def test_arithmetic():
a = ImmutableDenseNDimArray([3 for i in range(9)], (3, 3))
b = ImmutableDenseNDimArray([7 for i in range(9)], (3, 3))
c1 = a + b
c2 = b + a
assert c1 == c2
d1 = a - b
d2 = b - a
assert d1 == d2 * (-1)
e1 = a * 5
e2 = 5 * a
e3 = copy(a)
e3 *= 5
assert e1 == e2 == e3
f1 = a / 5
f2 = copy(a)
f2 /= 5
assert f1 == f2
assert f1[0, 0] == f1[0, 1] == f1[0, 2] == f1[1, 0] == f1[1, 1] == \
f1[1, 2] == f1[2, 0] == f1[2, 1] == f1[2, 2] == Rational(3, 5)
assert type(a) == type(b) == type(c1) == type(c2) == type(d1) == type(d2) \
== type(e1) == type(e2) == type(e3) == type(f1)
def test_symbolic_indexing():
M = ImmutableDenseNDimArray([[x, y], [z, w]])
Mij = M[i, j]
assert isinstance(Mij, Indexed)
Ms = ImmutableSparseNDimArray([[2, 3 * x], [4, 5]])
msij = Ms[i, j]
assert isinstance(msij, Indexed)
for oi, oj in [(0, 0), (0, 1), (1, 0), (1, 1)]:
assert Mij.subs({i: oi, j: oj}) == M[oi, oj]
assert msij.subs({i: oi, j: oj}) == Ms[oi, oj]
A = IndexedBase("A", (0, 2))
assert A[0, 0].subs({A: M}) == x
assert A[i, j].subs({A: M}) == M[i, j]
assert M[i, j].subs({M: A}) == A[i, j]
assert isinstance(M[3 * i - 2, j], Indexed)
assert M[3 * i - 2, j].subs({i: 1, j: 0}) == M[1, 0]
assert isinstance(M[i, 0], Indexed)
assert M[i, 0].subs({i: 0}) == M[0, 0]
assert M[0, i].subs({i: 1}) == M[0, 1]
Mo = ImmutableDenseNDimArray([1, 2, 3])
assert Mo[i].subs({i: 1}) == 2
Mos = ImmutableSparseNDimArray([1, 2, 3])
assert Mos[i].subs({i: 1}) == 2
pytest.raises(ValueError, lambda: M[i, 2])
pytest.raises(ValueError, lambda: M[i, -1])
pytest.raises(ValueError, lambda: M[2, i])
pytest.raises(ValueError, lambda: M[-1, i])
pytest.raises(ValueError, lambda: Ms[i, 2])
pytest.raises(ValueError, lambda: Ms[i, -1])
pytest.raises(ValueError, lambda: Ms[2, i])
pytest.raises(ValueError, lambda: Ms[-1, i])
def test_op_priority():
md = ImmutableDenseNDimArray([1, 2, 3])
e1 = (1 + x) * md
e2 = md * (1 + x)
assert e1 == ImmutableDenseNDimArray([1 + x, 2 + 2 * x, 3 + 3 * x])
assert e1 == e2
e3 = (1 + x) * md
e4 = md * (1 + x)
assert e3 == ImmutableDenseNDimArray([1 + x, 2 + 2 * x, 3 + 3 * x])
assert e3 == e4
def test_iterator():
array = ImmutableDenseNDimArray(range(4), (2, 2))
j = 0
for i in array:
assert i == j
j += 1
array = array.reshape(4)
j = 0
for i in array:
assert i == j
j += 1
def test_higher_dimenions():
m3 = ImmutableDenseNDimArray(range(10, 34), (2, 3, 4))
assert m3.tolist() == [[[10, 11, 12, 13], [14, 15, 16, 17],
[18, 19, 20, 21]],
[[22, 23, 24, 25], [26, 27, 28, 29],
[30, 31, 32, 33]]]
assert m3._get_tuple_index(0) == (0, 0, 0)
assert m3._get_tuple_index(1) == (0, 0, 1)
assert m3._get_tuple_index(4) == (0, 1, 0)
assert m3._get_tuple_index(12) == (1, 0, 0)
assert str(
m3
) == '[[[10, 11, 12, 13], [14, 15, 16, 17], [18, 19, 20, 21]], [[22, 23, 24, 25], [26, 27, 28, 29], [30, 31, 32, 33]]]'
m3_rebuilt = ImmutableDenseNDimArray([[[10, 11, 12, 13], [14, 15, 16, 17],
[18, 19, 20, 21]],
[[22, 23, 24, 25], [26, 27, 28, 29],
[30, 31, 32, 33]]])
assert m3 == m3_rebuilt
m3_other = ImmutableDenseNDimArray(
[[[10, 11, 12, 13], [14, 15, 16, 17], [18, 19, 20, 21]],
[[22, 23, 24, 25], [26, 27, 28, 29], [30, 31, 32, 33]]], (2, 3, 4))
assert m3 == m3_other
def test_calculation():
a = ImmutableDenseNDimArray([1] * 9, (3, 3))
b = ImmutableDenseNDimArray([9] * 9, (3, 3))
c = a + b
for i in c:
assert i == 10
assert c == ImmutableDenseNDimArray([10] * 9, (3, 3))
assert c == ImmutableSparseNDimArray([10] * 9, (3, 3))
c = b - a
for i in c:
assert i == 8
assert c == ImmutableDenseNDimArray([8] * 9, (3, 3))
assert c == ImmutableSparseNDimArray([8] * 9, (3, 3))
def test_equality():
first_list = [1, 2, 3, 4]
second_list = [1, 2, 3, 4]
third_list = [4, 3, 2, 1]
assert first_list == second_list
assert first_list != third_list
first_ndim_array = ImmutableDenseNDimArray(first_list, (2, 2))
second_ndim_array = ImmutableDenseNDimArray(second_list, (2, 2))
fourth_ndim_array = ImmutableDenseNDimArray(first_list, (2, 2))
assert first_ndim_array == second_ndim_array
def assignment_attempt(a):
a[0, 0] = 0
pytest.raises(TypeError, lambda: assignment_attempt(second_ndim_array))
assert first_ndim_array == second_ndim_array
assert first_ndim_array == fourth_ndim_array
assert hash(first_ndim_array) == hash(second_ndim_array)
def test_reshape():
array = ImmutableDenseNDimArray(range(50), 50)
assert array.shape == (50, )
assert array.rank() == 1
array = array.reshape(5, 5, 2)
assert array.shape == (5, 5, 2)
assert array.rank() == 3
assert len(array) == 50
pytest.raises(ValueError, lambda: array.reshape(1, 1))
def test_converting_functions():
arr_list = [1, 2, 3, 4]
arr_matrix = Matrix(((1, 2), (3, 4)))
# list
arr_ndim_array = ImmutableDenseNDimArray(arr_list, (2, 2))
assert isinstance(arr_ndim_array, ImmutableDenseNDimArray)
assert arr_matrix.tolist() == arr_ndim_array.tolist()
# Matrix
arr_ndim_array = ImmutableDenseNDimArray(arr_matrix)
assert isinstance(arr_ndim_array, ImmutableDenseNDimArray)
assert arr_matrix.tolist() == arr_ndim_array.tolist()
assert arr_matrix.shape == arr_ndim_array.shape
def test_slices():
md = ImmutableDenseNDimArray(range(10, 34), (2, 3, 4))
assert md[:] == md._array
assert md[:, :, 0].tomatrix() == Matrix([[10, 14, 18], [22, 26, 30]])
assert md[0, 1:2, :].tomatrix() == Matrix([[14, 15, 16, 17]])
assert md[0, 1:3, :].tomatrix() == Matrix([[14, 15, 16, 17],
[18, 19, 20, 21]])
assert md[:, :, :] == md
sd = ImmutableSparseNDimArray(range(10, 34), (2, 3, 4))
assert sd == ImmutableSparseNDimArray(md)
assert sd[:] == md._array
assert sd[:] == list(sd)
assert sd[:, :, 0].tomatrix() == Matrix([[10, 14, 18], [22, 26, 30]])
assert sd[0, 1:2, :].tomatrix() == Matrix([[14, 15, 16, 17]])
assert sd[0, 1:3, :].tomatrix() == Matrix([[14, 15, 16, 17],
[18, 19, 20, 21]])
assert sd[:, :, :] == sd
def test_diff_and_applyfunc():
md = ImmutableDenseNDimArray([[x, y], [x * z, x * y * z]])
assert md.diff(x) == ImmutableDenseNDimArray([[1, 0], [z, y * z]])
sd = ImmutableSparseNDimArray(md)
assert sd == ImmutableSparseNDimArray([x, y, x * z, x * y * z], (2, 2))
assert sd.diff(x) == ImmutableSparseNDimArray([[1, 0], [z, y * z]])
mdn = md.applyfunc(lambda x: x * 3)
assert mdn == ImmutableDenseNDimArray([[3 * x, 3 * y],
[3 * x * z, 3 * x * y * z]])
assert md != mdn
sdn = sd.applyfunc(lambda x: x / 2)
assert sdn == ImmutableSparseNDimArray([[x / 2, y / 2],
[x * z / 2, x * y * z / 2]])
assert sd != sdn
def test_ndim_array_converting():
dense_array = ImmutableDenseNDimArray([1, 2, 3, 4], (2, 2))
alist = dense_array.tolist()
alist == [[1, 2], [3, 4]]
matrix = dense_array.tomatrix()
assert isinstance(matrix, Matrix)
for i in range(len(dense_array)):
assert dense_array[i] == matrix[i]
assert matrix.shape == dense_array.shape
assert ImmutableDenseNDimArray(matrix) == dense_array
assert ImmutableDenseNDimArray(matrix.as_immutable()) == dense_array
assert ImmutableDenseNDimArray(matrix.as_mutable()) == dense_array
sparse_array = ImmutableSparseNDimArray([1, 2, 3, 4], (2, 2))
alist = sparse_array.tolist()
assert alist == [[1, 2], [3, 4]]
matrix = sparse_array.tomatrix()
assert isinstance(matrix, SparseMatrix)
pytest.raises(
ValueError, lambda: ImmutableDenseNDimArray([1] * 6,
(2, 2, 2)).tomatrix())
for i in range(len(sparse_array)):
assert sparse_array[i] == matrix[i]
assert matrix.shape == sparse_array.shape
assert ImmutableSparseNDimArray(matrix) == sparse_array
assert ImmutableSparseNDimArray(matrix.as_immutable()) == sparse_array
assert ImmutableSparseNDimArray(matrix.as_mutable()) == sparse_array
def test_rebuild_immutable_arrays():
sparr = ImmutableSparseNDimArray(range(10, 34), (2, 3, 4))
densarr = ImmutableDenseNDimArray(range(10, 34), (2, 3, 4))
assert sparr == sparr.func(*sparr.args)
assert densarr == densarr.func(*densarr.args)
def test_ndim_array_initiation():
arr_with_one_element = ImmutableDenseNDimArray([23])
assert len(arr_with_one_element) == 1
assert arr_with_one_element[0] == 23
assert arr_with_one_element[:] == [23]
assert arr_with_one_element.rank() == 1
arr_with_symbol_element = ImmutableDenseNDimArray([Symbol('x')])
assert len(arr_with_symbol_element) == 1
assert arr_with_symbol_element[0] == Symbol('x')
assert arr_with_symbol_element[:] == [Symbol('x')]
assert arr_with_symbol_element.rank() == 1
number5 = 5
vector = ImmutableDenseNDimArray.zeros(number5)
assert len(vector) == number5
assert vector.shape == (number5, )
assert vector.rank() == 1
vector = ImmutableSparseNDimArray.zeros(number5)
assert len(vector) == number5
assert vector.shape == (number5, )
assert vector._sparse_array == Dict()
assert vector.rank() == 1
n_dim_array = ImmutableDenseNDimArray(range(3**4), (
3,
3,
3,
3,
))
assert len(n_dim_array) == 3 * 3 * 3 * 3
assert n_dim_array.shape == (3, 3, 3, 3)
assert n_dim_array.rank() == 4
array_shape = (3, 3, 3, 3)
sparse_array = ImmutableSparseNDimArray.zeros(*array_shape)
assert len(sparse_array._sparse_array) == 0
assert len(sparse_array) == 3 * 3 * 3 * 3
assert n_dim_array.shape == array_shape
assert n_dim_array.rank() == 4
one_dim_array = ImmutableDenseNDimArray([2, 3, 1])
assert len(one_dim_array) == 3
assert one_dim_array.shape == (3, )
assert one_dim_array.rank() == 1
assert one_dim_array.tolist() == [2, 3, 1]
shape = (3, 3)
array_with_many_args = ImmutableSparseNDimArray.zeros(*shape)
assert len(array_with_many_args) == 3 * 3
assert array_with_many_args.shape == shape
assert array_with_many_args[0, 0] == 0
assert array_with_many_args.rank() == 2
def test_H2():
TP = diofant.diffgeom.TensorProduct
R2 = diofant.diffgeom.rn.R2
y = R2.y
dy = R2.dy
dx = R2.dx
g = (TP(dx, dx) + TP(dy, dy)) * y**(-2)
automat = twoform_to_matrix(g)
mat = diag(y**(-2), y**(-2))
assert mat == automat
gamma1 = metric_to_Christoffel_1st(g)
assert gamma1[0, 0, 0] == 0
assert gamma1[0, 0, 1] == -y**(-3)
assert gamma1[0, 1, 0] == -y**(-3)
assert gamma1[0, 1, 1] == 0
assert gamma1[1, 1, 1] == -y**(-3)
assert gamma1[1, 1, 0] == 0
assert gamma1[1, 0, 1] == 0
assert gamma1[1, 0, 0] == y**(-3)
gamma2 = metric_to_Christoffel_2nd(g)
assert gamma2[0, 0, 0] == 0
assert gamma2[0, 0, 1] == -y**(-1)
assert gamma2[0, 1, 0] == -y**(-1)
assert gamma2[0, 1, 1] == 0
assert gamma2[1, 1, 1] == -y**(-1)
assert gamma2[1, 1, 0] == 0
assert gamma2[1, 0, 1] == 0
assert gamma2[1, 0, 0] == y**(-1)
Rm = metric_to_Riemann_components(g)
assert Rm[0, 0, 0, 0] == 0
assert Rm[0, 0, 0, 1] == 0
assert Rm[0, 0, 1, 0] == 0
assert Rm[0, 0, 1, 1] == 0
assert Rm[0, 1, 0, 0] == 0
assert Rm[0, 1, 0, 1] == -y**(-2)
assert Rm[0, 1, 1, 0] == y**(-2)
assert Rm[0, 1, 1, 1] == 0
assert Rm[1, 0, 0, 0] == 0
assert Rm[1, 0, 0, 1] == y**(-2)
assert Rm[1, 0, 1, 0] == -y**(-2)
assert Rm[1, 0, 1, 1] == 0
assert Rm[1, 1, 0, 0] == 0
assert Rm[1, 1, 0, 1] == 0
assert Rm[1, 1, 1, 0] == 0
assert Rm[1, 1, 1, 1] == 0
Ric = metric_to_Ricci_components(g)
assert Ric[0, 0] == -y**(-2)
assert Ric[0, 1] == 0
assert Ric[1, 0] == 0
assert Ric[0, 0] == -y**(-2)
assert Ric == ImmutableDenseNDimArray([-y**(-2), 0, 0, -y**(-2)], (2, 2))
# scalar curvature is -2
# TODO - it would be nice to have index contraction built-in
R = (Ric[0, 0] + Ric[1, 1]) * y**2
assert R == -2
# Gauss curvature is -1
assert R / 2 == -1