def get_mean_crps_loss(batch_predictions, batch_targets, batch_ids): nbatches = len(batch_predictions) npredictions = len(batch_predictions[0]) crpss = [] for i in range(npredictions): p, t = [], [] for j in range(nbatches): p.append(batch_predictions[j][i]) t.append(batch_targets[j][i]) p, t = np.vstack(p), np.vstack(t) target_cdf = utils_heart.heaviside_function(t) crpss.append(np.mean((p - target_cdf) ** 2)) return crpss
def get_mean_crps_loss(batch_predictions, batch_targets, batch_ids): nbatches = len(batch_predictions) npredictions = len(batch_predictions[0]) crpss = [] for i in xrange(npredictions): p, t = [], [] for j in xrange(nbatches): p.append(batch_predictions[j][i]) t.append(batch_targets[j][i]) p, t = np.vstack(p), np.vstack(t) target_cdf = utils_heart.heaviside_function(t) crpss.append(np.mean((p - target_cdf) ** 2)) return crpss