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-rw-r--r--test/experiment.rb301
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diff --git a/test/experiment.rb b/test/experiment.rb
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index 418f7fe..0000000
--- a/test/experiment.rb
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-require_relative "setup.rb"
-
-class ExperimentTest < MiniTest::Test
-
- def test_regression_experiment
- skip
- datasets = [
- "EPAFHM.medi_log10.csv",
- #"EPAFHM.csv",
- #"FDA_v3b_Maximum_Recommended_Daily_Dose_mmol.csv",
- "LOAEL_mmol_corrected_smiles.csv"
- ]
- experiment = Experiment.create(
- :name => "Default regression for datasets #{datasets}.",
- :dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
- :model_settings => [
- {
- :algorithm => "OpenTox::Model::LazarRegression",
- }
- ]
- )
- #experiment.run
- puts experiment.report.to_yaml
- assert_equal datasets.size, experiment.results.size
- experiment.results.each do |dataset_id, result|
- assert_equal 1, result.size
- result.each do |r|
- assert_kind_of BSON::ObjectId, r[:model_id]
- assert_kind_of BSON::ObjectId, r[:repeated_crossvalidation_id]
- end
- end
- end
-
- def test_classification_experiment
-
- skip
- datasets = [ "hamster_carcinogenicity.csv" ]
- experiment = Experiment.create(
- :name => "Fminer vs fingerprint classification for datasets #{datasets}.",
- :dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
- :model_settings => [
- {
- :algorithm => "OpenTox::Model::LazarClassification",
- },{
- :algorithm => "OpenTox::Model::LazarClassification",
- :neighbor_algorithm_parameter => {:min_sim => 0.3}
- },
- #{
- #:algorithm => "OpenTox::Model::LazarFminerClassification",
- #}
- ]
- )
- #experiment.run
-=begin
- experiment = Experiment.find "55f944a22b72ed7de2000000"
-=end
- puts experiment.report.to_yaml
- experiment.results.each do |dataset_id, result|
- assert_equal 2, result.size
- result.each do |r|
- assert_kind_of BSON::ObjectId, r[:model_id]
- assert_kind_of BSON::ObjectId, r[:repeated_crossvalidation_id]
- end
- end
- end
-
- def test_regression_fingerprints
- skip
-#=begin
- datasets = [
- "EPAFHM.medi_log10.csv",
- #"LOAEL_mmol_corrected_smiles.csv"
- ]
- min_sims = [0.3,0.7]
- #min_sims = [0.7]
- #types = ["FP2","FP3","FP4","MACCS","MP2D"]
- types = ["MP2D","FP3"]
- experiment = Experiment.create(
- :name => "Fingerprint regression with different types for datasets #{datasets}.",
- :dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
- )
- types.each do |type|
- min_sims.each do |min_sim|
- experiment.model_settings << {
- :model_algorithm => "OpenTox::Model::LazarRegression",
- :prediction_algorithm => "OpenTox::Algorithm::Regression.weighted_average",
- :neighbor_algorithm => "fingerprint_neighbors",
- :neighbor_algorithm_parameters => {
- :type => type,
- :min_sim => min_sim,
- }
- }
- end
- end
- experiment.run
-#=end
-=begin
- experiment = Experiment.find '56029cb92b72ed673d000000'
-=end
- p experiment.id
- experiment.results.each do |dataset,result|
- result.each do |r|
- params = Model::Lazar.find(r["model_id"])[:neighbor_algorithm_parameters]
- RepeatedCrossValidation.find(r["repeated_crossvalidation_id"]).crossvalidations.each do |cv|
- cv.validation_ids.each do |vid|
- model_params = Model::Lazar.find(Validation.find(vid).model_id)[:neighbor_algorithm_parameters]
- assert_equal params[:type], model_params[:type]
- assert_equal params[:min_sim], model_params[:min_sim]
- refute_equal params[:training_dataset_id], model_params[:training_dataset_id]
- end
- end
- end
- end
- puts experiment.report.to_yaml
- p experiment.summary
- end
-
- def test_mpd_fingerprints
- skip
- datasets = [
- "EPAFHM.medi_log10.csv",
- ]
- types = ["FP2","MP2D"]
- experiment = Experiment.create(
- :name => "FP2 vs MP2D fingerprint regression for datasets #{datasets}.",
- :dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
- )
- types.each do |type|
- experiment.model_settings << {
- :algorithm => "OpenTox::Model::LazarRegression",
- :neighbor_algorithm => "fingerprint_neighbors",
- :neighbor_algorithm_parameter => {
- :type => type,
- :min_sim => 0.7,
- }
- }
- end
- experiment.run
- p experiment.id
-=begin
-=end
- #experiment = Experiment.find '55ffd0c02b72ed123c000000'
- p experiment
- puts experiment.report.to_yaml
- end
-
- def test_multiple_datasets
- skip
- datasets = [
- "EPAFHM.medi_log10.csv",
- "LOAEL_mmol_corrected_smiles.csv"
- ]
- min_sims = [0.3]
- types = ["FP2"]
- experiment = Experiment.create(
- :name => "Fingerprint regression with mutiple datasets #{datasets}.",
- :dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
- )
- types.each do |type|
- min_sims.each do |min_sim|
- experiment.model_settings << {
- :model_algorithm => "OpenTox::Model::LazarRegression",
- :prediction_algorithm => "OpenTox::Algorithm::Regression.weighted_average",
- :neighbor_algorithm => "fingerprint_neighbors",
- :neighbor_algorithm_parameters => {
- :type => type,
- :min_sim => min_sim,
- }
- }
- end
- end
- experiment.run
- p experiment.id
- experiment.results.each do |dataset,result|
- result.each do |r|
- params = Model::Lazar.find(r["model_id"])[:neighbor_algorithm_parameters]
- RepeatedCrossValidation.find(r["repeated_crossvalidation_id"]).crossvalidations.each do |cv|
- cv.validation_ids.each do |vid|
- model_params = Model::Lazar.find(Validation.find(vid).model_id)[:neighbor_algorithm_parameters]
- assert_equal params[:type], model_params[:type]
- assert_equal params[:min_sim], model_params[:min_sim]
- refute_equal params[:training_dataset_id], model_params[:training_dataset_id]
- end
- end
- end
- end
- puts experiment.report.to_yaml
- p experiment.summary
- end
-
- def test_mpd_mna_regression_fingerprints
- skip
- datasets = [
- "EPAFHM.medi.csv",
- #"hamster_carcinogenicity.csv"
- ]
- min_sims = [0.0,0.3]
- types = ["MP2D","MNA"]
- neighbor_algos = [
- "fingerprint_neighbors",
- "fingerprint_count_neighbors",
- ]
- experiment = Experiment.create(
- :name => "MNA vs MPD descriptors",
- :dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
- )
- types.each do |type|
- min_sims.each do |min_sim|
- neighbor_algos.each do |neighbor_algo|
- experiment.model_settings << {
- :model_algorithm => "OpenTox::Model::LazarRegression",
- :prediction_algorithm => "OpenTox::Algorithm::Regression.weighted_average",
- :neighbor_algorithm => neighbor_algo,
- :neighbor_algorithm_parameters => {
- :type => type,
- :min_sim => min_sim,
- }
- }
- end
- end
- end
- experiment.run
-#=end
-=begin
- experiment = Experiment.find '56029cb92b72ed673d000000'
-=end
- p experiment.id
- puts experiment.report.to_yaml
- #p experiment.summary
- experiment.results.each do |dataset,result|
- result.each do |r|
- p r
- # TODO fix r["model_id"]
- params = Model::Lazar.find(r["model_id"])[:neighbor_algorithm_parameters]
- RepeatedCrossValidation.find(r["repeated_crossvalidation_id"]).crossvalidations.each do |cv|
- cv.validation_ids.each do |vid|
- model_params = Model::Lazar.find(Validation.find(vid).model_id)[:neighbor_algorithm_parameters]
- assert_equal params[:type], model_params[:type]
- assert_equal params[:min_sim], model_params[:min_sim]
- refute_equal params[:training_dataset_id], model_params[:training_dataset_id]
- end
- end
- end
- end
- end
-
- def test_mpd_mna_classification_fingerprints
- skip
- datasets = [
- #"EPAFHM.medi.csv",
- "hamster_carcinogenicity.csv"
- ]
- min_sims = [0.0,0.3]
- types = ["MP2D","MNA"]
- neighbor_algos = [
- "fingerprint_count_neighbors",
- "fingerprint_neighbors",
- ]
- experiment = Experiment.create(
- :name => "MNA vs MPD descriptors",
- :dataset_ids => datasets.collect{|d| Dataset.from_csv_file(File.join(DATA_DIR, d)).id},
- )
- types.each do |type|
- min_sims.each do |min_sim|
- neighbor_algos.each do |neighbor_algo|
- experiment.model_settings << {
- :model_algorithm => "OpenTox::Model::LazarClassification",
- :prediction_algorithm => "OpenTox::Algorithm::Classification.weighted_majority_vote",
- :neighbor_algorithm => neighbor_algo,
- :neighbor_algorithm_parameters => {
- :type => type,
- :min_sim => min_sim,
- }
- }
- end
- end
- end
- experiment.run
-#=end
-=begin
- experiment = Experiment.find '56029cb92b72ed673d000000'
-=end
- p experiment.id
- puts experiment.report.to_yaml
- #p experiment.summary
- experiment.results.each do |dataset,result|
- result.each do |r|
- # TODO fix r["model_id"]
- params = Model::Lazar.find(r["model_id"])[:neighbor_algorithm_parameters]
- RepeatedCrossValidation.find(r["repeated_crossvalidation_id"]).crossvalidations.each do |cv|
- cv.validation_ids.each do |vid|
- model_params = Model::Lazar.find(Validation.find(vid).model_id)[:neighbor_algorithm_parameters]
- assert_equal params[:type], model_params[:type]
- assert_equal params[:min_sim], model_params[:min_sim]
- refute_equal params[:training_dataset_id], model_params[:training_dataset_id]
- end
- end
- end
- end
- end
-end
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