def test_cse_MatrixExpr():
from sympy import MatrixSymbol
A = MatrixSymbol('A', 3, 3)
y = MatrixSymbol('y', 3, 1)
expr1 = 2 * (A.T * A).I * A * y
expr2 = (A.T * A) * A * y
replacements, reduced_exprs = cse([expr1, expr2])
assert len(replacements) > 0
replacements, reduced_exprs = cse([expr1 + expr2, expr1])
assert replacements
replacements, reduced_exprs = cse([A**2, A + A**2])
assert replacements
def test_matrix_element_sets_slices_blocks():
from sympy.matrices.expressions import BlockMatrix
X = MatrixSymbol("X", 4, 4)
assert ask(Q.integer_elements(X[:, 3]), Q.integer_elements(X))
assert ask(Q.integer_elements(BlockMatrix([[X], [X]])),
Q.integer_elements(X))
def test_transpose():
Sq = MatrixSymbol('Sq', n, n)
assert transpose(A) == Transpose(A)
assert Transpose(A).shape == (m, n)
assert Transpose(A * B).shape == (l, n)
assert transpose(Transpose(A)) == A
assert isinstance(Transpose(Transpose(A)), Transpose)
assert adjoint(Transpose(A)) == Adjoint(Transpose(A))
assert conjugate(Transpose(A)) == Adjoint(A)
assert Transpose(eye(3)).doit() == eye(3)
assert Transpose(S(5)).doit() == S(5)
assert Transpose(Matrix([[1, 2], [3, 4]])).doit() == Matrix([[1, 3],
[2, 4]])
assert transpose(trace(Sq)) == trace(Sq)
assert trace(Transpose(Sq)) == trace(Sq)
assert Transpose(Sq)[0, 1] == Sq[1, 0]
assert Transpose(A * B).doit() == Transpose(B) * Transpose(A)
def test_field_assumptions():
X = MatrixSymbol('X', 4, 4)
Y = MatrixSymbol('Y', 4, 4)
assert ask(Q.real_elements(X), Q.real_elements(X))
assert not ask(Q.integer_elements(X), Q.real_elements(X))
assert ask(Q.complex_elements(X), Q.real_elements(X))
assert ask(Q.real_elements(X + Y), Q.real_elements(X)) is None
assert ask(Q.real_elements(X + Y), Q.real_elements(X) & Q.real_elements(Y))
assert ask(Q.complex_elements(X + Y),
Q.real_elements(X) & Q.complex_elements(Y))
assert ask(Q.real_elements(X.T), Q.real_elements(X))
assert ask(Q.real_elements(X.I), Q.real_elements(X) & Q.invertible(X))
assert ask(Q.real_elements(Trace(X)), Q.real_elements(X))
assert ask(Q.integer_elements(Determinant(X)), Q.integer_elements(X))
assert not ask(Q.integer_elements(X.I), Q.integer_elements(X))
def test_Trace_MatAdd_doit():
# See issue #9028
X = ImmutableMatrix([[1, 2, 3]] * 3)
Y = MatrixSymbol('Y', 3, 3)
q = MatAdd(X, 2 * X, Y, -3 * Y)
assert Trace(q).arg == q
assert Trace(q).doit() == 18 - 2 * Trace(Y)
def test_DiagonalMatrix():
x = MatrixSymbol('x', n, m)
D = DiagonalMatrix(x)
assert D.diagonal_length is None
assert D.shape == (n, m)
x = MatrixSymbol('x', n, n)
D = DiagonalMatrix(x)
assert D.diagonal_length == n
assert D.shape == (n, n)
assert D[1, 2] == 0
assert D[1, 1] == x[1, 1]
i = Symbol('i')
j = Symbol('j')
x = MatrixSymbol('x', 3, 3)
ij = DiagonalMatrix(x)[i, j]
assert ij != 0
assert ij.subs({i:0, j:0}) == x[0, 0]
assert ij.subs({i:0, j:1}) == 0
assert ij.subs({i:1, j:1}) == x[1, 1]
assert ask(Q.diagonal(D)) # affirm that D is diagonal
x = MatrixSymbol('x', n, 3)
D = DiagonalMatrix(x)
assert D.diagonal_length == 3
assert D.shape == (n, 3)
assert D[2, m] == KroneckerDelta(2, m)*x[2, m]
assert D[3, m] == 0
raises(IndexError, lambda: D[m, 3])
x = MatrixSymbol('x', 3, n)
D = DiagonalMatrix(x)
assert D.diagonal_length == 3
assert D.shape == (3, n)
assert D[m, 2] == KroneckerDelta(m, 2)*x[m, 2]
assert D[m, 3] == 0
raises(IndexError, lambda: D[3, m])
x = MatrixSymbol('x', n, m)
D = DiagonalMatrix(x)
assert D.diagonal_length is None
assert D.shape == (n, m)
assert D[m, 4] != 0
x = MatrixSymbol('x', 3, 4)
assert [DiagonalMatrix(x)[i] for i in range(12)] == [
x[0, 0], 0, 0, 0, 0, x[1, 1], 0, 0, 0, 0, x[2, 2], 0]
# shape is retained, issue 12427
assert (
DiagonalMatrix(MatrixSymbol('x', 3, 4))*
DiagonalMatrix(MatrixSymbol('x', 4, 2))).shape == (3, 2)
def test_BlockMatrix_Determinant():
A, B, C, D = map(lambda s: MatrixSymbol(s, 3, 3), 'ABCD')
X = BlockMatrix([[A, B], [C, D]])
from sympy import assuming, Q
with assuming(Q.invertible(A)):
assert det(X) == det(A) * det(D - C * A.I * B)
assert isinstance(det(X), Expr)
def test_DiagonalizeVector():
x = MatrixSymbol('x', n, 1)
d = DiagonalizeVector(x)
assert d.shape == (n, n)
assert d[0, 1] == 0
assert d[0, 0] == x[0, 0]
a = MatrixSymbol('a', 1, 1)
d = diagonalize_vector(a)
assert isinstance(d, MatrixSymbol)
assert a == d
assert diagonalize_vector(Identity(3)) == Identity(3)
assert isinstance(DiagonalizeVector(Identity(3)), DiagonalizeVector)
# A diagonal matrix is equal to its transpose:
assert DiagonalizeVector(x).T == DiagonalizeVector(x)
assert diagonalize_vector(x.T) == DiagonalizeVector(x)
dx = DiagonalizeVector(x)
assert dx[0, 0] == x[0, 0]
assert dx[1, 1] == x[1, 0]
assert dx[0, 1] == 0
assert dx[0, m] == x[0, 0] * KroneckerDelta(0, m)
z = MatrixSymbol('z', 1, n)
dz = DiagonalizeVector(z)
assert dz[0, 0] == z[0, 0]
assert dz[1, 1] == z[0, 1]
assert dz[0, 1] == 0
assert dz[0, m] == z[0, m] * KroneckerDelta(0, m)
v = MatrixSymbol('v', 3, 1)
dv = DiagonalizeVector(v)
assert dv.as_explicit() == Matrix([
[v[0, 0], 0, 0],
[0, v[1, 0], 0],
[0, 0, v[2, 0]],
])
v = MatrixSymbol('v', 1, 3)
dv = DiagonalizeVector(v)
assert dv.as_explicit() == Matrix([
[v[0, 0], 0, 0],
[0, v[0, 1], 0],
[0, 0, v[0, 2]],
])
def test_block_lu_decomposition():
A = MatrixSymbol('A', n, n)
B = MatrixSymbol('B', n, m)
C = MatrixSymbol('C', m, n)
D = MatrixSymbol('D', m, m)
X = BlockMatrix([[A, B], [C, D]])
#LDU decomposition
L, D, U = X.LDUdecomposition()
assert block_collapse(L*D*U) == X
#UDL decomposition
U, D, L = X.UDLdecomposition()
assert block_collapse(U*D*L) == X
#LU decomposition
L, U = X.LUdecomposition()
assert block_collapse(L*U) == X
def test_matrix_element_sets():
X = MatrixSymbol('X', 4, 4)
assert ask(Q.real(X[1, 2]), Q.real_elements(X))
assert ask(Q.integer(X[1, 2]), Q.integer_elements(X))
assert ask(Q.complex(X[1, 2]), Q.complex_elements(X))
assert ask(Q.integer_elements(Identity(3)))
assert ask(Q.integer_elements(ZeroMatrix(3, 3)))
from sympy.matrices.expressions.fourier import DFT
assert ask(Q.complex_elements(DFT(3)))
def test_print_tree_MatAdd_noassumptions():
from sympy.matrices.expressions import MatrixSymbol
A = MatrixSymbol('A', 3, 3)
B = MatrixSymbol('B', 3, 3)
test_str = \
"""MatAdd: A + B
+-MatrixSymbol: A
| +-Str: A
| +-Integer: 3
| +-Integer: 3
+-MatrixSymbol: B
+-Str: B
+-Integer: 3
+-Integer: 3
"""
assert tree(A + B, assumptions=False) == test_str
def _rebuild(expr):
if not isinstance(expr, Basic):
return expr
if not expr.args:
return expr
if iterable(expr):
new_args = [_rebuild(arg) for arg in expr]
return expr.func(*new_args)
if expr in subs:
return subs[expr]
orig_expr = expr
if expr in opt_subs:
expr = opt_subs[expr]
# If enabled, parse Muls and Adds arguments by order to ensure
# replacement order independent from hashes
if order != 'none':
if isinstance(expr, (Mul, MatMul)):
c, nc = expr.args_cnc()
if c == [1]:
args = nc
else:
args = list(ordered(c)) + nc
elif isinstance(expr, (Add, MatAdd)):
args = list(ordered(expr.args))
else:
args = expr.args
else:
args = expr.args
new_args = list(map(_rebuild, args))
if new_args != args:
new_expr = expr.func(*new_args)
else:
new_expr = expr
if orig_expr in to_eliminate:
try:
sym = next(symbols)
except StopIteration:
raise ValueError("Symbols iterator ran out of symbols.")
if isinstance(orig_expr, MatrixExpr):
sym = MatrixSymbol(sym.name, orig_expr.rows,
orig_expr.cols)
subs[orig_expr] = sym
replacements.append((sym, new_expr))
return sym
else:
return new_expr
def test_BlockMatrix_3x3_symbolic():
# Only test one of these, instead of all permutations, because it's slow
rowblocksizes = (n, m, k)
colblocksizes = (m, k, n)
K = BlockMatrix([
[MatrixSymbol('M%s%s' % (rows, cols), rows, cols) for cols in colblocksizes]
for rows in rowblocksizes
])
collapse = block_collapse(K.I)
assert isinstance(collapse, BlockMatrix)
def test_BlockMatrix_Determinant():
A, B, C, D = [MatrixSymbol(s, 3, 3) for s in 'ABCD']
X = BlockMatrix([[A, B], [C, D]])
from sympy import assuming, Q
with assuming(Q.invertible(A)):
assert det(X) == det(A) * det(D - C * A.I * B)
assert isinstance(det(X), Expr)
assert det(BlockMatrix([A])) == det(A)
assert det(BlockMatrix([ZeroMatrix(n, n)])) == 0
def test_field_assumptions():
X = MatrixSymbol('X', 4, 4)
Y = MatrixSymbol('Y', 4, 4)
assert ask(Q.real_elements(X), Q.real_elements(X))
assert not ask(Q.integer_elements(X), Q.real_elements(X))
assert ask(Q.complex_elements(X), Q.real_elements(X))
assert ask(Q.real_elements(X + Y), Q.real_elements(X)) is None
assert ask(Q.real_elements(X + Y), Q.real_elements(X) & Q.real_elements(Y))
from sympy.matrices.expressions.hadamard import HadamardProduct
assert ask(Q.real_elements(HadamardProduct(X, Y)),
Q.real_elements(X) & Q.real_elements(Y))
assert ask(Q.complex_elements(X + Y),
Q.real_elements(X) & Q.complex_elements(Y))
assert ask(Q.real_elements(X.T), Q.real_elements(X))
assert ask(Q.real_elements(X.I), Q.real_elements(X) & Q.invertible(X))
assert ask(Q.real_elements(Trace(X)), Q.real_elements(X))
assert ask(Q.integer_elements(Determinant(X)), Q.integer_elements(X))
assert not ask(Q.integer_elements(X.I), Q.integer_elements(X))
def test_HadamardProduct():
n, m, k = symbols('n,m,k')
Z = MatrixSymbol('Z', n, n)
A = MatrixSymbol('A', n, m)
B = MatrixSymbol('B', n, m)
C = MatrixSymbol('C', m, k)
assert HadamardProduct(A, B, A).shape == A.shape
raises(ShapeError, lambda: HadamardProduct(A, B.T))
raises(TypeError, lambda: HadamardProduct(A, n))
raises(TypeError, lambda: HadamardProduct(A, 1))
assert HadamardProduct(A, 2 * B, -A)[1, 1] == -2 * A[1, 1]**2 * B[1, 1]
mix = HadamardProduct(Z * A, B) * C
assert mix.shape == (n, k)
assert HadamardProduct(A, B, A).T == HadamardProduct(A.T, B.T, A.T)
def test_codegen_einsum():
if not tf:
skip("TensorFlow not installed")
graph = tf.Graph()
with graph.as_default():
session = tf.compat.v1.Session(graph=graph)
M = MatrixSymbol("M", 2, 2)
N = MatrixSymbol("N", 2, 2)
cg = convert_matrix_to_array(M * N)
f = lambdify((M, N), cg, 'tensorflow')
ma = tf.constant([[1, 2], [3, 4]])
mb = tf.constant([[1, -2], [-1, 3]])
y = session.run(f(ma, mb))
c = session.run(tf.matmul(ma, mb))
assert (y == c).all()
def test_reblock_2x2():
B = BlockMatrix([[MatrixSymbol('A_%d%d' % (i, j), 2, 2) for j in range(3)]
for i in range(3)])
assert B.blocks.shape == (3, 3)
BB = reblock_2x2(B)
assert BB.blocks.shape == (2, 2)
assert B.shape == BB.shape
assert B.as_explicit() == BB.as_explicit()
def test_BlockMatrix_Determinant():
A, B, C, D = [MatrixSymbol(s, 3, 3) for s in 'ABCD']
X = BlockMatrix([[A, B], [C, D]])
from sympy.assumptions.ask import Q
from sympy.assumptions.assume import assuming
with assuming(Q.invertible(A)):
assert det(X) == det(A) * det(X.schur('A'))
assert isinstance(det(X), Expr)
assert det(BlockMatrix([A])) == det(A)
assert det(BlockMatrix([ZeroMatrix(n, n)])) == 0
def test_blockcut():
A = MatrixSymbol('A', n, m)
B = blockcut(A, (n/2, n/2), (m/2, m/2))
assert B == BlockMatrix([[A[:n/2, :m/2], A[:n/2, m/2:]],
[A[n/2:, :m/2], A[n/2:, m/2:]]])
M = ImmutableMatrix(4, 4, range(16))
B = blockcut(M, (2, 2), (2, 2))
assert M == ImmutableMatrix(B)
B = blockcut(M, (1, 3), (2, 2))
assert ImmutableMatrix(B.blocks[0, 1]) == ImmutableMatrix([[2, 3]])
def test_DiagonalMatrix():
assert D.shape == (n, n)
assert D[1, 2] == 0
assert D[1, 1] == X[1, 1]
i = Symbol('i')
j = Symbol('j')
x = MatrixSymbol('x', 3, 3)
ij = DiagonalMatrix(x)[i, j]
assert ij != 0
assert ij.subs({i:0, j:0}) == x[0, 0]
assert ij.subs({i:0, j:1}) == 0
assert ij.subs({i:1, j:1}) == x[1, 1]
def test_squareBlockMatrix():
A = MatrixSymbol('A', n, n)
B = MatrixSymbol('B', n, m)
C = MatrixSymbol('C', m, n)
D = MatrixSymbol('D', m, m)
X = BlockMatrix([[A, B], [C, D]])
Y = BlockMatrix([[A]])
assert X.is_square
assert (block_collapse(X + Identity(m + n)) == BlockMatrix(
[[A + Identity(n), B], [C, D + Identity(m)]]))
Q = X + Identity(m + n)
assert (X + MatrixSymbol('Q', n + m, n + m)).is_MatAdd
assert (X * MatrixSymbol('Q', n + m, n + m)).is_MatMul
assert block_collapse(Y.I) == A.I
assert block_collapse(X.inverse()) == BlockMatrix([[
(-B * D.I * C + A).I, -A.I * B * (D + -C * A.I * B).I
], [-(D - C * A.I * B).I * C * A.I, (D - C * A.I * B).I]])
assert isinstance(X.inverse(), Inverse)
assert not X.is_Identity
Z = BlockMatrix([[Identity(n), B], [C, D]])
assert not Z.is_Identity
def test_MatrixSlice():
X = MatrixSymbol('X', 4, 4)
B = MatrixSlice(X, (1, 3), (1, 3))
C = MatrixSlice(X, (0, 3), (1, 3))
assert ask(Q.symmetric(B), Q.symmetric(X))
assert ask(Q.invertible(B), Q.invertible(X))
assert ask(Q.diagonal(B), Q.diagonal(X))
assert ask(Q.orthogonal(B), Q.orthogonal(X))
assert ask(Q.upper_triangular(B), Q.upper_triangular(X))
assert not ask(Q.symmetric(C), Q.symmetric(X))
assert not ask(Q.invertible(C), Q.invertible(X))
assert not ask(Q.diagonal(C), Q.diagonal(X))
assert not ask(Q.orthogonal(C), Q.orthogonal(X))
assert not ask(Q.upper_triangular(C), Q.upper_triangular(X))
def test_adjoint():
Sq = MatrixSymbol('Sq', n, n)
assert Adjoint(A).shape == (m, n)
assert Adjoint(A * B).shape == (l, n)
assert Adjoint(Adjoint(A)) == A
assert Adjoint(eye(3)) == eye(3)
assert Adjoint(S(5)) == S(5)
assert Adjoint(Matrix([[1, 2], [3, 4]])) == Matrix([[1, 3], [2, 4]])
assert Adjoint(Trace(Sq)) == conjugate(Trace(Sq))
assert Trace(Adjoint(Sq)) == conjugate(Trace(Sq))
assert Adjoint(Sq)[0, 1] == conjugate(Sq[1, 0])
def test_adjoint():
Sq = MatrixSymbol("Sq", n, n)
assert Adjoint(A).shape == (m, n)
assert Adjoint(A * B).shape == (l, n)
assert adjoint(Adjoint(A)) == A
assert isinstance(Adjoint(Adjoint(A)), Adjoint)
assert conjugate(Adjoint(A)) == Transpose(A)
assert transpose(Adjoint(A)) == Adjoint(Transpose(A))
assert Adjoint(eye(3)).doit() == eye(3)
assert Adjoint(S(5)).doit() == S(5)
assert Adjoint(Matrix([[1, 2], [3, 4]])).doit() == Matrix([[1, 3], [2, 4]])
assert adjoint(trace(Sq)) == conjugate(trace(Sq))
assert trace(adjoint(Sq)) == conjugate(trace(Sq))
assert Adjoint(Sq)[0, 1] == conjugate(Sq[1, 0])
assert Adjoint(A * B).doit() == Adjoint(B) * Adjoint(A)
def test_DiagonalOf():
x = MatrixSymbol('x', n, n)
d = DiagonalOf(x)
assert d.shape == (n, 1)
assert d.diagonal_length == n
assert d[2, 0] == d[2] == x[2, 2]
x = MatrixSymbol('x', n, m)
d = DiagonalOf(x)
assert d.shape == (None, 1)
assert d.diagonal_length is None
assert d[2, 0] == d[2] == x[2, 2]
d = DiagonalOf(MatrixSymbol('x', 4, 3))
assert d.shape == (3, 1)
d = DiagonalOf(MatrixSymbol('x', n, 3))
assert d.shape == (3, 1)
d = DiagonalOf(MatrixSymbol('x', 3, n))
assert d.shape == (3, 1)
x = MatrixSymbol('x', n, m)
assert [DiagonalOf(x)[i]
for i in range(4)] == [x[0, 0], x[1, 1], x[2, 2], x[3, 3]]
def test_negative_index():
X = MatrixSymbol('x', 10, 10)
assert X[-1, :] == X[9, :]
def test_slice_of_slice():
X = MatrixSymbol('x', 10, 10)
assert X[2, :][:, 3][0, 0] == X[2, 3]
assert X[:5, :5][:4, :4] == X[:4, :4]
assert X[1:5, 2:6][1:3, 2] == X[2:4, 4]
assert X[1:9:2, 2:6][1:3, 2] == X[3:7:2, 4]
def test_symmetry():
X = MatrixSymbol('x', 10, 10)
Y = X[:5, 5:]
with assuming(Q.symmetric(X)):
assert Y.T == X[5:, :5]
def test_exceptions():
X = MatrixSymbol('x', 10, 20)
raises(IndexError, lambda: X[0:12, 2])
raises(IndexError, lambda: X[0:9, 22])
raises(IndexError, lambda: X[-1:5, 2])
