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:
result – Dictionary containing the verification results.
- Return type:
dict