xskillscore.spearman_r_p_value
- xskillscore.spearman_r_p_value(a, b, dim=None, weights=None, skipna=False, keep_attrs=False)
2-tailed p-value associated with Spearman’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 Spearman’s correlation coefficient.
- Return type:
See also
scipy.stats.spearman_r
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.spearman_r_p_value(a, b, dim="time") <xarray.DataArray (x: 3, y: 3)> Size: 72B array([[0.28475698, 0.39100222, 0.1881204 ], [0.50463158, 0.62383766, 0.62383766], [0.62383766, 0.87288857, 0.03738607]]) Dimensions without coordinates: x, y