issue_comments: 850650732

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https://github.com/pydata/xarray/pull/5390#issuecomment-850650732 https://api.github.com/repos/pydata/xarray/issues/5390 850650732 MDEyOklzc3VlQ29tbWVudDg1MDY1MDczMg== 2448579 2021-05-28T20:19:56Z 2021-05-28T20:20:52Z MEMBER

python # 3. Detrend along the given dim # 4. Compute covariance along the given dim # N.B. `skipna=False` is required or there is a bug when computing # auto-covariance. E.g. Try xr.cov(da,da) for # da = xr.DataArray([[1, 2], [1, np.nan]], dims=["x", "time"]) def _mean(da): return da.sum(dim=dim, skipna=True, min_count=1) / (valid_count) cov = _mean(da_a * da_b) - _mean(da_a.mean(dim=dim) * da_b.mean(dim=dim))

This second term looks very weird to me, it should be a no-op python _mean(da_a.mean(dim=dim) * da_b.mean(dim=dim))

is it just cov = _mean(da_a * da_b) - da_a.mean(dim=dim) * da_b.mean(dim=dim)

 
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