pysteps.verification.detcontscores.det_cont_fct_compute¶

pysteps.verification.detcontscores.det_cont_fct_compute(err, scores='')¶

Compute simple and skill scores for deterministic continuous forecasts from a verification error object.

Parameters

err: dict

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
beta1 \| linear regression slope (type 1 conditional bias)
beta2 \| linear regression slope (type 2 conditional bias)
corr_p	pearson’s correleation coefficien (linear correlation)
DRMSE	debiased root mean squared error, i.e. \(DRMSE = \sqrt{RMSE - ME^2}\)
MAE	mean absolute error
ME	mean error or bias
MSE	mean squared error
NMSE	normalized mean squared error
RMSE	root mean squared error
RV	reduction of variance (Brier Score, Nash-Sutcliffe Efficiency), i.e. \(RV = 1 - \frac{MSE}{s^2_o}\)

Returns