xskillscore.pearson_r_p_value

xskillscore.pearson_r_p_value(a, b, dim=None, weights=None, skipna=False, keep_attrs=False)

2-tailed p-value associated with pearson’s correlation coefficient.

Parameters

  • a (xarray.Dataset or xarray.DataArray) – Labeled array(s) over which to apply the function.

  • b (xarray.Dataset or xarray.DataArray) – Labeled array(s) over which to apply the function.

  • dim (str, list) – The dimension(s) to apply the correlation along. Note that this dimension will be reduced as a result. Defaults to None reducing all dimensions.

  • weights (xarray.Dataset or xarray.DataArray or None) – Weights matching dimensions of dim to apply during the function.

  • skipna (bool) – If True, skip NaNs when computing function.

  • keep_attrs (bool) – If True, the attributes (attrs) will be copied from the first input to the new one. If False (default), the new object will be returned without attributes.

Returns

2-tailed p-value of Pearson’s correlation coefficient.

Return type

xarray.Dataset or xarray.DataArray

See also

scipy.stats.pearsonr

Examples

>>> a = xr.DataArray(np.random.rand(5, 3, 3),
...                  dims=['time', 'x', 'y'])
>>> b = xr.DataArray(np.random.rand(5, 3, 3),
...                  dims=['time', 'x', 'y'])
>>> xs.pearson_r_p_value(a, b, dim='time')
<xarray.DataArray (x: 3, y: 3)>
array([[0.77888033, 0.66476199, 0.15051516],
       [0.59316935, 0.47567465, 0.75446898],
       [0.59925464, 0.58509064, 0.04161894]])
Dimensions without coordinates: x, y