def test_true_weight_length_mismatch(self, transform_y_a, transform_s_w):
y_a = transform_y_a([0, 0, 1, 1, 0, 1, 1, 1])
y_p = [0, 1, 1, 1, 1, 0, 0, 0]
gid = [0, 0, 0, 0, 1, 1, 2, 3]
s_w = transform_s_w([1, 1, 1, 1, 2, 2, 3])
with pytest.raises(ValueError) as exception_context:
_ = metrics.metric_by_group(mock_func_weight, y_a, y_p, gid, s_w)
expected = "Array sample_weight is not the same size as y_true"
assert exception_context.value.args[0] == expected
def test_matrix_metric(self, transform_y_a, transform_y_p, transform_gid):
a = "ABC"
b = "DEF"
c = "GHI"
y_a = transform_y_a([0, 0, 1, 1, 0, 1, 1, 1])
y_p = transform_y_p([0, 1, 1, 1, 1, 0, 0, 1])
gid = transform_gid([a, a, a, b, b, c, c, c])
result = metrics.metric_by_group(mock_func_matrix_return, y_a, y_p,
gid)
assert np.array_equal(result.overall, np.ones([8, 5]))
assert np.array_equal(result.by_group[a], np.ones([3, 2]))
assert np.array_equal(result.by_group[b], np.ones([2, 2]))
assert np.array_equal(result.by_group[c], np.ones([3, 1]))
def test_groups_only_one_element(self):
y_t = [1, 2]
y_p = [1, 2]
gid = [0, 1]
def sum_lengths(y_true, y_pred):
return len(y_true) + len(y_pred)
result = metrics.metric_by_group(sum_lengths, y_t, y_p, gid)
assert result.overall == 4
assert result.by_group[0] == 2
assert result.by_group[1] == 2
assert result.minimum == 2
assert result.maximum == 2
assert result.range == 0
assert result.range_ratio == 1
def test_smoke(self, transform_y_a, transform_y_p, transform_gid):
y_a = transform_y_a([0, 0, 1, 1, 0, 1, 1, 1])
y_p = transform_y_p([0, 1, 1, 1, 1, 0, 0, 1])
gid = transform_gid([0, 0, 0, 0, 1, 1, 1, 1])
result = metrics.metric_by_group(mock_func, y_a, y_p, gid)
assert result.overall == 5
assert len(result.by_group) == 2
assert result.by_group[0] == 2
assert result.by_group[1] == 3
assert result.minimum == 2
assert result.argmin_set == {0}
assert result.maximum == 3
assert result.argmax_set == {1}
assert result.range == 1
assert result.range_ratio == pytest.approx(0.6666666667)
def test_negative_results(self):
y_a = [0, 0, 1, 1, 0, 1, 1, 1]
y_p = [0, 1, 1, 1, 1, 0, 0, 1]
gid = [0, 0, 0, 0, 0, 1, 1, 1]
def negative_results(y_true, y_pred):
return -(len(y_true) + len(y_pred))
result = metrics.metric_by_group(negative_results, y_a, y_p, gid)
assert result.overall == -16
assert result.by_group[0] == -10
assert result.by_group[1] == -6
assert result.minimum == -10
assert result.maximum == -6
assert result.range == 4
assert np.isnan(result.range_ratio)
def test_metric_results_zero(self):
y_a = [0, 0, 1, 1, 0, 1, 1, 1]
y_p = [0, 1, 1, 1, 1, 0, 0, 1]
gid = [0, 0, 0, 0, 0, 1, 1, 1]
def zero_results(y_true, y_pred):
# Arrays will always be same length
return len(y_true) - len(y_pred)
result = metrics.metric_by_group(zero_results, y_a, y_p, gid)
assert result.overall == 0
assert result.by_group[0] == 0
assert result.by_group[1] == 0
assert result.minimum == 0
assert result.maximum == 0
assert result.range == 0
# Following is special case
assert result.range_ratio == 1
def test_single_element_input(self):
y_t = [0]
y_p = [0]
gid = [0]
s_w = [0]
def sum_lengths(y_true, y_pred, sample_weight):
return len(y_true) + len(y_pred) + len(sample_weight)
result = metrics.metric_by_group(sum_lengths,
y_t,
y_p,
gid,
sample_weight=s_w)
assert result.overall == 3
assert result.by_group[0] == 3
assert result.minimum == 3
assert result.maximum == 3
assert result.range == 0
assert result.range_ratio == 1
def test_string_groups(self, transform_y_a, transform_y_p, transform_gid):
a = "ABC"
b = "DEF"
c = "GHI"
y_a = transform_y_a([0, 0, 1, 1, 0, 1, 1, 1])
y_p = transform_y_p([0, 1, 1, 1, 1, 0, 0, 1])
gid = transform_gid([a, a, a, b, b, c, c, c])
result = metrics.metric_by_group(mock_func, y_a, y_p, gid)
assert result.overall == 5
assert len(result.by_group) == 3
assert result.by_group[a] == 1
assert result.by_group[b] == 1
assert result.by_group[c] == 3
assert result.minimum == 1
assert result.argmin_set == {a, b}
assert result.maximum == 3
assert result.argmax_set == {c}
assert result.range == 2
assert result.range_ratio == pytest.approx(0.33333333333333)
def test_matrix_metric_other_properties(self):
a = "ABC"
b = "DEF"
c = "GHI"
y_a = [0, 0, 1, 1, 0, 1, 1, 1]
y_p = [0, 1, 1, 1, 1, 0, 0, 1]
gid = [a, a, a, b, b, c, c, c]
result = metrics.metric_by_group(mock_func_matrix_return, y_a, y_p,
gid)
# Other fields should fail
with pytest.raises(ValueError):
_ = result.minimum
with pytest.raises(ValueError):
_ = result.maximum
with pytest.raises(ValueError):
_ = result.argmin_set
with pytest.raises(ValueError):
_ = result.argmax_set
with pytest.raises(ValueError):
_ = result.range
with pytest.raises(ValueError):
_ = result.range_ratio
def test_with_weights(self, transform_y_a, transform_y_p, transform_gid,
transform_s_w):
y_a = transform_y_a([0, 0, 1, 1, 0, 1, 1, 1])
y_p = transform_y_p([0, 1, 1, 1, 1, 0, 0, 1])
gid = transform_gid([0, 0, 0, 0, 1, 1, 2, 2])
s_w = transform_s_w([1, 1, 1, 1, 2, 2, 3, 3])
result = metrics.metric_by_group(mock_func_weight,
y_a,
y_p,
gid,
sample_weight=s_w)
assert result.overall == 10
assert len(result.by_group) == 3
assert result.by_group[0] == 2
assert result.by_group[1] == 2
assert result.by_group[2] == 6
assert result.minimum == 2
assert result.argmin_set == {0, 1}
assert result.maximum == 6
assert result.argmax_set == {2}
assert result.range == 4
assert result.range_ratio == pytest.approx(0.33333333333333)
