forecaster.metrics.crps_from_quantiles

forecaster.metrics.crps_from_quantiles(y_true, pred_quantiles, quantile_levels)

Calculate the Continuous Ranked Probability Score (CRPS) from quantiles.

The empirical cdf is approximated using linear interpolation between the predicted quantiles.

Parameters

Name	Type	Description	Default
y_true	float	The true value of the random variable.	required
pred_quantiles	np.ndarray	The predicted quantile values.	required
quantile_levels	np.ndarray	The quantile levels corresponding to the predicted quantiles.	required

Returns

Name	Type	Description
	float	The CRPS score.

Examples

>>> from spotforecast2.forecaster.metrics import crps_from_quantiles
>>> y_true = 5.0
>>> pred_quantiles = np.array([4.0, 4.5, 5.0, 5.5, 6.0])
>>> quantile_levels = np.array([0.1, 0.25, 0.5, 0.75, 0.9])
>>> crps = crps_from_quantiles(y_true, pred_quantiles, quantile_levels)
>>> crps >= 0
True