import unittest from mdlp import MDLP from sklearn.datasets import load_wine, load_iris from ..Selection import MFS class MFS_test(unittest.TestCase): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) mdlp = MDLP(random_state=1) self.X_wc, self.y_w = load_wine(return_X_y=True) self.X_w = mdlp.fit_transform(self.X_wc, self.y_w).astype("int64") self.X_ic, self.y_i = load_iris(return_X_y=True) mdlp = MDLP(random_state=1) self.X_i = mdlp.fit_transform(self.X_ic, self.y_i).astype("int64") def assertListAlmostEqual(self, list1, list2, tol=7): self.assertEqual(len(list1), len(list2)) for a, b in zip(list1, list2): self.assertAlmostEqual(a, b, tol) def test_initialize(self): mfs = MFS() mfs.fcbf(self.X_w, self.y_w, 0.05) mfs._initialize(self.X_w, self.y_w) self.assertIsNone(mfs.get_results()) self.assertListEqual([], mfs.get_scores()) self.assertDictEqual({}, mfs._su_features) self.assertIsNone(mfs._su_labels) def test_csf_wine(self): mfs = MFS() expected = [6, 12, 9, 4, 10, 0] self.assertListAlmostEqual( expected, mfs.cfs(self.X_w, self.y_w).get_results() ) expected = [ 0.5218299405215557, 0.602513857132804, 0.4877384978817362, 0.3743688234383051, 0.28795671854246285, 0.2309165735173175, ] self.assertListAlmostEqual(expected, mfs.get_scores()) def test_csf_wine_cont(self): mfs = MFS(discrete=False) expected = [10, 6, 0, 2, 11, 9] self.assertListEqual( expected, mfs.cfs(self.X_wc, self.y_w).get_results() ) expected = [ 0.735264150416997, 0.8321684551546848, 0.7439915858469107, 0.6238883340158233, 0.513637402071709, 0.41596400981378984, ] self.assertListAlmostEqual(expected, mfs.get_scores()) def test_csf_max_features(self): mfs = MFS(max_features=3) expected = [6, 12, 9] self.assertListAlmostEqual( expected, mfs.cfs(self.X_w, self.y_w).get_results() ) expected = [ 0.5218299405215557, 0.602513857132804, 0.4877384978817362, ] self.assertListAlmostEqual(expected, mfs.get_scores()) def test_csf_iris(self): mfs = MFS() expected = [3, 2, 0, 1] computed = mfs.cfs(self.X_i, self.y_i).get_results() self.assertListAlmostEqual(expected, computed) expected = [ 0.870521418179061, 0.8968651482682227, 0.5908278453318913, 0.40371971570693366, ] self.assertListAlmostEqual(expected, mfs.get_scores()) def test_fcbf_wine(self): mfs = MFS() computed = mfs.fcbf(self.X_w, self.y_w, threshold=0.05).get_results() expected = [6, 9, 12, 0, 11, 4] self.assertListAlmostEqual(expected, computed) expected = [ 0.5218299405215557, 0.46224298637417455, 0.44518278979085646, 0.38942355544213786, 0.3790082191220976, 0.24972405134844652, ] self.assertListAlmostEqual(expected, mfs.get_scores()) def test_fcbf_max_features(self): mfs = MFS(max_features=3) computed = mfs.fcbf(self.X_w, self.y_w, threshold=0.05).get_results() expected = [6, 9, 12] self.assertListAlmostEqual(expected, computed) expected = [ 0.5218299405215557, 0.46224298637417455, 0.44518278979085646, ] self.assertListAlmostEqual(expected, mfs.get_scores()) def test_fcbf_iris(self): mfs = MFS() computed = mfs.fcbf(self.X_i, self.y_i, threshold=0.05).get_results() expected = [3, 2] self.assertListAlmostEqual(expected, computed) expected = [0.870521418179061, 0.810724587460511] self.assertListAlmostEqual(expected, mfs.get_scores()) def test_compute_su_labels(self): mfs = MFS() mfs.fcbf(self.X_i, self.y_i, threshold=0.05) expected = [0.0, 0.0, 0.810724587460511, 0.870521418179061] self.assertListAlmostEqual(expected, mfs._compute_su_labels().tolist()) mfs._su_labels = [1, 2, 3, 4] self.assertListAlmostEqual([1, 2, 3, 4], mfs._compute_su_labels()) def test_invalid_threshold(self): mfs = MFS() with self.assertRaises(ValueError): mfs.fcbf(self.X_i, self.y_i, threshold=1e-15) def test_fcbf_exit_threshold(self): mfs = MFS() computed = mfs.fcbf(self.X_w, self.y_w, threshold=0.4).get_results() expected = [6, 9, 12] self.assertListAlmostEqual(expected, computed) expected = [ 0.5218299405215557, 0.46224298637417455, 0.44518278979085646, ] self.assertListAlmostEqual(expected, mfs.get_scores())