def test_view_of_view(matrix_type, subset_func, subset_func2):
    adata = gen_adata((30, 15), X_type=matrix_type)
    adata.raw = adata
    if subset_func is single_subset:
        pytest.xfail("Other subset generating functions have trouble with this")
    var_s1 = subset_func(adata.var_names, min_size=4)
    var_view1 = adata[:, var_s1]
    var_s2 = subset_func2(var_view1.var_names)
    var_view2 = var_view1[:, var_s2]
    assert var_view2._adata_ref is adata
    obs_s1 = subset_func(adata.obs_names, min_size=4)
    obs_view1 = adata[obs_s1, :]
    obs_s2 = subset_func2(obs_view1.obs_names)
    assert adata[obs_s1, :][:, var_s1][obs_s2, :]._adata_ref is adata

    view_of_actual_copy = adata[:, var_s1].copy()[obs_s1, :].copy()[:, var_s2].copy()

    view_of_view_copy = adata[:, var_s1][obs_s1, :][:, var_s2].copy()

    assert_equal(view_of_actual_copy, view_of_view_copy, exact=True)
def _read_soundings(sounding_file_name, sounding_field_names, radar_image_dict):
    """Reads storm-centered soundings and matches w storm-centered radar imgs.

    :param sounding_file_name: Path to input file (will be read by
        `soundings.read_soundings`).
    :param sounding_field_names: See doc for `soundings.read_soundings`.
    :param radar_image_dict: Dictionary created by
        `storm_images.read_storm_images`.
    :return: sounding_dict: Dictionary created by `soundings.read_soundings`.
    :return: radar_image_dict: Same as input, but excluding storm objects with
        no sounding.
    """

    print('Reading data from: "{0:s}"...'.format(sounding_file_name))
    sounding_dict, _ = soundings.read_soundings(
        netcdf_file_name=sounding_file_name,
        field_names_to_keep=sounding_field_names,
        full_id_strings_to_keep=radar_image_dict[storm_images.FULL_IDS_KEY],
        init_times_to_keep_unix_sec=radar_image_dict[
            storm_images.VALID_TIMES_KEY]
    )

    num_examples_with_soundings = len(sounding_dict[soundings.FULL_IDS_KEY])
    if num_examples_with_soundings == 0:
        return None, None

    radar_full_id_strings = numpy.array(
        radar_image_dict[storm_images.FULL_IDS_KEY]
    )
    orig_storm_times_unix_sec = (
        radar_image_dict[storm_images.VALID_TIMES_KEY] + 0
    )

    indices_to_keep = []

    for i in range(num_examples_with_soundings):
        this_index = numpy.where(numpy.logical_and(
            radar_full_id_strings == sounding_dict[soundings.FULL_IDS_KEY][i],
            orig_storm_times_unix_sec ==
            sounding_dict[soundings.INITIAL_TIMES_KEY][i]
        ))[0][0]

        indices_to_keep.append(this_index)

    indices_to_keep = numpy.array(indices_to_keep, dtype=int)
    radar_image_dict[storm_images.STORM_IMAGE_MATRIX_KEY] = radar_image_dict[
        storm_images.STORM_IMAGE_MATRIX_KEY
    ][indices_to_keep, ...]

    radar_image_dict[storm_images.FULL_IDS_KEY] = sounding_dict[
        soundings.FULL_IDS_KEY
    ]
    radar_image_dict[storm_images.VALID_TIMES_KEY] = sounding_dict[
        soundings.INITIAL_TIMES_KEY
    ]

    return sounding_dict, radar_image_dict