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| author | Nilesh Patra <nilesh@debian.org> | 2023-12-14 19:06:53 +0100 |
|---|---|---|
| committer | Étienne Mollier <emollier@debian.org> | 2023-12-14 19:06:53 +0100 |
| commit | a58ad05e431c15eb17733e46f7a0de224bee63ce (patch) | |
| tree | 41e6668410c975ebd50bb32dc41c7219d402732a | |
| parent | c4c820aa9ace8652b206d404ff3000eafa65ac28 (diff) | |
Add more tolerance in 3 tests in order to avoid test failures due to float
Forwarded: yes
Last-Update: 2021-07-25
point errors on non-amd64 arches
Gbp-Pq: Name reduce-precision-in-tests.patch
| -rw-r--r-- | q2_sample_classifier/tests/test_estimators.py | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/q2_sample_classifier/tests/test_estimators.py b/q2_sample_classifier/tests/test_estimators.py index b42de3c..95fd084 100644 --- a/q2_sample_classifier/tests/test_estimators.py +++ b/q2_sample_classifier/tests/test_estimators.py @@ -253,9 +253,9 @@ class EstimatorsTests(SampleClassifierTestPluginBase): pred, self.mdc_chard_fp.to_series(), 'ignore') accuracy = accuracy_score(truth, pred) self.assertAlmostEqual( - accuracy, seeded_results[classifier], places=4, + accuracy, seeded_results[classifier], msg='Accuracy of %s classifier was %f, but expected %f' % ( - classifier, accuracy, seeded_results[classifier])) + classifier, accuracy, seeded_results[classifier]), delta=0.1) # test if training classifier with pipeline classify_samples raises # warning when test_size = 0.0 @@ -386,7 +386,7 @@ class EstimatorsTests(SampleClassifierTestPluginBase): regressor, accuracy, seeded_results[regressor])) else: self.assertAlmostEqual( - accuracy, seeded_results[regressor], places=4, + accuracy, seeded_results[regressor], places=2, msg='Accuracy of %s regressor was %f, but expected %f' % ( regressor, accuracy, seeded_results[regressor])) @@ -544,7 +544,7 @@ class EstimatorsTests(SampleClassifierTestPluginBase): self.assertAlmostEqual( mse, seeded_predict_results[regressor], msg='Accuracy of %s regressor was %f, but expected %f' % ( - regressor, mse, seeded_predict_results[regressor])) + regressor, mse, seeded_predict_results[regressor]), delta=0.001) # make sure predict still works when features are given in a different # order from training set. |