def test_view_mixin_copies_data(adata, array_type: type, attr):
    N = 100
    adata = ad.AnnData(
        obs=pd.DataFrame(index=np.arange(N)), var=pd.DataFrame(index=np.arange(N))
    )

    X = array_type(sparse.eye(N, N).multiply(np.arange(1, N + 1)))
    if attr == "X":
        adata.X = X
    else:
        getattr(adata, attr)["arr"] = X

    view = adata[:50]

    if attr == "X":
        arr_view = view.X
    else:
        arr_view = getattr(view, attr)["arr"]

    arr_view_copy = arr_view.copy()

    if sparse.issparse(X):
        assert not np.shares_memory(arr_view.indices, arr_view_copy.indices)
        assert not np.shares_memory(arr_view.indptr, arr_view_copy.indptr)
        assert not np.shares_memory(arr_view.data, arr_view_copy.data)

        arr_view_copy.data[0] = -5
        assert not np.array_equal(arr_view_copy.data, arr_view.data)
    else:
        assert not np.shares_memory(arr_view, arr_view_copy)

        arr_view_copy[0, 0] = -5
        assert not np.array_equal(arr_view_copy, arr_view)
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()