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+-----------------+-----------+
See also:
* xskillscore.pearson_r
* xskillscore.pearson_r_p_value
* climpred.pearson_r
* climpred.pearson_r_eff_p_value
"""
weights = metric_kwargs.get('weights', None)
skipna = metric_kwargs.get('skipna', False)
# p value returns a runtime error when working with NaNs, such as on a climate
# model grid. We can avoid this annoying output by specifically suppressing
# warning here.
with warnings.catch_warnings():
warnings.simplefilter('ignore')
return pearson_r_p_value(
forecast, verif, dim=dim, weights=weights, skipna=skipna
)