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(eye(3)).doit(deep=False) == eye(3)
assert Transpose(Integer(5)).doit() == Integer(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_BlockMatrix():
A = MatrixSymbol('A', n, m)
B = MatrixSymbol('B', n, k)
C = MatrixSymbol('C', l, m)
D = MatrixSymbol('D', l, k)
M = MatrixSymbol('M', m + k, p)
N = MatrixSymbol('N', l + n, k + m)
X = BlockMatrix(Matrix([[A, B], [C, D]]))
assert X.__class__(*X.args) == X
# block_collapse does nothing on normal inputs
E = MatrixSymbol('E', n, m)
assert block_collapse(A + 2 * E) == A + 2 * E
F = MatrixSymbol('F', m, m)
assert block_collapse(E.T * A * F) == E.T * A * F
assert X.shape == (l + n, k + m)
assert X.blockshape == (2, 2)
assert transpose(X) == BlockMatrix(Matrix([[A.T, C.T], [B.T, D.T]]))
assert transpose(X).shape == X.shape[::-1]
# Test that BlockMatrices and MatrixSymbols can still mix
assert (X * M).is_MatMul
assert X._blockmul(M).is_MatMul
assert (X * M).shape == (n + l, p)
assert (X + N).is_MatAdd
assert X._blockadd(N).is_MatAdd
assert (X + N).shape == X.shape
E = MatrixSymbol('E', m, 1)
F = MatrixSymbol('F', k, 1)
Y = BlockMatrix(Matrix([[E], [F]]))
assert (X * Y).shape == (l + n, 1)
assert block_collapse(X * Y).blocks[0, 0] == A * E + B * F
assert block_collapse(X * Y).blocks[1, 0] == C * E + D * F
# block_collapse passes down into container objects, transposes, and inverse
assert block_collapse(transpose(X * Y)) == transpose(block_collapse(X * Y))
assert block_collapse(Tuple(X * Y, 2 * X)) == (block_collapse(X * Y),
block_collapse(2 * X))
# Make sure that MatrixSymbols will enter 1x1 BlockMatrix if it simplifies
Ab = BlockMatrix([[A]])
Z = MatrixSymbol('Z', *A.shape)
assert block_collapse(Ab + Z) == A + Z
def test_BlockMatrix():
A = MatrixSymbol('A', n, m)
B = MatrixSymbol('B', n, k)
C = MatrixSymbol('C', l, m)
D = MatrixSymbol('D', l, k)
M = MatrixSymbol('M', m + k, p)
N = MatrixSymbol('N', l + n, k + m)
X = BlockMatrix(Matrix([[A, B], [C, D]]))
assert X.__class__(*X.args) == X
# block_collapse does nothing on normal inputs
E = MatrixSymbol('E', n, m)
assert block_collapse(A + 2*E) == A + 2*E
F = MatrixSymbol('F', m, m)
assert block_collapse(E.T*A*F) == E.T*A*F
assert X.shape == (l + n, k + m)
assert X.blockshape == (2, 2)
assert transpose(X) == BlockMatrix(Matrix([[A.T, C.T], [B.T, D.T]]))
assert transpose(X).shape == X.shape[::-1]
# Test that BlockMatrices and MatrixSymbols can still mix
assert (X*M).is_MatMul
assert X._blockmul(M).is_MatMul
assert (X*M).shape == (n + l, p)
assert (X + N).is_MatAdd
assert X._blockadd(N).is_MatAdd
assert (X + N).shape == X.shape
E = MatrixSymbol('E', m, 1)
F = MatrixSymbol('F', k, 1)
Y = BlockMatrix(Matrix([[E], [F]]))
assert (X*Y).shape == (l + n, 1)
assert block_collapse(X*Y).blocks[0, 0] == A*E + B*F
assert block_collapse(X*Y).blocks[1, 0] == C*E + D*F
# block_collapse passes down into container objects, transposes, and inverse
assert block_collapse(transpose(X*Y)) == transpose(block_collapse(X*Y))
assert block_collapse(Tuple(X*Y, 2*X)) == (
block_collapse(X*Y), block_collapse(2*X))
# Make sure that MatrixSymbols will enter 1x1 BlockMatrix if it simplifies
Ab = BlockMatrix([[A]])
Z = MatrixSymbol('Z', *A.shape)
assert block_collapse(Ab + Z) == A + Z
def test_Trace():
assert isinstance(Trace(A), Trace)
assert not isinstance(Trace(A), MatrixExpr)
pytest.raises(ShapeError, lambda: Trace(C))
assert trace(eye(3)) == 3
assert trace(Matrix(3, 3, [1, 2, 3, 4, 5, 6, 7, 8, 9])) == 15
assert adjoint(Trace(A)) == trace(Adjoint(A))
assert conjugate(Trace(A)) == trace(Adjoint(A))
assert transpose(Trace(A)) == Trace(A)
A / Trace(A) # Make sure this is possible
# Some easy simplifications
assert trace(Identity(5)) == 5
assert trace(ZeroMatrix(5, 5)) == 0
assert trace(2*A*B) == 2*Trace(A*B)
assert trace(A.T) == trace(A)
i, j = symbols('i j')
F = FunctionMatrix(3, 3, Lambda((i, j), i + j))
assert trace(F) == (0 + 0) + (1 + 1) + (2 + 2)
pytest.raises(TypeError, lambda: Trace(1))
assert Trace(A).arg is A
assert str(trace(A)) == str(Trace(A).doit())
def test_Trace():
assert isinstance(Trace(A), Trace)
assert not isinstance(Trace(A), MatrixExpr)
pytest.raises(ShapeError, lambda: Trace(C))
assert trace(eye(3)) == 3
assert trace(Matrix(3, 3, [1, 2, 3, 4, 5, 6, 7, 8, 9])) == 15
assert adjoint(Trace(A)) == trace(Adjoint(A))
assert conjugate(Trace(A)) == trace(Adjoint(A))
assert transpose(Trace(A)) == Trace(A)
A / Trace(A) # Make sure this is possible
# Some easy simplifications
assert trace(Identity(5)) == 5
assert trace(ZeroMatrix(5, 5)) == 0
assert trace(2 * A * B) == 2 * Trace(A * B)
assert trace(A.T) == trace(A)
i, j = symbols('i j')
F = FunctionMatrix(3, 3, Lambda((i, j), i + j))
assert trace(F) == (0 + 0) + (1 + 1) + (2 + 2)
pytest.raises(TypeError, lambda: Trace(S.One))
assert Trace(A).arg is A
assert str(trace(A)) == str(Trace(A).doit())
def test_Identity():
A = MatrixSymbol('A', n, m)
In = Identity(n)
Im = Identity(m)
assert A * Im == A
assert In * A == A
assert transpose(In) == In
assert In.inverse() == In
assert In.conjugate() == In
def test_Identity():
A = MatrixSymbol('A', n, m)
In = Identity(n)
Im = Identity(m)
assert A*Im == A
assert In*A == A
assert transpose(In) == In
assert In.inverse() == In
assert In.conjugate() == In
def test_transpose():
assert transpose(A*B) == Transpose(B)*Transpose(A)
assert transpose(2*A*B) == 2*Transpose(B)*Transpose(A)
assert transpose(2*I*C) == 2*I*Transpose(C)
M = Matrix(2, 2, [1, 2 + I, 3, 4]).as_immutable()
MT = Matrix(2, 2, [1, 3, 2 + I, 4])
assert transpose(M) == MT
assert transpose(2*M) == 2*MT
assert transpose(MatMul(2, M)) == MatMul(2, MT).doit()
def test_ZeroMatrix():
A = MatrixSymbol('A', n, m)
Z = ZeroMatrix(n, m)
assert A + Z == A
assert A * Z.T == ZeroMatrix(n, n)
assert Z * A.T == ZeroMatrix(n, n)
assert A - A == ZeroMatrix(*A.shape)
assert not Z
assert transpose(Z) == ZeroMatrix(m, n)
assert Z.conjugate() == Z
assert ZeroMatrix(n, n)**0 == Identity(n)
with pytest.raises(ShapeError):
Z**0
with pytest.raises(ShapeError):
Z**2
def test_ZeroMatrix():
A = MatrixSymbol('A', n, m)
Z = ZeroMatrix(n, m)
assert A + Z == A
assert A*Z.T == ZeroMatrix(n, n)
assert Z*A.T == ZeroMatrix(n, n)
assert A - A == ZeroMatrix(*A.shape)
assert not Z
assert transpose(Z) == ZeroMatrix(m, n)
assert Z.conjugate() == Z
assert ZeroMatrix(n, n)**0 == Identity(n)
with pytest.raises(ShapeError):
Z**0
with pytest.raises(ShapeError):
Z**2
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(Integer(5)).doit() == Integer(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_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) == Adjoint(A).conjugate()
assert transpose(Adjoint(A)) == Adjoint(Transpose(A)) == Transpose(A).adjoint()
assert Adjoint(eye(3)).doit() == Adjoint(eye(3)).doit(deep=False) == eye(3)
assert Adjoint(Integer(5)).doit() == Integer(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)
assert Adjoint(C + D).doit() == Adjoint(C) + Adjoint(D)
