def compute_theil_on_bins(y_pred, mask, bin_indices, target_efficiencies,
sample_weight):
y_pred = column_or_1d(y_pred)
sample_weight = check_sample_weight(y_pred, sample_weight=sample_weight)
# ignoring events from other classes
y_pred = y_pred[mask]
bin_indices = bin_indices[mask]
sample_weight = sample_weight[mask]
bin_weights = compute_bin_weights(bin_indices=bin_indices,
sample_weight=sample_weight)
cuts = compute_cut_for_efficiency(target_efficiencies,
mask=numpy.ones(len(y_pred), dtype=bool),
y_pred=y_pred,
sample_weight=sample_weight)
result = 0.
for cut in cuts:
bin_efficiencies = compute_bin_efficiencies(
y_pred,
bin_indices=bin_indices,
cut=cut,
sample_weight=sample_weight)
result += theil(bin_efficiencies, weights=bin_weights)
return result / len(cuts)
def compute_theil_on_groups(y_pred, mask, groups_indices, target_efficiencies, sample_weight):
y_pred = column_or_1d(y_pred)
sample_weight = check_sample_weight(y_pred, sample_weight=sample_weight)
groups_weights = compute_group_weights_by_indices(groups_indices, sample_weight=sample_weight)
divided_weight = compute_divided_weight_by_indices(groups_indices, sample_weight=sample_weight * mask)
cuts = compute_cut_for_efficiency(target_efficiencies, mask=mask,
y_pred=y_pred, sample_weight=sample_weight)
result = 0.
for cut in cuts:
groups_efficiencies = compute_group_efficiencies_by_indices(y_pred, groups_indices=groups_indices,
cut=cut, divided_weight=divided_weight)
result += theil(groups_efficiencies, groups_weights)
return result / len(cuts)
def compute_theil_on_bins(y_pred, mask, bin_indices, target_efficiencies, sample_weight):
y_pred = column_or_1d(y_pred)
sample_weight = check_sample_weight(y_pred, sample_weight=sample_weight)
# ignoring events from other classes
y_pred = y_pred[mask]
bin_indices = bin_indices[mask]
sample_weight = sample_weight[mask]
bin_weights = compute_bin_weights(bin_indices=bin_indices, sample_weight=sample_weight)
cuts = compute_cut_for_efficiency(target_efficiencies, mask=numpy.ones(len(y_pred), dtype=bool),
y_pred=y_pred, sample_weight=sample_weight)
result = 0.
for cut in cuts:
bin_efficiencies = compute_bin_efficiencies(y_pred, bin_indices=bin_indices,
cut=cut, sample_weight=sample_weight)
result += theil(bin_efficiencies, weights=bin_weights)
return result / len(cuts)
def compute_theil_on_groups(y_pred, mask, groups_indices, target_efficiencies,
sample_weight):
y_pred = column_or_1d(y_pred)
sample_weight = check_sample_weight(y_pred, sample_weight=sample_weight)
groups_weights = compute_group_weights_by_indices(
groups_indices, sample_weight=sample_weight)
divided_weight = compute_divided_weight_by_indices(
groups_indices, sample_weight=sample_weight * mask)
cuts = compute_cut_for_efficiency(target_efficiencies,
mask=mask,
y_pred=y_pred,
sample_weight=sample_weight)
result = 0.
for cut in cuts:
groups_efficiencies = compute_group_efficiencies_by_indices(
y_pred,
groups_indices=groups_indices,
cut=cut,
divided_weight=divided_weight)
result += theil(groups_efficiencies, groups_weights)
return result / len(cuts)