test_filter_windows.py 文件源码

def test_get_measurements_std():
    dt_means, dt_stds, dlna_means, dlna_stds = \
        fw.get_measurements_std({})
    assert len(dt_means) == 0
    assert len(dt_stds) == 0
    assert len(dlna_means) == 0
    assert len(dlna_stds) == 0

    dt_means, dt_stds, dlna_means, dlna_stds = \
        fw.get_measurements_std(measures)

    # from tests/data/window/measurements.fake.json
    _true_dt_mean = \
        {"R": np.mean([1, -1, 1, 1, -2]),
         "T": np.mean([1, 1.5, -2.5]),
         "Z": np.mean([1, 2, -1.5, 2, -5, -0.2, 0.8, -1.6, 1.6, 0.9])}
    _true_dt_stds = \
        {"R": np.std([1, -1, 1, 1, -2]),
         "T": np.std([1, 1.5, -2.5]),
         "Z": np.std([1, 2, -1.5, 2, -5, -0.2, 0.8, -1.6, 1.6, 0.9])}

    _true_dlna_mean = \
        {"R": np.mean([0.7, -0.7, 0.6, 1.0, -0.8]),
         "T": np.mean([0.9, 0.3, -0.7]),
         "Z": np.mean([0.6, 0.4, -0.5, 1.2, -1.5, -0.2, 0.8, -0.6, 1.1, 0.9])}
    _true_dlna_stds = \
        {"R": np.std([0.7, -0.7, 0.6, 1.0, -0.8]),
         "T": np.std([0.9, 0.3, -0.7]),
         "Z": np.std([0.6, 0.4, -0.5, 1.2, -1.5, -0.2, 0.8, -0.6, 1.1, 0.9])}

    for comp in dt_means:
        npt.assert_array_almost_equal(dt_means[comp], _true_dt_mean[comp])
        npt.assert_array_almost_equal(dt_stds[comp], _true_dt_stds[comp])
        npt.assert_array_almost_equal(dlna_means[comp], _true_dlna_mean[comp])
        npt.assert_array_almost_equal(dlna_stds[comp], _true_dlna_stds[comp])