forecaster.metrics.crps_from_predictions

forecaster.metrics.crps_from_predictions(y_true, y_pred)

Compute the Continuous Ranked Probability Score (CRPS) from predictions.

The CRPS compares the empirical distribution of a set of forecasted values to a scalar observation. The smaller the CRPS, the better.

Parameters

Name	Type	Description	Default
y_true	float	The true value of the random variable.	required
y_pred	np.ndarray	The predicted values of the random variable. These are the multiple forecasted values for a single observation.	required

Returns

Name	Type	Description
	float	The CRPS score.

Examples

import numpy as np
from spotforecast2_safe.forecaster.metrics import crps_from_predictions

y_true = 5.0
y_pred = np.array([4.5, 5.1, 4.9, 5.3, 4.7])
crps = crps_from_predictions(y_true, y_pred)
print(crps >= 0)

True