From bd2689c94b9fdd76d163ed6aa80ddd0675d20d6c Mon Sep 17 00:00:00 2001 From: Andreas Maunz Date: Tue, 31 Jan 2012 08:46:55 +0100 Subject: Adjusted tests to new parameters (see http://goo.gl/lXJBS) --- 5x_cv/fs/MOU_ELECT2.R | Bin 88872 -> 86941 bytes 5x_cv/fs/RAT_ELECT2.R | Bin 112940 -> 109467 bytes lazar.rb | 186 +++++++++++++++++--------------------------------- 3 files changed, 63 insertions(+), 123 deletions(-) diff --git a/5x_cv/fs/MOU_ELECT2.R b/5x_cv/fs/MOU_ELECT2.R index 257123b..eaa84af 100644 Binary files a/5x_cv/fs/MOU_ELECT2.R and b/5x_cv/fs/MOU_ELECT2.R differ diff --git a/5x_cv/fs/RAT_ELECT2.R b/5x_cv/fs/RAT_ELECT2.R index d330091..031b26c 100644 Binary files a/5x_cv/fs/RAT_ELECT2.R and b/5x_cv/fs/RAT_ELECT2.R differ diff --git a/lazar.rb b/lazar.rb index 0b68fee..f890525 100644 --- a/lazar.rb +++ b/lazar.rb @@ -54,136 +54,76 @@ class LazarTest < Test::Unit::TestCase FileUtils.cp f, reference FileUtils.rm f end - #@predictions.each do |dataset| - # dataset.delete(@@subjectid) - #end - #@model.delete(@@subjectid) - end - - def test_create_regression_pc_model - create_model :dataset_uri => @@regression_training_dataset.uri, :feature_dataset_uri => @@regression_feature_dataset.uri, :pc_type => "constitutional", :propositionalized => "false", :min_train_performance => -1000 - predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") - assert_in_delta @predictions.first.value(@compounds.first), 3.5, 1.0 - assert_equal 0.603, @predictions.first.confidence(@compounds.first).round_to(3) - assert_equal 74, @predictions.first.neighbors(@compounds.first).size - cleanup - end - - def test_create_regression_pc_prop_model - create_model :dataset_uri => @@regression_training_dataset.uri, :feature_dataset_uri => @@regression_feature_dataset.uri, :pc_type => "constitutional", :propositionalized => "true", :min_train_performance => -1000 - predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") - assert_in_delta @predictions.first.value(@compounds.first), 3.5, 1.0 - assert_equal 0.603, @predictions.first.confidence(@compounds.first).round_to(3) - assert_equal 74, @predictions.first.neighbors(@compounds.first).size - cleanup - end - - - def test_create_regression_model - create_model :dataset_uri => @@regression_training_dataset.uri, :propositionalized => "false", :min_train_performance => -1000 - predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") - assert_in_delta @predictions.first.value(@compounds.first), 0.7, 0.5 - assert_equal 0.61, @predictions.first.confidence(@compounds.first).round_to(2) - assert_equal 253, @predictions.first.neighbors(@compounds.first).size - cleanup - end - - def test_create_regression_prop_model - create_model :dataset_uri => @@regression_training_dataset.uri, :propositionalized => "true", :min_train_performance => -1000 - predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") - assert_in_delta @predictions.first.value(@compounds.first), 0.6, 0.5 - assert_equal 0.61, @predictions.first.confidence(@compounds.first).round_to(2) - assert_equal 253, @predictions.first.neighbors(@compounds.first).size - assert_equal 131, @model.features.size - cleanup - end - - -# def test_create_regression_prop_nr_hits_model -# create_model :dataset_uri => @@regression_training_dataset.uri, :propositionalized => "true", :nr_hits => "false" -# predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") -# assert_equal 0.61, @predictions.first.confidence(@compounds.first).round_to(2) -# assert_equal 253, @predictions.first.neighbors(@compounds.first).size -# assert_equal 131, @model.features.size -# cleanup -# end - - - def test_classification_model - create_model :dataset_uri => @@classification_training_dataset.uri - # single prediction - predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") - # dataset activity - predict_compound OpenTox::Compound.from_smiles("CNN") - # dataset prediction - predict_dataset OpenTox::Dataset.create_from_csv_file("data/multicolumn.csv", @@subjectid) - # assertions - # single prediction - assert_equal "false", @predictions[0].value(@compounds[0]) - assert_equal 0.3383.round_to(4), @predictions[0].confidence(@compounds[0]).round_to(4) - assert_equal 16, @predictions[0].neighbors(@compounds[0]).size - # dataset activity - assert !@predictions[1].measured_activities(@compounds[1]).empty? - assert_equal "true", @predictions[1].measured_activities(@compounds[1]).first.to_s - assert @predictions[1].value(@compounds[1]).nil? - # dataset prediction - c = OpenTox::Compound.from_smiles("CC(=Nc1ccc2c(c1)Cc1ccccc21)O") - assert_equal nil, @predictions[2].value(c) - assert_equal "true", @predictions[2].measured_activities(c).first.to_s - c = OpenTox::Compound.from_smiles("c1ccccc1NN") - assert_equal "false", @predictions[2].value(c) - assert_equal 0.3383 , @predictions[2].confidence(c).round_to(4) - # model - assert_equal 41, @model.features.size - cleanup + @predictions.each do |dataset| + dataset.delete(@@subjectid) + end + @model.delete(@@subjectid) end -# def test_classification_svm_model -# create_model :dataset_uri => @@classification_training_dataset.uri, :prediction_algorithm => "local_svm_classification" -# predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") -# predict_dataset OpenTox::Dataset.create_from_csv_file("data/multicolumn.csv", @@subjectid) -# -# assert_equal "true", @predictions[0].value(@compounds[0]) -# assert_equal 0.5587, @predictions[0].confidence(@compounds[0]).round_to(4) -# assert_equal 16, @predictions[0].neighbors(@compounds[0]).size -# -# c = OpenTox::Compound.from_smiles("c1ccccc1NN") -# assert_equal 4, @predictions[1].compounds.size -# assert_equal "false", @predictions[1].value(c) -# -# assert_equal 41, @model.features.size -# cleanup -# end +## Regression +def test_create_regression_svm_pc_model + create_model :dataset_uri => @@regression_training_dataset.uri, :feature_dataset_uri => @@regression_feature_dataset.uri, :pc_type => "constitutional" + predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") + assert_in_delta @predictions.first.value(@compounds.first), 7.8, 0.1 + assert_equal 0.603, @predictions.first.confidence(@compounds.first).round_to(3) + assert_equal 74, @predictions.first.neighbors(@compounds.first).size + cleanup +end +def test_create_regression_svm_model + create_model :dataset_uri => @@regression_training_dataset.uri, :min_train_performance => 0.0001 + predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") + assert_in_delta @predictions.first.value(@compounds.first), 0.6, 0.5 + assert_equal 0.61, @predictions.first.confidence(@compounds.first).round_to(2) + assert_equal 253, @predictions.first.neighbors(@compounds.first).size + assert_equal 131, @model.features.size + cleanup +end -# def test_classification_svm_prop_model -# create_model :dataset_uri => @@classification_training_dataset.uri, :prediction_algorithm => "local_svm_classification", :propositionalized => "true" -# predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") -# predict_dataset OpenTox::Dataset.create_from_csv_file("data/multicolumn.csv", @@subjectid) -# -# assert_equal "false", @predictions[0].value(@compounds[0]) -# assert_equal 0.5587, @predictions[0].confidence(@compounds[0]).round_to(4) -# assert_equal 16, @predictions[0].neighbors(@compounds[0]).size -# -# c = OpenTox::Compound.from_smiles("c1ccccc1NN") -# assert_equal 4, @predictions[1].compounds.size -# assert_equal "false", @predictions[1].value(c) -# -# assert_equal 41, @model.features.size -# cleanup -# end +#Classification +def test_classification_model + create_model :dataset_uri => @@classification_training_dataset.uri + # single prediction + predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") + # dataset activity + predict_compound OpenTox::Compound.from_smiles("CNN") + # dataset prediction + predict_dataset OpenTox::Dataset.create_from_csv_file("data/multicolumn.csv", @@subjectid) + # assertions + # single prediction + assert_equal "false", @predictions[0].value(@compounds[0]) + assert_equal 0.3383.round_to(4), @predictions[0].confidence(@compounds[0]).round_to(4) + assert_equal 16, @predictions[0].neighbors(@compounds[0]).size + # dataset activity + assert !@predictions[1].measured_activities(@compounds[1]).empty? + assert_equal "true", @predictions[1].measured_activities(@compounds[1]).first.to_s + assert @predictions[1].value(@compounds[1]).nil? + # dataset prediction + c = OpenTox::Compound.from_smiles("CC(=Nc1ccc2c(c1)Cc1ccccc21)O") + assert_equal nil, @predictions[2].value(c) + assert_equal "true", @predictions[2].measured_activities(c).first.to_s + c = OpenTox::Compound.from_smiles("c1ccccc1NN") + assert_equal "false", @predictions[2].value(c) + assert_equal 0.3383 , @predictions[2].confidence(c).round_to(4) + # model + assert_equal 41, @model.features.size + cleanup +end + +def test_classification_svm_model + create_model :dataset_uri => @@classification_training_dataset.uri, :prediction_algorithm => "local_svm_classification" + predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") + predict_dataset OpenTox::Dataset.create_from_csv_file("data/multicolumn.csv", @@subjectid) + + assert_equal "false", @predictions[0].value(@compounds[0]) + assert_equal 0.5358, @predictions[0].confidence(@compounds[0]).round_to(4) + assert_equal 22, @predictions[0].neighbors(@compounds[0]).size + assert_equal 41, @model.features.size + cleanup +end -# DISABLED TEMPORARILY -# def test_create_regression_pc_mlr_prop_model -# create_model :dataset_uri => @@regression_training_dataset.uri, :feature_dataset_uri => @@regression_feature_dataset.uri, :pc_type => "constitutional", :prediction_algorithm => "local_mlr_prop" -# predict_compound OpenTox::Compound.from_smiles("c1ccccc1NN") -# assert_in_delta @predictions.first.value(@compounds.first), 1.02, 0.2 -# assert_equal 0.728, @predictions.first.confidence(@compounds.first).round_to(3) -# #assert_equal 34, @predictions.first.neighbors(@compounds.first).size -# cleanup -# end # DISABLED TEMPORARILY # def test_ambit_classification_model -- cgit v1.2.3