568 lines
17 KiB
Python
568 lines
17 KiB
Python
from sympy.concrete.summations import Sum
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from sympy.core.exprtools import gcd_terms
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from sympy.core.function import (diff, expand)
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from sympy.core.relational import Eq
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from sympy.core.symbol import (Dummy, Symbol, Str)
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from sympy.functions.special.tensor_functions import KroneckerDelta
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from sympy.matrices.dense import zeros
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from sympy.polys.polytools import factor
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from sympy.core import (S, symbols, Add, Mul, SympifyError, Rational,
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Function)
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from sympy.functions import sin, cos, tan, sqrt, cbrt, exp
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from sympy.simplify import simplify
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from sympy.matrices import (ImmutableMatrix, Inverse, MatAdd, MatMul,
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MatPow, Matrix, MatrixExpr, MatrixSymbol,
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SparseMatrix, Transpose, Adjoint, MatrixSet)
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from sympy.matrices.common import NonSquareMatrixError
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from sympy.matrices.expressions.determinant import Determinant, det
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from sympy.matrices.expressions.matexpr import MatrixElement
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from sympy.matrices.expressions.special import ZeroMatrix, Identity
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from sympy.testing.pytest import raises, XFAIL
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n, m, l, k, p = symbols('n m l k p', integer=True)
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x = symbols('x')
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A = MatrixSymbol('A', n, m)
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B = MatrixSymbol('B', m, l)
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C = MatrixSymbol('C', n, n)
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D = MatrixSymbol('D', n, n)
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E = MatrixSymbol('E', m, n)
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w = MatrixSymbol('w', n, 1)
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def test_matrix_symbol_creation():
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assert MatrixSymbol('A', 2, 2)
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assert MatrixSymbol('A', 0, 0)
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raises(ValueError, lambda: MatrixSymbol('A', -1, 2))
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raises(ValueError, lambda: MatrixSymbol('A', 2.0, 2))
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raises(ValueError, lambda: MatrixSymbol('A', 2j, 2))
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raises(ValueError, lambda: MatrixSymbol('A', 2, -1))
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raises(ValueError, lambda: MatrixSymbol('A', 2, 2.0))
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raises(ValueError, lambda: MatrixSymbol('A', 2, 2j))
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n = symbols('n')
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assert MatrixSymbol('A', n, n)
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n = symbols('n', integer=False)
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raises(ValueError, lambda: MatrixSymbol('A', n, n))
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n = symbols('n', negative=True)
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raises(ValueError, lambda: MatrixSymbol('A', n, n))
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def test_matexpr_properties():
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assert A.shape == (n, m)
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assert (A * B).shape == (n, l)
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assert A[0, 1].indices == (0, 1)
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assert A[0, 0].symbol == A
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assert A[0, 0].symbol.name == 'A'
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def test_matexpr():
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assert (x*A).shape == A.shape
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assert (x*A).__class__ == MatMul
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assert 2*A - A - A == ZeroMatrix(*A.shape)
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assert (A*B).shape == (n, l)
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def test_matexpr_subs():
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A = MatrixSymbol('A', n, m)
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B = MatrixSymbol('B', m, l)
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C = MatrixSymbol('C', m, l)
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assert A.subs(n, m).shape == (m, m)
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assert (A*B).subs(B, C) == A*C
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assert (A*B).subs(l, n).is_square
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W = MatrixSymbol("W", 3, 3)
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X = MatrixSymbol("X", 2, 2)
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Y = MatrixSymbol("Y", 1, 2)
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Z = MatrixSymbol("Z", n, 2)
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# no restrictions on Symbol replacement
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assert X.subs(X, Y) == Y
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# it might be better to just change the name
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y = Str('y')
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assert X.subs(Str("X"), y).args == (y, 2, 2)
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# it's ok to introduce a wider matrix
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assert X[1, 1].subs(X, W) == W[1, 1]
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# but for a given MatrixExpression, only change
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# name if indexing on the new shape is valid.
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# Here, X is 2,2; Y is 1,2 and Y[1, 1] is out
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# of range so an error is raised
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raises(IndexError, lambda: X[1, 1].subs(X, Y))
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# here, [0, 1] is in range so the subs succeeds
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assert X[0, 1].subs(X, Y) == Y[0, 1]
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# and here the size of n will accept any index
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# in the first position
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assert W[2, 1].subs(W, Z) == Z[2, 1]
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# but not in the second position
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raises(IndexError, lambda: W[2, 2].subs(W, Z))
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# any matrix should raise if invalid
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raises(IndexError, lambda: W[2, 2].subs(W, zeros(2)))
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A = SparseMatrix([[1, 2], [3, 4]])
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B = Matrix([[1, 2], [3, 4]])
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C, D = MatrixSymbol('C', 2, 2), MatrixSymbol('D', 2, 2)
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assert (C*D).subs({C: A, D: B}) == MatMul(A, B)
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def test_addition():
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A = MatrixSymbol('A', n, m)
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B = MatrixSymbol('B', n, m)
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assert isinstance(A + B, MatAdd)
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assert (A + B).shape == A.shape
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assert isinstance(A - A + 2*B, MatMul)
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raises(TypeError, lambda: A + 1)
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raises(TypeError, lambda: 5 + A)
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raises(TypeError, lambda: 5 - A)
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assert A + ZeroMatrix(n, m) - A == ZeroMatrix(n, m)
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raises(TypeError, lambda: ZeroMatrix(n, m) + S.Zero)
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def test_multiplication():
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A = MatrixSymbol('A', n, m)
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B = MatrixSymbol('B', m, l)
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C = MatrixSymbol('C', n, n)
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assert (2*A*B).shape == (n, l)
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assert (A*0*B) == ZeroMatrix(n, l)
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assert (2*A).shape == A.shape
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assert A * ZeroMatrix(m, m) * B == ZeroMatrix(n, l)
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assert C * Identity(n) * C.I == Identity(n)
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assert B/2 == S.Half*B
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raises(NotImplementedError, lambda: 2/B)
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A = MatrixSymbol('A', n, n)
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B = MatrixSymbol('B', n, n)
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assert Identity(n) * (A + B) == A + B
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assert A**2*A == A**3
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assert A**2*(A.I)**3 == A.I
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assert A**3*(A.I)**2 == A
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def test_MatPow():
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A = MatrixSymbol('A', n, n)
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AA = MatPow(A, 2)
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assert AA.exp == 2
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assert AA.base == A
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assert (A**n).exp == n
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assert A**0 == Identity(n)
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assert A**1 == A
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assert A**2 == AA
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assert A**-1 == Inverse(A)
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assert (A**-1)**-1 == A
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assert (A**2)**3 == A**6
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assert A**S.Half == sqrt(A)
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assert A**Rational(1, 3) == cbrt(A)
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raises(NonSquareMatrixError, lambda: MatrixSymbol('B', 3, 2)**2)
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def test_MatrixSymbol():
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n, m, t = symbols('n,m,t')
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X = MatrixSymbol('X', n, m)
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assert X.shape == (n, m)
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raises(TypeError, lambda: MatrixSymbol('X', n, m)(t)) # issue 5855
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assert X.doit() == X
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def test_dense_conversion():
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X = MatrixSymbol('X', 2, 2)
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assert ImmutableMatrix(X) == ImmutableMatrix(2, 2, lambda i, j: X[i, j])
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assert Matrix(X) == Matrix(2, 2, lambda i, j: X[i, j])
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def test_free_symbols():
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assert (C*D).free_symbols == {C, D}
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def test_zero_matmul():
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assert isinstance(S.Zero * MatrixSymbol('X', 2, 2), MatrixExpr)
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def test_matadd_simplify():
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A = MatrixSymbol('A', 1, 1)
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assert simplify(MatAdd(A, ImmutableMatrix([[sin(x)**2 + cos(x)**2]]))) == \
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MatAdd(A, Matrix([[1]]))
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def test_matmul_simplify():
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A = MatrixSymbol('A', 1, 1)
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assert simplify(MatMul(A, ImmutableMatrix([[sin(x)**2 + cos(x)**2]]))) == \
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MatMul(A, Matrix([[1]]))
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def test_invariants():
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A = MatrixSymbol('A', n, m)
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B = MatrixSymbol('B', m, l)
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X = MatrixSymbol('X', n, n)
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objs = [Identity(n), ZeroMatrix(m, n), A, MatMul(A, B), MatAdd(A, A),
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Transpose(A), Adjoint(A), Inverse(X), MatPow(X, 2), MatPow(X, -1),
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MatPow(X, 0)]
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for obj in objs:
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assert obj == obj.__class__(*obj.args)
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def test_matexpr_indexing():
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A = MatrixSymbol('A', n, m)
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A[1, 2]
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A[l, k]
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A[l + 1, k + 1]
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A = MatrixSymbol('A', 2, 1)
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for i in range(-2, 2):
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for j in range(-1, 1):
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A[i, j]
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def test_single_indexing():
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A = MatrixSymbol('A', 2, 3)
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assert A[1] == A[0, 1]
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assert A[int(1)] == A[0, 1]
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assert A[3] == A[1, 0]
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assert list(A[:2, :2]) == [A[0, 0], A[0, 1], A[1, 0], A[1, 1]]
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raises(IndexError, lambda: A[6])
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raises(IndexError, lambda: A[n])
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B = MatrixSymbol('B', n, m)
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raises(IndexError, lambda: B[1])
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B = MatrixSymbol('B', n, 3)
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assert B[3] == B[1, 0]
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def test_MatrixElement_commutative():
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assert A[0, 1]*A[1, 0] == A[1, 0]*A[0, 1]
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def test_MatrixSymbol_determinant():
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A = MatrixSymbol('A', 4, 4)
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assert A.as_explicit().det() == A[0, 0]*A[1, 1]*A[2, 2]*A[3, 3] - \
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A[0, 0]*A[1, 1]*A[2, 3]*A[3, 2] - A[0, 0]*A[1, 2]*A[2, 1]*A[3, 3] + \
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A[0, 0]*A[1, 2]*A[2, 3]*A[3, 1] + A[0, 0]*A[1, 3]*A[2, 1]*A[3, 2] - \
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A[0, 0]*A[1, 3]*A[2, 2]*A[3, 1] - A[0, 1]*A[1, 0]*A[2, 2]*A[3, 3] + \
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A[0, 1]*A[1, 0]*A[2, 3]*A[3, 2] + A[0, 1]*A[1, 2]*A[2, 0]*A[3, 3] - \
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A[0, 1]*A[1, 2]*A[2, 3]*A[3, 0] - A[0, 1]*A[1, 3]*A[2, 0]*A[3, 2] + \
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A[0, 1]*A[1, 3]*A[2, 2]*A[3, 0] + A[0, 2]*A[1, 0]*A[2, 1]*A[3, 3] - \
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A[0, 2]*A[1, 0]*A[2, 3]*A[3, 1] - A[0, 2]*A[1, 1]*A[2, 0]*A[3, 3] + \
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A[0, 2]*A[1, 1]*A[2, 3]*A[3, 0] + A[0, 2]*A[1, 3]*A[2, 0]*A[3, 1] - \
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A[0, 2]*A[1, 3]*A[2, 1]*A[3, 0] - A[0, 3]*A[1, 0]*A[2, 1]*A[3, 2] + \
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A[0, 3]*A[1, 0]*A[2, 2]*A[3, 1] + A[0, 3]*A[1, 1]*A[2, 0]*A[3, 2] - \
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A[0, 3]*A[1, 1]*A[2, 2]*A[3, 0] - A[0, 3]*A[1, 2]*A[2, 0]*A[3, 1] + \
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A[0, 3]*A[1, 2]*A[2, 1]*A[3, 0]
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B = MatrixSymbol('B', 4, 4)
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assert Determinant(A + B).doit() == det(A + B) == (A + B).det()
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def test_MatrixElement_diff():
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assert (A[3, 0]*A[0, 0]).diff(A[0, 0]) == A[3, 0]
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def test_MatrixElement_doit():
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u = MatrixSymbol('u', 2, 1)
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v = ImmutableMatrix([3, 5])
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assert u[0, 0].subs(u, v).doit() == v[0, 0]
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def test_identity_powers():
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M = Identity(n)
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assert MatPow(M, 3).doit() == M**3
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assert M**n == M
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assert MatPow(M, 0).doit() == M**2
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assert M**-2 == M
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assert MatPow(M, -2).doit() == M**0
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N = Identity(3)
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assert MatPow(N, 2).doit() == N**n
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assert MatPow(N, 3).doit() == N
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assert MatPow(N, -2).doit() == N**4
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assert MatPow(N, 2).doit() == N**0
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def test_Zero_power():
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z1 = ZeroMatrix(n, n)
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assert z1**4 == z1
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raises(ValueError, lambda:z1**-2)
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assert z1**0 == Identity(n)
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assert MatPow(z1, 2).doit() == z1**2
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raises(ValueError, lambda:MatPow(z1, -2).doit())
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z2 = ZeroMatrix(3, 3)
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assert MatPow(z2, 4).doit() == z2**4
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raises(ValueError, lambda:z2**-3)
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assert z2**3 == MatPow(z2, 3).doit()
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assert z2**0 == Identity(3)
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raises(ValueError, lambda:MatPow(z2, -1).doit())
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def test_matrixelement_diff():
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dexpr = diff((D*w)[k,0], w[p,0])
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assert w[k, p].diff(w[k, p]) == 1
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assert w[k, p].diff(w[0, 0]) == KroneckerDelta(0, k, (0, n-1))*KroneckerDelta(0, p, (0, 0))
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_i_1 = Dummy("_i_1")
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assert dexpr.dummy_eq(Sum(KroneckerDelta(_i_1, p, (0, n-1))*D[k, _i_1], (_i_1, 0, n - 1)))
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assert dexpr.doit() == D[k, p]
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def test_MatrixElement_with_values():
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x, y, z, w = symbols("x y z w")
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M = Matrix([[x, y], [z, w]])
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i, j = symbols("i, j")
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Mij = M[i, j]
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assert isinstance(Mij, MatrixElement)
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Ms = SparseMatrix([[2, 3], [4, 5]])
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msij = Ms[i, j]
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assert isinstance(msij, MatrixElement)
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for oi, oj in [(0, 0), (0, 1), (1, 0), (1, 1)]:
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assert Mij.subs({i: oi, j: oj}) == M[oi, oj]
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assert msij.subs({i: oi, j: oj}) == Ms[oi, oj]
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A = MatrixSymbol("A", 2, 2)
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assert A[0, 0].subs(A, M) == x
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assert A[i, j].subs(A, M) == M[i, j]
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assert M[i, j].subs(M, A) == A[i, j]
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assert isinstance(M[3*i - 2, j], MatrixElement)
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assert M[3*i - 2, j].subs({i: 1, j: 0}) == M[1, 0]
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assert isinstance(M[i, 0], MatrixElement)
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assert M[i, 0].subs(i, 0) == M[0, 0]
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assert M[0, i].subs(i, 1) == M[0, 1]
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assert M[i, j].diff(x) == Matrix([[1, 0], [0, 0]])[i, j]
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raises(ValueError, lambda: M[i, 2])
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raises(ValueError, lambda: M[i, -1])
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raises(ValueError, lambda: M[2, i])
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raises(ValueError, lambda: M[-1, i])
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def test_inv():
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B = MatrixSymbol('B', 3, 3)
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assert B.inv() == B**-1
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# https://github.com/sympy/sympy/issues/19162
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X = MatrixSymbol('X', 1, 1).as_explicit()
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assert X.inv() == Matrix([[1/X[0, 0]]])
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X = MatrixSymbol('X', 2, 2).as_explicit()
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detX = X[0, 0]*X[1, 1] - X[0, 1]*X[1, 0]
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invX = Matrix([[ X[1, 1], -X[0, 1]],
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[-X[1, 0], X[0, 0]]]) / detX
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assert X.inv() == invX
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@XFAIL
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def test_factor_expand():
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A = MatrixSymbol("A", n, n)
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B = MatrixSymbol("B", n, n)
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expr1 = (A + B)*(C + D)
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expr2 = A*C + B*C + A*D + B*D
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assert expr1 != expr2
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assert expand(expr1) == expr2
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assert factor(expr2) == expr1
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expr = B**(-1)*(A**(-1)*B**(-1) - A**(-1)*C*B**(-1))**(-1)*A**(-1)
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I = Identity(n)
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# Ideally we get the first, but we at least don't want a wrong answer
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assert factor(expr) in [I - C, B**-1*(A**-1*(I - C)*B**-1)**-1*A**-1]
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def test_issue_2749():
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A = MatrixSymbol("A", 5, 2)
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assert (A.T * A).I.as_explicit() == Matrix([[(A.T * A).I[0, 0], (A.T * A).I[0, 1]], \
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[(A.T * A).I[1, 0], (A.T * A).I[1, 1]]])
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def test_issue_2750():
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x = MatrixSymbol('x', 1, 1)
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assert (x.T*x).as_explicit()**-1 == Matrix([[x[0, 0]**(-2)]])
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def test_issue_7842():
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A = MatrixSymbol('A', 3, 1)
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B = MatrixSymbol('B', 2, 1)
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assert Eq(A, B) == False
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assert Eq(A[1,0], B[1, 0]).func is Eq
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A = ZeroMatrix(2, 3)
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B = ZeroMatrix(2, 3)
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assert Eq(A, B) == True
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def test_issue_21195():
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t = symbols('t')
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x = Function('x')(t)
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dx = x.diff(t)
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exp1 = cos(x) + cos(x)*dx
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exp2 = sin(x) + tan(x)*(dx.diff(t))
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exp3 = sin(x)*sin(t)*(dx.diff(t)).diff(t)
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A = Matrix([[exp1], [exp2], [exp3]])
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B = Matrix([[exp1.diff(x)], [exp2.diff(x)], [exp3.diff(x)]])
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assert A.diff(x) == B
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def test_MatMul_postprocessor():
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z = zeros(2)
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z1 = ZeroMatrix(2, 2)
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assert Mul(0, z) == Mul(z, 0) in [z, z1]
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M = Matrix([[1, 2], [3, 4]])
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Mx = Matrix([[x, 2*x], [3*x, 4*x]])
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assert Mul(x, M) == Mul(M, x) == Mx
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A = MatrixSymbol("A", 2, 2)
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assert Mul(A, M) == MatMul(A, M)
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assert Mul(M, A) == MatMul(M, A)
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# Scalars should be absorbed into constant matrices
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a = Mul(x, M, A)
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b = Mul(M, x, A)
|
|
c = Mul(M, A, x)
|
|
assert a == b == c == MatMul(Mx, A)
|
|
a = Mul(x, A, M)
|
|
b = Mul(A, x, M)
|
|
c = Mul(A, M, x)
|
|
assert a == b == c == MatMul(A, Mx)
|
|
assert Mul(M, M) == M**2
|
|
assert Mul(A, M, M) == MatMul(A, M**2)
|
|
assert Mul(M, M, A) == MatMul(M**2, A)
|
|
assert Mul(M, A, M) == MatMul(M, A, M)
|
|
|
|
assert Mul(A, x, M, M, x) == MatMul(A, Mx**2)
|
|
|
|
|
|
@XFAIL
|
|
def test_MatAdd_postprocessor_xfail():
|
|
# This is difficult to get working because of the way that Add processes
|
|
# its args.
|
|
z = zeros(2)
|
|
assert Add(z, S.NaN) == Add(S.NaN, z)
|
|
|
|
|
|
def test_MatAdd_postprocessor():
|
|
# Some of these are nonsensical, but we do not raise errors for Add
|
|
# because that breaks algorithms that want to replace matrices with dummy
|
|
# symbols.
|
|
|
|
z = zeros(2)
|
|
|
|
assert Add(0, z) == Add(z, 0) == z
|
|
|
|
a = Add(S.Infinity, z)
|
|
assert a == Add(z, S.Infinity)
|
|
assert isinstance(a, Add)
|
|
assert a.args == (S.Infinity, z)
|
|
|
|
a = Add(S.ComplexInfinity, z)
|
|
assert a == Add(z, S.ComplexInfinity)
|
|
assert isinstance(a, Add)
|
|
assert a.args == (S.ComplexInfinity, z)
|
|
|
|
a = Add(z, S.NaN)
|
|
# assert a == Add(S.NaN, z) # See the XFAIL above
|
|
assert isinstance(a, Add)
|
|
assert a.args == (S.NaN, z)
|
|
|
|
M = Matrix([[1, 2], [3, 4]])
|
|
a = Add(x, M)
|
|
assert a == Add(M, x)
|
|
assert isinstance(a, Add)
|
|
assert a.args == (x, M)
|
|
|
|
A = MatrixSymbol("A", 2, 2)
|
|
assert Add(A, M) == Add(M, A) == A + M
|
|
|
|
# Scalars should be absorbed into constant matrices (producing an error)
|
|
a = Add(x, M, A)
|
|
assert a == Add(M, x, A) == Add(M, A, x) == Add(x, A, M) == Add(A, x, M) == Add(A, M, x)
|
|
assert isinstance(a, Add)
|
|
assert a.args == (x, A + M)
|
|
|
|
assert Add(M, M) == 2*M
|
|
assert Add(M, A, M) == Add(M, M, A) == Add(A, M, M) == A + 2*M
|
|
|
|
a = Add(A, x, M, M, x)
|
|
assert isinstance(a, Add)
|
|
assert a.args == (2*x, A + 2*M)
|
|
|
|
|
|
def test_simplify_matrix_expressions():
|
|
# Various simplification functions
|
|
assert type(gcd_terms(C*D + D*C)) == MatAdd
|
|
a = gcd_terms(2*C*D + 4*D*C)
|
|
assert type(a) == MatAdd
|
|
assert a.args == (2*C*D, 4*D*C)
|
|
|
|
|
|
def test_exp():
|
|
A = MatrixSymbol('A', 2, 2)
|
|
B = MatrixSymbol('B', 2, 2)
|
|
expr1 = exp(A)*exp(B)
|
|
expr2 = exp(B)*exp(A)
|
|
assert expr1 != expr2
|
|
assert expr1 - expr2 != 0
|
|
assert not isinstance(expr1, exp)
|
|
assert not isinstance(expr2, exp)
|
|
|
|
|
|
def test_invalid_args():
|
|
raises(SympifyError, lambda: MatrixSymbol(1, 2, 'A'))
|
|
|
|
|
|
def test_matrixsymbol_from_symbol():
|
|
# The label should be preserved during doit and subs
|
|
A_label = Symbol('A', complex=True)
|
|
A = MatrixSymbol(A_label, 2, 2)
|
|
|
|
A_1 = A.doit()
|
|
A_2 = A.subs(2, 3)
|
|
assert A_1.args == A.args
|
|
assert A_2.args[0] == A.args[0]
|
|
|
|
|
|
def test_as_explicit():
|
|
Z = MatrixSymbol('Z', 2, 3)
|
|
assert Z.as_explicit() == ImmutableMatrix([
|
|
[Z[0, 0], Z[0, 1], Z[0, 2]],
|
|
[Z[1, 0], Z[1, 1], Z[1, 2]],
|
|
])
|
|
raises(ValueError, lambda: A.as_explicit())
|
|
|
|
|
|
def test_MatrixSet():
|
|
M = MatrixSet(2, 2, set=S.Reals)
|
|
assert M.shape == (2, 2)
|
|
assert M.set == S.Reals
|
|
X = Matrix([[1, 2], [3, 4]])
|
|
assert X in M
|
|
X = ZeroMatrix(2, 2)
|
|
assert X in M
|
|
raises(TypeError, lambda: A in M)
|
|
raises(TypeError, lambda: 1 in M)
|
|
M = MatrixSet(n, m, set=S.Reals)
|
|
assert A in M
|
|
raises(TypeError, lambda: C in M)
|
|
raises(TypeError, lambda: X in M)
|
|
M = MatrixSet(2, 2, set={1, 2, 3})
|
|
X = Matrix([[1, 2], [3, 4]])
|
|
Y = Matrix([[1, 2]])
|
|
assert (X in M) == S.false
|
|
assert (Y in M) == S.false
|
|
raises(ValueError, lambda: MatrixSet(2, -2, S.Reals))
|
|
raises(ValueError, lambda: MatrixSet(2.4, -1, S.Reals))
|
|
raises(TypeError, lambda: MatrixSet(2, 2, (1, 2, 3)))
|
|
|
|
|
|
def test_matrixsymbol_solving():
|
|
A = MatrixSymbol('A', 2, 2)
|
|
B = MatrixSymbol('B', 2, 2)
|
|
Z = ZeroMatrix(2, 2)
|
|
assert -(-A + B) - A + B == Z
|
|
assert (-(-A + B) - A + B).simplify() == Z
|
|
assert (-(-A + B) - A + B).expand() == Z
|
|
assert (-(-A + B) - A + B - Z).simplify() == Z
|
|
assert (-(-A + B) - A + B - Z).expand() == Z
|
|
assert (A*(A + B) + B*(A.T + B.T)).expand() == A**2 + A*B + B*A.T + B*B.T
|