Dask type checking #643
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Dask type checking #643
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…data types to a numpy generic (e.g. a scalar, such as int or float) rather than to an array of such things. This change modifies the test to incorporate a union type of array and generic in assert statements for dask operations
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This PR still needs review, but is a safe change and is needed to restore test compliance so that others can test their changes. I will re-open the issue and ensure a review occurs before the next release. |
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Thanks @tennlee, this seems reasonable. Can you explain why these changes are only needed for some of the dask tests, but not all? |
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Great, thanks for checking through it. I only fixed test cases which were failing. I imagine the only tests that were affected are the ones which are calculating a single number, whereas many of the tests are creating arrays which are then still array types. |
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Okay that makes sense. I can see that the ones that didn't need changing preserve a dim in the calculation |
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Dask type checking
tennlee
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* Allow use of slightly earlier pandas versions * Merge pull request #643 from tennlee/dask_type_checking Dask type checking
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With the most recent updates to numpy, the computed dask objects have a different numpy type. I have made the type checking in the automated tests more generic to allow for a range of numpy types in the computed object. This should be compatible across a wide range of Python and numpy versions while still being a correct test.