8000 CI failure on test_iterative_imputer_catch_warning · Issue #21690 · scikit-learn/scikit-learn · GitHub
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adrinjalali opened this issue Nov 16, 2021 · 2 comments · Fixed by #21697
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CI failure on test_iterative_imputer_catch_warning #21690

adrinjalali opened this issue Nov 16, 2021 · 2 comments · Fixed by #21697
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@adrinjalali
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adrinjalali commented Nov 16, 2021 •
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pandas CI fails with the following error link

_____________________ test_iterative_imputer_catch_warning _____________________
[gw0] linux -- Python 3.9.7 /usr/share/miniconda/envs/testvenv/bin/python

    def test_iterative_imputer_catch_warning():
../1/s/sklearn/impute/tests/test_impute.py:953: AssertionError
_____________ test_calibration_display_default_labels[None-_line1] _____________
[gw1] linux -- Python 3.9.7 /usr/share/miniconda/envs/testvenv/bin/python

pyplot = <module 'matplotlib.pyplot' from '/usr/share/miniconda/envs/testvenv/lib/python3.9/site-packages/matplotlib/pyplot.py'>
name = None, expected_label = '_line1'

    @pytest.mark.parametrize(
        "name, expected_label", [(None, "_line1"), ("my_est", "my_est")]
    )
    def test_calibration_display_default_labels(pyplot, name, expected_label):
        prob_true = np.array([0, 1, 1, 0])
        prob_pred = np.array([0.2, 0.8, 0.8, 0.4])
        y_prob = np.array([])
    
        viz = CalibrationDisplay(prob_true, prob_pred, y_prob, estimator_name=name)
        viz.plot()
>       assert viz.line_.get_label() == expected_label
E       AssertionError: assert '_child1' == '_line1'
E         - _line1
E         + _child1

expected_label = '_line1'
name       = None
prob_pred  = array([0.2, 0.8, 0.8, 0.4])
prob_true  = array([0, 1, 1, 0])
pyplot     = <module 'matplotlib.pyplot' from '/usr/share/miniconda/envs/testvenv/lib/python3.9/site-packages/matplotlib/pyplot.py'>
viz        = <sklearn.calibration.CalibrationDisplay object at 0x7f555b005a90>
y_prob     = array([], dtype=float64)

../1/s/sklearn/tests/test_calibration.py:715: AssertionError
@adrinjalali
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ping @thomasjpfan @glemaitre I think

@adrinjalali adrinjalali mentioned this issue Nov 17, 2021
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@glemaitre
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Here, there are 2 tests that are failing. The second one is indeed solved in #21697.
However, the first test is a flaky test. I am not sure that we can always reproduce it.

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TST check the legend instead of label names in CalibrationDisplay jjerphan/scikit-learn
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