earthkit.meteo.score

Submodules

• earthkit.meteo.score.array
• earthkit.meteo.score.xarray

Functions

abs_error(fcst, obs[, agg_method, agg_dim, ...])	Calculates the absolute error between a forecast and observations.
cosine_similarity(fcst, obs, over[, weights])	Calculates the cosine similarity between a forecast and observations.
crps_from_cdf(fcst, obs, over[, weight, return_components])	Calculates the continuous ranked probability score (CRPS) for forecasts provided as CDFs.
crps_from_ensemble(fcst, obs, over[, method, ...])	Calculates the continuous ranked probability score (CRPS) of an ensemble forecast.
crps_from_gaussian(fcst, obs)	Calculates the continuous ranked probability score (CRPS) of a forecast
error(fcst, obs[, agg_method, agg_dim, agg_weights])	Calculates the error between a forecast and observations.
kge(fcst, obs, over[, method, return_components])	Calculates the Kling-Gupta Efficiency (KGE) between a forecast and observations.
mean_abs_error(fcst, obs, over[, weights, is_angular])	Calculates the mean absolute error between a forecast and observations.
mean_error(fcst, obs, over[, weights])	Calculates the mean error between a forecast and observations.
mean_squared_error(fcst, obs, over[, weights, is_angular])	Calculates the mean squared error between a forecast and observations.
pearson_correlation(fcst, obs, over[, weights])	Calculates the Pearson correlation between a forecast and observations.
quantile_score(fcst, obs, tau, over)	Calculates the quantile score of a forecast compared to a set of observations.
root_mean_squared_error(fcst, obs, over[, weights, ...])	Calculates the root mean squared error between a forecast and observations.
spread(fcst, over[, reference])	Calculates the spread of a forecast compared to a reference.
squared_error(fcst, obs[, agg_method, agg_dim, ...])	Calculates the squared error between a forecast and observations.
standard_deviation_of_error(fcst, obs, over[, weights])	Calculates the standard deviation of error between a forecast and observations.