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 mtpa(pmrel, i1max, title='', projection='', ax=0):
    """create a line or surface plot with torque and mtpa curve"""
    nsamples = 10
    i1 = np.linspace(0, i1max, nsamples)
    iopt = np.array([pmrel.mtpa(x) for x in i1]).T

    iqmax, idmax = pmrel.iqdmax(i1max)
    iqmin, idmin = pmrel.iqdmin(i1max)

    if projection == '3d':
        nsamples = 50
    else:
        if iqmin == 0:
            iqmin = 0.1*iqmax
    id = np.linspace(idmin, idmax, nsamples)
    iq = np.linspace(iqmin, iqmax, nsamples)

    torque_iqd = np.array(
        [[pmrel.torque_iqd(x, y)
          for y in id] for x in iq])
    if projection == '3d':
        ax = idq_torque(id, iq, torque_iqd, ax)
        ax.plot(iopt[1], iopt[0], iopt[2],
                color='red', linewidth=2, label='MTPA: {0:5.0f} Nm'.format(
                    np.max(iopt[2][-1])))
    else:
        if ax == 0:
            ax = plt.gca()

        ax.set_aspect('equal')
        x, y = np.meshgrid(id, iq)
        CS = ax.contour(x, y, torque_iqd, 6, colors='k')
        ax.clabel(CS, fmt='%d', inline=1)

        ax.set_xlabel('Id/A')
        ax.set_ylabel('Iq/A')
        ax.plot(iopt[1], iopt[0],
                color='red', linewidth=2, label='MTPA: {0:5.0f} Nm'.format(
                    np.max(iopt[2][-1])))
        ax.grid()

    if title:
        ax.set_title(title)
    ax.legend()