from mpmath.matrices.matrices import _matrix from sympy.core import Basic, Dict, Tuple from sympy.core.numbers import Integer from sympy.core.cache import cacheit from sympy.core.sympify import _sympy_converter as sympify_converter, _sympify from sympy.matrices.dense import DenseMatrix from sympy.matrices.expressions import MatrixExpr from sympy.matrices.matrices import MatrixBase from sympy.matrices.repmatrix import RepMatrix from sympy.matrices.sparse import SparseRepMatrix from sympy.multipledispatch import dispatch def sympify_matrix(arg): return arg.as_immutable() sympify_converter[MatrixBase] = sympify_matrix def sympify_mpmath_matrix(arg): mat = [_sympify(x) for x in arg] return ImmutableDenseMatrix(arg.rows, arg.cols, mat) sympify_converter[_matrix] = sympify_mpmath_matrix class ImmutableRepMatrix(RepMatrix, MatrixExpr): # type: ignore """Immutable matrix based on RepMatrix Uses DomainMAtrix as the internal representation. """ # # This is a subclass of RepMatrix that adds/overrides some methods to make # the instances Basic and immutable. ImmutableRepMatrix is a superclass for # both ImmutableDenseMatrix and ImmutableSparseMatrix. # def __new__(cls, *args, **kwargs): return cls._new(*args, **kwargs) __hash__ = MatrixExpr.__hash__ def copy(self): return self @property def cols(self): return self._cols @property def rows(self): return self._rows @property def shape(self): return self._rows, self._cols def as_immutable(self): return self def _entry(self, i, j, **kwargs): return self[i, j] def __setitem__(self, *args): raise TypeError("Cannot set values of {}".format(self.__class__)) def is_diagonalizable(self, reals_only=False, **kwargs): return super().is_diagonalizable( reals_only=reals_only, **kwargs) is_diagonalizable.__doc__ = SparseRepMatrix.is_diagonalizable.__doc__ is_diagonalizable = cacheit(is_diagonalizable) class ImmutableDenseMatrix(DenseMatrix, ImmutableRepMatrix): # type: ignore """Create an immutable version of a matrix. Examples ======== >>> from sympy import eye, ImmutableMatrix >>> ImmutableMatrix(eye(3)) Matrix([ [1, 0, 0], [0, 1, 0], [0, 0, 1]]) >>> _[0, 0] = 42 Traceback (most recent call last): ... TypeError: Cannot set values of ImmutableDenseMatrix """ # MatrixExpr is set as NotIterable, but we want explicit matrices to be # iterable _iterable = True _class_priority = 8 _op_priority = 10.001 @classmethod def _new(cls, *args, **kwargs): if len(args) == 1 and isinstance(args[0], ImmutableDenseMatrix): return args[0] if kwargs.get('copy', True) is False: if len(args) != 3: raise TypeError("'copy=False' requires a matrix be initialized as rows,cols,[list]") rows, cols, flat_list = args else: rows, cols, flat_list = cls._handle_creation_inputs(*args, **kwargs) flat_list = list(flat_list) # create a shallow copy rep = cls._flat_list_to_DomainMatrix(rows, cols, flat_list) return cls._fromrep(rep) @classmethod def _fromrep(cls, rep): rows, cols = rep.shape flat_list = rep.to_sympy().to_list_flat() obj = Basic.__new__(cls, Integer(rows), Integer(cols), Tuple(*flat_list, sympify=False)) obj._rows = rows obj._cols = cols obj._rep = rep return obj # make sure ImmutableDenseMatrix is aliased as ImmutableMatrix ImmutableMatrix = ImmutableDenseMatrix class ImmutableSparseMatrix(SparseRepMatrix, ImmutableRepMatrix): # type:ignore """Create an immutable version of a sparse matrix. Examples ======== >>> from sympy import eye, ImmutableSparseMatrix >>> ImmutableSparseMatrix(1, 1, {}) Matrix([[0]]) >>> ImmutableSparseMatrix(eye(3)) Matrix([ [1, 0, 0], [0, 1, 0], [0, 0, 1]]) >>> _[0, 0] = 42 Traceback (most recent call last): ... TypeError: Cannot set values of ImmutableSparseMatrix >>> _.shape (3, 3) """ is_Matrix = True _class_priority = 9 @classmethod def _new(cls, *args, **kwargs): rows, cols, smat = cls._handle_creation_inputs(*args, **kwargs) rep = cls._smat_to_DomainMatrix(rows, cols, smat) return cls._fromrep(rep) @classmethod def _fromrep(cls, rep): rows, cols = rep.shape smat = rep.to_sympy().to_dok() obj = Basic.__new__(cls, Integer(rows), Integer(cols), Dict(smat)) obj._rows = rows obj._cols = cols obj._rep = rep return obj @dispatch(ImmutableDenseMatrix, ImmutableDenseMatrix) def _eval_is_eq(lhs, rhs): # noqa:F811 """Helper method for Equality with matrices.sympy. Relational automatically converts matrices to ImmutableDenseMatrix instances, so this method only applies here. Returns True if the matrices are definitively the same, False if they are definitively different, and None if undetermined (e.g. if they contain Symbols). Returning None triggers default handling of Equalities. """ if lhs.shape != rhs.shape: return False return (lhs - rhs).is_zero_matrix