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Simplify missing value handling in xarray.corr #6025

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Nov 28, 2021
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Simplify missing value handling in xarray.corr #6025

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19 changes: 2 additions & 17 deletions xarray/core/computation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1346,25 +1346,10 @@ def _cov_corr(da_a, da_b, dim=None, ddof=0, method=None):

# 2. Ignore the nans
valid_values = da_a.notnull() & da_b.notnull()
da_a = da_a.where(valid_values)
da_b = da_b.where(valid_values)
valid_count = valid_values.sum(dim) - ddof

def _get_valid_values(da, other):
"""
Function to lazily mask da_a and da_b
following a similar approach to
https://github.com/pydata/xarray/pull/4559
"""
missing_vals = np.logical_or(da.isnull(), other.isnull())
if missing_vals.any():
da = da.where(~missing_vals)
return da
else:
# ensure consistent return dtype
return da.astype(float)

da_a = da_a.map_blocks(_get_valid_values, args=[da_b])
da_b = da_b.map_blocks(_get_valid_values, args=[da_a])

# 3. Detrend along the given dim
demeaned_da_a = da_a - da_a.mean(dim=dim)
demeaned_da_b = da_b - da_b.mean(dim=dim)
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