metrics_test.py 文件源码

def testShuffledTwoDimensionalCumulativeDistribution(self):
    df = pd.DataFrame({"X": [1, 1, 1, 2, 2, 3, 4],
                       "Y": [1, 2, 0, 1, 1, 1, 1],
                       "Z": [1, 0, 0, 0, 0, 0, 0]})
    weights = np.array([1, 1, 1, 1, 1, 1, 1])
    metric = metrics.CumulativeDistribution("X", ["Y", "Z"])
    output = metric(df.iloc[np.random.permutation(7)], weights)
    correct = pd.DataFrame(
        np.array([1 / 14., 12 / 14., 13 / 14., 1.]),
        columns=[""],
        index=pd.MultiIndex(levels=[[0, 1, 2], [0, 1]],
                            labels=[[0, 1, 1, 2], [0, 0, 1, 0]],
                            names=["Y", "Z"]))
    self.assertTrue(all(output.index == correct.index) and
                    all(output.columns == correct.columns) and
                    all(abs(output.values - correct.values) < 1e-10))