Initial GUI for Nestec models

6 files changed, 52 insertions, 18 deletions

diff --git a/lib/compound.rb b/lib/compound.rb
index a819f56..8f393f5 100644
--- a/lib/compound.rb
+++ b/lib/compound.rb
@@ -133,7 +133,7 @@ module OpenTox
       if self.svg_id.nil?
        svg = obconversion(smiles,"smi","svg")
        file = Mongo::Grid::File.new(svg, :filename => "#{id}.svg", :content_type => "image/svg")
-       update(:image_id => $gridfs.insert_one(file))
+       update(:svg_id => $gridfs.insert_one(file))
       end
       $gridfs.find_one(_id: self.svg_id).data
 
diff --git a/lib/crossvalidation.rb b/lib/crossvalidation.rb
index 58a9664..a10dc1d 100644
--- a/lib/crossvalidation.rb
+++ b/lib/crossvalidation.rb
@@ -105,9 +105,9 @@ module OpenTox
     field :mae, type: Float
     field :weighted_rmse, type: Float
     field :weighted_mae, type: Float
-    field :weighted_mae, type: Float
     field :r_squared, type: Float
     field :correlation_plot_id, type: BSON::ObjectId
+    field :confidence_plot_id, type: BSON::ObjectId
 
     def self.create model, n=10
       cv = self.new
@@ -147,7 +147,7 @@ module OpenTox
       predictions.each do |pred|
         compound_id,activity,prediction,confidence = pred
         if activity and prediction
-          error = Math.log(prediction)-Math.log(activity)
+          error = Math.log10(prediction)-Math.log10(activity)
           rmse += error**2
           weighted_rmse += confidence*error**2
           mae += error.abs
@@ -224,9 +224,27 @@ module OpenTox
       end
     end
 
+    def confidence_plot
+      tmpfile = "/tmp/#{id.to_s}_confidence.svg"
+      sorted_predictions = predictions.sort{|a,b| b[3]<=>a[3]}.collect{|p| [(Math.log10(p[1])-Math.log10(p[2]))**2,p[3]]}
+      R.assign "error", sorted_predictions.collect{|p| p[0]}
+      #R.assign "p", predictions.collect{|p| p[2]}
+      R.assign "confidence", predictions.collect{|p| p[2]}
+      #R.eval "diff = log(m)-log(p)"
+      R.eval "library(ggplot2)"
+      R.eval "svg(filename='#{tmpfile}')"
+      R.eval "image = qplot(confidence,error)"#,main='#{self.name}',asp=1,xlim=range, ylim=range)"
+      R.eval "ggsave(file='#{tmpfile}', plot=image)"
+        R.eval "dev.off()"
+        file = Mongo::Grid::File.new(File.read(tmpfile), :filename => "#{self.id.to_s}_confidence_plot.svg")
+        plot_id = $gridfs.insert_one(file)
+        update(:confidence_plot_id => plot_id)
+      $gridfs.find_one(_id: confidence_plot_id).data
+    end
+
     def correlation_plot
       unless correlation_plot_id
-        tmpfile = "/tmp/#{id.to_s}.svg"
+        tmpfile = "/tmp/#{id.to_s}_correlation.svg"
         x = predictions.collect{|p| p[1]}
         y = predictions.collect{|p| p[2]}
         attributes = Model::Lazar.find(self.model_id).attributes
diff --git a/lib/dataset.rb b/lib/dataset.rb
index 979753c..28d2120 100644
--- a/lib/dataset.rb
+++ b/lib/dataset.rb
@@ -118,7 +118,7 @@ module OpenTox
     def density_plot
       # TODO: create/store svg
       R.assign "acts", data_entries.collect{|r| r.first }#.compact
-      R.eval "plot(density(log(acts),na.rm= TRUE), main='log(#{features.first.name})')"
+      R.eval "plot(density(-log(acts),na.rm= TRUE), main='-log(#{features.first.name})')"
     end
 
     # Serialisation
diff --git a/lib/feature.rb b/lib/feature.rb
index 9521597..6fc2c06 100644
--- a/lib/feature.rb
+++ b/lib/feature.rb
@@ -2,7 +2,6 @@ module OpenTox
 
   # Basic feature class
   class Feature
-    field :name, type: String
     field :nominal, type: Boolean
     field :numeric, type: Boolean
     field :measured, type: Boolean
@@ -85,14 +84,10 @@ module OpenTox
 
   # Feature for categorical bioassay results
   class NominalBioAssay < NominalFeature
-    # TODO: needed? move to dataset?
-    field :description, type: String
   end
 
   # Feature for quantitative bioassay results
   class NumericBioAssay < NumericFeature
-    # TODO: needed? move to dataset?
-    field :description, type: String
   end
 
 end
diff --git a/lib/model.rb b/lib/model.rb
index 418ec18..aed789c 100644
--- a/lib/model.rb
+++ b/lib/model.rb
@@ -86,7 +86,7 @@ module OpenTox
             acts.empty? ? nil : n << acts
           end
           neighbors.compact! # remove neighbors without training activities
-          predictions << Algorithm.run(prediction_algorithm, compound, neighbors)
+          predictions << Algorithm.run(prediction_algorithm, compound, {:neighbors => neighbors,:training_dataset_size => training_dataset.data_entries.size})
         end 
 
         # serialize result
@@ -138,7 +138,6 @@ module OpenTox
     end
 
     class LazarFminerClassification < LazarClassification
-
       def self.create training_dataset
         model = super(training_dataset)
         model.update "_type" => self.to_s # adjust class
@@ -155,14 +154,12 @@ module OpenTox
     end
 
     class LazarRegression < Lazar
-
       def initialize
         super
         self.neighbor_algorithm = "OpenTox::Algorithm::Neighbor.fingerprint_similarity"
         self.prediction_algorithm = "OpenTox::Algorithm::Regression.weighted_average" 
         self.neighbor_algorithm_parameters = {:min_sim => 0.7}
       end
-
     end
 
     class Prediction
@@ -179,15 +176,38 @@ module OpenTox
       field :crossvalidation_id, type: BSON::ObjectId
 
       def predict object
-        Model::Lazar.find(model_id).predict object
+        Lazar.find(model_id).predict object
+      end
+
+      def training_dataset
+        model.training_dataset
+      end
+
+      def model
+        Lazar.find model_id
       end
 
       def crossvalidation
         CrossValidation.find crossvalidation_id
       end
+
+      def self.from_csv_file file
+        p file
+        metadata_file = file.sub(/csv$/,"json")
+        p metadata_file 
+        bad_request_error "No metadata file #{metadata_file}" unless File.exist? metadata_file
+        prediction_model = self.new JSON.parse(File.read(metadata_file))
+        training_dataset = Dataset.from_csv_file file
+        # TODO classification
+        model = LazarRegression.create training_dataset
+        cv = RegressionCrossValidation.create model
+        prediction_model[:model_id] = model.id
+        prediction_model[:crossvalidation_id] = cv.id
+        prediction_model.save
+        prediction_model
+      end
     end
 
   end
 
 end
-
diff --git a/lib/regression.rb b/lib/regression.rb
index 020bb3a..2580a1e 100644
--- a/lib/regression.rb
+++ b/lib/regression.rb
@@ -19,9 +19,10 @@ module OpenTox
     
     class Regression
 
-      def self.weighted_average compound, neighbors
+      def self.weighted_average compound, params
         weighted_sum = 0.0
         sim_sum = 0.0
+        neighbors = params[:neighbors]
         neighbors.each do |row|
           n,sim,acts = row
           acts.each do |act|
@@ -29,7 +30,7 @@ module OpenTox
             sim_sum += sim
           end
         end
-        confidence = sim_sum/neighbors.size.to_f
+        confidence = sim_sum*neighbors.size.to_f/params[:training_dataset_size]
         sim_sum == 0 ? prediction = nil : prediction = 10**(weighted_sum/sim_sum)
         {:value => prediction,:confidence => confidence}
       end