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Fix precision issues in tests executed in Travis

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This commit is contained in:
Ricardo Montañana Gómez
2020-05-20 15:02:31 +02:00
parent 6e35628c85
commit 316f84cc63
1 changed files with 11 additions and 6 deletions
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17
tests/Stree_test.py
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@@ -144,17 +144,21 @@ class Stree_test(unittest.TestCase):
"""Check that element 28 has a prediction different that the current label """Check that element 28 has a prediction different that the current label
""" """
# Element 28 has a different prediction than the truth # Element 28 has a different prediction than the truth
decimals = 8 decimals = 5
X, y = self._get_Xy() X, y = self._get_Xy()
yp = self._clf.predict_proba(X[28, :].reshape(-1, X.shape[1])) yp = self._clf.predict_proba(X[28, :].reshape(-1, X.shape[1]))
self.assertEqual(0, yp[0:, 0]) self.assertEqual(0, yp[0:, 0])
self.assertEqual(1, y[28]) self.assertEqual(1, y[28])
self.assertEqual(round(0.29026400766, decimals), round(yp[0, 1], decimals)) self.assertAlmostEqual(
round(0.29026400766, decimals),
round(yp[0, 1], decimals),
decimals
)
def test_multiple_predict_proba(self): def test_multiple_predict_proba(self):
# First 27 elements the predictions are the same as the truth # First 27 elements the predictions are the same as the truth
num = 27 num = 27
decimals = 8 decimals = 5
X, y = self._get_Xy() X, y = self._get_Xy()
yp = self._clf.predict_proba(X[:num, :]) yp = self._clf.predict_proba(X[:num, :])
self.assertListEqual(y[:num].tolist(), yp[:, 0].tolist()) self.assertListEqual(y[:num].tolist(), yp[:, 0].tolist())
@@ -163,9 +167,10 @@ class Stree_test(unittest.TestCase):
0.30756427, 0.8318412, 0.18981198, 0.15564624, 0.25740655, 0.22923355, 0.30756427, 0.8318412, 0.18981198, 0.15564624, 0.25740655, 0.22923355,
0.87365959, 0.49928689, 0.95574351, 0.28761257, 0.28906333, 0.32643692, 0.87365959, 0.49928689, 0.95574351, 0.28761257, 0.28906333, 0.32643692,
0.29788483, 0.01657364, 0.81149083] 0.29788483, 0.01657364, 0.81149083]
self.assertListEqual( expected = np.round(expected_proba, decimals=decimals).tolist()
np.round(expected_proba, decimals=decimals).tolist(), computed = np.round(yp[:, 1], decimals=decimals).tolist()
np.round(yp[:, 1], decimals=decimals).tolist()) for i in range(len(expected)):
self.assertAlmostEqual(expected[i], computed[i], decimals)
def build_models(self): def build_models(self):
"""Build and train two models, model_clf will use the sklearn classifier to """Build and train two models, model_clf will use the sklearn classifier to