def test_set_varm(adata):
    init_hash = joblib.hash(adata)

    dim0_size = np.random.randint(2, adata.shape[1] - 1)
    dim1_size = np.random.randint(1, 99)
    orig_varm_val = adata.varm["o"].copy()
    subset_idx = np.random.choice(adata.var_names, dim0_size, replace=False)

    subset = adata[:, subset_idx]
    assert subset.is_view
    subset.varm = dict(o=np.ones((dim0_size, dim1_size)))
    assert not subset.is_view
    assert np.all(orig_varm_val == adata.varm["o"])  # Checking for mutation
    assert np.all(subset.varm["o"] == np.ones((dim0_size, dim1_size)))

    subset = adata[:, subset_idx]
    subset_hash = joblib.hash(subset)
    with pytest.raises(ValueError):
        subset.varm = dict(o=np.ones((dim0_size + 1, dim1_size)))
    with pytest.raises(ValueError):
        subset.varm = dict(o=np.ones((dim0_size - 1, dim1_size)))
    # subset should not be changed by failed setting
    assert subset_hash == joblib.hash(subset)
    assert init_hash == joblib.hash(adata)
def airgap_fft(airgap, bmin=1e-2, ax=0):
    """plot airgap harmonics"""
    unit = 'T'
    if ax == 0:
        ax = plt.gca()
    ax.set_title('Airgap Flux Density Harmonics / {}'.format(unit))
    ax.grid(True)
    order, fluxdens = np.array([(n, b) for n, b in zip(airgap['nue'],
                                                       airgap['B_nue']) if b > bmin]).T
    try:
        markerline1, stemlines1, _ = ax.stem(order, fluxdens, '-.', basefmt=" ",
                                             use_line_collection=True)
        ax.set_xticks(order)
    except ValueError:  # empty sequence
        pass