(self, x=Dummy('lambda'), simplify=_simplify)
return PurePoly(list(map(simplify, self.berkowitz()[-1])), x)
Computes characteristic polynomial minors using Berkowitz method.

        A PurePoly is returned so using different variables for ``x`` does
        not affect the comparison or the polynomials:

        Examples
        ========

        >>> from sympy import Matrix
        >>> from sympy.abc import x, y
        >>> A = Matrix([[1, 3], [2, 0]])
        >>> A.berkowitz_charpoly(x) == A.berkowitz_charpoly(y)
        True

        Specifying ``x`` is optional; a Dummy with name ``lambda`` is used by
        default (which looks good when pretty-printed in unicode):

        >>> A.berkowitz_charpoly().as_expr()
        _lambda**2 - _lambda - 6

        No test is done to see that ``x`` doesn't clash with an existing
        symbol, so using the default (``lambda``) or your own Dummy symbol is
        the safest option:

        >>> A = Matrix([[1, 2], [x, 0]])
        >>> A.charpoly().as_expr()
        _lambda**2 - _lambda - 2*x
        >>> A.charpoly(x).as_expr()
        x**2 - 3*x

        See Also
        ========

        berkowitz
Computes characteristic polynomial minors using Berkowitz method.
Computes characteristic polynomial minors using Berkowitz method .
def berkowitz_charpoly(self, x=Dummy('lambda'), simplify=_simplify):
        """Computes characteristic polynomial minors using Berkowitz method.

        A PurePoly is returned so using different variables for ``x`` does
        not affect the comparison or the polynomials:

        Examples
        ========

        >>> from sympy import Matrix
        >>> from sympy.abc import x, y
        >>> A = Matrix([[1, 3], [2, 0]])
        >>> A.berkowitz_charpoly(x) == A.berkowitz_charpoly(y)
        True

        Specifying ``x`` is optional; a Dummy with name ``lambda`` is used by
        default (which looks good when pretty-printed in unicode):

        >>> A.berkowitz_charpoly().as_expr()
        _lambda**2 - _lambda - 6

        No test is done to see that ``x`` doesn't clash with an existing
        symbol, so using the default (``lambda``) or your own Dummy symbol is
        the safest option:

        >>> A = Matrix([[1, 2], [x, 0]])
        >>> A.charpoly().as_expr()
        _lambda**2 - _lambda - 2*x
        >>> A.charpoly(x).as_expr()
        x**2 - 3*x

        See Also
        ========

        berkowitz
        """
        return PurePoly(list(map(simplify, self.berkowitz()[-1])), x)
def berkowitz_charpoly ( self , x = Dummy ( 'lambda' ) , simplify = _simplify ) : return PurePoly ( list ( map ( simplify , self . berkowitz ( ) [ - 1 ] ) ) , x )