def test_group_names_do_not_match_groups(self):
target = GroupMetricSet()
target.model_type = GroupMetricSet.BINARY_CLASSIFICATION
target.y_true = [0, 1, 0, 0]
target.y_pred = [1, 1, 1, 0]
target.groups = [0, 1, 1, 0]
# Some wholly synthetic metrics
firstMetric = GroupMetricResult()
firstMetric.overall = 0.2
firstMetric.by_group[0] = 0.3
firstMetric.by_group[1] = 0.4
secondMetric = GroupMetricResult()
secondMetric.overall = 0.6
secondMetric.by_group[0] = 0.7
secondMetric.by_group[1] = 0.8
metric_dict = {
GroupMetricSet.GROUP_ACCURACY_SCORE: firstMetric,
GroupMetricSet.GROUP_MISS_RATE: secondMetric
}
target.metrics = metric_dict
target.group_names = ['First']
target.group_title = "Some string"
with pytest.raises(ValueError) as exception_context:
target.check_consistency()
expected = "Count of group_names not the same as the number of unique groups"
assert exception_context.value.args[0] == expected
def test_length_mismatch_groups(self):
target = GroupMetricSet()
target.y_true = [0, 1, 0, 1]
target.y_pred = [0, 1, 1, 0]
target.groups = [0, 1, 1]
with pytest.raises(ValueError) as exception_context:
target.check_consistency()
assert exception_context.value.args[
0] == "Lengths of y_true, y_pred and groups must match"
def test_metric_has_bad_groups(self):
target = GroupMetricSet()
target.y_true = [0, 1, 1, 1, 0]
target.y_pred = [1, 1, 1, 0, 0]
target.groups = [0, 1, 0, 1, 1]
bad_metric = GroupMetricResult()
bad_metric.by_group[0] = 0.1
metric_dict = {'bad_metric': bad_metric}
target.metrics = metric_dict
with pytest.raises(ValueError) as exception_context:
target.check_consistency()
expected = "The groups for metric bad_metric do not match the groups property"
assert exception_context.value.args[0] == expected