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authorChristoph Helma <helma@in-silico.ch>2016-10-13 22:59:45 +0200
committerChristoph Helma <helma@in-silico.ch>2016-10-13 22:59:45 +0200
commit09452bba5c407c27721223d126e3f45c12b20a0c (patch)
treeed4f73a874ddb12c98e7c62af49c2de5fcc4f4d1 /test
parent2dc66aef3b7932105868ee8c7d32ad975e142d1b (diff)
tests pass
Diffstat (limited to 'test')
-rw-r--r--test/dataset.rb3
-rw-r--r--test/model-nanoparticle.rb4
-rw-r--r--test/validation-nanoparticle.rb9
-rw-r--r--test/validation-regression.rb57
4 files changed, 58 insertions, 15 deletions
diff --git a/test/dataset.rb b/test/dataset.rb
index 2c0aa01..e91e65a 100644
--- a/test/dataset.rb
+++ b/test/dataset.rb
@@ -231,10 +231,7 @@ class DatasetTest < MiniTest::Test
datasets.each{|d| d.delete}
end
- # skips, may be removed in the future
-
def test_simultanous_upload
- skip
threads = []
3.times do |t|
threads << Thread.new(t) do |up|
diff --git a/test/model-nanoparticle.rb b/test/model-nanoparticle.rb
index 6e18add..7244a29 100644
--- a/test/model-nanoparticle.rb
+++ b/test/model-nanoparticle.rb
@@ -31,10 +31,6 @@ class NanoparticleModelTest < MiniTest::Test
model.delete
end
- def test_nanoparticle_parameters
- skip
- end
-
def test_import_ld
skip # Ambit JSON-LD export defunct
dataset_ids = Import::Enanomapper.import_ld
diff --git a/test/validation-nanoparticle.rb b/test/validation-nanoparticle.rb
index c5618e8..c0f2f92 100644
--- a/test/validation-nanoparticle.rb
+++ b/test/validation-nanoparticle.rb
@@ -31,8 +31,7 @@ class NanoparticleValidationTest < MiniTest::Test
:prediction => {:method => 'Algorithm::Caret.pls' },
}
model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
- assert_equal "pls", model.algorithms[:prediction][:parameters]
- assert_equal "Algorithm::Caret.regression", model.algorithms[:prediction][:method]
+ assert_equal "Algorithm::Caret.pls", model.algorithms[:prediction][:method]
cv = CrossValidation.create model
p cv.rmse
p cv.r_squared
@@ -49,7 +48,6 @@ class NanoparticleValidationTest < MiniTest::Test
:prediction => {:method => 'Algorithm::Caret.pls' },
}
model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
- assert_equal "pls", model.algorithms[:prediction][:parameters]
assert_equal "Algorithm::Caret.pls", model.algorithms[:prediction][:method]
cv = CrossValidation.create model
p cv.rmse
@@ -73,9 +71,4 @@ class NanoparticleValidationTest < MiniTest::Test
refute_nil cv.rmse
end
-
- def test_import_ld
- skip # Ambit JSON-LD export defunct
- dataset_ids = Import::Enanomapper.import_ld
- end
end
diff --git a/test/validation-regression.rb b/test/validation-regression.rb
new file mode 100644
index 0000000..efce849
--- /dev/null
+++ b/test/validation-regression.rb
@@ -0,0 +1,57 @@
+require_relative "setup.rb"
+
+class ValidationRegressionTest < MiniTest::Test
+ include OpenTox::Validation
+
+ # defaults
+
+ def test_default_regression_crossvalidation
+ dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi_log10.csv"
+ model = Model::Lazar.create training_dataset: dataset
+ cv = RegressionCrossValidation.create model
+ assert cv.rmse < 1.5, "RMSE #{cv.rmse} should be smaller than 1.5, this may occur due to an unfavorable training/test set split"
+ assert cv.mae < 1, "MAE #{cv.mae} should be smaller than 1, this may occur due to an unfavorable training/test set split"
+ end
+
+ # parameters
+
+ def test_regression_crossvalidation_params
+ dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi_log10.csv"
+ algorithms = {
+ :prediction => { :method => "OpenTox::Algorithm::Regression.weighted_average" },
+ :descriptors => { :type => "MACCS", },
+ :similarity => {:min => 0.7}
+ }
+ model = Model::Lazar.create training_dataset: dataset, algorithms: algorithms
+ assert_equal algorithms[:descriptors][:type], model.algorithms[:descriptors][:type]
+ cv = RegressionCrossValidation.create model
+ cv.validation_ids.each do |vid|
+ model = Model::Lazar.find(Validation.find(vid).model_id)
+ assert_equal algorithms[:descriptors][:type], model.algorithms[:descriptors][:type]
+ assert_equal algorithms[:similarity][:min], model.algorithms[:similarity][:min]
+ refute_nil model.training_dataset_id
+ refute_equal dataset.id, model.training_dataset_id
+ end
+
+ refute_nil cv.rmse
+ refute_nil cv.mae
+ end
+
+ def test_physchem_regression_crossvalidation
+ training_dataset = OpenTox::Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.medi_log10.csv")
+ model = Model::Lazar.create training_dataset:training_dataset
+ cv = RegressionCrossValidation.create model
+ refute_nil cv.rmse
+ refute_nil cv.mae
+ end
+
+ # LOO
+
+ def test_regression_loo_validation
+ dataset = OpenTox::Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.medi_log10.csv")
+ model = Model::Lazar.create training_dataset: dataset
+ loo = RegressionLeaveOneOut.create model
+ assert loo.r_squared > 0.34, "R^2 (#{loo.r_squared}) should be larger than 0.034"
+ end
+
+end