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- from sympy.core.assumptions import check_assumptions
- from sympy.core.logic import fuzzy_and
- from sympy.core.sympify import _sympify
- from sympy.sets.sets import Set
- from .matexpr import MatrixExpr
- class MatrixSet(Set):
- """
- MatrixSet represents the set of matrices with ``shape = (n, m)`` over the
- given set.
- Examples
- ========
- >>> from sympy.matrices import MatrixSet
- >>> from sympy import S, I, Matrix
- >>> M = MatrixSet(2, 2, set=S.Reals)
- >>> X = Matrix([[1, 2], [3, 4]])
- >>> X in M
- True
- >>> X = Matrix([[1, 2], [I, 4]])
- >>> X in M
- False
- """
- is_empty = False
- def __new__(cls, n, m, set):
- n, m, set = _sympify(n), _sympify(m), _sympify(set)
- cls._check_dim(n)
- cls._check_dim(m)
- if not isinstance(set, Set):
- raise TypeError("{} should be an instance of Set.".format(set))
- return Set.__new__(cls, n, m, set)
- @property
- def shape(self):
- return self.args[:2]
- @property
- def set(self):
- return self.args[2]
- def _contains(self, other):
- if not isinstance(other, MatrixExpr):
- raise TypeError("{} should be an instance of MatrixExpr.".format(other))
- if other.shape != self.shape:
- are_symbolic = any(_sympify(x).is_Symbol for x in other.shape + self.shape)
- if are_symbolic:
- return None
- return False
- return fuzzy_and(self.set.contains(x) for x in other)
- @classmethod
- def _check_dim(cls, dim):
- """Helper function to check invalid matrix dimensions"""
- ok = check_assumptions(dim, integer=True, nonnegative=True)
- if ok is False:
- raise ValueError(
- "The dimension specification {} should be "
- "a nonnegative integer.".format(dim))
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