramer_rules_extensions"][idx] : "none"}\n"
           end
-          #predictions = []
-          #predictions << {"Cramer rules" => output["cramer_rules"]}
-          #predictions << {"Cramer rules, with extensions" => output["cramer_rules_extensions"]}
           predictions = {}
           predictions["Cramer rules"] = output["cramer_rules"].collect{|rule| rule != "nil" ? rule : "none"}
           predictions["Cramer rules, with extensions"] = output["cramer_rules_extensions"].collect{|rule| rule != "nil" ? rule : "none"}
@@ -442,9 +296,11 @@ post '/predict/?' do
       end#models
 
     end#main task
+    @pid = task.pid
+    $logger.debug "application pid: #{@pid}"
 
     File.delete File.join("tmp", params[:fileselect][:filename])
-    return haml :task
+    return haml :batch
   end
 
   # single compound prediction
diff --git a/helper.rb b/helper.rb
index 8837161..12a6ce2 100644
--- a/helper.rb
+++ b/helper.rb
@@ -97,7 +97,6 @@ helpers do
           else # Classification
 
             # consensus mutagenicity
-              
             sa_prediction = KaziusAlerts.predict(compound.smiles)
             lazar_mutagenicity = prediction
             confidence = 0
@@ -153,7 +152,6 @@ helpers do
         end
         csv += line
       end
-      $logger.debug csv
       csv
     end
   end
diff --git a/prediction.rb b/prediction.rb
new file mode 100644
index 0000000..4e46d52
--- /dev/null
+++ b/prediction.rb
@@ -0,0 +1,30 @@
+module OpenTox
+
+  class Prediction
+
+    include OpenTox
+    include Mongoid::Document
+    include Mongoid::Timestamps
+    store_in collection: "predictions"
+    field :compound, type: BSON::ObjectId
+    field :model, type: BSON::ObjectId
+    field :prediction, type: Hash, default:{}
+
+    attr_accessor :compound, :model, :prediction
+
+    def compound
+      self[:compound]
+    end
+    
+    def model
+      self[:model]
+    end
+    
+    def prediction
+      self[:prediction]
+    end
+
+  end
+
+end
+
diff --git a/task.rb b/task.rb
index 295e580..9b9ca26 100644
--- a/task.rb
+++ b/task.rb
@@ -1,177 +1,53 @@
 DEFAULT_TASK_MAX_DURATION = 36000
+
 module OpenTox
 
-  # Class for handling asynchronous tasks
   class Task
 
-    attr_accessor :pid, :observer_pid
+    include OpenTox
+    include Mongoid::Document
+    include Mongoid::Timestamps
+    store_in collection: "tasks"
+    field :pid, type: Integer
+    field :percent, type: Float, default: 0
+    field :predictions, type: Hash, default:{}
+    field :csv, type: String
 
-    def metadata
-      super true # always update metadata
-    end
+    attr_accessor :pid, :percent, :predictions, :csv
 
-    def self.task_uri
-      Task.new.uri
-    end
-
-    def self.run(description, creator=nil, uri=nil)
-
-      task = Task.new uri
-      #task[RDF::OT.created_at] = DateTime.now
-      #task[RDF::OT.hasStatus] = "Running"
-      #task[RDF::DC.description] = description.to_s
-      #task[RDF::DC.creator] = creator.to_s
-      #task[RDF::OT.percentageCompleted] = "0"
-      #task.put
-      pid = fork do
-        begin
-          #task.completed yield
-        rescue => e
-          # wrap non-opentox-errors first
-          #e = OpenTox::Error.new(500,e.message,nil,e.backtrace) unless e.is_a?(OpenTox::Error)
-          #$logger.error "error in task #{task.uri} created by #{creator}" # creator is not logged because error is logged when thrown
-          #RestClientWrapper.put(File.join(task.uri,'Error'),{:errorReport => e.to_ntriples},{:content_type => 'text/plain'})
-          #task.kill
-        end
-      end
-      Process.detach(pid)
-      #task.pid = pid
-
-      # watch if task has been cancelled 
-      #observer_pid = fork do
-      #  task.wait
-      #  begin
-      #    Process.kill(9,task.pid) if task.cancelled?
-      #  rescue
-      #    $logger.warn "Could not kill process of task #{task.uri}, pid: #{task.pid}"
-      #  end
-      #end
-      #Process.detach(observer_pid)
-      #task.observer_pid = observer_pid
-      #task
-      pid
-
-    end
-
-    def kill
-      Process.kill(9,@pid)
-      Process.kill(9,@observer_pid)
-    rescue # no need to raise an exception if processes are not running
-    end
-
-    def description
-      self.[](RDF::DC.description)
-    end
-
-    def creator
-      self.[](RDF::DC.creator)
+    def pid
+      self[:pid]
     end
     
-    def cancel
-      kill
-      self.[]=(RDF::OT.hasStatus, "Cancelled")
-      self.[]=(RDF::OT.finished_at, DateTime.now)
-      put
-    end
-
-    def completed(uri)
-      self.[]=(RDF::OT.resultURI, uri)
-      self.[]=(RDF::OT.hasStatus, "Completed")
-      self.[]=(RDF::OT.finished_at, DateTime.now)
-      self.[]=(RDF::OT.percentageCompleted, "100")
-      put
-    end
-
-    # waits for a task, unless time exceeds or state is no longer running
-    def wait
-      start_time = Time.new
-      due_to_time = start_time + DEFAULT_TASK_MAX_DURATION
-      dur = 0.2
-      while running? 
-        sleep dur
-        dur = [[(Time.new - start_time)/20.0,0.3].max,300.0].min
-        request_timeout_error "max wait time exceeded ("+DEFAULT_TASK_MAX_DURATION.to_s+"sec), task: '"+@uri.to_s+"'" if (Time.new > due_to_time)
-      end
+    def percent
+      self[:percent]
     end
-
-  end
-
-  def code
-    RestClientWrapper.get(@uri).code.to_i
-  end
-
-  # get only header for status requests
-  def running?
-    code == 202 
-  end
-
-  def cancelled?
-    code == 503
-  end
-
-  def completed?
-    code == 200
-  end
-
-  def error?
-    code >= 400 and code != 503
-  end
-
-  [:hasStatus, :resultURI, :created_at, :finished_at, :percentageCompleted].each do |method|
-    define_method method do
-      response = self.[](RDF::OT[method])
-      response = self.[](RDF::OT1[method]) unless response  # API 1.1 compatibility
-      response
+    
+    def predictions
+      self[:predictions]
     end
-  end
-
-  # Check status of a task
-  # @return [String] Status
-  def status
-    self[RDF::OT.hasStatus]
-  end
 
-  def error_report
-    get
-    report = {}
-    query = RDF::Query.new({
-      :report => {
-        RDF.type  => RDF::OT.ErrorReport,
-        :property => :value,
-      }
-    })
-    query.execute(@rdf).each do |solution|
-      report[solution.property] = solution.value.to_s
+    def csv
+      self[:csv]
     end
-    report
-  end
-
-  #TODO: subtasks (only for progress in validation)
-  class SubTask
     
-    def initialize(task, min, max)
-      #TODO add subtask code
+    def update_percent(percent)
+      self[:percent] = percent
+      save
     end
 
-    def self.create(task, min, max)
-      if task
-        SubTask.new(task, min, max)
-      else
-        nil
+    def self.run
+      task = Task.new #uri
+      pid = fork do
+        yield
       end
+      Process.detach(pid)
+      task[:pid] = pid
+      task.save
+      task
     end
-    
-    def waiting_for(task_uri)
-      #TODO add subtask code
-    end
-    
-    def progress(pct)
-      #TODO add subtask code
-    end
-    
-    def running?()
-      #TODO add subtask code
-    end
+
   end
 
 end
+
diff --git a/views/batch.haml b/views/batch.haml
index fccd88c..2fb5966 100644
--- a/views/batch.haml
+++ b/views/batch.haml
@@ -1,14 +1,14 @@
 :javascript
-  function progress(model,idx,total) {
-    var p = 100/total;
-    var percent = Math.round((idx+1)*p);
-    var bar = document.getElementById("bar_"+model);
-    var prog = document.getElementById("progress_"+model);
-    bar.style.width = percent + '%';
+
+  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) {
@@ -22,248 +22,66 @@
     }
   };  
 
-  function renderResponse(model,idx,compound,last,total,tmppath) {
-    // create request
-    if (model == "Cramer"){
-      var dataset = '#{@dataset.id}';
-      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;
-    };
+  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) {
-      // progress bar function
-      progress(model,idx,total);
-
       var response = JSON.parse(res);
-      var td = document.getElementById("prediction_"+compound+'_'+model+'_'+idx);
-      //td.innerHTML = "";
-      if (model != "Cramer"){
-        // init general structure
-        a = ["title", "type", "db_hit", "measurements", "prediction", "interval", "probability", "warnings", "info"];
-        
-        // handles consesus mutagenicity
-        if (response['sa_prediction'] != false){
-          var p = document.createElement("p");
-          var h = document.createElement("h5");
-          p.id = "sa";
-          // Consensus mutagenicity
-          var t = document.createTextNode("Consensus mutagenicity");
-          h.appendChild(t);
-          p.appendChild(h);
-          // handle db_hit first
-          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);
-            };
-          };
-          // Consensus prediction
-          var h3 = document.createElement("h5");
-          var t = document.createTextNode("Consensus prediction:");
-          if (response['sa_prediction']['prediction'] == false){
-            var value = document.createTextNode("non-mutagenic");
-          };
-          if (response['sa_prediction']['prediction'] == true){
-            var value = document.createTextNode("mutagenic");
-          };
-          h3.appendChild(t);
-          p.appendChild(h3);
-          p.appendChild(value);
-          // Consensus confidence
-          var h4 = document.createElement("h5");
-          var t = document.createTextNode("Consensus confidence:");
-          var value = document.createTextNode(response['confidence']);
-          h4.appendChild(t);
-          p.appendChild(h4);
-          p.appendChild(value);
-          // Structural alerts for mutagenicity
-          var h5 = document.createElement("h5");
-          var t = document.createTextNode("Structural alerts for mutagenicity:");
-          h5.appendChild(t);
-          p.appendChild(h5);
-          if (response['sa_matches'] != false){
-            var value = document.createTextNode(response['sa_matches']);
-            p.appendChild(value);
-          } else {
-            var span = document.createElement("span");
-            var value = document.createTextNode("none");
-            span.style.fontStyle = "italic";
-            span.appendChild(value);
-            p.appendChild(span);
-          };
-          
-          // append to td
-          td.appendChild(p);
-        };
-
-        // proceed to general structure
-        for (val of a){
-          var p = document.createElement("p");
-          var h = document.createElement("h5");
-          p.id = val;
-          if (val == "title") {
-            var value = document.createTextNode(response['model_name']);
-            h.appendChild(value);
-            p.appendChild(h);
-          } else if (val == "db_hit" && response['db_hit'] != false && response['sa_prediction'] == false) {
-            var value = document.createTextNode(response['db_hit']);
-            p.appendChild(value);
-          } else if (val == "measurements" && response['measurements'] != false) {
-            var t = document.createTextNode("Measurements:");
-            h.appendChild(t);
-            p.appendChild(h);
-            if (response['model_type'] == "Regression"){
-              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);
-                if (response['converted_measurements'] != false) {
-                  var value = document.createTextNode(response['converted_measurements'][i]);
-                  var br = document.createElement("br");
-                  p.appendChild(value);
-                  p.appendChild(br);
-                  if (i+1 != response['measurements'].length){
-                    var br2 = document.createElement("br");
-                    p.appendChild(br2);
-                  };
-                };
-              };
-            } else if (response['model_type'] == "Classification"){
-              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);
-              };
-            };
-          } else if (val == "prediction" && response['prediction_value'] != false) {
-            var t = document.createTextNode("Prediction:");
-            var value = document.createTextNode(response['prediction_value']+" "+response['model_unit']);
-            h.appendChild(t);
-            p.appendChild(h);
-            p.appendChild(value);
-            if (response['converted_value'] != false) {
-              var br = document.createElement("br");
-              var value = document.createTextNode(response['converted_value']+" "+response['converted_model_unit']);
-              p.appendChild(br);
-              p.appendChild(value);
-            };
-            if (response['model_type'] == "Classification" && response['probability'] != false){
-              var h = document.createElement("h5");
-              var t = document.createTextNode("Probability:");
-              h.appendChild(t);
-              p.appendChild(h);
-              for (var i=0; i<response['probability'].length; i++){
-                var value = document.createTextNode(response['probability'][i]);
-                var br = document.createElement("br");
-                p.appendChild(value);
-                p.appendChild(br);
-              };
-            };
-          } else if (val == "interval" && response['interval'] != false) {
-            var t = document.createTextNode("95% Prediction interval:");
-            var value = document.createTextNode(response['interval']+" "+response['model_unit']);
-            h.appendChild(t);
-            p.appendChild(h);
-            p.appendChild(value);
-            if (response['converted_interval'] != false) {
-              var br = document.createElement("br");
-              var value = document.createTextNode(response['converted_interval']+" "+response['converted_model_unit']);
-              p.appendChild(br);
-              p.appendChild(value);
-            };
-          } else if (val == "warnings" && response['warnings'] != false && response['db_hit'] == false) {
-            var t = document.createTextNode("Warnings: ");
-            h.appendChild(t);
-            p.appendChild(h);
-            for (var i=0; i<response['warnings'].length; i++){
-              var value = document.createTextNode(response['warnings'][i]);
-              var br = document.createElement("br");
-              p.appendChild(value);
-              p.appendChild(br);
-            };
-          } else if (val == "info" && response['info'] != false) {
-            var t = document.createTextNode("Info: ");
-            var value = document.createTextNode(response['info']);
-            h.appendChild(t);
-            p.appendChild(h);
-            p.appendChild(value);
-          };
-
-          // append to td
-          td.appendChild(p);
-        };
-      };// if model != Cramer
-      if (model == "Cramer"){
-        for(i=0; i < response['tds'].length; i++){
-          progress('Cramer',i,response['tds'].length);
-          var td = document.getElementById(response['tds'][i]);
-          var p = document.createElement("p");
-          var h = document.createElement("h5");
-          var t = document.createTextNode("Oral toxicity (Cramer rules)");
-          p.id = "cramer";
-          h.appendChild(t);
-          p.appendChild(h);
-          var h2 = document.createElement("h5");
-          var t = document.createTextNode("Cramer rules:");
-          h2.appendChild(t);
-          p.appendChild(h2);
-          if (response['cramer_rules'][i] != "nil"){
-            var value = document.createTextNode(response['cramer_rules'][i]);
-            p.appendChild(value);
-          } else {
-            var span = document.createElement("span");
-            var value = document.createTextNode("none");
-            span.style.fontStyle = "italic";
-            span.appendChild(value);
-            p.appendChild(span);
-          };
-          var h3 = document.createElement("h5");
-          var t = document.createTextNode("Cramer rules, with extensions:");
-          h3.appendChild(t);
-          p.appendChild(h3);
-          if (response['cramer_rules_extensions'][i] != "nil"){
-            var value = document.createTextNode(response['cramer_rules_extensions'][i]);
-            p.appendChild(value);
-          } else {
-            var span = document.createElement("span");
-            var value = document.createTextNode("none");
-            span.style.fontStyle = "italic";
-            span.appendChild(value);
-            p.appendChild(span);
-          };
-
-          // append to td
-          td.appendChild(p);
-          if (i === response['tds'].length-1) {
-            $("img#circle_Cramer").hide();
-            $("a#downbutton_Cramer").show();
-          };
-
-        };
-      };// if model == Cramer
-      // if last compound change progress to download;
-      if (last == true) {
-        $("img#circle_"+model).hide();
-        $("a#downbutton_"+model).show();
+      progress(response['percent'],id);
+      if (response['percent'] == 100){
+        window.clearInterval(markers[id]);
+        $("a#downbutton_"+id).removeClass("disabled");
+        $("a#detailsbutton_"+id).removeClass("disabled");
       };
     });
   };
-
-
+  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){
+    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).css("min-height", $(window).height() + "px" );
+        }
+      });
+    } else if (span.className = "glyphicon glyphicon-menu-down"){
+      span.className = "glyphicon glyphicon-menu-right";
+      $('#data-container_'+id).hide();
+      $('#pager_'+id).hide();
+    };
+  };
 %div.well
-  %a.btn.btn-warning{:href => to('/predict')}
+  %a.btn.btn-warning{:href => to("/predict?tpid=#{@pid}")}
     %span.glyphicon.glyphicon-menu-left{:aria=>{:hidden=>"true"}}
     New Prediction
 
@@ -274,63 +92,34 @@
         %h3 Batch Prediction Results:
       %div.col-md-8
         %h3= @filename
-  
-  / displays prediction result in table tabs
-  #tabs
-    %ul.nav.nav-tabs.nav-justified{:id=>"batchTabs", :role=>"tablist"}
-      - @models.each_with_index do |model,i|
-        - m = Model::Validation.find model unless model == "Cramer"
-        %li{:class => ("active" if i == 0)}
-          %a{:href => "#results_#{i+1}", :id => "linkTab#{i+1}", data: {toggle:"tab"}}
-            = (model == "Cramer") ? "Oral toxicity (Cramer rules)" : "#{m.endpoint} (#{m.species})"
-          %img.dlwait{:src=>"/images/wait30trans.gif", :id=>"circle_#{model}", :class=>"circle", :alt=>"wait", :style=>"display:none;"}
-          %a.csv.btn{:id => "downbutton_#{model}", :href=>"#{to("/predict/#{@tmppaths[model]}/#{model}/#{@filename}")}", :title=>"download", :style=>"display:none;"}
+
+
+  - @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})")
+          #pager{:id=>idx}
+        %div.col-md-6.h5
+          %a.btn.btn-default.btn-xs.disabled{:id => "detailsbutton_#{idx}", :data=>{:toggle=>"collapse"}, :href=>"javascript:void(0)", :onclick=>"pagePredictions('#{task}','#{model}','#{idx}')", :style=>"font-size:small;"}
+            %span.glyphicon.glyphicon-menu-right
+            Details
+          %a.btn.btn-default.btn-xs.disabled{:id => "downbutton_#{idx}", :href=>"#{to("/predict/csv/#{task}/#{model}/#{@filename}")}", :title=>"download", :style=>"font-size:small;"}
             %span.glyphicon.glyphicon-download-alt
             CSV
-
-    %div.tab-content
-      - csize = @compounds.size
-      - msize = @models.size
-      - timer = 0
-      - @models.each_with_index do |model,j|
-        #results.tab-pane{:id=>"#{j+1}", :class => ("active" if j == 0)}
-          %div{:id=>"progress_"+model, :style=>"width:100%;height:2px;position:relative;background-color:#ccc;"}
-            %div{:id=>"bar_"+model, :style=>"background-color: #4CAF50;width:10px;height:2px;position:absolute;"}
-          %table.table.table-bordered
-            %tbody
-              - @compounds.each_with_index do |compound,cidx|
-                - timer += 800
-                :javascript
-                  $(document).ready(function() {
-                    $("img.circle").show();
-                    var model = '#{model}',
-                        msize = #{msize},
-                        idx = #{j+1},
-                        last = false,
-                        compound = '#{compound.id}',
-                        csize = #{csize},
-                        cidx = #{cidx},
-                        timer = #{timer},
-                        tmppath = '#{@tmppaths[model]}';
-                    // check for last request;
-                    if (cidx+1 == csize) {
-                      last = true;
-                    };
-                    setTimeout(function(){
-                      if (model != "Cramer"){
-                        renderResponse(model,cidx,compound,last,csize,tmppath);
-                      } else if (model == "Cramer" && cidx == 0){
-                        renderResponse(model,cidx,compound,last,csize,tmppath);
-                      };
-                    }, timer );
-                  });
-                // table layout:
-                // one row per prediction;
-                // first col compound; sec col results
-                %tr{:id=>model}
-                  // compound
-                  %td.col-md-6{:id=>"compound"}
-                    %p=embedded_svg(compound.svg, title: compound.smiles)
-                    %p=compound.smiles
-                  // prediction values from js function
-                  %td.col-md-6{:id=>"prediction_#{compound.id}_#{model}_#{cidx}", :style => "vertical-align:top;"}
+      %div{:id=>"progress_#{idx}", :style=>"width:100%;height:3px;position:relative;background-color:#ccc;"}
+        %div{:id=>"bar_#{idx}", :style=>"background-color: #4CAF50;width:10px;height:3px;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}
diff --git a/views/task.haml b/views/task.haml
deleted file mode 100644
index 6d87416..0000000
--- a/views/task.haml
+++ /dev/null
@@ -1,130 +0,0 @@
-: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).removeClass("disabled");
-        $("a#detailsbutton_"+id).removeClass("disabled");
-        //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).css("min-height", $(window).height() + "px" );
-          //$('#data-container_'+id).height(500);
-        }
-      });
-    } else if (span.className = "glyphicon glyphicon-menu-down"){
-      span.className = "glyphicon glyphicon-menu-right";
-      $('#data-container_'+id).hide();
-      $('#pager_'+id).hide();
-    };
-  };
-%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})")
-          #pager{:id=>idx}
-        %div.col-md-6.h5
-          %a.btn.btn-default.btn-xs.disabled{:id => "detailsbutton_#{idx}", :data=>{:toggle=>"collapse"}, :href=>"javascript:void(0)", :onclick=>"pagePredictions('#{task}','#{model}','#{idx}')", :style=>"font-size:small;"}
-            %span.glyphicon.glyphicon-menu-right
-            Details
-          %a.btn.btn-default.btn-xs.disabled{:id => "downbutton_#{idx}", :href=>"#{to("/predict/csv/#{task}/#{model}/#{@filename}")}", :title=>"download", :style=>"font-size:small;"}
-            %span.glyphicon.glyphicon-download-alt
-            CSV
-      %div{:id=>"progress_#{idx}", :style=>"width:100%;height:3px;position:relative;background-color:#ccc;"}
-        %div{:id=>"bar_#{idx}", :style=>"background-color: #4CAF50;width:10px;height:3px;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}