test_dc_stat_think.py 文件源码

def test_bootstrap_replicate_1d(data, seed):
    np.random.seed(seed)
    x = dcst.bootstrap_replicate_1d(data, np.mean)
    np.random.seed(seed)
    x_correct = original.bootstrap_replicate_1d(data[~np.isnan(data)], np.mean)
    assert (np.isnan(x) and np.isnan(x_correct, atol=atol, equal_nan=True)) \
                or np.isclose(x, x_correct, atol=atol, equal_nan=True)

    np.random.seed(seed)
    x = dcst.bootstrap_replicate_1d(data, np.median)
    np.random.seed(seed)
    x_correct = original.bootstrap_replicate_1d(data[~np.isnan(data)], np.median)
    assert (np.isnan(x) and np.isnan(x_correct, atol=atol, equal_nan=True)) \
                or np.isclose(x, x_correct, atol=atol, equal_nan=True)

    np.random.seed(seed)
    x = dcst.bootstrap_replicate_1d(data, np.std)
    np.random.seed(seed)
    x_correct = original.bootstrap_replicate_1d(data[~np.isnan(data)], np.std)
    assert (np.isnan(x) and np.isnan(x_correct, atol=atol, equal_nan=True)) \
                or np.isclose(x, x_correct, atol=atol, equal_nan=True)