[MRG + 1] Fix sklearn.model_selection.tests.test_split:test_cv_iterable_wrapper on numpy master #7946
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Until now we were in a edge case on assert_array_equal
lesteve
commented
Nov 27, 2016
| splits_are_equal = True | ||
| except AssertionError: | ||
| splits_are_equal = False | ||
| assert_false(splits_are_equal, "If the splits are randomized, " |
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I am afraid I did not find a better way of emulating numpy.testing.assert_not_equal. Better suggestions welcome!
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we could also implement our own version of that?
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Is this related to #7823 |
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LGTM as quick fix. |
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LGTM as well. Feel free to merge! |
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I can refactor this out of #7823... |
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Thx @lesteve |
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Feb 28, 2017
Until now we were in a edge case on assert_array_equal
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Until now we were in a edge case on assert_array_equal
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Until now we were in a edge case on assert_array_equal
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* Fix tests on numpy master (#7946) Until now we were in a edge case on assert_array_equal * Fix tests on numpy master (#8355) numpy.apply_along_axis has changed behaviour when the function passed in returns a 2d array * [MRG] Updated plot_stock_market.py to use Google Finance (#9010) * DOC updated plot_stock_market.py to use Google Finance The implementations is intentionally very basic not to distract the users from the example. Specifically unlike ``quotes_historical_yahoo_ochl`` it does not cache downloaded data. I also had to remove some symbols because the have no data on Google for the specified date interval. These are WBA, LMT, KFT and MTU. Closes #8899 * DOC removed plot_stock_market.py from expected failing examples * Addressed review comments * Addressed another pass of review comments * [MRG] Remove DeprecationWarnings in examples due to using floats instead of ints (#8040)
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Until now we were in a edge case on assert_array_equal
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Until now we were in a edge case on assert_array_equal
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Until now we were in a edge case on assert_array_equal
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As mentioned in #7910 (comment) the tests started failing with numpy master one day or so ago.
What does this implement/fix? Explain your changes.
It looks like we were in a edge case of assert_array_equal. See numpy/numpy#8323 (comment) for more details.
I am using
numpy.testing.assert_equalwhich seems better at dealing with nested structures containing arrays.