Example #1
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def test_metric_list():
    assert recall(l_true, l_pred) == 4 / 6
    assert isnan(recall(l0, l_pred))
    assert precision(l_true, l_pred) == 4 / 7
    assert recall(l_true, l_pred, thresh=1) == 3 / 6
    assert precision(l_true, l_pred, thresh=1) == 3 / 7
    assert iou(l_true, l_pred) == 3 / 13
    assert isnan(iou(l0, l0))
Example #2
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def test_metric_series():
    assert recall(s_true, s_pred) == 9 / 12
    assert isnan(recall(s0, s_pred))
    assert precision(s_true, s_pred) == 9 / 15
    assert f1_score(s_true, s_pred) == pytest.approx(2 / 3)
    assert isnan(f1_score(s0, s_pred))
    assert isnan(f1_score(1 - s_pred, s_pred))
    assert iou(s_true, s_pred) == 9 / 17
    assert iou(s_pred, s_true) == 9 / 17
    assert isnan(iou(s0, s0))
Example #3
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def test_metric_dict():
    assert recall(d_true, d_pred) == {"A": 4 / 6, "B": 4 / 7}
    assert all([isnan(x) for x in recall(d0, d_pred).values()]) and (recall(
        d0, d_pred).keys() == {
            "A": n,
            "B": n
        }.keys())
    assert precision(d_true, d_pred) == {"A": 4 / 7, "B": 4 / 6}
    assert f1_score(d_true, d_pred) == {
        "A": pytest.approx(2 * 4 / 7 * 4 / 6 / (4 / 7 + 4 / 6)),
        "B": pytest.approx(2 * 4 / 7 * 4 / 6 / (4 / 7 + 4 / 6)),
    }
    assert recall(d_true, d_pred, thresh=1) == {"A": 3 / 6, "B": 3 / 7}
    assert precision(d_true, d_pred, thresh=1) == {"A": 3 / 7, "B": 3 / 6}
    assert iou(d_true, d_pred) == {"A": 3 / 13, "B": 3 / 13}
Example #4
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def test_metric_dataframe():
    assert recall(df_true, df_pred) == {"A": 9 / 12, "B": 9 / 15}
    assert all([isnan(x) for x in recall(df0, df_pred).values()]) and (recall(
        df0, df_pred).keys() == {
            "A": n,
            "B": n
        }.keys())
    assert precision(df_true, df_pred) == {"A": 9 / 15, "B": 9 / 12}
    assert f1_score(df_true, df_pred) == {
        "A": pytest.approx(2 / 3),
        "B": pytest.approx(2 / 3),
    }
    assert all([isnan(x) for x in f1_score(df0, df_pred).values()
                ]) and (f1_score(df0, df_pred).keys() == {
                    "A": n,
                    "B": n
                }.keys())
    assert iou(df_true, df_pred) == {"A": 9 / 17, "B": 9 / 17}
    assert all([isnan(x) for x in iou(df0, df0).values()]) and (iou(
        df0, df0).keys() == {
            "A": n,
            "B": n
        }.keys())
Example #5
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def test_metric_dict():
    assert recall(d_true, d_pred) == {"A": 4 / 6, "B": 4 / 7}
    assert precision(d_true, d_pred) == {"A": 4 / 7, "B": 4 / 6}
    assert recall(d_true, d_pred, thresh=1) == {"A": 3 / 6, "B": 3 / 7}
    assert precision(d_true, d_pred, thresh=1) == {"A": 3 / 7, "B": 3 / 6}
Example #6
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def test_metric_dataframe():
    assert recall(df_true, df_pred) == {"A": 9 / 12, "B": 9 / 15}
    assert precision(df_true, df_pred) == {"A": 9 / 15, "B": 9 / 12}
    assert iou(df_true, df_pred) == {"A": 9 / 17, "B": 9 / 17}
Example #7
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def test_metric_series():
    assert recall(s_true, s_pred) == 9 / 12
    assert precision(s_true, s_pred) == 9 / 15
    assert iou(s_true, s_pred) == 9 / 17
    assert iou(s_pred, s_true) == 9 / 17