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from mpmath.matrices.matrices import _matrix
from sympy.core import Basic, Dict, Integer, Tuple
from sympy.core.cache import cacheit
from sympy.core.sympify import 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.sparse import SparseMatrix
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 ImmutableDenseMatrix(DenseMatrix, MatrixExpr): # type: ignore
"""Create an immutable version of a matrix.
Examples
========
>>> from sympy import eye
>>> from sympy.matrices import 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
def __new__(cls, *args, **kwargs):
return cls._new(*args, **kwargs)
__hash__ = MatrixExpr.__hash__
@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
obj = Basic.__new__(cls,
Integer(rows),
Integer(cols),
Tuple(*flat_list))
obj._rows = rows
obj._cols = cols
obj._mat = flat_list
return obj
def _entry(self, i, j, **kwargs):
return DenseMatrix.__getitem__(self, (i, j))
def __setitem__(self, *args):
raise TypeError("Cannot set values of {}".format(self.__class__))
def _eval_extract(self, rowsList, colsList):
# self._mat is a Tuple. It is slightly faster to index a
# tuple over a Tuple, so grab the internal tuple directly
mat = self._mat
cols = self.cols
indices = (i * cols + j for i in rowsList for j in colsList)
return self._new(len(rowsList), len(colsList),
Tuple(*(mat[i] for i in indices), sympify=False), copy=False)
@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 is_diagonalizable(self, reals_only=False, **kwargs):
return super().is_diagonalizable(
reals_only=reals_only, **kwargs)
is_diagonalizable.__doc__ = DenseMatrix.is_diagonalizable.__doc__
is_diagonalizable = cacheit(is_diagonalizable)
# make sure ImmutableDenseMatrix is aliased as ImmutableMatrix
ImmutableMatrix = ImmutableDenseMatrix
class ImmutableSparseMatrix(SparseMatrix, MatrixExpr): # type:ignore
"""Create an immutable version of a sparse matrix.
Examples
========
>>> from sympy import eye
>>> from sympy.matrices.immutable import 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
def __new__(cls, *args, **kwargs):
return cls._new(*args, **kwargs)
__hash__ = MatrixExpr.__hash__
@classmethod
def _new(cls, *args, **kwargs):
rows, cols, smat = cls._handle_creation_inputs(*args, **kwargs)
obj = Basic.__new__(cls, Integer(rows), Integer(cols), Dict(smat))
obj._rows = rows
obj._cols = cols
obj._smat = smat
return obj
def __setitem__(self, *args):
raise TypeError("Cannot set values of ImmutableSparseMatrix")
def _entry(self, i, j, **kwargs):
return SparseMatrix.__getitem__(self, (i, j))
@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 is_diagonalizable(self, reals_only=False, **kwargs):
return super().is_diagonalizable(
reals_only=reals_only, **kwargs)
is_diagonalizable.__doc__ = SparseMatrix.is_diagonalizable.__doc__
is_diagonalizable = cacheit(is_diagonalizable)
@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
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