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 mcv_hbj(mcv, log=True, ax=0):
    """plot H, B, J of mcv dict"""
    import femagtools.mcv
    MUE0 = 4e-7*np.pi
    ji = []

    csiz = len(mcv['curve'])
    if ax == 0:
        ax = plt.gca()
    ax.set_title(mcv['name'])
    for k, c in enumerate(mcv['curve']):
        bh = [(bi, hi*1e-3)
              for bi, hi in zip(c['bi'],
                                c['hi'])]
        try:
            if csiz == 1 and mcv['ctype'] in (femagtools.mcv.MAGCRV,
                                              femagtools.mcv.ORIENT_CRV):
                ji = [b-MUE0*h*1e3 for b, h in bh]
        except Exception:
            pass
        bi, hi = zip(*bh)

        label = 'Flux Density'
        if csiz > 1:
            label = 'Flux Density ({0}°)'.format(mcv.mc1_angle[k])
        if log:
            ax.semilogx(hi, bi, label=label)
            if ji:
                ax.semilogx(hi, ji, label='Polarisation')
        else:
            ax.plot(hi, bi, label=label)
            if ji:
                ax.plot(hi, ji, label='Polarisation')
    ax.set_xlabel('H / kA/m')
    ax.set_ylabel('T')
    if ji or csiz > 1:
        ax.legend(loc='lower right')
    ax.grid()