From cf63863e645d54e593d345b5534583d2fd132a57 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Ricardo=20Montan=CC=83ana?= Date: Sun, 3 Apr 2022 18:02:02 +0200 Subject: [PATCH] Complete graphviz test Add comments to some tests --- stree/tests/Stree_test.py | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/stree/tests/Stree_test.py b/stree/tests/Stree_test.py index b46e6ff..95ca945 100644 --- a/stree/tests/Stree_test.py +++ b/stree/tests/Stree_test.py @@ -358,6 +358,7 @@ class Stree_test(unittest.TestCase): # Tests of score def test_score_binary(self): + """Check score for binary classification.""" X, y = load_dataset(self._random_state) accuracies = [ 0.9506666666666667, @@ -380,6 +381,7 @@ class Stree_test(unittest.TestCase): self.assertAlmostEqual(accuracy_expected, accuracy_score) def test_score_max_features(self): + """Check score using max_features.""" X, y = load_dataset(self._random_state) clf = Stree( kernel="liblinear", @@ -391,6 +393,7 @@ class Stree_test(unittest.TestCase): self.assertAlmostEqual(0.9453333333333334, clf.score(X, y)) def test_bogus_splitter_parameter(self): + """Check that bogus splitter parameter raises exception.""" clf = Stree(splitter="duck") with self.assertRaises(ValueError): clf.fit(*load_dataset()) @@ -446,6 +449,7 @@ class Stree_test(unittest.TestCase): self.assertListEqual([47], resdn[1].tolist()) def test_score_multiclass_rbf(self): + """Test score for multiclass classification with rbf kernel.""" X, y = load_dataset( random_state=self._random_state, n_classes=3, @@ -463,6 +467,7 @@ class Stree_test(unittest.TestCase): self.assertEqual(1.0, clf2.fit(X, y).score(X, y)) def test_score_multiclass_poly(self): + """Test score for multiclass classification with poly kernel.""" X, y = load_dataset( random_state=self._random_state, n_classes=3, @@ -484,6 +489,7 @@ class Stree_test(unittest.TestCase): self.assertEqual(1.0, clf2.fit(X, y).score(X, y)) def test_score_multiclass_liblinear(self): + """Test score for multiclass classification with liblinear kernel.""" X, y = load_dataset( random_state=self._random_state, n_classes=3, @@ -509,6 +515,7 @@ class Stree_test(unittest.TestCase): self.assertEqual(1.0, clf2.fit(X, y).score(X, y)) def test_score_multiclass_sigmoid(self): + """Test score for multiclass classification with sigmoid kernel.""" X, y = load_dataset( random_state=self._random_state, n_classes=3, @@ -529,6 +536,7 @@ class Stree_test(unittest.TestCase): self.assertEqual(0.9662921348314607, clf2.fit(X, y).score(X, y)) def test_score_multiclass_linear(self): + """Test score for multiclass classification with linear kernel.""" warnings.filterwarnings("ignore", category=ConvergenceWarning) warnings.filterwarnings("ignore", category=RuntimeWarning) X, y = load_dataset( @@ -556,11 +564,13 @@ class Stree_test(unittest.TestCase): self.assertEqual(1.0, clf2.fit(X, y).score(X, y)) def test_zero_all_sample_weights(self): + """Test exception raises when all sample weights are zero.""" X, y = load_dataset(self._random_state) with self.assertRaises(ValueError): Stree().fit(X, y, np.zeros(len(y))) def test_mask_samples_weighted_zero(self): + """Check that the weighted zero samples are masked.""" X = np.array( [ [1, 1], @@ -588,6 +598,7 @@ class Stree_test(unittest.TestCase): self.assertEqual(model2.score(X, y, w), 1) def test_depth(self): + """Check depth of the tree.""" X, y = load_dataset( random_state=self._random_state, n_classes=3, @@ -603,6 +614,7 @@ class Stree_test(unittest.TestCase): self.assertEqual(4, clf.depth_) def test_nodes_leaves(self): + """Check number of nodes and leaves.""" X, y = load_dataset( random_state=self._random_state, n_classes=3, @@ -622,6 +634,7 @@ class Stree_test(unittest.TestCase): self.assertEqual(6, leaves) def test_nodes_leaves_artificial(self): + """Check leaves of artificial dataset.""" n1 = Snode(None, [1, 2, 3, 4], [1, 0, 1, 1], [], 0.0, "test1") n2 = Snode(None, [1, 2, 3, 4], [1, 0, 1, 1], [], 0.0, "test2") n3 = Snode(None, [1, 2, 3, 4], [1, 0, 1, 1], [], 0.0, "test3") @@ -640,12 +653,14 @@ class Stree_test(unittest.TestCase): self.assertEqual(2, leaves) def test_bogus_multiclass_strategy(self): + """Check invalid multiclass strategy.""" clf = Stree(multiclass_strategy="other") X, y = load_wine(return_X_y=True) with self.assertRaises(ValueError): clf.fit(X, y) def test_multiclass_strategy(self): + """Check multiclass strategy.""" X, y = load_wine(return_X_y=True) clf_o = Stree(multiclass_strategy="ovo") clf_r = Stree(multiclass_strategy="ovr") @@ -655,6 +670,7 @@ class Stree_test(unittest.TestCase): self.assertEqual(0.9269662921348315, score_r) def test_incompatible_hyperparameters(self): + """Check incompatible hyperparameters.""" X, y = load_wine(return_X_y=True) clf = Stree(kernel="liblinear", multiclass_strategy="ovo") with self.assertRaises(ValueError): @@ -664,12 +680,15 @@ class Stree_test(unittest.TestCase): clf.fit(X, y) def test_version(self): + """Check STree version.""" clf = Stree() self.assertEqual(__version__, clf.version()) def test_graph(self): + """Check graphviz representation of the tree.""" X, y = load_wine(return_X_y=True) clf = Stree(random_state=self._random_state) + self.assertEqual(clf.graph(), "digraph STree {\n}\n") clf.fit(X, y) expected_head = "digraph STree {\n" expected_tail = (