def test_view_of_view_modification():
    adata = ad.AnnData(np.zeros((10, 10)))
    adata[0, :][:, 5:].X = np.ones(5)
    assert np.all(adata.X[0, 5:] == np.ones(5))
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2))
    assert np.all(adata.X[1:3, 1:3] == np.ones((2, 2)))

    adata.X = sparse.csr_matrix(adata.X)
    adata[0, :][:, 5:].X = np.ones(5) * 2
    assert np.all(asarray(adata.X)[0, 5:] == np.ones(5) * 2)
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2)) * 2
    assert np.all(asarray(adata.X)[1:3, 1:3] == np.ones((2, 2)) * 2)
def test_deviation():
    n1, n2 = symbols('n1, n2')
    r1 = Ray3D(Point3D(-1, -1, 1), Point3D(0, 0, 0))
    n = Matrix([0, 0, 1])
    i = Matrix([-1, -1, -1])
    normal_ray = Ray3D(Point3D(0, 0, 0), Point3D(0, 0, 1))
    P = Plane(Point3D(0, 0, 0), normal_vector=[0, 0, 1])
    assert deviation(r1, 1, 1, normal=n) == 0
    assert deviation(r1, 1, 1, plane=P) == 0
    assert deviation(r1, 1, 1.1, plane=P).evalf(3) + 0.119 < 1e-3
    assert deviation(i, 1, 1.1, normal=normal_ray).evalf(3) + 0.119 < 1e-3
    assert deviation(r1, 1.33, 1, plane=P) is None  # TIR
    assert deviation(r1, 1, 1, normal=[0, 0, 1]) == 0
    assert deviation([-1, -1, -1], 1, 1, normal=[0, 0, 1]) == 0
    assert ae(deviation(0.5, 1, 2), -0.25793, 5)
    assert ae(deviation(0.5, 2, 1), 0.78293, 5)