def test_featurize_time_series_default_errors():
    n_channels = 3
    t, m, _ = sample_time_series(channels=n_channels)
    features_to_use = ['amplitude', 'std_err']
    target = 'class1'
    meta_features = {}
    fset = featurize.featurize_time_series(t, m, None, features_to_use, target,
                                           meta_features, use_celery=False)
    npt.assert_array_equal(fset.channel, np.arange(n_channels))
    t = [[t, t[0:-5], t[0:-10]]]
    m = [[m[0], m[1][0:-5], m[2][0:-10]]]
    fset = featurize.featurize_time_series(t, m, None, features_to_use, target,
                                           meta_features, use_celery=False)
    npt.assert_array_equal(fset.channel, np.arange(n_channels))
    t = t[0][0]
    m = m[0][0]
    fset = featurize.featurize_time_series(t, m, None, features_to_use, target,
                                           meta_features, use_celery=False)
    npt.assert_array_equal(fset.channel, [0])
Applies a given function to a given stash.
dataset/ETHPy150Open cesium-ml/cesium/cesium/tests/test_featurize.py/test_featurize_time_series_default_errors--crossover with--dataset/ETHPy150Open angr/angr/angr/path_group.py/PathGroup.apply