/

Source code for sympy.core.power

from math import log as _log

from .sympify import _sympify
from .cache import cacheit
from .core import C
from sympy.core.function import (_coeff_isneg, expand_complex,
expand_multinomial, expand_mul)
from .singleton import S
from .expr import Expr

from sympy import mpmath
from sympy.utilities.iterables import sift

[docs]def integer_nthroot(y, n):
"""
Return a tuple containing x = floor(y**(1/n))
and a boolean indicating whether the result is exact (that is,
whether x**n == y).

>>> from sympy import integer_nthroot
>>> integer_nthroot(16,2)
(4, True)
>>> integer_nthroot(26,2)
(5, False)

"""
y, n = int(y), int(n)
if y < 0: raise ValueError("y must be nonnegative")
if n < 1: raise ValueError("n must be positive")
if y in (0, 1): return y, True
if n == 1: return y, True
if n == 2:
x, rem = mpmath.libmp.sqrtrem(y)
return int(x), not rem
if n > y: return 1, False
# Get initial estimate for Newton's method. Care must be taken to
# avoid overflow
try:
guess = int(y**(1./n) + 0.5)
except OverflowError:
exp = _log(y, 2)/n
if exp > 53:
shift = int(exp - 53)
guess = int(2.0**(exp - shift) + 1) << shift
else:
guess = int(2.0**exp)
#print n
if guess > 2**50:
# Newton iteration
xprev, x = -1, guess
while 1:
t = x**(n-1)
#xprev, x = x, x - (t*x-y)//(n*t)
xprev, x = x, ((n-1)*x + y//t)//n
#print n, x-xprev, abs(x-xprev) < 2
if abs(x - xprev) < 2:
break
else:
x = guess
# Compensate
t = x**n
while t < y:
x += 1
t = x**n
while t > y:
x -= 1
t = x**n
return x, t == y

[docs]class Pow(Expr):

is_Pow = True

__slots__ = ['is_commutative']

@cacheit
def __new__(cls, b, e, evaluate=True):
# don't optimize "if e==0; return 1" here; it's better to handle that
# in the calling routine so this doesn't get called
b = _sympify(b)
e = _sympify(e)
if evaluate:
if e is S.Zero:
return S.One
elif e is S.One:
return b
elif S.NaN in (b, e):
if b is S.One: # already handled e == 0 above
return S.One
return S.NaN
else:
obj = b._eval_power(e)
if obj is not None:
return obj
obj = Expr.__new__(cls, b, e)
obj.is_commutative = (b.is_commutative and e.is_commutative)
return obj

@property
def base(self):
return self._args

@property
def exp(self):
return self._args

@classmethod
def class_key(cls):
return 3, 2, cls.__name__

def _eval_power(self, other):
from sympy.functions.elementary.exponential import log

b, e = self.as_base_exp()
b_nneg = b.is_nonnegative
if b.is_real and not b_nneg and e.is_even:
b = abs(b)
b_nneg = True
smallarg = (abs(e) <= abs(S.Pi/log(b)))
if (other.is_Rational and other.q == 2 and
e.is_real is False and smallarg is False):
return -Pow(b, e*other)
if (other.is_integer or
e.is_real and (b_nneg or abs(e) < 1) or
e.is_real is False and smallarg is True or
b.is_polar):
return Pow(b, e*other)

def _eval_is_even(self):
if self.exp.is_integer and self.exp.is_positive:
return self.base.is_even

def _eval_is_positive(self):
if self.base.is_positive:
if self.exp.is_real:
return True
elif self.base.is_negative:
if self.exp.is_even:
return True
if self.exp.is_odd:
return False
elif self.base.is_nonpositive:
if self.exp.is_odd:
return False

def _eval_is_negative(self):
if self.base.is_negative:
if self.exp.is_odd:
return True
if self.exp.is_even:
return False
elif self.base.is_positive:
if self.exp.is_real:
return False
elif self.base.is_nonnegative:
if self.exp.is_real:
return False
elif self.base.is_nonpositive:
if self.exp.is_even:
return False
elif self.base.is_real:
if self.exp.is_even:
return False

def _eval_is_integer(self):
b, e = self.args
c1 = b.is_integer
c2 = e.is_integer
if c1 is None or c2 is None:
return None
if not c1 and e.is_nonnegative: #rat**nonneg
return False
if c1 and c2: # int**int
if e.is_nonnegative or e.is_positive:
return True
if self.exp.is_negative:
return False
if c1 and e.is_negative and e.is_bounded: #int**neg
return False
if b.is_Number and e.is_Number:
# int**nonneg or rat**?
check = Pow(*self.args)
return check.is_Integer

def _eval_is_real(self):
real_b = self.base.is_real
if real_b is None: return
real_e = self.exp.is_real
if real_e is None: return
if real_b and real_e:
if self.base.is_positive:
return True
else:   # negative or zero (or positive)
if self.exp.is_integer:
return True
elif self.base.is_negative:
if self.exp.is_Rational:
return False
im_b = self.base.is_imaginary
im_e = self.exp.is_imaginary
if im_b:
if self.exp.is_integer:
if self.exp.is_even:
return True
elif self.exp.is_odd:
return False
elif (self.exp in [S.ImaginaryUnit, -S.ImaginaryUnit] and
self.base in [S.ImaginaryUnit, -S.ImaginaryUnit]):
return True
if real_b and im_e:
c = self.exp.coeff(S.ImaginaryUnit)
if c:
ok = (c*C.log(self.base)/S.Pi).is_Integer
if ok is not None:
return ok

def _eval_is_odd(self):
if self.exp.is_integer:
if self.exp.is_positive:
return self.base.is_odd
elif self.exp.is_nonnegative and self.base.is_odd:
return True

def _eval_is_bounded(self):
if self.exp.is_negative:
if self.base.is_infinitesimal:
return False
if self.base.is_unbounded:
return True
c1 = self.base.is_bounded
if c1 is None: return
c2 = self.exp.is_bounded
if c2 is None: return
if c1 and c2:
if self.exp.is_nonnegative or self.base.is_nonzero:
return True

def _eval_is_polar(self):
return self.base.is_polar

def _eval_subs(self, old, new):
if old.func is self.func and self.base == old.base:
coeff1, terms1 = self.exp.as_coeff_Mul()
coeff2, terms2 = old.exp.as_coeff_Mul()
if terms1 == terms2:
pow = coeff1/coeff2
if pow == int(pow) or self.base.is_positive:
# issue 2081
return Pow(new, pow) # (x**(6*y)).subs(x**(3*y),z)->z**2
if old.func is C.exp and self.exp.is_real and self.base.is_positive:
coeff1, terms1 = old.args.as_coeff_Mul()
# we can only do this when the base is positive AND the exponent
# is real
coeff2, terms2 = (self.exp*C.log(self.base)).as_coeff_Mul()
if terms1 == terms2:
pow = coeff1/coeff2
if pow == int(pow) or self.base.is_positive:
return Pow(new, pow) # (2**x).subs(exp(x*log(2)), z) -> z

[docs]    def as_base_exp(self):
"""Return base and exp of self unless base is 1/Integer, then return Integer, -exp.

If this extra processing is not needed, the base and exp properties will
give the raw arguments, e.g. (1/2, 2) for (1/2)**2 rather than (2, -2).
"""

b, e = self.args
if b.is_Rational and b.p == 1:
return Integer(b.q), -e
return b, e

i, p = self.exp.is_integer, self.base.is_positive
if i:
if p:
if i is False and p is False:
expanded = expand_complex(self)
if expanded != self:

def _eval_conjugate(self):
from sympy.functions.elementary.complexes import conjugate as c
i, p = self.exp.is_integer, self.base.is_positive
if i:
return c(self.base)**self.exp
if p:
return self.base**c(self.exp)
if i is False and p is False:
expanded = expand_complex(self)
if expanded != self:
return c(expanded)

def _eval_transpose(self):
from sympy.functions.elementary.complexes import transpose
i, p = self.exp.is_integer, self.base.is_complex
if p:
return self.base**self.exp
if i:
return transpose(self.base)**self.exp
if i is False and p is False:
expanded = expand_complex(self)
if expanded != self:
return transpose(expanded)

def _eval_expand_power_exp(self, **hints):
"""a**(n+m) -> a**n*a**m"""
b = self.base
e = self.exp
expr = []
for x in e.args:
expr.append(Pow(self.base, x))
return Mul(*expr)
return Pow(b, e)

def _eval_expand_power_base(self, **hints):
"""(a*b)**n -> a**n * b**n"""
force = hints.get('force', False)
b, ewas = self.args
e = self.exp
if b.is_Mul:
bargs = b.args
if force or e.is_integer:
nonneg = bargs
other = []
elif ewas.is_Rational or len(bargs) == 2 and bargs is S.NegativeOne:
# the Rational exponent was already expanded automatically
# if there is a negative Number * foo, foo must be unknown
#    or else it, too, would have automatically expanded;
#    sqrt(-Number*foo) -> sqrt(Number)*sqrt(-foo); then
#    sqrt(-foo) -> unchanged if foo is not positive else
#               -> I*sqrt(foo)
#    So...if we have a 2 arg Mul and the first is a Number
#    that number is -1 and there is nothing more than can
#    be done without the force=True hint
nonneg= []
else:
# this is just like what is happening automatically, except
# that now we are doing it for an arbitrary exponent for which
# no automatic expansion is done
def pred(x):
if x.is_polar is None:
return x.is_nonnegative
return x.is_polar
sifted = sift(b.args, pred)
nonneg = sifted[True]
other = sifted[None]
neg = sifted[False]

# make sure the Number gets pulled out
if neg and neg.is_Number and neg is not S.NegativeOne:
nonneg.append(-neg)
neg = S.NegativeOne

# leave behind a negative sign
oddneg = len(neg) % 2
if oddneg:
other.append(S.NegativeOne)

# negate all negatives and append to nonneg
nonneg += [-n for n in neg]

if nonneg: # then there's a new expression to return
d = sift(nonneg, lambda x: x.is_commutative is True)
c = d[True]
nc = d[False]
if not e.is_Integer:
other.extend(nc)
nc = []
elif len(nc) == 1:
c.extend(nc)
nc = []
else:
nc = [Mul._from_args(nc)]*e
other = [Pow(Mul(*other), e)] + nc
return Mul(*([Pow(b, e) for b in c] + other))
return Pow(b, e)

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

if b is None:
base = self.base
else:
base = b

if e is None:
exp = self.exp
else:
exp = e

if e is not None or b is not None:
result = Pow(base, exp)

if result.is_Pow:
base, exp = result.base, result.exp
else:
return result
else:
result = None

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 Pow(base, exp)
else:
radical, result = Pow(base, exp - n), []

expanded_base_n = Pow(base, n)
if expanded_base_n.is_Pow:
expanded_base_n = expanded_base_n._eval_expand_multinomial()

n = int(exp)

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

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

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

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

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 = Pow(a.q * b.q, n)
a, b = a.p*b.q, a.q*b.p
else:
k = Pow(a.q, n)
a, b = a.p, a.q*b
elif not b.is_Integer:
k = Pow(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
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.

# An elegant way would be to use Poly, but unfortunately it is
# slower than the direct method below, so it is commented out:
#b = {}
#for k in expansion_dict:
#    b[k] = Integer(expansion_dict[k])
#return Poly(b, *p).as_expr()

from sympy.polys.polyutils import basic_from_dict
result = basic_from_dict(expansion_dict, *p)
return result
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()
return Add(*[f*g for f in base.args for g in multi.args])
else:
return Add(*[f*multi for f in base.args])
elif exp.is_Rational and exp.p < 0 and base.is_Add and abs(exp.p) > exp.q:
return 1 / Pow(base, -exp)._eval_expand_multinomial()
#  a + b      a  b
# n      --> n  n  , where n, a, b are Numbers

coeff, tail = S.One, S.Zero

for term in exp.args:
if term.is_Number:
coeff *= Pow(base, term)
else:
tail += term

return coeff * Pow(base, tail)
else:
return result

def as_real_imag(self, deep=True, **hints):
from sympy.core.symbol import symbols
from sympy.polys.polytools import poly

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 or not 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 % 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 % 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 % 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)
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

expanded = self.expand(deep, **hints)
if hints.get('ignore') == expanded:
return None
else:
return (C.re(expanded), C.im(expanded))
else:
return (C.re(self), C.im(self))

def _eval_derivative(self, s):
dbase = self.base.diff(s)
dexp = self.exp.diff(s)
return self * (dexp * C.log(self.base) + dbase * self.exp/self.base)

def _eval_evalf(self, prec):
base, exp = self.as_base_exp()
base = base._evalf(prec)
if not exp.is_Integer:
exp = exp._evalf(prec)
if exp < 0 and base.is_number and base.is_real is False:
base = base.conjugate() / (base * base.conjugate())._evalf(prec)
exp = -exp
return Pow(base, exp).expand()
return Pow(base, exp)

def _eval_is_polynomial(self, syms):
if self.exp.has(*syms):
return False

if self.base.has(*syms):
return self.base._eval_is_polynomial(syms) and \
self.exp.is_Integer and \
self.exp >= 0
else:
return True

def _eval_is_rational(self):
p = self.func(*self.as_base_exp()) # in case it's unevaluated
if not p.is_Pow:
return p.is_rational
b, e = p.as_base_exp()
if e.is_Rational and b.is_Rational:
# we didn't check that e is not an Integer
# because Rational**Integer autosimplifies
return False
if e.is_integer:
return b.is_rational

def _eval_is_rational_function(self, syms):
if self.exp.has(*syms):
return False

if self.base.has(*syms):
return self.base._eval_is_rational_function(syms) and \
self.exp.is_Integer
else:
return True

def as_numer_denom(self):
if not self.is_commutative:
return self, S.One
base, exp = self.as_base_exp()
n, d = base.as_numer_denom()
# this should be the same as ExpBase.as_numer_denom wrt
# exponent handling
neg_exp = exp.is_negative
int_exp = exp.is_integer
if not neg_exp and not exp.is_real:
neg_exp = _coeff_isneg(exp)
# the denominator cannot be separated from the numerator if
# its sign is unknown unless the exponent is an integer, e.g.
# sqrt(a/b) != sqrt(a)/sqrt(b) when a=1 and b=-1. But if the
# denominator is negative the numerator and denominator can
# be negated and the denominator (now positive) separated.
if not (d.is_real or int_exp):
n = base
d = S.One
dnonpos = d.is_nonpositive
if dnonpos:
n, d = -n, -d
elif dnonpos is None and not int_exp:
n = base
d = S.One
if neg_exp:
n, d = d, n
exp = -exp
return Pow(n, exp), Pow(d, exp)

def matches(self, expr, repl_dict={}):
expr = _sympify(expr)
b, e = expr.as_base_exp()

# special case, pattern = 1 and expr.exp can match to 0
if expr is S.One:
d = repl_dict.copy()
d = self.exp.matches(S.Zero, d)
if d is not None:
return d

d = repl_dict.copy()
d = self.base.matches(b, d)
if d is None:
return None

d = self.exp.xreplace(d).matches(e, d)
if d is None:
return Expr.matches(self, expr, repl_dict)
return d

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 expression
# 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(Pow(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"

b = b._eval_nseries(x, n=n, logx=logx)
# express "rest" as: rest = 1 + k*x**l + ... + O(x**n)
rest = expand_mul((b - prefactor)/prefactor)
if rest == 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)
if rest.is_Order:
return 1/prefactor + rest/prefactor
n2 = rest.getn()
if n2 is not None:
n = n2
# remove the O - powering this is slow
if logx is not None:
rest = rest.removeO()

if l.is_Rational and l > 0:
pass
elif l.is_number and l > 0:
l = l.evalf()
else:
raise NotImplementedError()

terms = [1/prefactor]
for m in range(1, ceiling(n/l)):
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)

# Append O(...), we know the order.
if n2 is None or logx is not None:
terms.append(O(x**n))
else:
# negative powers are rewritten to the cases above, for example:
# sin(x)**(-4) = 1/( sin(x)**4) = ...
# and expand the denominator:
denominator = (b**(-e))._eval_nseries(x, n=n, logx=logx)
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):
return exp(e*log(b))._eval_nseries(x, n=n, logx=logx)

# see if the base is as simple as possible
bx = b
while bx.is_Pow and bx.exp.is_Rational:
bx = bx.base
if bx == x:
return self

# work for b(x)**e where e is not an Integer and does not contain x
# and hopefully has no other symbols

def e2int(e):
"""return the integer value (if possible) of e and a
flag indicating whether it is bounded or not."""
n = e.limit(x, 0)
unbounded = n.is_unbounded
if not unbounded:
# XXX was int or floor intended? int used to behave like floor
# so int(-Rational(1, 2)) returned -1 rather than int's 0
try:
n = int(n)
except TypeError:
#well, the n is something more complicated (like 1+log(2))
try:
n = int(n.evalf()) + 1 # XXX why is 1 being added?
except TypeError:
pass # hope that base allows this to be resolved
n = _sympify(n)
return n, unbounded

order = O(x**n, x)
ei, unbounded = e2int(e)
b0 = b.limit(x, 0)
if unbounded and (b0 is S.One or b0.has(Symbol)):
# XXX what order
if b0 is S.One:
resid = (b - 1)
if resid.is_positive:
return S.Infinity
elif resid.is_negative:
return S.Zero
raise ValueError('cannot determine sign of %s' % resid)

return b0**ei

if (b0 is S.Zero or b0.is_unbounded):
if unbounded is not False:
return b0**e # XXX what order

if not ei.is_number: # if not, how will we proceed?
raise ValueError('expecting numerical exponent but got %s' % ei)

nuse = n - ei
bs = b._eval_nseries(x, n=nuse, logx=logx)
terms = bs.removeO()
bs = terms

# bs -> lt + rest -> lt*(1 + (bs/lt - 1))
return ((Pow(lt, e)*
Pow((bs/lt).expand(), e).
nseries(x, n=nuse, logx=logx)).expand() +
order)

rv = bs**e
if terms != bs:
rv += order
return rv

# either b0 is bounded but neither 1 nor 0 or e is unbounded
# b -> b0 + (b-b0) -> b0 * (1 + (b/b0-1))
o2 = order*(b0**-e)
z = (b/b0 - 1)
o = O(z, x)
#r = self._compute_oseries3(z, o2, self.taylor_term)
if o is S.Zero or o2 is S.Zero:
unbounded = True
else:
if o.expr.is_number:
e2 = log(o2.expr*x)/log(x)
else:
e2 = log(o2.expr)/log(o.expr)
n, unbounded = e2int(e2)
if unbounded:
# requested accuracy gives infinite series,
# order is probably non-polynomial e.g. O(exp(-1/x), x).
r = 1 + z
else:
l = []
g = None
for i in range(n + 2):
g = self.taylor_term(i, z, g)
g = g.nseries(x, n=n, logx=logx)
l.append(g)
return r*b0**e + order

if not self.exp.has(x):

@cacheit
def taylor_term(self, n, x, *previous_terms): # of (1+x)**e
if n<0: return S.Zero
x = _sympify(x)
return C.binomial(self.exp, n) * Pow(x, n)

def _sage_(self):
return self.args._sage_()**self.args._sage_()

"""Return the tuple (R, self/R) where R is the positive Rational
extracted from self.

Examples
========

>>> from sympy import sqrt
>>> sqrt(4 + 4*sqrt(2)).as_content_primitive()
(2, sqrt(1 + sqrt(2)))
>>> sqrt(3 + 3*sqrt(2)).as_content_primitive()
(1, sqrt(3)*sqrt(1 + sqrt(2)))

>>> from sympy import expand_power_base, powsimp, Mul
>>> from sympy.abc import x, y

>>> ((2*x + 2)**2).as_content_primitive()
(4, (x + 1)**2)
>>> (4**((1 + y)/2)).as_content_primitive()
(2, 4**(y/2))
>>> (3**((1 + y)/2)).as_content_primitive()
(1, 3**((y + 1)/2))
>>> (3**((5 + y)/2)).as_content_primitive()
(9, 3**((y + 1)/2))
>>> eq = 3**(2 + 2*x)
>>> powsimp(eq) == eq
True
>>> eq.as_content_primitive()
(9, 3**(2*x))
>>> powsimp(Mul(*_))
9**(x + 1)

>>> eq = (2 + 2*x)**y
>>> s = expand_power_base(eq); s.is_Mul, s
(False, (2*x + 2)**y)
>>> eq.as_content_primitive()
(1, (2*(x + 1))**y)
>>> s = expand_power_base(_); s.is_Mul, s
(True, 2**y*(x + 1)**y)

See docstring of Expr.as_content_primitive for more examples.
"""

b, e = self.as_base_exp()
if b.is_Rational:
#e
#= ce*pe
#= ce*(h + t)
#= ce*h + ce*t
#=> self
#= b**(ce*h)*b**(ce*t)
#= b**(cehp/cehq)*b**(ce*t)
#= b**(iceh+r/cehq)*b**(ce*t)
#= b**(iceh)*b**(r/cehq)*b**(ce*t)
#= b**(iceh)*b**(ce*t + r/cehq)
if h.is_Rational:
ceh = ce*h
c = Pow(b, ceh)
r = S.Zero
if not c.is_Rational:
iceh, r = divmod(ceh.p, ceh.q)
c = Pow(b, iceh)
return c, Pow(b, _keep_coeff(ce, t + r/ce/ceh.q))
e = _keep_coeff(ce, pe)
# b**e = (h*t)**e = h**e*t**e = c*m*t**e
if e.is_Rational and b.is_Mul:
c, m = Pow(h, e).as_coeff_Mul() # so c is positive
m, me = m.as_base_exp()
if m is S.One or me == e: # probably always true
# return the following, not return c, m*Pow(t, e)
# which would change Pow into Mul; we let sympy
# decide what to do by using the unevaluated Mul, e.g
# should it stay as sqrt(2 + 2*sqrt(5)) or become
# sqrt(2)*sqrt(1 + sqrt(5))
return c, Pow(_keep_coeff(m, t), e)
return S.One, Pow(b, e)

def is_constant(self, *wrt, **flags):
if flags.get('simplify', True):
self = self.simplify()
b, e = self.as_base_exp()
bz = b.equals(0)
if bz: # recalculate with assumptions in case it's unevaluated
new = b**e
if new != self:
return new.is_constant()
econ = e.is_constant(*wrt)
bcon = b.is_constant(*wrt)
if bcon:
if econ:
return True
bz = b.equals(0)
if bz is False:
return False
elif bcon is None:
return None

return e.equals(0)