pysteps.verification.probscores.ROC_curve(P_f, X_o, X_min, n_prob_thrs=10, compute_area=False)#

Compute the ROC curve and its area from the given ROC object.

  • P_f (array_like) – Forecasted probabilities for exceeding the threshold specified in the ROC object. Non-finite values are ignored.

  • X_o (array_like) – Observed values. Non-finite values are ignored.

  • X_min (float) – Precipitation intensity threshold for yes/no prediction.

  • n_prob_thrs (int) – The number of probability thresholds to use. The interval [0,1] is divided into n_prob_thrs evenly spaced values.

  • compute_area (bool) – If True, compute the area under the ROC curve (between 0.5 and 1).


out – A two-element tuple containing the probability of detection (POD) and probability of false detection (POFD) for the probability thresholds specified in the ROC curve object. If compute_area is True, return the area under the ROC curve as the third element of the tuple.

Return type: