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  • xr.corr produces incorrect output for complex arrays · 3 ✖

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  • NONE · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1334059488 https://github.com/pydata/xarray/issues/7340#issuecomment-1334059488 https://api.github.com/repos/pydata/xarray/issues/7340 IC_kwDOAMm_X85PhCHg mattragoza 7647340 2022-12-01T16:50:49Z 2022-12-01T16:50:49Z NONE

The problem is in https://github.com/pydata/xarray/blob/main/xarray/core/computation.py#L1402-L1404. You need to conjugate one of the arrays before computing the dot product.

 
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   xr.corr produces incorrect output for complex arrays 1470583016
1334027040 https://github.com/pydata/xarray/issues/7340#issuecomment-1334027040 https://api.github.com/repos/pydata/xarray/issues/7340 IC_kwDOAMm_X85Pg6Mg mattragoza 7647340 2022-12-01T16:25:26Z 2022-12-01T16:25:26Z NONE

I'm now noticing that scipy.stats.pearsonr returns the same value as xr.corr.

 
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   xr.corr produces incorrect output for complex arrays 1470583016
1334024381 https://github.com/pydata/xarray/issues/7340#issuecomment-1334024381 https://api.github.com/repos/pydata/xarray/issues/7340 IC_kwDOAMm_X85Pg5i9 mattragoza 7647340 2022-12-01T16:23:25Z 2022-12-01T16:23:25Z NONE

Yes. If I use a np.array and call np.corrcoef, I get a 2x2 correlation matrix full of ones.

 
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   xr.corr produces incorrect output for complex arrays 1470583016

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