TST Extend tests for scipy.sparse.*array in sklearn/preprocessing/tests/test_label.py
#27227
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| classes=[1, 2], | ||
| threshold=0, | ||
| ) | ||
| for csr_container in CSR_CONTAINERS: |
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How about splitting the two loops that are using spare containers into a separate test and then parametrizing that? I think these tests are not dependent on anything else within this test.
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Can't this loop also be moved into the added test test_label_binarizer_sparse_errors?
| @@ -350,8 +352,11 @@ def test_sparse_output_multilabel_binarizer(): | |||
| assert_array_equal([1, 2, 3], mlb.classes_) | |||
| assert mlb.inverse_transform(got) == inverse | |||
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| with pytest.raises(ValueError): | |||
| mlb.inverse_transform(csr_matrix(np.array([[0, 1, 1], [2, 0, 0], [1, 1, 0]]))) | |||
| for csr_container in CSR_CONTAINERS: | |||
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Similarly you might also be able to move this into a separate test and parametrize that since this part is just checking for an error and is independent from the rest of the test.
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@OmarManzoor Thanks for your comments. In second test I used MultiLabelBinarizer and input according to last values in for loop, because it was used in original test, if you have better solution, I will be glad to make a fix |
I think it looks fine considering it is replicating the original behavior. 👍 |
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@OmarManzoor if you want to have a second look at it. |
…tests/test_label.py` (scikit-learn#27227)
Reference Issues/PRs
Towards #27090.
What does this implement/fix? Explain your changes.
Any other comments?
I used for loops instead of parameterisation in some tests to save time and do not repeat other checks in test that do not depend on sparse type.
Also i fixed test
test_label_binarize_multilabel. It used only lastyfrom for loop inpytest.raises(ValueError)