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 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)