xskillscore.crps_quadrature

xskillscore.crps_quadrature(observations, cdf_or_dist, xmin=None, xmax=None, tol=1e-06, dim=None, weights=None, keep_attrs=False)

Continuous Ranked Probability Score with numerical integration of the normal distribution.

Parameters:

observations (xarray.Dataset or xarray.DataArray) – Observations associated with the forecast distribution cdf_or_dist.
cdf_or_dist (callable or scipy.stats.distribution) – Function which returns the cumulative density of the forecast distribution at value x.
xmin (see properscoring.crps_quadrature) –
xmax (see properscoring.crps_quadrature) –
tol (see properscoring.crps_quadrature) –
dim (str or list of str, optional) – Dimension over which to compute mean after computing crps_quadrature. Defaults to None implying averaging over all dimensions.
weights (xr.DataArray with dimensions from dim, optional) – Weights for weighted.mean(dim). Defaults to None, such that no weighting is applied.
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.

Return type:

xarray.Dataset or xarray.DataArray

Examples

>>> observations = xr.DataArray(
...     np.random.normal(size=(3, 3)),
...     coords=[("x", np.arange(3)), ("y", np.arange(3))],
... )
>>> from scipy.stats import norm
>>> xs.crps_quadrature(observations, norm, dim="x")
<xarray.DataArray (y: 3)> Size: 24B
array([0.80280921, 0.31818197, 0.32364912])
Coordinates:
  * y        (y) int64 24B 0 1 2