(self, iszerofunc=_iszero)
return self._new(red[:, big.rows:])
Calculates the inverse using Gaussian elimination.

        See Also
        ========

        inv
        inverse_LU
        inverse_ADJ
Calculates the inverse using Gaussian elimination.
Calculates the inverse using Gaussian elimination .
def inverse_GE(self, iszerofunc=_iszero):
        """Calculates the inverse using Gaussian elimination.

        See Also
        ========

        inv
        inverse_LU
        inverse_ADJ
        """
        from .dense import Matrix
        if not self.is_square:
            raise NonSquareMatrixError("A Matrix must be square to invert.")

        big = Matrix.hstack(self.as_mutable(), Matrix.eye(self.rows))
        red = big.rref(iszerofunc=iszerofunc, simplify=True)[0]
        if any(iszerofunc(red[j, j]) for j in range(red.rows)):
            raise ValueError("Matrix det == 0; not invertible.")

        return self._new(red[:, big.rows:])
def inverse_GE ( self , iszerofunc = _iszero ) : from . dense import Matrix if not self . is_square : raise NonSquareMatrixError ( "A Matrix must be square to invert." ) big = Matrix . hstack ( self . as_mutable ( ) , Matrix . eye ( self . rows ) ) red = big . rref ( iszerofunc = iszerofunc , simplify = True ) [ 0 ] if any ( iszerofunc ( red [ j , j ] ) for j in range ( red . rows ) ) : raise ValueError ( "Matrix det == 0; not invertible." ) return self . _new ( red [ : , big . rows : ] )