Module ImportFrom alias alias ImportFrom alias ImportFrom alias alias ImportFrom alias ImportFrom alias ClassDef bases NameLoad body Expr Str Assign NameStore NameLoad Assign NameStore Call NameLoad Num FunctionDef arguments args NameParam NameParam defaults body Assign NameStore Call NameLoad NameLoad If UnaryOpNot AttributeLoad NameLoad attr body Raise Call NameLoad Str If UnaryOpNot AttributeLoad NameLoad attr body Raise Call NameLoad BinOpMod Str NameLoad Return Call AttributeLoad NameLoad attr NameLoad NameLoad decorator_list FunctionDef arguments args NameParam defaults body Return SubscriptLoad AttributeLoad NameLoad attr Index Num decorator_list NameLoad FunctionDef arguments args NameParam defaults body Return AttributeLoad AttributeLoad NameLoad attr attr decorator_list NameLoad FunctionDef arguments args NameParam defaults body Return AttributeLoad NameLoad attr decorator_list FunctionDef arguments args NameParam defaults body ImportFrom alias Return BinOpDiv Num Call NameLoad AttributeLoad NameLoad attr decorator_list FunctionDef arguments args NameParam defaults kwarg body If Call AttributeLoad NameLoad attr Str NameLoad body Return Call AttributeLoad Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad attr orelse Return Call AttributeLoad AttributeLoad NameLoad attr attr decorator_list decorator_list ImportFrom alias alias ImportFrom alias FunctionDef arguments args NameParam NameParam defaults body Expr Str If Call NameLoad Call AttributeLoad NameLoad attr NameLoad NameLoad body Return AttributeLoad AttributeLoad NameLoad attr attr orelse If Call NameLoad Call AttributeLoad NameLoad attr NameLoad NameLoad body Return Call AttributeLoad AttributeLoad NameLoad attr attr orelse If Call NameLoad Call AttributeLoad NameLoad attr NameLoad NameLoad body Raise Call NameLoad BinOpMod Str AttributeLoad NameLoad attr Return NameLoad decorator_list Assign SubscriptStore NameLoad Index Str NameLoad
N/A __future__ print_function division sympy.core.sympify _sympify sympy.core S Basic sympy.matrices.expressions.matexpr ShapeError sympy.matrices.expressions.matpow MatPow Inverse N/A MatPow N/A N/A 
    The multiplicative inverse of a matrix expression

    This is a symbolic object that simply stores its argument without
    evaluating it. To actually compute the inverse, use the ``.inverse()``
    method of matrices.

    Examples
    ========

    >>> from sympy import MatrixSymbol, Inverse
    >>> A = MatrixSymbol('A', 3, 3)
    >>> B = MatrixSymbol('B', 3, 3)
    >>> Inverse(A)
    A^-1
    >>> A.inverse() == Inverse(A)
    True
    >>> (A*B).inverse()
    B^-1*A^-1
    >>> Inverse(A*B)
    (A*B)^-1

     N/A is_Inverse True N/A exp N/A S -1 __new__ N/A N/A cls mat N/A N/A N/A mat N/A _sympify mat N/A N/A N/A mat is_Matrix N/A N/A N/A TypeError mat should be a matrix N/A N/A N/A mat is_square N/A N/A N/A ShapeError N/A Inverse of non-square matrix %s mat N/A N/A N/A Basic __new__ cls mat N/A arg N/A N/A self N/A N/A N/A N/A N/A self args N/A 0 N/A property shape N/A N/A self N/A N/A N/A N/A N/A self arg shape N/A property _eval_inverse N/A N/A self N/A N/A N/A N/A self arg N/A _eval_determinant N/A N/A self N/A N/A sympy.matrices.expressions.determinant det N/A N/A 1 N/A det N/A self arg N/A doit N/A N/A self N/A hints N/A N/A N/A N/A hints get deep True N/A N/A N/A N/A N/A N/A N/A self arg doit hints inverse N/A N/A N/A N/A N/A self arg inverse N/A N/A sympy.assumptions.ask ask Q sympy.assumptions.refine handlers_dict refine_Inverse N/A N/A expr assumptions N/A N/A N/A 
    >>> from sympy import MatrixSymbol, Q, assuming, refine
    >>> X = MatrixSymbol('X', 2, 2)
    >>> X.I
    X^-1
    >>> with assuming(Q.orthogonal(X)):
    ...     print(refine(X.I))
    X'
     N/A N/A ask N/A N/A Q orthogonal expr assumptions N/A N/A N/A N/A expr arg T N/A N/A N/A ask N/A N/A Q unitary expr assumptions N/A N/A N/A N/A N/A expr arg conjugate N/A N/A N/A ask N/A N/A Q singular expr assumptions N/A N/A N/A ValueError N/A Inverse of singular matrix %s N/A expr arg N/A expr N/A N/A N/A handlers_dict N/A Inverse refine_Inverse