add read me

venv/lib/python3.12/site-packages/sympy/assumptions/handlers/matrices.py

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+"""
+This module contains query handlers responsible for Matrices queries:
+Square, Symmetric, Invertible etc.
+"""
+
+from sympy.logic.boolalg import conjuncts
+from sympy.assumptions import Q, ask
+from sympy.assumptions.handlers import test_closed_group
+from sympy.matrices import MatrixBase
+from sympy.matrices.expressions import (BlockMatrix, BlockDiagMatrix, Determinant,
+    DiagMatrix, DiagonalMatrix, HadamardProduct, Identity, Inverse, MatAdd, MatMul,
+    MatPow, MatrixExpr, MatrixSlice, MatrixSymbol, OneMatrix, Trace, Transpose,
+    ZeroMatrix)
+from sympy.matrices.expressions.blockmatrix import reblock_2x2
+from sympy.matrices.expressions.factorizations import Factorization
+from sympy.matrices.expressions.fourier import DFT
+from sympy.core.logic import fuzzy_and
+from sympy.utilities.iterables import sift
+from sympy.core import Basic
+
+from ..predicates.matrices import (SquarePredicate, SymmetricPredicate,
+    InvertiblePredicate, OrthogonalPredicate, UnitaryPredicate,
+    FullRankPredicate, PositiveDefinitePredicate, UpperTriangularPredicate,
+    LowerTriangularPredicate, DiagonalPredicate, IntegerElementsPredicate,
+    RealElementsPredicate, ComplexElementsPredicate)
+
+
+def _Factorization(predicate, expr, assumptions):
+    if predicate in expr.predicates:
+        return True
+
+
+# SquarePredicate
+
+@SquarePredicate.register(MatrixExpr)
+def _(expr, assumptions):
+    return expr.shape[0] == expr.shape[1]
+
+
+# SymmetricPredicate
+
+@SymmetricPredicate.register(MatMul)
+def _(expr, assumptions):
+    factor, mmul = expr.as_coeff_mmul()
+    if all(ask(Q.symmetric(arg), assumptions) for arg in mmul.args):
+        return True
+    # TODO: implement sathandlers system for the matrices.
+    # Now it duplicates the general fact: Implies(Q.diagonal, Q.symmetric).
+    if ask(Q.diagonal(expr), assumptions):
+        return True
+    if len(mmul.args) >= 2 and mmul.args[0] == mmul.args[-1].T:
+        if len(mmul.args) == 2:
+            return True
+        return ask(Q.symmetric(MatMul(*mmul.args[1:-1])), assumptions)
+
+@SymmetricPredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if not int_exp:
+        return None
+    non_negative = ask(~Q.negative(exp), assumptions)
+    if (non_negative or non_negative == False
+                        and ask(Q.invertible(base), assumptions)):
+        return ask(Q.symmetric(base), assumptions)
+    return None
+
+@SymmetricPredicate.register(MatAdd)
+def _(expr, assumptions):
+    return all(ask(Q.symmetric(arg), assumptions) for arg in expr.args)
+
+@SymmetricPredicate.register(MatrixSymbol)
+def _(expr, assumptions):
+    if not expr.is_square:
+        return False
+    # TODO: implement sathandlers system for the matrices.
+    # Now it duplicates the general fact: Implies(Q.diagonal, Q.symmetric).
+    if ask(Q.diagonal(expr), assumptions):
+        return True
+    if Q.symmetric(expr) in conjuncts(assumptions):
+        return True
+
+@SymmetricPredicate.register_many(OneMatrix, ZeroMatrix)
+def _(expr, assumptions):
+    return ask(Q.square(expr), assumptions)
+
+@SymmetricPredicate.register_many(Inverse, Transpose)
+def _(expr, assumptions):
+    return ask(Q.symmetric(expr.arg), assumptions)
+
+@SymmetricPredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    # TODO: implement sathandlers system for the matrices.
+    # Now it duplicates the general fact: Implies(Q.diagonal, Q.symmetric).
+    if ask(Q.diagonal(expr), assumptions):
+        return True
+    if not expr.on_diag:
+        return None
+    else:
+        return ask(Q.symmetric(expr.parent), assumptions)
+
+@SymmetricPredicate.register(Identity)
+def _(expr, assumptions):
+    return True
+
+
+# InvertiblePredicate
+
+@InvertiblePredicate.register(MatMul)
+def _(expr, assumptions):
+    factor, mmul = expr.as_coeff_mmul()
+    if all(ask(Q.invertible(arg), assumptions) for arg in mmul.args):
+        return True
+    if any(ask(Q.invertible(arg), assumptions) is False
+            for arg in mmul.args):
+        return False
+
+@InvertiblePredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if not int_exp:
+        return None
+    if exp.is_negative == False:
+        return ask(Q.invertible(base), assumptions)
+    return None
+
+@InvertiblePredicate.register(MatAdd)
+def _(expr, assumptions):
+    return None
+
+@InvertiblePredicate.register(MatrixSymbol)
+def _(expr, assumptions):
+    if not expr.is_square:
+        return False
+    if Q.invertible(expr) in conjuncts(assumptions):
+        return True
+
+@InvertiblePredicate.register_many(Identity, Inverse)
+def _(expr, assumptions):
+    return True
+
+@InvertiblePredicate.register(ZeroMatrix)
+def _(expr, assumptions):
+    return False
+
+@InvertiblePredicate.register(OneMatrix)
+def _(expr, assumptions):
+    return expr.shape[0] == 1 and expr.shape[1] == 1
+
+@InvertiblePredicate.register(Transpose)
+def _(expr, assumptions):
+    return ask(Q.invertible(expr.arg), assumptions)
+
+@InvertiblePredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    if not expr.on_diag:
+        return None
+    else:
+        return ask(Q.invertible(expr.parent), assumptions)
+
+@InvertiblePredicate.register(MatrixBase)
+def _(expr, assumptions):
+    if not expr.is_square:
+        return False
+    return expr.rank() == expr.rows
+
+@InvertiblePredicate.register(MatrixExpr)
+def _(expr, assumptions):
+    if not expr.is_square:
+        return False
+    return None
+
+@InvertiblePredicate.register(BlockMatrix)
+def _(expr, assumptions):
+    if not expr.is_square:
+        return False
+    if expr.blockshape == (1, 1):
+        return ask(Q.invertible(expr.blocks[0, 0]), assumptions)
+    expr = reblock_2x2(expr)
+    if expr.blockshape == (2, 2):
+        [[A, B], [C, D]] = expr.blocks.tolist()
+        if ask(Q.invertible(A), assumptions) == True:
+            invertible = ask(Q.invertible(D - C * A.I * B), assumptions)
+            if invertible is not None:
+                return invertible
+        if ask(Q.invertible(B), assumptions) == True:
+            invertible = ask(Q.invertible(C - D * B.I * A), assumptions)
+            if invertible is not None:
+                return invertible
+        if ask(Q.invertible(C), assumptions) == True:
+            invertible = ask(Q.invertible(B - A * C.I * D), assumptions)
+            if invertible is not None:
+                return invertible
+        if ask(Q.invertible(D), assumptions) == True:
+            invertible = ask(Q.invertible(A - B * D.I * C), assumptions)
+            if invertible is not None:
+                return invertible
+    return None
+
+@InvertiblePredicate.register(BlockDiagMatrix)
+def _(expr, assumptions):
+    if expr.rowblocksizes != expr.colblocksizes:
+        return None
+    return fuzzy_and([ask(Q.invertible(a), assumptions) for a in expr.diag])
+
+
+# OrthogonalPredicate
+
+@OrthogonalPredicate.register(MatMul)
+def _(expr, assumptions):
+    factor, mmul = expr.as_coeff_mmul()
+    if (all(ask(Q.orthogonal(arg), assumptions) for arg in mmul.args) and
+            factor == 1):
+        return True
+    if any(ask(Q.invertible(arg), assumptions) is False
+            for arg in mmul.args):
+        return False
+
+@OrthogonalPredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if int_exp:
+        return ask(Q.orthogonal(base), assumptions)
+    return None
+
+@OrthogonalPredicate.register(MatAdd)
+def _(expr, assumptions):
+    if (len(expr.args) == 1 and
+            ask(Q.orthogonal(expr.args[0]), assumptions)):
+        return True
+
+@OrthogonalPredicate.register(MatrixSymbol)
+def _(expr, assumptions):
+    if (not expr.is_square or
+                    ask(Q.invertible(expr), assumptions) is False):
+        return False
+    if Q.orthogonal(expr) in conjuncts(assumptions):
+        return True
+
+@OrthogonalPredicate.register(Identity)
+def _(expr, assumptions):
+    return True
+
+@OrthogonalPredicate.register(ZeroMatrix)
+def _(expr, assumptions):
+    return False
+
+@OrthogonalPredicate.register_many(Inverse, Transpose)
+def _(expr, assumptions):
+    return ask(Q.orthogonal(expr.arg), assumptions)
+
+@OrthogonalPredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    if not expr.on_diag:
+        return None
+    else:
+        return ask(Q.orthogonal(expr.parent), assumptions)
+
+@OrthogonalPredicate.register(Factorization)
+def _(expr, assumptions):
+    return _Factorization(Q.orthogonal, expr, assumptions)
+
+
+# UnitaryPredicate
+
+@UnitaryPredicate.register(MatMul)
+def _(expr, assumptions):
+    factor, mmul = expr.as_coeff_mmul()
+    if (all(ask(Q.unitary(arg), assumptions) for arg in mmul.args) and
+            abs(factor) == 1):
+        return True
+    if any(ask(Q.invertible(arg), assumptions) is False
+            for arg in mmul.args):
+        return False
+
+@UnitaryPredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if int_exp:
+        return ask(Q.unitary(base), assumptions)
+    return None
+
+@UnitaryPredicate.register(MatrixSymbol)
+def _(expr, assumptions):
+    if (not expr.is_square or
+                    ask(Q.invertible(expr), assumptions) is False):
+        return False
+    if Q.unitary(expr) in conjuncts(assumptions):
+        return True
+
+@UnitaryPredicate.register_many(Inverse, Transpose)
+def _(expr, assumptions):
+    return ask(Q.unitary(expr.arg), assumptions)
+
+@UnitaryPredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    if not expr.on_diag:
+        return None
+    else:
+        return ask(Q.unitary(expr.parent), assumptions)
+
+@UnitaryPredicate.register_many(DFT, Identity)
+def _(expr, assumptions):
+    return True
+
+@UnitaryPredicate.register(ZeroMatrix)
+def _(expr, assumptions):
+    return False
+
+@UnitaryPredicate.register(Factorization)
+def _(expr, assumptions):
+    return _Factorization(Q.unitary, expr, assumptions)
+
+
+# FullRankPredicate
+
+@FullRankPredicate.register(MatMul)
+def _(expr, assumptions):
+    if all(ask(Q.fullrank(arg), assumptions) for arg in expr.args):
+        return True
+
+@FullRankPredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if int_exp and ask(~Q.negative(exp), assumptions):
+        return ask(Q.fullrank(base), assumptions)
+    return None
+
+@FullRankPredicate.register(Identity)
+def _(expr, assumptions):
+    return True
+
+@FullRankPredicate.register(ZeroMatrix)
+def _(expr, assumptions):
+    return False
+
+@FullRankPredicate.register(OneMatrix)
+def _(expr, assumptions):
+    return expr.shape[0] == 1 and expr.shape[1] == 1
+
+@FullRankPredicate.register_many(Inverse, Transpose)
+def _(expr, assumptions):
+    return ask(Q.fullrank(expr.arg), assumptions)
+
+@FullRankPredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    if ask(Q.orthogonal(expr.parent), assumptions):
+        return True
+
+
+# PositiveDefinitePredicate
+
+@PositiveDefinitePredicate.register(MatMul)
+def _(expr, assumptions):
+    factor, mmul = expr.as_coeff_mmul()
+    if (all(ask(Q.positive_definite(arg), assumptions)
+            for arg in mmul.args) and factor > 0):
+        return True
+    if (len(mmul.args) >= 2
+            and mmul.args[0] == mmul.args[-1].T
+            and ask(Q.fullrank(mmul.args[0]), assumptions)):
+        return ask(Q.positive_definite(
+            MatMul(*mmul.args[1:-1])), assumptions)
+
+@PositiveDefinitePredicate.register(MatPow)
+def _(expr, assumptions):
+    # a power of a positive definite matrix is positive definite
+    if ask(Q.positive_definite(expr.args[0]), assumptions):
+        return True
+
+@PositiveDefinitePredicate.register(MatAdd)
+def _(expr, assumptions):
+    if all(ask(Q.positive_definite(arg), assumptions)
+            for arg in expr.args):
+        return True
+
+@PositiveDefinitePredicate.register(MatrixSymbol)
+def _(expr, assumptions):
+    if not expr.is_square:
+        return False
+    if Q.positive_definite(expr) in conjuncts(assumptions):
+        return True
+
+@PositiveDefinitePredicate.register(Identity)
+def _(expr, assumptions):
+    return True
+
+@PositiveDefinitePredicate.register(ZeroMatrix)
+def _(expr, assumptions):
+    return False
+
+@PositiveDefinitePredicate.register(OneMatrix)
+def _(expr, assumptions):
+    return expr.shape[0] == 1 and expr.shape[1] == 1
+
+@PositiveDefinitePredicate.register_many(Inverse, Transpose)
+def _(expr, assumptions):
+    return ask(Q.positive_definite(expr.arg), assumptions)
+
+@PositiveDefinitePredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    if not expr.on_diag:
+        return None
+    else:
+        return ask(Q.positive_definite(expr.parent), assumptions)
+
+
+# UpperTriangularPredicate
+
+@UpperTriangularPredicate.register(MatMul)
+def _(expr, assumptions):
+    factor, matrices = expr.as_coeff_matrices()
+    if all(ask(Q.upper_triangular(m), assumptions) for m in matrices):
+        return True
+
+@UpperTriangularPredicate.register(MatAdd)
+def _(expr, assumptions):
+    if all(ask(Q.upper_triangular(arg), assumptions) for arg in expr.args):
+        return True
+
+@UpperTriangularPredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if not int_exp:
+        return None
+    non_negative = ask(~Q.negative(exp), assumptions)
+    if (non_negative or non_negative == False
+                        and ask(Q.invertible(base), assumptions)):
+        return ask(Q.upper_triangular(base), assumptions)
+    return None
+
+@UpperTriangularPredicate.register(MatrixSymbol)
+def _(expr, assumptions):
+    if Q.upper_triangular(expr) in conjuncts(assumptions):
+        return True
+
+@UpperTriangularPredicate.register_many(Identity, ZeroMatrix)
+def _(expr, assumptions):
+    return True
+
+@UpperTriangularPredicate.register(OneMatrix)
+def _(expr, assumptions):
+    return expr.shape[0] == 1 and expr.shape[1] == 1
+
+@UpperTriangularPredicate.register(Transpose)
+def _(expr, assumptions):
+    return ask(Q.lower_triangular(expr.arg), assumptions)
+
+@UpperTriangularPredicate.register(Inverse)
+def _(expr, assumptions):
+    return ask(Q.upper_triangular(expr.arg), assumptions)
+
+@UpperTriangularPredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    if not expr.on_diag:
+        return None
+    else:
+        return ask(Q.upper_triangular(expr.parent), assumptions)
+
+@UpperTriangularPredicate.register(Factorization)
+def _(expr, assumptions):
+    return _Factorization(Q.upper_triangular, expr, assumptions)
+
+# LowerTriangularPredicate
+
+@LowerTriangularPredicate.register(MatMul)
+def _(expr, assumptions):
+    factor, matrices = expr.as_coeff_matrices()
+    if all(ask(Q.lower_triangular(m), assumptions) for m in matrices):
+        return True
+
+@LowerTriangularPredicate.register(MatAdd)
+def _(expr, assumptions):
+    if all(ask(Q.lower_triangular(arg), assumptions) for arg in expr.args):
+        return True
+
+@LowerTriangularPredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if not int_exp:
+        return None
+    non_negative = ask(~Q.negative(exp), assumptions)
+    if (non_negative or non_negative == False
+                        and ask(Q.invertible(base), assumptions)):
+        return ask(Q.lower_triangular(base), assumptions)
+    return None
+
+@LowerTriangularPredicate.register(MatrixSymbol)
+def _(expr, assumptions):
+    if Q.lower_triangular(expr) in conjuncts(assumptions):
+        return True
+
+@LowerTriangularPredicate.register_many(Identity, ZeroMatrix)
+def _(expr, assumptions):
+    return True
+
+@LowerTriangularPredicate.register(OneMatrix)
+def _(expr, assumptions):
+    return expr.shape[0] == 1 and expr.shape[1] == 1
+
+@LowerTriangularPredicate.register(Transpose)
+def _(expr, assumptions):
+    return ask(Q.upper_triangular(expr.arg), assumptions)
+
+@LowerTriangularPredicate.register(Inverse)
+def _(expr, assumptions):
+    return ask(Q.lower_triangular(expr.arg), assumptions)
+
+@LowerTriangularPredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    if not expr.on_diag:
+        return None
+    else:
+        return ask(Q.lower_triangular(expr.parent), assumptions)
+
+@LowerTriangularPredicate.register(Factorization)
+def _(expr, assumptions):
+    return _Factorization(Q.lower_triangular, expr, assumptions)
+
+
+# DiagonalPredicate
+
+def _is_empty_or_1x1(expr):
+    return expr.shape in ((0, 0), (1, 1))
+
+@DiagonalPredicate.register(MatMul)
+def _(expr, assumptions):
+    if _is_empty_or_1x1(expr):
+        return True
+    factor, matrices = expr.as_coeff_matrices()
+    if all(ask(Q.diagonal(m), assumptions) for m in matrices):
+        return True
+
+@DiagonalPredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if not int_exp:
+        return None
+    non_negative = ask(~Q.negative(exp), assumptions)
+    if (non_negative or non_negative == False
+                        and ask(Q.invertible(base), assumptions)):
+        return ask(Q.diagonal(base), assumptions)
+    return None
+
+@DiagonalPredicate.register(MatAdd)
+def _(expr, assumptions):
+    if all(ask(Q.diagonal(arg), assumptions) for arg in expr.args):
+        return True
+
+@DiagonalPredicate.register(MatrixSymbol)
+def _(expr, assumptions):
+    if _is_empty_or_1x1(expr):
+        return True
+    if Q.diagonal(expr) in conjuncts(assumptions):
+        return True
+
+@DiagonalPredicate.register(OneMatrix)
+def _(expr, assumptions):
+    return expr.shape[0] == 1 and expr.shape[1] == 1
+
+@DiagonalPredicate.register_many(Inverse, Transpose)
+def _(expr, assumptions):
+    return ask(Q.diagonal(expr.arg), assumptions)
+
+@DiagonalPredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    if _is_empty_or_1x1(expr):
+        return True
+    if not expr.on_diag:
+        return None
+    else:
+        return ask(Q.diagonal(expr.parent), assumptions)
+
+@DiagonalPredicate.register_many(DiagonalMatrix, DiagMatrix, Identity, ZeroMatrix)
+def _(expr, assumptions):
+    return True
+
+@DiagonalPredicate.register(Factorization)
+def _(expr, assumptions):
+    return _Factorization(Q.diagonal, expr, assumptions)
+
+
+# IntegerElementsPredicate
+
+def BM_elements(predicate, expr, assumptions):
+    """ Block Matrix elements. """
+    return all(ask(predicate(b), assumptions) for b in expr.blocks)
+
+def MS_elements(predicate, expr, assumptions):
+    """ Matrix Slice elements. """
+    return ask(predicate(expr.parent), assumptions)
+
+def MatMul_elements(matrix_predicate, scalar_predicate, expr, assumptions):
+    d = sift(expr.args, lambda x: isinstance(x, MatrixExpr))
+    factors, matrices = d[False], d[True]
+    return fuzzy_and([
+        test_closed_group(Basic(*factors), assumptions, scalar_predicate),
+        test_closed_group(Basic(*matrices), assumptions, matrix_predicate)])
+
+
+@IntegerElementsPredicate.register_many(Determinant, HadamardProduct, MatAdd,
+    Trace, Transpose)
+def _(expr, assumptions):
+    return test_closed_group(expr, assumptions, Q.integer_elements)
+
+@IntegerElementsPredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if not int_exp:
+        return None
+    if exp.is_negative == False:
+        return ask(Q.integer_elements(base), assumptions)
+    return None
+
+@IntegerElementsPredicate.register_many(Identity, OneMatrix, ZeroMatrix)
+def _(expr, assumptions):
+    return True
+
+@IntegerElementsPredicate.register(MatMul)
+def _(expr, assumptions):
+    return MatMul_elements(Q.integer_elements, Q.integer, expr, assumptions)
+
+@IntegerElementsPredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    return MS_elements(Q.integer_elements, expr, assumptions)
+
+@IntegerElementsPredicate.register(BlockMatrix)
+def _(expr, assumptions):
+    return BM_elements(Q.integer_elements, expr, assumptions)
+
+
+# RealElementsPredicate
+
+@RealElementsPredicate.register_many(Determinant, Factorization, HadamardProduct,
+    MatAdd, Trace, Transpose)
+def _(expr, assumptions):
+    return test_closed_group(expr, assumptions, Q.real_elements)
+
+@RealElementsPredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if not int_exp:
+        return None
+    non_negative = ask(~Q.negative(exp), assumptions)
+    if (non_negative or non_negative == False
+                        and ask(Q.invertible(base), assumptions)):
+        return ask(Q.real_elements(base), assumptions)
+    return None
+
+@RealElementsPredicate.register(MatMul)
+def _(expr, assumptions):
+    return MatMul_elements(Q.real_elements, Q.real, expr, assumptions)
+
+@RealElementsPredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    return MS_elements(Q.real_elements, expr, assumptions)
+
+@RealElementsPredicate.register(BlockMatrix)
+def _(expr, assumptions):
+    return BM_elements(Q.real_elements, expr, assumptions)
+
+
+# ComplexElementsPredicate
+
+@ComplexElementsPredicate.register_many(Determinant, Factorization, HadamardProduct,
+    Inverse, MatAdd, Trace, Transpose)
+def _(expr, assumptions):
+    return test_closed_group(expr, assumptions, Q.complex_elements)
+
+@ComplexElementsPredicate.register(MatPow)
+def _(expr, assumptions):
+    # only for integer powers
+    base, exp = expr.args
+    int_exp = ask(Q.integer(exp), assumptions)
+    if not int_exp:
+        return None
+    non_negative = ask(~Q.negative(exp), assumptions)
+    if (non_negative or non_negative == False
+                        and ask(Q.invertible(base), assumptions)):
+        return ask(Q.complex_elements(base), assumptions)
+    return None
+
+@ComplexElementsPredicate.register(MatMul)
+def _(expr, assumptions):
+    return MatMul_elements(Q.complex_elements, Q.complex, expr, assumptions)
+
+@ComplexElementsPredicate.register(MatrixSlice)
+def _(expr, assumptions):
+    return MS_elements(Q.complex_elements, expr, assumptions)
+
+@ComplexElementsPredicate.register(BlockMatrix)
+def _(expr, assumptions):
+    return BM_elements(Q.complex_elements, expr, assumptions)
+
+@ComplexElementsPredicate.register(DFT)
+def _(expr, assumptions):
+    return True