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  • Gijom · 5 ✖

issue 1

  • Make xr.corr and xr.map_blocks work without dask · 5 ✖

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  • CONTRIBUTOR 5
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
977725089 https://github.com/pydata/xarray/pull/5731#issuecomment-977725089 https://api.github.com/repos/pydata/xarray/issues/5731 IC_kwDOAMm_X846Ruah Gijom 9466648 2021-11-24T10:08:04Z 2021-11-24T10:08:04Z CONTRIBUTOR

Sorry for the unresponsiveness. I confirm that using the asfloat conversion also works for me. Should I close the issue or should I let you do it ?

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  Make xr.corr and xr.map_blocks work without dask 976790237
904403621 https://github.com/pydata/xarray/pull/5731#issuecomment-904403621 https://api.github.com/repos/pydata/xarray/issues/5731 IC_kwDOAMm_X8416Bql Gijom 9466648 2021-08-24T07:43:28Z 2021-08-31T14:41:01Z CONTRIBUTOR

I included the proposed changes, thanks for the help.

However the new test I implemented does not go through and I fail to understand why. Would you be able to check ? The idea of the test is to ensure that lazy computations give the same results than normal ones. I tracked down the problem to line 1377 of computation.py: python demeaned_da_a = da_a - da_a.mean(dim=dim) # <-- this one returns nan upon computation (.compute()) demeaned_da_b = da_b - da_b.mean(dim=dim) # <-- this one returns the correct value although the input is masked with nans in the same way

The values before the mean call are: da_a.compute() = <xarray.DataArray <this-array> (x: 2, time: 2)> array([[ 1., 2.], [ 2., nan]]) da_b.compute() = <xarray.DataArray <this-array> (x: 2, time: 2)> array([[ 1., 2.], [ 1., nan]])

And for the means (dim is None): da_a.mean(dim=dim).compute()=<xarray.DataArray <this-array> ()> array(nan) da_b.mean(dim=dim).compute()=<xarray.DataArray <this-array> ()> array(1.33333333)

For non lazy computations everything seems fine.

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  Make xr.corr and xr.map_blocks work without dask 976790237
909300955 https://github.com/pydata/xarray/pull/5731#issuecomment-909300955 https://api.github.com/repos/pydata/xarray/issues/5731 IC_kwDOAMm_X842MtTb Gijom 9466648 2021-08-31T14:40:24Z 2021-08-31T14:40:24Z CONTRIBUTOR

I was referring to: https://github.com/pydata/xarray/pull/5731#issuecomment-904403621

Otherwise I am working on the conflict with the main branch. Should be done soon.

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  Make xr.corr and xr.map_blocks work without dask 976790237
909095076 https://github.com/pydata/xarray/pull/5731#issuecomment-909095076 https://api.github.com/repos/pydata/xarray/issues/5731 IC_kwDOAMm_X842L7Ck Gijom 9466648 2021-08-31T10:10:15Z 2021-08-31T10:10:15Z CONTRIBUTOR

@keewis indeed this was the problem. I removed it and corrected one test which did not have the @require_dask decorator.

There is still a test error with the test arrays 5 and 6: the lazy array version do not return the same value than the usual corr. I consider this a different bug and just removed the tests with a TODO in the code.

The last commit pass the tests on my machine and I added the whats-new text to version 0.19.1.

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  Make xr.corr and xr.map_blocks work without dask 976790237
903574187 https://github.com/pydata/xarray/pull/5731#issuecomment-903574187 https://api.github.com/repos/pydata/xarray/issues/5731 IC_kwDOAMm_X84123Kr Gijom 9466648 2021-08-23T08:57:36Z 2021-08-23T08:57:36Z CONTRIBUTOR

Concerning the tests I added a test to check that lazy correlations have identical results to non-lazy correlations. But this is not directly related to the bug fix. Indeed there is a need to have a test that checks if the non-lazy correlation works without dask installed. The already existing test function test_corr does not have a @requires_dask decorator. But it did not fail as it should have. Not sure why.

About documenting the changes, I am not sure of the whats-new.rst format and I thus did not add it. Should I just add a bullet item on the top of the file ?

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  Make xr.corr and xr.map_blocks work without dask 976790237

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