human
Complete the below
def logcombine(expr, force=False):

    ''''Takes logarithms and combines them using the following rules:
    - log(x) + log(y) == log(x*y) if both are not negative
    - a*log(x) == log(x**a) if x is positive and a is real
    If ``force`` is True then the assumptions above will be assumed to hold if
    there is no assumption already in place on a quantity. For example, if
    ``a`` is imaginary or the argument negative, force will not perform a
    combination but if ``a`` is a symbol with no assumptions the change will
    take place.
    Examples
    >>> from sympy import Symbol, symbols, log, logcombine, I
    >>> from sympy.abc import a, x, y, z
    >>> logcombine(a*log(x) + log(y) - log(z))
    a*log(x) + log(y) - log(z)
    >>> logcombine(a*log(x) + log(y) - log(z), force=True)
    log(x**a*y/z)
    >>> x,y,z = symbols(\'x,y,z\', positive=True)
    >>> a = Symbol(\'a\', real=True)
    >>> logcombine(a*log(x) + log(y) - log(z))
    log(x**a*y/z)
    The transformation is limited to factors and/or terms that
    contain logs, so the result depends on the initial state of
    expansion:
    >>> eq = (2 + 3*I)*log(x)
    >>> logcombine(eq, force=True) == eq
    True
    >>> logcombine(eq.expand(), force=True)
    log(x**2) + I*log(x**3)
    See Also
    posify: replace all symbols with symbols having positive assumptions'
    '''
assistant
#Here is the Python code you requested.
    def f(rv):
        if (not (rv.is_Add or rv.is_Mul)):
            return rv
        def gooda(a):
            return ((a is not S.NegativeOne) and (a.is_real or (force and (a.is_real is not False))))
        def goodlog(l):
            a = l.args[0]
            return (a.is_positive or (force and (a.is_nonpositive is not False)))
        other = []
        logs = []
        log1 = defaultdict(list)
        for a in Add.make_args(rv):
            if ((a.func is log) and goodlog(a)):
                log1[()].append(([], a))
            elif (not a.is_Mul):
                other.append(a)
            else:
                ot = []
                co = []
                lo = []
                for ai in a.args:
                    if (ai.is_Rational and (ai < 0)):
                        ot.append(S.NegativeOne)
                        co.append((- ai))
                    elif ((ai.func is log) and goodlog(ai)):
                        lo.append(ai)
                    elif gooda(ai):
                        co.append(ai)
                    else:
                        ot.append(ai)
                if (len(lo) > 1):
                    logs.append((ot, co, lo))
                elif lo:
                    log1[tuple(ot)].append((co, lo[0]))
                else:
                    other.append(a)
        if ((not logs) and all((((len(log1[k]) == 1) and (log1[k][0] == [])) for k in log1))):
            return rv
        for (o, e, l) in logs:
            l = list(ordered(l))
            e = log((l.pop(0).args[0] ** Mul(*e)))
            while l:
                li = l.pop(0)
                e = log((li.args[0] ** e))
            (c, l) = (Mul(*o), e)
            if (l.func is log):
                log1[(c,)].append(([], l))
            else:
                other.append((c * l))
        for k in list(log1.keys()):
            log1[Mul(*k)] = log(logcombine(Mul(*[(l.args[0] ** Mul(*c)) for (c, l) in log1.pop(k)]), force=force))
        for k in ordered(list(log1.keys())):
            if (not (k in log1)):
 ...