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test: ⚡ Add scikit learn compatibility check_estimator test
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@@ -2,6 +2,7 @@ import unittest
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import sklearn
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import numpy as np
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from sklearn.datasets import load_iris
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from sklearn.utils.estimator_checks import check_estimator
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from ..cppfimdlp import factorize
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from ..mdlp import FImdlp
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from .. import version
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@@ -23,13 +24,13 @@ class FImdlpTest(unittest.TestCase):
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def test_fit_definitive(self):
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clf = FImdlp(algorithm=0)
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clf.fit([[1, 2], [3, 4]], [1, 2])
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self.assertEqual(clf.n_features_, 2)
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self.assertEqual(clf.n_features_in_, 2)
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self.assertListEqual(clf.X_.tolist(), [[1, 2], [3, 4]])
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self.assertListEqual(clf.y_.tolist(), [1, 2])
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self.assertListEqual([[2.0], [3.0]], clf.get_cut_points())
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X, y = load_iris(return_X_y=True)
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clf.fit(X, y)
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self.assertEqual(clf.n_features_, 4)
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self.assertEqual(clf.n_features_in_, 4)
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self.assertTrue(np.array_equal(X, clf.X_))
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self.assertTrue(np.array_equal(y, clf.y_))
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expected = [
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@@ -46,13 +47,13 @@ class FImdlpTest(unittest.TestCase):
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def test_fit_alternative(self):
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clf = FImdlp(algorithm=1)
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clf.fit([[1, 2], [3, 4]], [1, 2])
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self.assertEqual(clf.n_features_, 2)
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self.assertEqual(clf.n_features_in_, 2)
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self.assertListEqual(clf.X_.tolist(), [[1, 2], [3, 4]])
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self.assertListEqual(clf.y_.tolist(), [1, 2])
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self.assertListEqual([[2], [3]], clf.get_cut_points())
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X, y = load_iris(return_X_y=True)
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clf.fit(X, y)
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self.assertEqual(clf.n_features_, 4)
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self.assertEqual(clf.n_features_in_, 4)
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self.assertTrue(np.array_equal(X, clf.X_))
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self.assertTrue(np.array_equal(y, clf.y_))
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@@ -107,7 +108,7 @@ class FImdlpTest(unittest.TestCase):
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)
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X, y = load_iris(return_X_y=True)
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clf.fit(X, y)
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self.assertEqual(clf.n_features_, 4)
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self.assertEqual(clf.n_features_in_, 4)
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self.assertTrue(np.array_equal(X, clf.X_))
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self.assertTrue(np.array_equal(y, clf.y_))
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X_transformed = clf.transform(X)
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@@ -139,7 +140,7 @@ class FImdlpTest(unittest.TestCase):
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)
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X, y = load_iris(return_X_y=True)
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clf.fit(X, y)
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self.assertEqual(clf.n_features_, 4)
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self.assertEqual(clf.n_features_in_, 4)
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self.assertTrue(np.array_equal(X, clf.X_))
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self.assertTrue(np.array_equal(y, clf.y_))
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self.assertListEqual(
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@@ -213,3 +214,7 @@ class FImdlpTest(unittest.TestCase):
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]
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with self.assertRaises(ValueError):
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FImdlp().join_transform(x, y, 5)
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def test_sklearn_transformer(self):
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for check, test in check_estimator(FImdlp(), generate_only=True):
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test(check)
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