def as_real_imag(self, deep=True, **hints):
        from sympy.core.symbol import symbols
        from sympy.polys.polytools import poly
        from sympy.core.function import expand_multinomial
        if self.exp.is_Integer:
            exp = self.exp
            re, im = self.base.as_real_imag(deep=deep)
            if re.func == C.re or im.func == C.im:
                return self, S.Zero
            a, b = symbols('a b', cls=Dummy)
            if exp >= 0:
                if re.is_Number and im.is_Number:
                    # We can be more efficient in this case
                    expr = expand_multinomial(self.base**exp)
                    return expr.as_real_imag()

                expr = poly((a + b)**exp) # a = re, b = im; expr = (a + b*I)**exp
            else:
                mag = re**2 + im**2
                re, im = re/mag, -im/mag
                if re.is_Number and im.is_Number:
                    # We can be more efficient in this case
                    expr = expand_multinomial((re + im*S.ImaginaryUnit)**-exp)
                    return expr.as_real_imag()

                expr = poly((a + b)**-exp)

            # Terms with even b powers will be real
            r = [i for i in expr.terms() if not i[0][1] % 2]
            re_part = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
            # Terms with odd b powers will be imaginary
            r = [i for i in expr.terms() if i[0][1] % 4 == 1]
            im_part1 = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
            r = [i for i in expr.terms() if i[0][1] % 4 == 3]
            im_part3 = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])

            return (re_part.subs({a: re, b: S.ImaginaryUnit*im}),
            im_part1.subs({a: re, b: im}) + im_part3.subs({a: re, b: -im}))

        elif self.exp.is_Rational:
            # NOTE: This is not totally correct since for x**(p/q) with
            #       x being imaginary there are actually q roots, but
            #       only a single one is returned from here.
            re, im = self.base.as_real_imag(deep=deep)
            if re.func == C.re or im.func == C.im:
                return self, S.Zero
            r = Pow(Pow(re, 2) + Pow(im, 2), S.Half)
            t = C.atan2(im, re)

            rp, tp = Pow(r, self.exp), t*self.exp

            return (rp*C.cos(tp), rp*C.sin(tp))
        else:

            if deep:
                hints['complex'] = False
                return (C.re(self.expand(deep, **hints)),
                        C.im(self.expand(deep, **hints)))
            else:
                return (C.re(self), C.im(self))

def test_issues_5919_6830():
    # issue 5919
    n = -1 + 1 / x
    z = n / x / (-n) ** 2 - 1 / n / x
    assert expand(z) == 1 / (x ** 2 - 2 * x + 1) - 1 / (x - 2 + 1 / x) - 1 / (-x + 1)

    # issue 6830
    p = (1 + x) ** 2
    assert expand_multinomial((1 + x * p) ** 2) == (
        x ** 2 * (x ** 4 + 4 * x ** 3 + 6 * x ** 2 + 4 * x + 1) + 2 * x * (x ** 2 + 2 * x + 1) + 1
    )
    assert expand_multinomial((1 + (y + x) * p) ** 2) == (
        2 * ((x + y) * (x ** 2 + 2 * x + 1))
        + (x ** 2 + 2 * x * y + y ** 2) * (x ** 4 + 4 * x ** 3 + 6 * x ** 2 + 4 * x + 1)
        + 1
    )
    A = Symbol("A", commutative=False)
    p = (1 + A) ** 2
    assert expand_multinomial((1 + x * p) ** 2) == (
        x ** 2 * (1 + 4 * A + 6 * A ** 2 + 4 * A ** 3 + A ** 4) + 2 * x * (1 + 2 * A + A ** 2) + 1
    )
    assert expand_multinomial((1 + (y + x) * p) ** 2) == (
        (x + y) * (1 + 2 * A + A ** 2) * 2
        + (x ** 2 + 2 * x * y + y ** 2) * (1 + 4 * A + 6 * A ** 2 + 4 * A ** 3 + A ** 4)
        + 1
    )
    assert expand_multinomial((1 + (y + x) * p) ** 3) == (
        (x + y) * (1 + 2 * A + A ** 2) * 3
        + (x ** 2 + 2 * x * y + y ** 2) * (1 + 4 * A + 6 * A ** 2 + 4 * A ** 3 + A ** 4) * 3
        + (x ** 3 + 3 * x ** 2 * y + 3 * x * y ** 2 + y ** 3)
        * (1 + 6 * A + 15 * A ** 2 + 20 * A ** 3 + 15 * A ** 4 + 6 * A ** 5 + A ** 6)
        + 1
    )
    # unevaluate powers
    eq = Pow((x + 1) * ((A + 1) ** 2), 2, evaluate=False)
    # - in this case the base is not an Add so no further
    #   expansion is done
    assert expand_multinomial(eq) == (x ** 2 + 2 * x + 1) * (1 + 4 * A + 6 * A ** 2 + 4 * A ** 3 + A ** 4)
    # - but here, the expanded base *is* an Add so it gets expanded
    eq = Pow(((A + 1) ** 2), 2, evaluate=False)
    assert expand_multinomial(eq) == 1 + 4 * A + 6 * A ** 2 + 4 * A ** 3 + A ** 4

    # coverage
    def ok(a, b, n):
        e = (a + I * b) ** n
        return verify_numerically(e, expand_multinomial(e))

    for a in [2, S.Half]:
        for b in [3, S(1) / 3]:
            for n in range(2, 6):
                assert ok(a, b, n)

    assert expand_multinomial((x + 1 + O(z)) ** 2) == 1 + 2 * x + x ** 2 + O(z)
    assert expand_multinomial((x + 1 + O(z)) ** 3) == 1 + 3 * x + 3 * x ** 2 + x ** 3 + O(z)

    assert expand_multinomial(3 ** (x + y + 3)) == 27 * 3 ** (x + y)

def test_better_sqrt():
    n = Symbol('n', integer=True, nonnegative=True)
    assert sqrt(3 + 4*I) == 2 + I
    assert sqrt(3 - 4*I) == 2 - I
    assert sqrt(-3 - 4*I) == 1 - 2*I
    assert sqrt(-3 + 4*I) == 1 + 2*I
    assert sqrt(32 + 24*I) == 6 + 2*I
    assert sqrt(32 - 24*I) == 6 - 2*I
    assert sqrt(-32 - 24*I) == 2 - 6*I
    assert sqrt(-32 + 24*I) == 2 + 6*I

    # triple (3, 4, 5):
    # parity of 3 matches parity of 5 and
    # den, 4, is a square
    assert sqrt((3 + 4*I)/4) == 1 + I/2
    # triple (8, 15, 17)
    # parity of 8 doesn't match parity of 17 but
    # den/2, 8/2, is a square
    assert sqrt((8 + 15*I)/8) == (5 + 3*I)/4
    # handle the denominator
    assert sqrt((3 - 4*I)/25) == (2 - I)/5
    assert sqrt((3 - 4*I)/26) == (2 - I)/sqrt(26)
    # mul
    #  issue #12739
    assert sqrt((3 + 4*I)/(3 - 4*I)) == (3 + 4*I)/5
    assert sqrt(2/(3 + 4*I)) == sqrt(2)/5*(2 - I)
    assert sqrt(n/(3 + 4*I)).subs(n, 2) == sqrt(2)/5*(2 - I)
    assert sqrt(-2/(3 + 4*I)) == sqrt(2)/5*(1 + 2*I)
    assert sqrt(-n/(3 + 4*I)).subs(n, 2) == sqrt(2)/5*(1 + 2*I)
    # power
    assert sqrt(1/(3 + I*4)) == (2 - I)/5
    assert sqrt(1/(3 - I)) == sqrt(10)*sqrt(3 + I)/10
    # symbolic
    i = symbols('i', imaginary=True)
    assert sqrt(3/i) == Mul(sqrt(3), sqrt(-i)/abs(i), evaluate=False)
    # multiples of 1/2; don't make this too automatic
    assert sqrt((3 + 4*I))**3 == (2 + I)**3
    assert Pow(3 + 4*I, S(3)/2) == 2 + 11*I
    assert Pow(6 + 8*I, S(3)/2) == 2*sqrt(2)*(2 + 11*I)
    n, d = (3 + 4*I), (3 - 4*I)**3
    a = n/d
    assert a.args == (1/d, n)
    eq = sqrt(a)
    assert eq.args == (a, S.Half)
    assert expand_multinomial(eq) == sqrt((-117 + 44*I)*(3 + 4*I))/125
    assert eq.expand() == (7 - 24*I)/125

    # issue 12775
    # pos im part
    assert sqrt(2*I) == (1 + I)
    assert sqrt(2*9*I) == Mul(3, 1 + I, evaluate=False)
    assert Pow(2*I, 3*S.Half) == (1 + I)**3
    # neg im part
    assert sqrt(-I/2) == Mul(S.Half, 1 - I, evaluate=False)
    # fractional im part
    assert Pow(-9*I/2, 3/S(2)) == 27*(1 - I)**3/8

 def _eval_power(self, e):
     if e.is_Rational and self.is_number:
         from sympy.core.evalf import pure_complex
         from sympy.core.mul import _unevaluated_Mul
         from sympy.core.exprtools import factor_terms
         from sympy.core.function import expand_multinomial
         from sympy.functions.elementary.complexes import sign
         from sympy.functions.elementary.miscellaneous import sqrt
         ri = pure_complex(self)
         if ri:
             r, i = ri
             if e.q == 2:
                 D = sqrt(r**2 + i**2)
                 if D.is_Rational:
                     # (r, i, D) is a Pythagorean triple
                     root = sqrt(factor_terms((D - r)/2))**e.p
                     return root*expand_multinomial((
                         # principle value
                         (D + r)/abs(i) + sign(i)*S.ImaginaryUnit)**e.p)
             elif e == -1:
                 return _unevaluated_Mul(
                     r - i*S.ImaginaryUnit,
                     1/(r**2 + i**2))

    def _eval_nseries(self, x, n, logx):
        # NOTE! This function is an important part of the gruntz algorithm
        #       for computing limits. It has to return a generalized power
        #       series with coefficients in C(log, log(x)). In more detail:
        # It has to return an expression
        #     c_0*x**e_0 + c_1*x**e_1 + ... (finitely many terms)
        # where e_i are numbers (not necessarily integers) and c_i are
        # expressions involving only numbers, the log function, and log(x).
        from sympy import powsimp, collect, exp, log, O, ceiling
        b, e = self.args
        if e.is_Integer:
            if e > 0:
                # positive integer powers are easy to expand, e.g.:
                # sin(x)**4 = (x-x**3/3+...)**4 = ...
                return expand_multinomial(self.func(b._eval_nseries(x, n=n,
                    logx=logx), e), deep=False)
            elif e is S.NegativeOne:
                # this is also easy to expand using the formula:
                # 1/(1 + x) = 1 - x + x**2 - x**3 ...
                # so we need to rewrite base to the form "1+x"

                nuse = n
                cf = 1

                try:
                    ord = b.as_leading_term(x)
                    cf = C.Order(ord, x).getn()
                    if cf and cf.is_Number:
                        nuse = n + 2*ceiling(cf)
                    else:
                        cf = 1
                except NotImplementedError:
                    pass

                b_orig, prefactor = b, O(1, x)
                while prefactor.is_Order:
                    nuse += 1
                    b = b_orig._eval_nseries(x, n=nuse, logx=logx)
                    prefactor = b.as_leading_term(x)

                # express "rest" as: rest = 1 + k*x**l + ... + O(x**n)
                rest = expand_mul((b - prefactor)/prefactor)

                if rest.is_Order:
                    return 1/prefactor + rest/prefactor + O(x**n, x)

                k, l = rest.leadterm(x)
                if l.is_Rational and l > 0:
                    pass
                elif l.is_number and l > 0:
                    l = l.evalf()
                elif l == 0:
                    k = k.simplify()
                    if k == 0:
                        # if prefactor == w**4 + x**2*w**4 + 2*x*w**4, we need to
                        # factor the w**4 out using collect:
                        return 1/collect(prefactor, x)
                    else:
                        raise NotImplementedError()
                else:
                    raise NotImplementedError()

                if cf < 0:
                    cf = S.One/abs(cf)

                try:
                    dn = C.Order(1/prefactor, x).getn()
                    if dn and dn < 0:
                        pass
                    else:
                        dn = 0
                except NotImplementedError:
                    dn = 0

                terms = [1/prefactor]
                for m in xrange(1, ceiling((n - dn)/l*cf)):
                    new_term = terms[-1]*(-rest)
                    if new_term.is_Pow:
                        new_term = new_term._eval_expand_multinomial(
                            deep=False)
                    else:
                        new_term = expand_mul(new_term, deep=False)
                    terms.append(new_term)
                terms.append(O(x**n, x))
                return powsimp(Add(*terms), deep=True, combine='exp')
            else:
                # negative powers are rewritten to the cases above, for
                # example:
                # sin(x)**(-4) = 1/( sin(x)**4) = ...
                # and expand the denominator:
                nuse, denominator = n, O(1, x)
                while denominator.is_Order:
                    denominator = (b**(-e))._eval_nseries(x, n=nuse, logx=logx)
                    nuse += 1
                if 1/denominator == self:
                    return self
                # now we have a type 1/f(x), that we know how to expand
                return (1/denominator)._eval_nseries(x, n=n, logx=logx)

        if e.has(Symbol):
#.........这里部分代码省略.........

    def _eval_expand_multinomial(self, **hints):
        """(a+b+..) ** n -> a**n + n*a**(n-1)*b + .., n is nonzero integer"""

        base, exp = self.args
        result = self

        if exp.is_Rational and exp.p > 0 and base.is_Add:
            if not exp.is_Integer:
                n = Integer(exp.p // exp.q)

                if not n:
                    return result
                else:
                    radical, result = self.func(base, exp - n), []

                    expanded_base_n = self.func(base, n)
                    if expanded_base_n.is_Pow:
                        expanded_base_n = \
                            expanded_base_n._eval_expand_multinomial()
                    for term in Add.make_args(expanded_base_n):
                        result.append(term*radical)

                    return Add(*result)

            n = int(exp)

            if base.is_commutative:
                order_terms, other_terms = [], []

                for b in base.args:
                    if b.is_Order:
                        order_terms.append(b)
                    else:
                        other_terms.append(b)

                if order_terms:
                    # (f(x) + O(x^n))^m -> f(x)^m + m*f(x)^{m-1} *O(x^n)
                    f = Add(*other_terms)
                    o = Add(*order_terms)

                    if n == 2:
                        return expand_multinomial(f**n, deep=False) + n*f*o
                    else:
                        g = expand_multinomial(f**(n - 1), deep=False)
                        return expand_mul(f*g, deep=False) + n*g*o

                if base.is_number:
                    # Efficiently expand expressions of the form (a + b*I)**n
                    # where 'a' and 'b' are real numbers and 'n' is integer.
                    a, b = base.as_real_imag()

                    if a.is_Rational and b.is_Rational:
                        if not a.is_Integer:
                            if not b.is_Integer:
                                k = self.func(a.q * b.q, n)
                                a, b = a.p*b.q, a.q*b.p
                            else:
                                k = self.func(a.q, n)
                                a, b = a.p, a.q*b
                        elif not b.is_Integer:
                            k = self.func(b.q, n)
                            a, b = a*b.q, b.p
                        else:
                            k = 1

                        a, b, c, d = int(a), int(b), 1, 0

                        while n:
                            if n & 1:
                                c, d = a*c - b*d, b*c + a*d
                                n -= 1
                            a, b = a*a - b*b, 2*a*b
                            n //= 2

                        I = S.ImaginaryUnit

                        if k == 1:
                            return c + I*d
                        else:
                            return Integer(c)/k + I*d/k

                p = other_terms
                # (x+y)**3 -> x**3 + 3*x**2*y + 3*x*y**2 + y**3
                # in this particular example:
                # p = [x,y]; n = 3
                # so now it's easy to get the correct result -- we get the
                # coefficients first:
                from sympy import multinomial_coefficients
                from sympy.polys.polyutils import basic_from_dict
                expansion_dict = multinomial_coefficients(len(p), n)
                # in our example: {(3, 0): 1, (1, 2): 3, (0, 3): 1, (2, 1): 3}
                # and now construct the expression.
                return basic_from_dict(expansion_dict, *p)
            else:
                if n == 2:
                    return Add(*[f*g for f in base.args for g in base.args])
                else:
                    multi = (base**(n - 1))._eval_expand_multinomial()
                    if multi.is_Add:
                        return Add(*[f*g for f in base.args
#.........这里部分代码省略.........

 def ok(a, b, n):
     e = (a + I*b)**n
     return verify_numerically(e, expand_multinomial(e))

def _mexpand(expr):
    return expand_mul(expand_multinomial(expr))

def _minpoly_groebner(ex, x, cls):
    """
    Computes the minimal polynomial of an algebraic number
    using Groebner bases

    Examples
    ========

    >>> from sympy import minimal_polynomial, sqrt, Rational
    >>> from sympy.abc import x
    >>> minimal_polynomial(sqrt(2) + 3*Rational(1, 3), x, compose=False)
    x**2 - 2*x - 1

    """
    from sympy.polys.polytools import degree
    from sympy.core.function import expand_multinomial

    generator = numbered_symbols('a', cls=Dummy)
    mapping, symbols, replace = {}, {}, []

    def update_mapping(ex, exp, base=None):
        a = next(generator)
        symbols[ex] = a

        if base is not None:
            mapping[ex] = a**exp + base
        else:
            mapping[ex] = exp.as_expr(a)

        return a

    def bottom_up_scan(ex):
        if ex.is_Atom:
            if ex is S.ImaginaryUnit:
                if ex not in mapping:
                    return update_mapping(ex, 2, 1)
                else:
                    return symbols[ex]
            elif ex.is_Rational:
                return ex
        elif ex.is_Add:
            return Add(*[ bottom_up_scan(g) for g in ex.args ])
        elif ex.is_Mul:
            return Mul(*[ bottom_up_scan(g) for g in ex.args ])
        elif ex.is_Pow:
            if ex.exp.is_Rational:
                if ex.exp < 0 and ex.base.is_Add:
                    coeff, terms = ex.base.as_coeff_add()
                    elt, _ = primitive_element(terms, polys=True)

                    alg = ex.base - coeff

                    # XXX: turn this into eval()
                    inverse = invert(elt.gen + coeff, elt).as_expr()
                    base = inverse.subs(elt.gen, alg).expand()

                    if ex.exp == -1:
                        return bottom_up_scan(base)
                    else:
                        ex = base**(-ex.exp)
                if not ex.exp.is_Integer:
                    base, exp = (
                        ex.base**ex.exp.p).expand(), Rational(1, ex.exp.q)
                else:
                    base, exp = ex.base, ex.exp
                base = bottom_up_scan(base)
                expr = base**exp

                if expr not in mapping:
                    return update_mapping(expr, 1/exp, -base)
                else:
                    return symbols[expr]
        elif ex.is_AlgebraicNumber:
            if ex.root not in mapping:
                return update_mapping(ex.root, ex.minpoly)
            else:
                return symbols[ex.root]

        raise NotAlgebraic("%s doesn't seem to be an algebraic number" % ex)

    def simpler_inverse(ex):
        """
        Returns True if it is more likely that the minimal polynomial
        algorithm works better with the inverse
        """
        if ex.is_Pow:
            if (1/ex.exp).is_integer and ex.exp < 0:
                if ex.base.is_Add:
                    return True
        if ex.is_Mul:
            hit = True
            a = []
            for p in ex.args:
                if p.is_Add:
                    return False
                if p.is_Pow:
                    if p.base.is_Add and p.exp > 0:
                        return False

            if hit:
#.........这里部分代码省略.........

def minimal_polynomial(ex, x=None, **args):
    """
    Computes the minimal polynomial of an algebraic number.

    Parameters
    ==========

    ex : algebraic number expression

    x : indipendent variable of the minimal polynomial

    Options
    =======

    compose : if ``True`` _minpoly1`` is used, else the ``groebner`` algorithm

    polys : if ``True`` returns a ``Poly`` object

    Notes
    =====

    By default ``compose=True``, the minimal polynomial of the subexpressions of ``ex``
    are computed, then the arithmetic operations on them are performed using the resultant
    and factorization.
    If ``compose=False``, a bottom-up algorithm is used with ``groebner``.
    The default algorithm stalls less frequently.

    Examples
    ========

    >>> from sympy import minimal_polynomial, sqrt, solve
    >>> from sympy.abc import x

    >>> minimal_polynomial(sqrt(2), x)
    x**2 - 2
    >>> minimal_polynomial(sqrt(2) + sqrt(3), x)
    x**4 - 10*x**2 + 1
    >>> minimal_polynomial(solve(x**3 + x + 3)[0], x)
    x**3 + x + 3

    """
    from sympy.polys.polytools import degree
    from sympy.core.function import expand_multinomial
    from sympy.core.basic import preorder_traversal

    compose = args.get('compose', True)
    polys = args.get('polys', False)
    ex = sympify(ex)
    for expr in preorder_traversal(ex):
        if expr.is_AlgebraicNumber:
            compose = False
            break

    if ex.is_AlgebraicNumber:
        compose = False

    if x is not None:
        x, cls = sympify(x), Poly
    else:
        x, cls = Dummy('x'), PurePoly

    if compose:
        result = _minpoly1(ex, x)
        result = result.primitive()[1]
        c = result.coeff(x**degree(result, x))
        if c < 0:
            result = expand_mul(-result)
            c = -c
        return cls(result, x, field=True) if polys else result

    generator = numbered_symbols('a', cls=Dummy)
    mapping, symbols, replace = {}, {}, []

    def update_mapping(ex, exp, base=None):
        a = generator.next()
        symbols[ex] = a

        if base is not None:
            mapping[ex] = a**exp + base
        else:
            mapping[ex] = exp.as_expr(a)

        return a

    def bottom_up_scan(ex):
        if ex.is_Atom:
            if ex is S.ImaginaryUnit:
                if ex not in mapping:
                    return update_mapping(ex, 2, 1)
                else:
                    return symbols[ex]
            elif ex.is_Rational:
                return ex
        elif ex.is_Add:
            return Add(*[ bottom_up_scan(g) for g in ex.args ])
        elif ex.is_Mul:
            return Mul(*[ bottom_up_scan(g) for g in ex.args ])
        elif ex.is_Pow:
            if ex.exp.is_Rational:
                if ex.exp < 0 and ex.base.is_Add:
#.........这里部分代码省略.........

def minimal_polynomial(ex, x=None, **args):
    """
    Computes the minimal polynomial of an algebraic number.

    Examples
    ========

    >>> from sympy import minimal_polynomial, sqrt
    >>> from sympy.abc import x

    >>> minimal_polynomial(sqrt(2), x)
    x**2 - 2
    >>> minimal_polynomial(sqrt(2) + sqrt(3), x)
    x**4 - 10*x**2 + 1

    """
    from sympy.polys.polytools import degree
    from sympy.core.function import expand_mul, expand_multinomial
    from sympy.simplify.simplify import _is_sum_surds

    generator = numbered_symbols("a", cls=Dummy)
    mapping, symbols, replace = {}, {}, []

    ex = sympify(ex)

    if x is not None:
        x, cls = sympify(x), Poly
    else:
        x, cls = Dummy("x"), PurePoly

    def update_mapping(ex, exp, base=None):
        a = generator.next()
        symbols[ex] = a

        if base is not None:
            mapping[ex] = a ** exp + base
        else:
            mapping[ex] = exp.as_expr(a)

        return a

    def bottom_up_scan(ex):
        if ex.is_Atom:
            if ex is S.ImaginaryUnit:
                if ex not in mapping:
                    return update_mapping(ex, 2, 1)
                else:
                    return symbols[ex]
            elif ex.is_Rational:
                return ex
        elif ex.is_Add:
            return Add(*[bottom_up_scan(g) for g in ex.args])
        elif ex.is_Mul:
            return Mul(*[bottom_up_scan(g) for g in ex.args])
        elif ex.is_Pow:
            if ex.exp.is_Rational:
                if ex.exp < 0 and ex.base.is_Add:
                    coeff, terms = ex.base.as_coeff_add()
                    elt, _ = primitive_element(terms, polys=True)

                    alg = ex.base - coeff

                    # XXX: turn this into eval()
                    inverse = invert(elt.gen + coeff, elt).as_expr()
                    base = inverse.subs(elt.gen, alg).expand()

                    if ex.exp == -1:
                        return bottom_up_scan(base)
                    else:
                        ex = base ** (-ex.exp)
                if not ex.exp.is_Integer:
                    base, exp = (ex.base ** ex.exp.p).expand(), Rational(1, ex.exp.q)
                else:
                    base, exp = ex.base, ex.exp
                base = bottom_up_scan(base)
                expr = base ** exp

                if expr not in mapping:
                    return update_mapping(expr, 1 / exp, -base)
                else:
                    return symbols[expr]
        elif ex.is_AlgebraicNumber:
            if ex.root not in mapping:
                return update_mapping(ex.root, ex.minpoly)
            else:
                return symbols[ex.root]

        raise NotAlgebraic("%s doesn't seem to be an algebraic number" % ex)

    def simpler_inverse(ex):
        """
        Returns True if it is more likely that the minimal polynomial
        algorithm works better with the inverse
        """
        if ex.is_Pow:
            if (1 / ex.exp).is_integer and ex.exp < 0:
                if ex.base.is_Add:
                    return True
        if ex.is_Mul:
            hit = True
#.........这里部分代码省略.........