pysteps.verification.detcatscores.det_cat_fct_compute

pysteps.verification.detcatscores.det_cat_fct_compute(contab, scores='')

Compute simple and skill scores for deterministic categorical (dichotomous) forecasts from a contingency table object.

Parameters:

contab : dict

A contingency table object initialized with pysteps.verification.detcatscores.det_cat_fct_init and populated with pysteps.verification.detcatscores.det_cat_fct_accum.

scores : {string, list of strings}, optional

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

Name	Description
ACC	accuracy (proportion correct)
BIAS	frequency bias
CSI	critical success index (threat score)
FA	false alarm rate (prob. of false detection)
FAR	false alarm ratio
GSS	Gilbert skill score (equitable threat score)
HK	Hanssen-Kuipers discriminant (Pierce skill score)
HSS	Heidke skill score
POD	probability of detection (hit rate)
SEDI	symmetric extremal dependency index

Returns:

result : dict

Dictionary containing the verification results.