issue_comments: 902657635
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/5715#issuecomment-902657635 | https://api.github.com/repos/pydata/xarray/issues/5715 | 902657635 | IC_kwDOAMm_X841zXZj | 9466648 | 2021-08-20T12:30:19Z | 2021-08-20T12:30:33Z | CONTRIBUTOR | I had a look to it this morning and I think I managed to solve the issue by replacing the calls to For (successful) testing I used the same code as above plus the following: ```python ds_dask = ds.chunk({"t": 10}) yy = xr.corr(ds['y'], ds['y']).to_numpy() yy_dask = xr.corr(ds_dask['y'], ds_dask['y']).to_numpy() yx = xr.corr(ds['y'], ds['x']).to_numpy() yx_dask = xr.corr(ds_dask['y'], ds_dask['x']).to_numpy() np.testing.assert_allclose(yy, yy_dask), "YY: {} is different from {}".format(yy, yy_dask) np.testing.assert_allclose(yx, yx_dask), "YX: {} is different from {}".format(yx, yx_dask) ``` The results are not exactly identical but almost which is probably due to numerical approximations of multiple computations in the dask case. I also tested the correlation of simple DataArrays without dask installed and the result seem coherent (close to 0 for uncorrelated data and very close to 1 when correlating identical variables). Should I make a pull request ? Should I implement this test ? Any others ? |
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