pysteps.verification.detcatscores.det_cat_fct¶

pysteps.verification.detcatscores.det_cat_fct(pred, obs, thr, scores='', axis=None)¶

Calculate simple and skill scores for deterministic categorical (dichotomous) forecasts.

Parameters

pred: array_like

Array of predictions. NaNs are ignored.

obs: array_like

Array of verifying observations. NaNs are ignored.

thr: float

The threshold that is applied to predictions and observations in order to define events vs no events (yes/no).

scores: {string, list of strings}, optional

The name(s) of the scores. The default, scores=””, will compute all available scores. The available score names are:

Name	Description
ACC	accuracy (proportion correct)
BIAS	frequency bias
CSI	critical success index (threat score)
ETS	equitable threat score
F1	the harmonic mean of precision and sensitivity
FA	false alarm rate (prob. of false detection, fall-out, false positive rate)
FAR	false alarm ratio (false discovery rate)
GSS	Gilbert skill score (equitable threat score)
HK	Hanssen-Kuipers discriminant (Pierce skill score)
HSS	Heidke skill score
MCC	Matthews correlation coefficient
POD	probability of detection (hit rate, sensitivity, recall, true positive rate)
SEDI	symmetric extremal dependency index

axis: None or int or tuple of ints, optional

Axis or axes along which a score is integrated. The default, axis=None, will integrate all of the elements of the input arrays.

If axis is -1 (or any negative integer), the integration is not performed and scores are computed on all of the elements in the input arrays.

If axis is a tuple of ints, the integration is performed on all of the axes specified in the tuple.

Returns