From f8faf510b4574df1a00fa61a9f0a1681fc2f4857 Mon Sep 17 00:00:00 2001
From: Christoph Helma <helma@in-silico.ch>
Date: Tue, 25 Aug 2015 17:20:55 +0200
Subject: Experiments added

---
 lib/experiment.rb | 66 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 66 insertions(+)
 create mode 100644 lib/experiment.rb

(limited to 'lib/experiment.rb')

diff --git a/lib/experiment.rb b/lib/experiment.rb
new file mode 100644
index 0000000..b3ed174
--- /dev/null
+++ b/lib/experiment.rb
@@ -0,0 +1,66 @@
+module OpenTox
+
+  class Experiment
+    field :dataset_ids, type: Array
+    field :model_algorithms, type: Array
+    field :model_ids, type: Array, default: []
+    field :crossvalidation_ids, type: Array, default: []
+    field :prediction_algorithms, type: Array
+    field :neighbor_algorithms, type: Array
+    field :neighbor_algorithm_parameters, type: Array
+  end
+
+  # TODO more sophisticated experimental design
+  def run 
+    dataset_ids.each do |dataset_id|
+      dataset = Dataset.find(dataset_id)
+      model_algorithms.each do |model_algorithm|
+        prediction_algorithms.each do |prediction_algorithm|
+          neighbor_algorithms.each do |neighbor_algorithm|
+            neighbor_algorithm_parameters.each do |neighbor_algorithm_parameter|
+              $logger.debug "Creating #{model_algorithm} model for dataset #{dataset.name}, with prediction_algorithm #{prediction_algorithm}, neighbor_algorithm #{neighbor_algorithm}, neighbor_algorithm_parameters #{neighbor_algorithm_parameter}."
+              model = Object.const_get(model_algorithm).create dataset
+              model.prediction_algorithm = prediction_algorithm
+              model.neighbor_algorithm = neighbor_algorithm
+              model.neighbor_algorithm_parameters = neighbor_algorithm_parameter
+              model.save
+              model_ids << model.id
+              cv = nil
+              if dataset.features.first.nominal
+                cv = ClassificationCrossValidation
+              elsif dataset.features.first.numeric
+                cv = RegressionCrossValidation
+              end
+              if cv
+                $logger.debug "Creating #{cv} for #{model_algorithm}, dataset #{dataset.name}, with prediction_algorithm #{prediction_algorithm}, neighbor_algorithm #{neighbor_algorithm}, neighbor_algorithm_parameters #{neighbor_algorithm_parameter}."
+                crossvalidation = cv.create model
+                crossvalidation_ids << crossvalidation.id
+              else
+                $logger.warn "#{dataset.features.first} is neither nominal nor numeric."
+              end
+            end
+          end
+        end
+      end
+    end
+    save
+  end
+
+  def self.create params
+    experiment = self.new
+    $logge.debug "Experiment started ..."
+    experiment.run params
+    experiment
+  end
+
+  def report
+    crossvalidation_ids.each do |id|
+      cv = CrossValidation.find(id)
+      file = "/tmp/#{cv.name}.svg"
+      File.open(file,"w+"){|f| f.puts cv.correlation_plot}
+      `inkview '#{file}'`
+      #p Crossvalidation.find(id).correlation_plot
+    end
+  end
+
+end
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