From ca2bb0f90335b1f2c4ecc28ee423e85b281ffcf0 Mon Sep 17 00:00:00 2001
From: Christoph Helma <helma@in-silico.ch>
Date: Wed, 4 Nov 2015 17:50:17 +0100
Subject: neighbor search delegated to database backend

---
 test/validation.rb | 26 ++++++++++++++++----------
 1 file changed, 16 insertions(+), 10 deletions(-)

(limited to 'test/validation.rb')

diff --git a/test/validation.rb b/test/validation.rb
index 6764a32..7de944c 100644
--- a/test/validation.rb
+++ b/test/validation.rb
@@ -3,6 +3,7 @@ require_relative "setup.rb"
 class ValidationTest < MiniTest::Test
 
   def test_fminer_crossvalidation
+    skip
     dataset = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv"
     model = Model::LazarFminerClassification.create dataset
     cv = ClassificationCrossValidation.create model
@@ -15,12 +16,13 @@ class ValidationTest < MiniTest::Test
     dataset = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv"
     model = Model::LazarClassification.create dataset#, features
     cv = ClassificationCrossValidation.create model
-    assert cv.accuracy > 0.7
-    File.open("tmp.svg","w+"){|f| f.puts cv.confidence_plot}
-    `inkview tmp.svg`
+    #p cv
+    assert cv.accuracy > 0.7, "Accuracy (#{cv.accuracy}) should be larger than 0.7"
+    #File.open("tmp.svg","w+"){|f| f.puts cv.confidence_plot}
+    #`inkview tmp.svg`
     p cv.nr_unpredicted
     p cv.accuracy
-    #assert cv.weighted_accuracy > cv.accuracy, "Weighted accuracy should be larger than unweighted accuracy."
+    assert cv.weighted_accuracy > cv.accuracy, "Weighted accuracy (#{cv.weighted_accuracy}) should be larger than unweighted accuracy (#{cv.accuracy}) ."
   end
 
   def test_default_regression_crossvalidation
@@ -28,11 +30,11 @@ class ValidationTest < MiniTest::Test
     model = Model::LazarRegression.create dataset
     cv = RegressionCrossValidation.create model
     #cv = RegressionCrossValidation.find '561503262b72ed54fd000001'
-    p cv.id
-    File.open("tmp.svg","w+"){|f| f.puts cv.correlation_plot}
-    `inkview tmp.svg`
-    File.open("tmp.svg","w+"){|f| f.puts cv.confidence_plot}
-    `inkview tmp.svg`
+    #p cv.id
+    #File.open("tmp.svg","w+"){|f| f.puts cv.correlation_plot}
+    #`inkview tmp.svg`
+    #File.open("tmp.svg","w+"){|f| f.puts cv.confidence_plot}
+    #`inkview tmp.svg`
     
     #puts cv.misclassifications.to_yaml
     p cv.rmse
@@ -91,9 +93,13 @@ class ValidationTest < MiniTest::Test
     model.save
     cv = ClassificationCrossValidation.create model
     params = model.neighbor_algorithm_parameters
+    params.delete :training_dataset_id
     params = Hash[params.map{ |k, v| [k.to_s, v] }] # convert symbols to string
+
     cv.validations.each do |validation|
-      assert_equal params, validation.model.neighbor_algorithm_parameters
+      validation_params = validation.model.neighbor_algorithm_parameters
+      validation_params.delete "training_dataset_id"
+      assert_equal params, validation_params
     end
   end
 
-- 
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