introduced batch prediction

2 files changed, 16 insertions, 11 deletions

diff --git a/application.rb b/application.rb
index 0214db4..07af20b 100644
--- a/application.rb
+++ b/application.rb
@@ -208,13 +208,13 @@ post '/predict/?' do
     input = OpenTox::Dataset.from_csv_file File.join "tmp", params[:fileselect][:filename]
     dataset = OpenTox::Dataset.find input.id 
     @compounds = dataset.compounds
-    @models = []
-    @predictions = []
+    @batch = {}
     @compounds.each do |compound|
+      @batch[compound] = []
       params[:selection].keys.each do |model_id|
         model = Model::Prediction.find model_id
-        @models << model
-        @predictions << model.predict(compound)
+        prediction = model.predict(compound)
+        @batch[compound] << [model, prediction]
       end
     end
     input.delete
diff --git a/views/batch.haml b/views/batch.haml
index 5bae411..8fbc8cc 100644
--- a/views/batch.haml
+++ b/views/batch.haml
@@ -6,31 +6,36 @@
         %h3 Batch Prediction Results:
 
     %tbody
-    - @compounds.each_with_index do |compound,i|
+    / key = compound, values = array of arrays with model, prediction
+    - @batch.each do |key, values|
+      - compound = key
       %tr
-        %td{:id=>"compound", :style=>"vertical-align:top;"}
+        %td{:style=>"vertical-align:top;"}
           %p= compound.svg
           %p= compound.smiles
-        - @predictions.each_with_index do |prediction,i|
+        / array = single prediction [endpoint, result]
+        - values.each_with_index do |array,i|
           %td{:style=>"vertical-align:top;"}
+            - model = array[0]
+            - prediction = array[1]
             %b{:class => "title"}
-              = "#{@models[i].endpoint.gsub('_', ' ')} (#{@models[i].species})"
+              = "#{model.endpoint.gsub('_', ' ')} (#{model.species})"
             %p
             - if prediction[:confidence] == "measured"
               %p
               / TODO fix scientific notation from database
               %b Measured activity:
-              = prediction[:value].numeric? ? "#{prediction[:value].round(3)} (#{@models[i].unit})" : prediction[:value]
+              = prediction[:value].numeric? ? "#{prediction[:value].round(3)} (#{model.unit})" : prediction[:value]
               %p Compound is part of the training dataset
             - elsif prediction[:neighbors].size > 0
               %p
               / model type (classification|regression)
               %b Type:
-              = @models[i].model.class.to_s.match("Classification") ? "Classification" : "Regression"
+              = model.model.class.to_s.match("Classification") ? "Classification" : "Regression"
               %br
               %b Prediction:
               / TODO scientific notation
-              = prediction[:value].numeric? ? "#{'%.2e' % prediction[:value]} #{@models[i].unit}" : prediction[:value]
+              = prediction[:value].numeric? ? "#{'%.2e' % prediction[:value]} #{model.unit}" : prediction[:value]
               %br
               / TODO probability
               %b Confidence: