pysteps.verification.ensscores.rankhist¶
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pysteps.verification.ensscores.
rankhist
(X_f, X_o, X_min=None, normalize=True)¶ Compute a rank histogram counts and optionally normalize the histogram.
- Parameters
- X_f: array-like
Array of shape (k,m,n,…) containing the values from an ensemble forecast of k members with shape (m,n,…).
- X_o: array_like
Array of shape (m,n,…) containing the observed values corresponding to the forecast.
- X_min: {float,None}
Threshold for minimum intensity. Forecast-observation pairs, where all ensemble members and verifying observations are below X_min, are not counted in the rank histogram. If set to None, thresholding is not used.
- normalize: {bool, True}
If True, normalize the rank histogram so that the bin counts sum to one.