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|
| import numpy as np |
| import pytest |
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|
| import fairlearn.metrics as metrics |
| from test.unit.input_convertors import conversions_for_1d |
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|
| def mock_func(y_true, y_pred): |
| return np.sum(y_true) |
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| def mock_func_weight(y_true, y_pred, sample_weight): |
| return np.sum(np.multiply(y_true, sample_weight)) |
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|
|
| def mock_func_matrix_return(y_true, y_pred): |
| return np.ones([len(y_true), sum(y_pred)]) |
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|
|
| class TestMetricByGroup: |
| @pytest.mark.parametrize("transform_gid", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_p", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_a", conversions_for_1d) |
| 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) |
|
|
| @pytest.mark.parametrize("transform_gid", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_p", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_a", conversions_for_1d) |
| 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) |
|
|
| @pytest.mark.parametrize("transform_gid", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_p", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_a", conversions_for_1d) |
| 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_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) |
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|
| |
| 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 |
|
|
| @pytest.mark.parametrize("transform_s_w", conversions_for_1d) |
| @pytest.mark.parametrize("transform_gid", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_p", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_a", conversions_for_1d) |
| 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) |
|
|
| @pytest.mark.parametrize("transform_y_p", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_a", conversions_for_1d) |
| def test_true_predict_length_mismatch(self, transform_y_a, transform_y_p): |
| 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]) |
| gid = [0, 0, 0, 0, 1, 1, 2, 2] |
| s_w = [1, 1, 1, 1, 2, 2, 3, 3] |
|
|
| with pytest.raises(ValueError) as exception_context: |
| _ = metrics.metric_by_group(mock_func_weight, y_a, y_p, gid, s_w) |
|
|
| expected = "Array y_pred is not the same size as y_true" |
| assert exception_context.value.args[0] == expected |
|
|
| @pytest.mark.parametrize("transform_gid", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_a", conversions_for_1d) |
| def test_true_group_length_mismatch(self, transform_y_a, transform_gid): |
| y_a = transform_y_a([0, 0, 1, 1, 0, 1, 1, 1]) |
| y_p = [0, 1, 1, 1, 1, 0, 0, 0] |
| gid = transform_gid([0, 0, 0, 0, 1, 1, 2]) |
| s_w = [1, 1, 1, 1, 2, 2, 3, 3] |
|
|
| with pytest.raises(ValueError) as exception_context: |
| _ = metrics.metric_by_group(mock_func_weight, y_a, y_p, gid, s_w) |
|
|
| expected = "Array group_membership is not the same size as y_true" |
| assert exception_context.value.args[0] == expected |
|
|
| @pytest.mark.parametrize("transform_s_w", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_a", conversions_for_1d) |
| 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_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): |
| |
| 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 |
| |
| 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_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 |
|
|
|
|
| class TestMakeGroupMetric: |
| def test_smoke(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, 1, 1, 1, 1] |
|
|
| grouped_metric_func = metrics.make_group_metric(mock_func) |
| result = grouped_metric_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.maximum == 3 |
| assert result.argmin_set == {0} |
| assert result.argmax_set == {1} |
| assert result.range == 1 |
| assert result.range_ratio == pytest.approx(0.66666666667) |
|
|
| @pytest.mark.parametrize("transform_s_w", conversions_for_1d) |
| @pytest.mark.parametrize("transform_gid", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_p", conversions_for_1d) |
| @pytest.mark.parametrize("transform_y_a", conversions_for_1d) |
| def test_keys_and_weights(self, transform_y_a, transform_y_p, transform_gid, transform_s_w): |
| a = "ABC" |
| b = "DEF" |
| c = "GHI" |
| z = "something_longer" |
| y_a = transform_y_a([0, 1, 1, 1, 0, 1, 1, 1]) |
| y_p = transform_y_p([0, 1, 1, 1, 1, 0, 0, 1]) |
| gid = transform_gid([a, z, a, b, b, c, c, c]) |
| s_w = transform_s_w([1, 1, 1, 5, 5, 7, 7, 7]) |
|
|
| grouped_metric_func = metrics.make_group_metric(mock_func_weight) |
| result = grouped_metric_func(y_a, y_p, gid, s_w) |
| assert result.overall == 28 |
| assert len(result.by_group) == 4 |
| assert result.by_group[a] == 1 |
| assert result.by_group[b] == 5 |
| assert result.by_group[c] == 21 |
| assert result.by_group[z] == 1 |
| assert result.minimum == 1 |
| assert result.maximum == 21 |
| assert result.argmin_set == {a, z} |
| assert result.argmax_set == {c} |
| assert result.range == 20 |
| assert result.range_ratio == pytest.approx(1.0/21.0) |
|
|
