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 test_fresnel_coefficients():
    assert all(ae(i, j, 5) for i, j in zip(
        fresnel_coefficients(0.5, 1, 1.33),
        [0.11163, -0.17138, 0.83581, 0.82862]))
    assert all(ae(i, j, 5) for i, j in zip(
        fresnel_coefficients(0.5, 1.33, 1),
        [-0.07726, 0.20482, 1.22724, 1.20482]))
    m1 = Medium('m1')
    m2 = Medium('m2', n=2)
    assert all(ae(i, j, 5) for i, j in zip(
        fresnel_coefficients(0.3, m1, m2),
        [0.31784, -0.34865, 0.65892, 0.65135]))
    ans = [[-0.23563, -0.97184], [0.81648, -0.57738]]
    got = fresnel_coefficients(0.6, m2, m1)
    for i, j in zip(got, ans):
        for a, b in zip(i.as_real_imag(), j):
            assert ae(a, b, 5)