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
