def _eval_expand_log(self, deep=True, **hints):
from sympy import unpolarify
force = hints.get('force', False)
arg = self.args[0]
if arg.is_Mul:
expr = []
nonpos = []
for x in arg.args:
if force or x.is_positive or x.is_polar:
a = self.func(x)
if isinstance(a, log):
expr.append(self.func(x)._eval_expand_log(**hints))
else:
expr.append(a)
else:
nonpos.append(x)
return Add(*expr) + log(Mul(*nonpos))
elif arg.is_Pow:
if force or (arg.exp.is_real and arg.base.is_positive) or \
arg.base.is_polar:
b = arg.base
e = arg.exp
a = self.func(b)
if isinstance(a, log):
return unpolarify(e) * a._eval_expand_log(**hints)
else:
return unpolarify(e) * a
return self.func(arg)
def eval(cls, nu, z):
if z.is_zero:
if nu.is_zero:
return S.One
elif (nu.is_integer and nu.is_zero is False) or re(nu).is_positive:
return S.Zero
elif re(nu).is_negative and not (nu.is_integer is True):
return S.ComplexInfinity
elif nu.is_imaginary:
return S.NaN
if z is S.Infinity or (z is S.NegativeInfinity):
return S.Zero
if z.could_extract_minus_sign():
return (z)**nu*(-z)**(-nu)*besselj(nu, -z)
if nu.is_integer:
if nu.could_extract_minus_sign():
return S(-1)**(-nu)*besselj(-nu, z)
newz = z.extract_multiplicatively(I)
if newz: # NOTE we don't want to change the function if z==0
return I**(nu)*besseli(nu, newz)
# branch handling:
from sympy import unpolarify, exp
if nu.is_integer:
newz = unpolarify(z)
if newz != z:
return besselj(nu, newz)
else:
newz, n = z.extract_branch_factor()
if n != 0:
return exp(2*n*pi*nu*I)*besselj(nu, newz)
nnu = unpolarify(nu)
if nu != nnu:
return besselj(nnu, z)
def test_expint():
""" Test various exponential integrals. """
from sympy import (expint, unpolarify, Symbol, Ci, Si, Shi, Chi,
sin, cos, sinh, cosh, Ei)
assert simplify(unpolarify(integrate(exp(-z*x)/x**y, (x, 1, oo),
meijerg=True, conds='none'
).rewrite(expint).expand(func=True))) == expint(y, z)
assert integrate(exp(-z*x)/x, (x, 1, oo), meijerg=True,
conds='none').rewrite(expint).expand() == \
expint(1, z)
assert integrate(exp(-z*x)/x**2, (x, 1, oo), meijerg=True,
conds='none').rewrite(expint).expand() == \
expint(2, z).rewrite(Ei).rewrite(expint)
assert integrate(exp(-z*x)/x**3, (x, 1, oo), meijerg=True,
conds='none').rewrite(expint).expand() == \
expint(3, z).rewrite(Ei).rewrite(expint).expand()
t = Symbol('t', positive=True)
assert integrate(-cos(x)/x, (x, t, oo), meijerg=True).expand() == Ci(t)
assert integrate(-sin(x)/x, (x, t, oo), meijerg=True).expand() == \
Si(t) - pi/2
assert integrate(sin(x)/x, (x, 0, z), meijerg=True) == Si(z)
assert integrate(sinh(x)/x, (x, 0, z), meijerg=True) == Shi(z)
assert integrate(exp(-x)/x, x, meijerg=True).expand().rewrite(expint) == \
I*pi - expint(1, x)
assert integrate(exp(-x)/x**2, x, meijerg=True).rewrite(expint).expand() \
== expint(1, x) - exp(-x)/x - I*pi
u = Symbol('u', polar=True)
assert integrate(cos(u)/u, u, meijerg=True).expand().as_independent(u)[1] \
== Ci(u)
assert integrate(cosh(u)/u, u, meijerg=True).expand().as_independent(u)[1] \
== Chi(u)
assert integrate(expint(1, x), x, meijerg=True
).rewrite(expint).expand() == x*expint(1, x) - exp(-x)
assert integrate(expint(2, x), x, meijerg=True
).rewrite(expint).expand() == \
-x**2*expint(1, x)/2 + x*exp(-x)/2 - exp(-x)/2
assert simplify(unpolarify(integrate(expint(y, x), x,
meijerg=True).rewrite(expint).expand(func=True))) == \
-expint(y + 1, x)
assert integrate(Si(x), x, meijerg=True) == x*Si(x) + cos(x)
assert integrate(Ci(u), u, meijerg=True).expand() == u*Ci(u) - sin(u)
assert integrate(Shi(x), x, meijerg=True) == x*Shi(x) - cosh(x)
assert integrate(Chi(u), u, meijerg=True).expand() == u*Chi(u) - sinh(u)
assert integrate(Si(x)*exp(-x), (x, 0, oo), meijerg=True) == pi/4
assert integrate(expint(1, x)*sin(x), (x, 0, oo), meijerg=True) == log(2)/2
def _eval_expand_func(self, **hints):
from sympy import exp, I, floor, Add, Poly, Dummy, exp_polar, unpolarify
z, s, a = self.args
if z == 1:
return zeta(s, a)
if s.is_Integer and s <= 0:
t = Dummy('t')
p = Poly((t + a)**(-s), t)
start = 1/(1 - t)
res = S(0)
for c in reversed(p.all_coeffs()):
res += c*start
start = t*start.diff(t)
return res.subs(t, z)
if a.is_Rational:
# See section 18 of
# Kelly B. Roach. Hypergeometric Function Representations.
# In: Proceedings of the 1997 International Symposium on Symbolic and
# Algebraic Computation, pages 205-211, New York, 1997. ACM.
# TODO should something be polarified here?
add = S(0)
mul = S(1)
# First reduce a to the interaval (0, 1]
if a > 1:
n = floor(a)
if n == a:
n -= 1
a -= n
mul = z**(-n)
add = Add(*[-z**(k - n)/(a + k)**s for k in xrange(n)])
elif a <= 0:
n = floor(-a) + 1
a += n
mul = z**n
add = Add(*[z**(n - 1 - k)/(a - k - 1)**s for k in xrange(n)])
m, n = S([a.p, a.q])
zet = exp_polar(2*pi*I/n)
root = z**(1/n)
return add + mul*n**(s - 1)*Add(
*[polylog(s, zet**k*root)._eval_expand_func(**hints)
/ (unpolarify(zet)**k*root)**m for k in xrange(n)])
# TODO use minpoly instead of ad-hoc methods when issue 2789 is fixed
if z.func is exp and (z.args[0]/(pi*I)).is_Rational or z in [-1, I, -I]:
# TODO reference?
if z == -1:
p, q = S([1, 2])
elif z == I:
p, q = S([1, 4])
elif z == -I:
p, q = S([-1, 4])
else:
arg = z.args[0]/(2*pi*I)
p, q = S([arg.p, arg.q])
return Add(*[exp(2*pi*I*k*p/q)/q**s*zeta(s, (k + a)/q)
for k in xrange(q)])
return lerchphi(z, s, a)
def _eval_expand_log(self, deep=True, **hints):
from sympy import unpolarify
force = hints.get('force', False)
if deep:
arg = self.args[0].expand(deep=deep, **hints)
else:
arg = self.args[0]
if arg.is_Mul:
expr = []
nonpos = []
for x in arg.args:
if deep:
x = x.expand(deep=deep, **hints)
if force or x.is_positive or x.is_polar:
expr.append(self.func(x)._eval_expand_log(deep=deep, **hints))
else:
nonpos.append(x)
return Add(*expr) + log(Mul(*nonpos))
elif arg.is_Pow:
if force or (arg.exp.is_real and arg.base.is_positive) or \
arg.base.is_polar:
if deep:
b = arg.base.expand(deep=deep, **hints)
e = arg.exp.expand(deep=deep, **hints)
else:
b = arg.base
e = arg.exp
return unpolarify(e) * self.func(b)._eval_expand_log(deep=deep,\
**hints)
return self.func(arg)
def can_do_meijer(a1, a2, b1, b2, numeric=True):
"""
This helper function tries to hyperexpand() the meijer g-function
corresponding to the parameters a1, a2, b1, b2.
It returns False if this expansion still contains g-functions.
If numeric is True, it also tests the so-obtained formula numerically
(at random values) and returns False if the test fails.
Else it returns True.
"""
from sympy import unpolarify, expand
r = hyperexpand(meijerg(a1, a2, b1, b2, z))
if r.has(meijerg):
return False
# NOTE hyperexpand() returns a truly branched function, whereas numerical
# evaluation only works on the main branch. Since we are evaluating on
# the main branch, this should not be a problem, but expressions like
# exp_polar(I*pi/2*x)**a are evaluated incorrectly. We thus have to get
# rid of them. The expand heuristically does this...
r = unpolarify(expand(r, force=True, power_base=True, power_exp=False,
mul=False, log=False, multinomial=False, basic=False))
if not numeric:
return True
repl = {}
for n, a in enumerate(meijerg(a1, a2, b1, b2, z).free_symbols - set([z])):
repl[a] = randcplx(n)
return tn(meijerg(a1, a2, b1, b2, z).subs(repl), r.subs(repl), z)
def fdiff(self, argindex=1):
from sympy import unpolarify
arg = unpolarify(self.args[0])
if argindex == 1:
return C.exp(arg)/arg
else:
raise ArgumentIndexError(self, argindex)
def eval(cls, s, z):
s, z = sympify((s, z))
if z == 1:
return zeta(s)
elif z == -1:
return -dirichlet_eta(s)
elif z == 0:
return S.Zero
elif s == 2:
if z == S.Half:
return pi**2/12 - log(2)**2/2
elif z == 2:
return pi**2/4 - I*pi*log(2)
elif z == -(sqrt(5) - 1)/2:
return -pi**2/15 + log((sqrt(5)-1)/2)**2/2
elif z == -(sqrt(5) + 1)/2:
return -pi**2/10 - log((sqrt(5)+1)/2)**2
elif z == (3 - sqrt(5))/2:
return pi**2/15 - log((sqrt(5)-1)/2)**2
elif z == (sqrt(5) - 1)/2:
return pi**2/10 - log((sqrt(5)-1)/2)**2
# For s = 0 or -1 use explicit formulas to evaluate, but
# automatically expanding polylog(1, z) to -log(1-z) seems undesirable
# for summation methods based on hypergeometric functions
elif s == 0:
return z/(1 - z)
elif s == -1:
return z/(1 - z)**2
# polylog is branched, but not over the unit disk
from sympy.functions.elementary.complexes import (Abs, unpolarify,
polar_lift)
if z.has(exp_polar, polar_lift) and (Abs(z) <= S.One) == True:
return cls(s, unpolarify(z))
def eval(cls, arg, base=None):
from sympy import unpolarify
if base is not None:
base = sympify(base)
if arg.is_positive and arg.is_Integer and \
base.is_positive and base.is_Integer:
base = int(base)
arg = int(arg)
n = multiplicity(base, arg)
return S(n) + log(arg // base ** n) / log(base)
if base is not S.Exp1:
return cls(arg)/cls(base)
else:
return cls(arg)
arg = sympify(arg)
if arg.is_Number:
if arg is S.Zero:
return S.ComplexInfinity
elif arg is S.One:
return S.Zero
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Infinity
elif arg is S.NaN:
return S.NaN
elif arg.is_negative:
return S.Pi * S.ImaginaryUnit + cls(-arg)
elif arg.is_Rational:
if arg.q != 1:
return cls(arg.p) - cls(arg.q)
# remove perfect powers automatically
p = perfect_power(int(arg))
if p is not False:
return p[1]*cls(p[0])
elif arg is S.ComplexInfinity:
return S.ComplexInfinity
elif arg is S.Exp1:
return S.One
elif arg.func is exp and arg.args[0].is_real:
return arg.args[0]
elif arg.func is exp_polar:
return unpolarify(arg.exp)
#don't autoexpand Pow or Mul (see the issue 252):
elif not arg.is_Add:
coeff = arg.as_coefficient(S.ImaginaryUnit)
if coeff is not None:
if coeff is S.Infinity:
return S.Infinity
elif coeff is S.NegativeInfinity:
return S.Infinity
elif coeff.is_Rational:
if coeff.is_nonnegative:
return S.Pi * S.ImaginaryUnit * S.Half + cls(coeff)
else:
return -S.Pi * S.ImaginaryUnit * S.Half + cls(-coeff)
def eval(cls, n, z):
n, z = list(map(sympify, (n, z)))
from sympy import unpolarify
if n.is_integer:
if n.is_nonnegative:
nz = unpolarify(z)
if z != nz:
return polygamma(n, nz)
if n == -1:
return loggamma(z)
else:
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
if n.is_Number:
if n is S.Zero:
return S.Infinity
else:
return S.Zero
elif z.is_Integer:
if z.is_nonpositive:
return S.ComplexInfinity
else:
if n is S.Zero:
return -S.EulerGamma + C.harmonic(z - 1, 1)
elif n.is_odd:
return (-1) ** (n + 1) * C.factorial(n) * zeta(n + 1, z)
if n == 0:
if z is S.NaN:
return S.NaN
elif z.is_Rational:
# TODO actually *any* n/m can be done, but that is messy
lookup = {
S(1) / 2: -2 * log(2) - S.EulerGamma,
S(1) / 3: -S.Pi / 2 / sqrt(3) - 3 * log(3) / 2 - S.EulerGamma,
S(1) / 4: -S.Pi / 2 - 3 * log(2) - S.EulerGamma,
S(3) / 4: -3 * log(2) - S.EulerGamma + S.Pi / 2,
S(2) / 3: -3 * log(3) / 2 + S.Pi / 2 / sqrt(3) - S.EulerGamma,
}
if z > 0:
n = floor(z)
z0 = z - n
if z0 in lookup:
return lookup[z0] + Add(*[1 / (z0 + k) for k in range(n)])
elif z < 0:
n = floor(1 - z)
z0 = z + n
if z0 in lookup:
return lookup[z0] - Add(*[1 / (z0 - 1 - k) for k in range(n)])
elif z in (S.Infinity, S.NegativeInfinity):
return S.Infinity
else:
t = z.extract_multiplicatively(S.ImaginaryUnit)
if t in (S.Infinity, S.NegativeInfinity):
return S.Infinity
def _eval_expand_log(self, deep=True, **hints):
from sympy import unpolarify, expand_log
from sympy.concrete import Sum, Product
force = hints.get('force', False)
if (len(self.args) == 2):
return expand_log(self.func(*self.args), deep=deep, force=force)
arg = self.args[0]
if arg.is_Integer:
# remove perfect powers
p = perfect_power(int(arg))
if p is not False:
return p[1]*self.func(p[0])
elif arg.is_Rational:
return log(arg.p) - log(arg.q)
elif arg.is_Mul:
expr = []
nonpos = []
for x in arg.args:
if force or x.is_positive or x.is_polar:
a = self.func(x)
if isinstance(a, log):
expr.append(self.func(x)._eval_expand_log(**hints))
else:
expr.append(a)
elif x.is_negative:
a = self.func(-x)
expr.append(a)
nonpos.append(S.NegativeOne)
else:
nonpos.append(x)
return Add(*expr) + log(Mul(*nonpos))
elif arg.is_Pow or isinstance(arg, exp):
if force or (arg.exp.is_real and (arg.base.is_positive or ((arg.exp+1)
.is_positive and (arg.exp-1).is_nonpositive))) or arg.base.is_polar:
b = arg.base
e = arg.exp
a = self.func(b)
if isinstance(a, log):
return unpolarify(e) * a._eval_expand_log(**hints)
else:
return unpolarify(e) * a
elif isinstance(arg, Product):
if arg.function.is_positive:
return Sum(log(arg.function), *arg.limits)
return self.func(arg)
def fdiff(self, argindex=2):
from sympy import meijerg, unpolarify
if argindex == 2:
a, z = self.args
return -C.exp(-unpolarify(z))*z**(a - 1)
elif argindex == 1:
a, z = self.args
return uppergamma(a, z)*log(z) + meijerg([], [1, 1], [0, 0, a], [], z)
else:
raise ArgumentIndexError(self, argindex)
def eval(cls, nu, z):
if nu.is_Integer:
newz = z.extract_multiplicatively(I)
if newz: # NOTE we don't want to change the function if z==0
return I**(-nu)*besselj(nu, -newz)
# branch handling:
from sympy import unpolarify, exp
if nu.is_integer:
newz = unpolarify(z)
if newz != z:
return besseli(nu, newz)
else:
newz, n = z.extract_branch_factor()
if n != 0:
return exp(2*n*pi*nu*I)*besseli(nu, newz)
nnu = unpolarify(nu)
if nu != nnu:
return besseli(nnu, z)
def eval(cls, nu, z):
from sympy import unpolarify, expand_mul, uppergamma, exp, gamma, factorial
nu2 = unpolarify(nu)
if nu != nu2:
return expint(nu2, z)
if nu.is_Integer and nu <= 0 or (not nu.is_Integer and (2 * nu).is_Integer):
return unpolarify(expand_mul(z ** (nu - 1) * uppergamma(1 - nu, z)))
# Extract branching information. This can be deduced from what is
# explained in lowergamma.eval().
z, n = z.extract_branch_factor()
if n == 0:
return
if nu.is_integer:
if (nu > 0) is not True:
return
return expint(nu, z) - 2 * pi * I * n * (-1) ** (nu - 1) / factorial(nu - 1) * unpolarify(z) ** (nu - 1)
else:
return (exp(2 * I * pi * nu * n) - 1) * z ** (nu - 1) * gamma(1 - nu) + expint(nu, z)
def eval(cls, a, z):
from sympy import unpolarify, I, expint
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
return S.Zero
elif z is S.Zero:
# TODO: Holds only for Re(a) > 0:
return gamma(a)
# We extract branching information here. C/f lowergamma.
nx, n = z.extract_branch_factor()
if a.is_integer and (a > 0) == True:
nx = unpolarify(z)
if z != nx:
return uppergamma(a, nx)
elif a.is_integer and (a <= 0) == True:
if n != 0:
return -2*pi*I*n*(-1)**(-a)/factorial(-a) + uppergamma(a, nx)
elif n != 0:
return gamma(a)*(1 - exp(2*pi*I*n*a)) + exp(2*pi*I*n*a)*uppergamma(a, nx)
# Special values.
if a.is_Number:
if a is S.One:
return exp(-z)
elif a is S.Half:
return sqrt(pi)*erfc(sqrt(z))
elif a.is_Integer or (2*a).is_Integer:
b = a - 1
if b.is_positive:
if a.is_integer:
return exp(-z) * factorial(b) * Add(*[z**k / factorial(k) for k in range(a)])
else:
return gamma(a) * erfc(sqrt(z)) + (-1)**(a - S(3)/2) * exp(-z) * sqrt(z) * Add(*[gamma(-S.Half - k) * (-z)**k / gamma(1-a) for k in range(a - S.Half)])
elif b.is_Integer:
return expint(-b, z)*unpolarify(z)**(b + 1)
if not a.is_Integer:
return (-1)**(S.Half - a) * pi*erfc(sqrt(z))/gamma(1-a) - z**a * exp(-z) * Add(*[z**k * gamma(a) / gamma(a+k+1) for k in range(S.Half - a)])
def _eval_rewrite_as_Ei(self, nu, z):
from sympy import exp_polar, unpolarify, exp, factorial
if nu == 1:
return -Ei(z*exp_polar(-I*pi)) - I*pi
elif nu.is_Integer and nu > 1:
# DLMF, 8.19.7
x = -unpolarify(z)
return x**(nu - 1)/factorial(nu - 1)*E1(z).rewrite(Ei) + \
exp(x)/factorial(nu - 1) * \
Add(*[factorial(nu - k - 2)*x**k for k in range(nu - 1)])
else:
return self
def eval(cls, a, z):
from sympy import unpolarify, I, factorial, exp, expint
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
return S.Zero
elif z is S.Zero:
# TODO: Holds only for Re(a) > 0:
return gamma(a)
# We extract branching information here. C/f lowergamma.
nx, n = z.extract_branch_factor()
if a.is_integer and (a > 0) == True:
nx = unpolarify(z)
if z != nx:
return uppergamma(a, nx)
elif a.is_integer and (a <= 0) == True:
if n != 0:
return -2 * pi * I * n * (-1) ** (-a) / factorial(-a) + uppergamma(a, nx)
elif n != 0:
return gamma(a) * (1 - exp(2 * pi * I * n * a)) + exp(2 * pi * I * n * a) * uppergamma(a, nx)
# Special values.
if a.is_Number:
# TODO this should be non-recursive
if a is S.One:
return C.exp(-z)
elif a is S.Half:
return sqrt(pi) * (1 - erf(sqrt(z))) # TODO could use erfc...
elif a.is_Integer or (2 * a).is_Integer:
b = a - 1
if b.is_positive:
return b * cls(b, z) + z ** b * C.exp(-z)
elif b.is_Integer:
return expint(-b, z) * unpolarify(z) ** (b + 1)
if not a.is_Integer:
return (cls(a + 1, z) - z ** a * C.exp(-z)) / a
def eval(cls, a, z):
from sympy import unpolarify, I, expint
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
return S.Zero
elif z is S.Zero:
# TODO: Holds only for Re(a) > 0:
return gamma(a)
# We extract branching information here. C/f lowergamma.
nx, n = z.extract_branch_factor()
if a.is_integer and (a > 0) == True:
nx = unpolarify(z)
if z != nx:
return uppergamma(a, nx)
elif a.is_integer and (a <= 0) == True:
if n != 0:
return -2*pi*I*n*(-1)**(-a)/factorial(-a) + uppergamma(a, nx)
elif n != 0:
return gamma(a)*(1 - exp(2*pi*I*n*a)) + exp(2*pi*I*n*a)*uppergamma(a, nx)
# Special values.
if a.is_Number:
# TODO this should be non-recursive
if a is S.One:
return exp(-z)
elif a is S.Half:
return sqrt(pi)*erfc(sqrt(z))
elif a.is_Integer or (2*a).is_Integer:
b = a - 1
if b.is_positive:
return b*cls(b, z) + z**b * exp(-z)
elif b.is_Integer:
return expint(-b, z)*unpolarify(z)**(b + 1)
if not a.is_Integer:
return (cls(a + 1, z) - z**a * exp(-z))/a
def eval(cls, n, z):
n, z = map(sympify, (n, z))
from sympy import unpolarify
if n.is_integer:
if n.is_nonnegative:
nz = unpolarify(z)
if z != nz:
return polygamma(n, nz)
if n is S.NegativeOne:
return loggamma(z)
else:
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
if n.is_Number:
if n.is_zero:
return S.Infinity
else:
return S.Zero
if n.is_zero:
return S.Infinity
elif z.is_Integer:
if z.is_nonpositive:
return S.ComplexInfinity
else:
if n.is_zero:
return -S.EulerGamma + harmonic(z - 1, 1)
elif n.is_odd:
return (-1)**(n + 1) * factorial(n) * zeta(
n + 1, z)
if n.is_zero:
if z is S.NaN:
return S.NaN
elif z.is_Rational:
p, q = z.as_numer_denom()
# only expand for small denominators to avoid creating long expressions
if q <= 5:
return expand_func(polygamma(S.Zero, z, evaluate=False))
elif z in (S.Infinity, S.NegativeInfinity):
return S.Infinity
else:
t = z.extract_multiplicatively(S.ImaginaryUnit)
if t in (S.Infinity, S.NegativeInfinity):
return S.Infinity
def _eval_expand_log(self, deep=True, **hints):
from sympy import unpolarify
from sympy.concrete import Sum, Product
force = hints.get('force', False)
arg = self.args[0]
if arg.is_Integer:
# remove perfect powers
p = perfect_power(int(arg))
if p is not False:
return p[1] * self.func(p[0])
elif arg.is_Mul:
expr = []
nonpos = []
for x in arg.args:
if force or x.is_positive or x.is_polar:
a = self.func(x)
if isinstance(a, log):
expr.append(self.func(x)._eval_expand_log(**hints))
else:
expr.append(a)
else:
nonpos.append(x)
return Add(*expr) + log(Mul(*nonpos))
elif arg.is_Pow:
if force or (arg.exp.is_real and arg.base.is_positive) or \
arg.base.is_polar:
b = arg.base
e = arg.exp
a = self.func(b)
if isinstance(a, log):
return unpolarify(e) * a._eval_expand_log(**hints)
else:
return unpolarify(e) * a
elif isinstance(arg, Product):
if arg.function.is_positive:
return Sum(log(arg.function), *arg.limits)
return self.func(arg)
def _eval_expand_log(self, deep=True, **hints):
from sympy import unpolarify
from sympy.concrete import Sum, Product
force = hints.get('force', False)
arg = self.args[0]
if arg.is_Integer:
# remove perfect powers
p = perfect_power(int(arg))
if p is not False:
return p[1]*self.func(p[0])
elif arg.is_Mul:
expr = []
nonpos = []
for x in arg.args:
if force or x.is_positive or x.is_polar:
a = self.func(x)
if isinstance(a, log):
expr.append(self.func(x)._eval_expand_log(**hints))
else:
expr.append(a)
else:
nonpos.append(x)
return Add(*expr) + log(Mul(*nonpos))
elif arg.is_Pow:
if force or (arg.exp.is_real and arg.base.is_positive) or \
arg.base.is_polar:
b = arg.base
e = arg.exp
a = self.func(b)
if isinstance(a, log):
return unpolarify(e) * a._eval_expand_log(**hints)
else:
return unpolarify(e) * a
elif isinstance(arg, Product):
if arg.function.is_positive:
return Sum(log(arg.function), *arg.limits)
return self.func(arg)
def eval(cls, nu, z):
if nu.is_Integer:
if nu < 0:
return S(-1)**nu * besselj(-nu, z)
if z.could_extract_minus_sign():
return S(-1)**nu * besselj(nu, -z)
newz = z.extract_multiplicatively(I)
if newz: # NOTE we don't want to change the function if z==0
return I**(nu) * besseli(nu, newz)
# branch handling:
from sympy import unpolarify, exp
if nu.is_integer:
newz = unpolarify(z)
if newz != z:
return besselj(nu, newz)
else:
newz, n = z.extract_branch_factor()
if n != 0:
return exp(2 * n * pi * nu * I) * besselj(nu, newz)
nnu = unpolarify(nu)
if nu != nnu:
return besselj(nnu, z)
def eval(cls, nu, z):
from sympy import (unpolarify, expand_mul, uppergamma, exp, gamma,
factorial)
nu2 = unpolarify(nu)
if nu != nu2:
return expint(nu2, z)
if nu.is_Integer and nu <= 0 or (not nu.is_Integer and
(2 * nu).is_Integer):
return unpolarify(expand_mul(z**(nu - 1) * uppergamma(1 - nu, z)))
# Extract branching information. This can be deduced from what is
# explained in lowergamma.eval().
z, n = z.extract_branch_factor()
if n == 0:
return
if nu.is_integer:
if (nu > 0) is not True:
return
return expint(nu, z) \
- 2*pi*I*n*(-1)**(nu - 1)/factorial(nu - 1)*unpolarify(z)**(nu - 1)
else:
return (exp(2 * I * pi * nu * n) -
1) * z**(nu - 1) * gamma(1 - nu) + expint(nu, z)
def eval(cls, a, x):
# For lack of a better place, we use this one to extract branching
# information. The following can be
# found in the literature (c/f references given above), albeit scattered:
# 1) For fixed x != 0, lowergamma(s, x) is an entire function of s
# 2) For fixed positive integers s, lowergamma(s, x) is an entire
# function of x.
# 3) For fixed non-positive integers s,
# lowergamma(s, exp(I*2*pi*n)*x) =
# 2*pi*I*n*(-1)**(-s)/factorial(-s) + lowergamma(s, x)
# (this follows from lowergamma(s, x).diff(x) = x**(s-1)*exp(-x)).
# 4) For fixed non-integral s,
# lowergamma(s, x) = x**s*gamma(s)*lowergamma_unbranched(s, x),
# where lowergamma_unbranched(s, x) is an entire function (in fact
# of both s and x), i.e.
# lowergamma(s, exp(2*I*pi*n)*x) = exp(2*pi*I*n*a)*lowergamma(a, x)
from sympy import unpolarify, I
if x is S.Zero:
return S.Zero
nx, n = x.extract_branch_factor()
if a.is_integer and a.is_positive:
nx = unpolarify(x)
if nx != x:
return lowergamma(a, nx)
elif a.is_integer and a.is_nonpositive:
if n != 0:
return 2*pi*I*n*(-1)**(-a)/factorial(-a) + lowergamma(a, nx)
elif n != 0:
return exp(2*pi*I*n*a)*lowergamma(a, nx)
# Special values.
if a.is_Number:
if a is S.One:
return S.One - exp(-x)
elif a is S.Half:
return sqrt(pi)*erf(sqrt(x))
elif a.is_Integer or (2*a).is_Integer:
b = a - 1
if b.is_positive:
if a.is_integer:
return factorial(b) - exp(-x) * factorial(b) * Add(*[x ** k / factorial(k) for k in range(a)])
else:
return gamma(a)*(lowergamma(S.Half, x)/sqrt(pi) - exp(-x)*Add(*[x**(k - S.Half)/gamma(S.Half + k) for k in range(1, a + S.Half)]))
if not a.is_Integer:
return (-1)**(S.Half - a)*pi*erf(sqrt(x))/gamma(1 - a) + exp(-x)*Add(*[x**(k + a - 1)*gamma(a)/gamma(a + k) for k in range(1, Rational(3, 2) - a)])
if x.is_zero:
return S.Zero
def eval(cls, s, z):
s, z = sympify((s, z))
if z is S.One:
return zeta(s)
elif z is S.NegativeOne:
return -dirichlet_eta(s)
elif z is S.Zero:
return S.Zero
elif s == 2:
if z == S.Half:
return pi**2 / 12 - log(2)**2 / 2
elif z == 2:
return pi**2 / 4 - I * pi * log(2)
elif z == -(sqrt(5) - 1) / 2:
return -pi**2 / 15 + log((sqrt(5) - 1) / 2)**2 / 2
elif z == -(sqrt(5) + 1) / 2:
return -pi**2 / 10 - log((sqrt(5) + 1) / 2)**2
elif z == (3 - sqrt(5)) / 2:
return pi**2 / 15 - log((sqrt(5) - 1) / 2)**2
elif z == (sqrt(5) - 1) / 2:
return pi**2 / 10 - log((sqrt(5) - 1) / 2)**2
if z.is_zero:
return S.Zero
# Make an effort to determine if z is 1 to avoid replacing into
# expression with singularity
zone = z.equals(S.One)
if zone:
return zeta(s)
elif zone is False:
# For s = 0 or -1 use explicit formulas to evaluate, but
# automatically expanding polylog(1, z) to -log(1-z) seems
# undesirable for summation methods based on hypergeometric
# functions
if s is S.Zero:
return z / (1 - z)
elif s is S.NegativeOne:
return z / (1 - z)**2
if s.is_zero:
return z / (1 - z)
# polylog is branched, but not over the unit disk
from sympy.functions.elementary.complexes import (Abs, unpolarify,
polar_lift)
if z.has(exp_polar, polar_lift) and (zone or
(Abs(z) <= S.One) == True):
return cls(s, unpolarify(z))
def eval(cls, nu, z):
if z.is_zero:
if nu.is_zero:
return S.One
elif (nu.is_integer and nu.is_zero == False) or re(nu).is_positive:
return S.Zero
elif re(nu).is_negative and not (nu.is_integer == True):
return S.ComplexInfinity
elif nu.is_imaginary:
return S.NaN
if z.is_imaginary:
if im(z) is S.Infinity or im(z) is S.NegativeInfinity:
return S.Zero
if z.could_extract_minus_sign():
return (z)**nu * (-z)**(-nu) * besseli(nu, -z)
if nu.is_integer:
if nu.could_extract_minus_sign():
return besseli(-nu, z)
newz = z.extract_multiplicatively(I)
if newz: # NOTE we don't want to change the function if z==0
return I**(-nu) * besselj(nu, -newz)
# branch handling:
from sympy import unpolarify, exp
if nu.is_integer:
newz = unpolarify(z)
if newz != z:
return besseli(nu, newz)
else:
newz, n = z.extract_branch_factor()
if n != 0:
return exp(2 * n * pi * nu * I) * besseli(nu, newz)
nnu = unpolarify(nu)
if nu != nnu:
return besseli(nnu, z)
def eval(cls, n, z):
n, z = map(sympify, (n, z))
from sympy import unpolarify
if n.is_integer:
if n.is_nonnegative:
nz = unpolarify(z)
if z != nz:
return polygamma(n, nz)
if n == -1:
return loggamma(z)
else:
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
if n.is_Number:
if n is S.Zero:
return S.Infinity
else:
return S.Zero
elif z.is_Integer:
if z.is_nonpositive:
return S.ComplexInfinity
else:
if n is S.Zero:
return -S.EulerGamma + C.harmonic(z-1, 1)
elif n.is_odd:
return (-1)**(n+1)*C.factorial(n)*zeta(n+1, z)
if n == 0 and z.is_Rational:
# TODO actually *any* n/m can be done, but that is messy
lookup = {S(1)/2: -2*log(2) - S.EulerGamma,
S(1)/3: -S.Pi/2/sqrt(3) - 3*log(3)/2 - S.EulerGamma,
S(1)/4: -S.Pi/2 - 3*log(2) - S.EulerGamma,
S(3)/4: -3*log(2) - S.EulerGamma + S.Pi/2,
S(2)/3: -3*log(3)/2 + S.Pi/2/sqrt(3) - S.EulerGamma}
if z > 0:
n = floor(z)
z0 = z - n
if z0 in lookup:
return lookup[z0] + Add(*[1/(z0 + k) for k in range(n)])
elif z < 0:
n = floor(1 - z)
z0 = z + n
if z0 in lookup:
return lookup[z0] - Add(*[1/(z0 - 1 - k) for k in range(n)])
def eval(cls, n, z):
n, z = list(map(sympify, (n, z)))
from sympy import unpolarify
if n.is_integer:
if n.is_nonnegative:
nz = unpolarify(z)
if z != nz:
return polygamma(n, nz)
if n == -1:
return loggamma(z)
else:
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
if n.is_Number:
if n is S.Zero:
return S.Infinity
else:
return S.Zero
elif z.is_Integer:
if z.is_nonpositive:
return S.ComplexInfinity
else:
if n is S.Zero:
return -S.EulerGamma + harmonic(z - 1, 1)
elif n.is_odd:
return (-1)**(n + 1)*factorial(n)*zeta(n + 1, z)
if n == 0:
if z is S.NaN:
return S.NaN
elif z.is_Rational:
p, q = z.as_numer_denom()
# only expand for small denominators to avoid creating long expressions
if q <= 5:
return expand_func(polygamma(n, z, evaluate=False))
elif z in (S.Infinity, S.NegativeInfinity):
return S.Infinity
else:
t = z.extract_multiplicatively(S.ImaginaryUnit)
if t in (S.Infinity, S.NegativeInfinity):
return S.Infinity
def fdiff(self, argindex=2):
from sympy import meijerg, unpolarify
if argindex == 2:
a, z = self.args
return exp(-unpolarify(z)) * z ** (a - 1)
elif argindex == 1:
a, z = self.args
return (
gamma(a) * digamma(a)
- log(z) * uppergamma(a, z)
- meijerg([], [1, 1], [0, 0, a], [], z)
)
else:
raise ArgumentIndexError(self, argindex)
def eval(cls, a, x):
# For lack of a better place, we use this one to extract branching
# information. The following can be
# found in the literature (c/f references given above), albeit scattered:
# 1) For fixed x != 0, lowergamma(s, x) is an entire function of s
# 2) For fixed positive integers s, lowergamma(s, x) is an entire
# function of x.
# 3) For fixed non-positive integers s,
# lowergamma(s, exp(I*2*pi*n)*x) =
# 2*pi*I*n*(-1)**(-s)/factorial(-s) + lowergamma(s, x)
# (this follows from lowergamma(s, x).diff(x) = x**(s-1)*exp(-x)).
# 4) For fixed non-integral s,
# lowergamma(s, x) = x**s*gamma(s)*lowergamma_unbranched(s, x),
# where lowergamma_unbranched(s, x) is an entire function (in fact
# of both s and x), i.e.
# lowergamma(s, exp(2*I*pi*n)*x) = exp(2*pi*I*n*a)*lowergamma(a, x)
from sympy import unpolarify, I
if x == 0:
return S.Zero
nx, n = x.extract_branch_factor()
if a.is_integer and a.is_positive:
nx = unpolarify(x)
if nx != x:
return lowergamma(a, nx)
elif a.is_integer and a.is_nonpositive:
if n != 0:
return 2*pi*I*n*(-1)**(-a)/factorial(-a) + lowergamma(a, nx)
elif n != 0:
return exp(2*pi*I*n*a)*lowergamma(a, nx)
# Special values.
if a.is_Number:
if a is S.One:
return S.One - exp(-x)
elif a is S.Half:
return sqrt(pi)*erf(sqrt(x))
elif a.is_Integer or (2*a).is_Integer:
b = a - 1
if b.is_positive:
if a.is_integer:
return factorial(b) - exp(-x) * factorial(b) * Add(*[x ** k / factorial(k) for k in range(a)])
else:
return gamma(a) * (lowergamma(S.Half, x)/sqrt(pi) - exp(-x) * Add(*[x**(k-S.Half) / gamma(S.Half+k) for k in range(1, a+S.Half)]))
if not a.is_Integer:
return (-1)**(S.Half - a) * pi*erf(sqrt(x)) / gamma(1-a) + exp(-x) * Add(*[x**(k+a-1)*gamma(a) / gamma(a+k) for k in range(1, S(3)/2-a)])
def test_expint():
from sympy import E1, expint, Max, re, lerchphi, Symbol, simplify, Si, Ci, Ei
aneg = Symbol("a", negative=True)
u = Symbol("u", polar=True)
assert mellin_transform(E1(x), x, s) == (gamma(s) / s, (0, oo), True)
assert inverse_mellin_transform(gamma(s) / s, s, x, (0, oo)).rewrite(expint).expand() == E1(x)
assert mellin_transform(expint(a, x), x, s) == (gamma(s) / (a + s - 1), (Max(1 - re(a), 0), oo), True)
# XXX IMT has hickups with complicated strips ...
assert simplify(
unpolarify(
inverse_mellin_transform(gamma(s) / (aneg + s - 1), s, x, (1 - aneg, oo)).rewrite(expint).expand(func=True)
)
) == expint(aneg, x)
assert mellin_transform(Si(x), x, s) == (
-2 ** s * sqrt(pi) * gamma(s / 2 + S(1) / 2) / (2 * s * gamma(-s / 2 + 1)),
(-1, 0),
True,
)
assert inverse_mellin_transform(
-2 ** s * sqrt(pi) * gamma((s + 1) / 2) / (2 * s * gamma(-s / 2 + 1)), s, x, (-1, 0)
) == Si(x)
assert mellin_transform(Ci(sqrt(x)), x, s) == (
-2 ** (2 * s - 1) * sqrt(pi) * gamma(s) / (s * gamma(-s + S(1) / 2)),
(0, 1),
True,
)
assert inverse_mellin_transform(
-4 ** s * sqrt(pi) * gamma(s) / (2 * s * gamma(-s + S(1) / 2)), s, u, (0, 1)
).expand() == Ci(sqrt(u))
# TODO LT of Si, Shi, Chi is a mess ...
assert laplace_transform(Ci(x), x, s) == (-log(1 + s ** 2) / 2 / s, 0, True)
assert laplace_transform(expint(a, x), x, s) == (lerchphi(s * polar_lift(-1), 1, a), 0, S(0) < re(a))
assert laplace_transform(expint(1, x), x, s) == (log(s + 1) / s, 0, True)
assert laplace_transform(expint(2, x), x, s) == ((s - log(s + 1)) / s ** 2, 0, True)
assert inverse_laplace_transform(-log(1 + s ** 2) / 2 / s, s, u).expand() == Heaviside(u) * Ci(u)
assert inverse_laplace_transform(log(s + 1) / s, s, x).rewrite(expint) == Heaviside(x) * E1(x)
assert (
inverse_laplace_transform((s - log(s + 1)) / s ** 2, s, x).rewrite(expint).expand()
== (expint(2, x) * Heaviside(x)).rewrite(Ei).rewrite(expint).expand()
)
def eval(cls, a, x):
# For lack of a better place, we use this one to extract branching
# information. The following can be
# found in the literature (c/f references given above), albeit scattered:
# 1) For fixed x != 0, lowergamma(s, x) is an entire function of s
# 2) For fixed positive integers s, lowergamma(s, x) is an entire
# function of x.
# 3) For fixed non-positive integers s,
# lowergamma(s, exp(I*2*pi*n)*x) =
# 2*pi*I*n*(-1)**(-s)/factorial(-s) + lowergamma(s, x)
# (this follows from lowergamma(s, x).diff(x) = x**(s-1)*exp(-x)).
# 4) For fixed non-integral s,
# lowergamma(s, x) = x**s*gamma(s)*lowergamma_unbranched(s, x),
# where lowergamma_unbranched(s, x) is an entire function (in fact
# of both s and x), i.e.
# lowergamma(s, exp(2*I*pi*n)*x) = exp(2*pi*I*n*a)*lowergamma(a, x)
from sympy import unpolarify, I
if x == 0:
return S.Zero
nx, n = x.extract_branch_factor()
if a.is_integer and a.is_positive:
nx = unpolarify(x)
if nx != x:
return lowergamma(a, nx)
elif a.is_integer and a.is_nonpositive:
if n != 0:
return 2 * pi * I * n * (-1)**(
-a) / factorial(-a) + lowergamma(a, nx)
elif n != 0:
return exp(2 * pi * I * n * a) * lowergamma(a, nx)
# Special values.
if a.is_Number:
# TODO this should be non-recursive
if a is S.One:
return S.One - exp(-x)
elif a is S.Half:
return sqrt(pi) * erf(sqrt(x))
elif a.is_Integer or (2 * a).is_Integer:
b = a - 1
if b.is_positive:
return b * cls(b, x) - x**b * exp(-x)
if not a.is_Integer:
return (cls(a + 1, x) + x**a * exp(-x)) / a
def _prep_tuple(v):
"""
Turn an iterable argument V into a Tuple and unpolarify, since both
hypergeometric and meijer g-functions are unbranched in their parameters.
Examples
========
>>> from sympy.functions.special.hyper import _prep_tuple
>>> _prep_tuple([1, 2, 3])
(1, 2, 3)
>>> _prep_tuple((4, 5))
(4, 5)
>>> _prep_tuple((7, 8, 9))
(7, 8, 9)
"""
from sympy import unpolarify
return TupleArg(*[unpolarify(x) for x in v])
def _prep_tuple(v):
"""
Turn an iterable argument V into a Tuple and unpolarify, since both
hypergeometric and meijer g-functions are unbranched in their parameters.
Examples
========
>>> from sympy.functions.special.hyper import _prep_tuple
>>> _prep_tuple([1, 2, 3])
(1, 2, 3)
>>> _prep_tuple((4, 5))
(4, 5)
>>> _prep_tuple((7, 8, 9))
(7, 8, 9)
"""
from sympy import unpolarify
return TupleArg(*[unpolarify(x) for x in v])
def _make_tuple(v):
"""
Turn an iterable argument V into a Tuple.
Also unpolarify, since both hypergeometric and meijer g-functions are
unbranched in their parameters.
Examples:
>>> from sympy.functions.special.hyper import _make_tuple as mt
>>> from sympy.core.containers import Tuple
>>> mt([1, 2, 3])
(1, 2, 3)
>>> mt((4, 5))
(4, 5)
>>> mt((7, 8, 9))
(7, 8, 9)
"""
from sympy import unpolarify
return Tuple(*[unpolarify(sympify(x)) for x in v])
def _make_tuple(v):
"""
Turn an iterable argument V into a Tuple.
Also unpolarify, since both hypergeometric and meijer g-functions are
unbranched in their parameters.
Examples:
>>> from sympy.functions.special.hyper import _make_tuple as mt
>>> from sympy.core.containers import Tuple
>>> mt([1, 2, 3])
(1, 2, 3)
>>> mt((4, 5))
(4, 5)
>>> mt((7, 8, 9))
(7, 8, 9)
"""
from sympy import unpolarify
return Tuple(*[unpolarify(sympify(x)) for x in v])
def test_expint():
from sympy import E1, expint, Max, re, lerchphi, Symbol, simplify, Si, Ci, Ei
aneg = Symbol('a', negative=True)
u = Symbol('u', polar=True)
assert mellin_transform(E1(x), x, s) == (gamma(s) / s, (0, oo), True)
assert inverse_mellin_transform(gamma(s) / s, s, x,
(0, oo)).rewrite(expint).expand() == E1(x)
assert mellin_transform(expint(a, x), x, s) == \
(gamma(s)/(a + s - 1), (Max(1 - re(a), 0), oo), True)
# XXX IMT has hickups with complicated strips ...
assert simplify(unpolarify(
inverse_mellin_transform(gamma(s)/(aneg + s - 1), s, x,
(1 - aneg, oo)).rewrite(expint).expand(func=True))) == \
expint(aneg, x)
assert mellin_transform(Si(x), x, s) == \
(-2**s*sqrt(pi)*gamma(s/2 + S(1)/2)/(
2*s*gamma(-s/2 + 1)), (-1, 0), True)
assert inverse_mellin_transform(-2**s*sqrt(pi)*gamma((s + 1)/2)
/(2*s*gamma(-s/2 + 1)), s, x, (-1, 0)) \
== Si(x)
assert mellin_transform(Ci(sqrt(x)), x, s) == \
(-2**(2*s - 1)*sqrt(pi)*gamma(s)/(s*gamma(-s + S(1)/2)), (0, 1), True)
assert inverse_mellin_transform(
-4**s * sqrt(pi) * gamma(s) / (2 * s * gamma(-s + S(1) / 2)), s, u,
(0, 1)).expand() == Ci(sqrt(u))
# TODO LT of Si, Shi, Chi is a mess ...
assert laplace_transform(Ci(x), x, s) == (-log(1 + s**2) / 2 / s, 0, True)
assert laplace_transform(expint(a, x), x, s) == \
(lerchphi(s*polar_lift(-1), 1, a), 0, S(0) < re(a))
assert laplace_transform(expint(1, x), x, s) == (log(s + 1) / s, 0, True)
assert laplace_transform(expint(2, x), x, s) == \
((s - log(s + 1))/s**2, 0, True)
assert inverse_laplace_transform(-log(1 + s**2)/2/s, s, u).expand() == \
Heaviside(u)*Ci(u)
assert inverse_laplace_transform(log(s + 1)/s, s, x).rewrite(expint) == \
Heaviside(x)*E1(x)
assert inverse_laplace_transform((s - log(s + 1))/s**2, s,
x).rewrite(expint).expand() == \
(expint(2, x)*Heaviside(x)).rewrite(Ei).rewrite(expint).expand()
def eval(cls, a, x):
# For lack of a better place, we use this one to extract branching
# information. The following can be
# found in the literature (c/f references given above), albeit scattered:
# 1) For fixed x != 0, lowergamma(s, x) is an entire function of s
# 2) For fixed positive integers s, lowergamma(s, x) is an entire
# function of x.
# 3) For fixed non-positive integers s,
# lowergamma(s, exp(I*2*pi*n)*x) =
# 2*pi*I*n*(-1)**(-s)/factorial(-s) + lowergamma(s, x)
# (this follows from lowergamma(s, x).diff(x) = x**(s-1)*exp(-x)).
# 4) For fixed non-integral s,
# lowergamma(s, x) = x**s*gamma(s)*lowergamma_unbranched(s, x),
# where lowergamma_unbranched(s, x) is an entire function (in fact
# of both s and x), i.e.
# lowergamma(s, exp(2*I*pi*n)*x) = exp(2*pi*I*n*a)*lowergamma(a, x)
from sympy import unpolarify, I
if x == 0:
return S.Zero
nx, n = x.extract_branch_factor()
if a.is_integer and a.is_positive:
nx = unpolarify(x)
if nx != x:
return lowergamma(a, nx)
elif a.is_integer and a.is_nonpositive:
if n != 0:
return 2*pi*I*n*(-1)**(-a)/factorial(-a) + lowergamma(a, nx)
elif n != 0:
return exp(2*pi*I*n*a)*lowergamma(a, nx)
# Special values.
if a.is_Number:
# TODO this should be non-recursive
if a is S.One:
return S.One - exp(-x)
elif a is S.Half:
return sqrt(pi)*erf(sqrt(x))
elif a.is_Integer or (2*a).is_Integer:
b = a - 1
if b.is_positive:
return b*cls(b, x) - x**b * exp(-x)
if not a.is_Integer:
return (cls(a + 1, x) + x**a * exp(-x))/a
def can_do_meijer(a1, a2, b1, b2, numeric=True):
"""
This helper function tries to hyperexpand() the meijer g-function
corresponding to the parameters a1, a2, b1, b2.
It returns False if this expansion still contains g-functions.
If numeric is True, it also tests the so-obtained formula numerically
(at random values) and returns False if the test fails.
Else it returns True.
"""
from sympy import unpolarify, expand
r = hyperexpand(meijerg(a1, a2, b1, b2, z))
if r.has(meijerg):
return False
# NOTE hyperexpand() returns a truly branched function, whereas numerical
# evaluation only works on the main branch. Since we are evaluating on
# the main branch, this should not be a problem, but expressions like
# exp_polar(I*pi/2*x)**a are evaluated incorrectly. We thus have to get
# rid of them. The expand heuristically does this...
r = unpolarify(
expand(
r,
force=True,
power_base=True,
power_exp=False,
mul=False,
log=False,
multinomial=False,
basic=False,
))
if not numeric:
return True
repl = {}
for n, ai in enumerate(meijerg(a1, a2, b1, b2, z).free_symbols - {z}):
repl[ai] = randcplx(n)
return tn(meijerg(a1, a2, b1, b2, z).subs(repl), r.subs(repl), z)
def test_unpolarify():
from sympy import (exp_polar, polar_lift, exp, unpolarify,
principal_branch)
from sympy import gamma, erf, sin, tanh, uppergamma, Eq, Ne
from sympy.abc import x
p = exp_polar(7 * I) + 1
u = exp(7 * I) + 1
assert unpolarify(1) == 1
assert unpolarify(p) == u
assert unpolarify(p**2) == u**2
assert unpolarify(p**x) == p**x
assert unpolarify(p * x) == u * x
assert unpolarify(p + x) == u + x
assert unpolarify(sqrt(sin(p))) == sqrt(sin(u))
# Test reduction to principal branch 2*pi.
t = principal_branch(x, 2 * pi)
assert unpolarify(t) == x
assert unpolarify(sqrt(t)) == sqrt(t)
# Test exponents_only.
assert unpolarify(p**p, exponents_only=True) == p**u
assert unpolarify(uppergamma(x, p**p)) == uppergamma(x, p**u)
# Test functions.
assert unpolarify(sin(p)) == sin(u)
assert unpolarify(tanh(p)) == tanh(u)
assert unpolarify(gamma(p)) == gamma(u)
assert unpolarify(erf(p)) == erf(u)
assert unpolarify(uppergamma(x, p)) == uppergamma(x, p)
assert unpolarify(uppergamma(sin(p), sin(p + exp_polar(0)))) == \
uppergamma(sin(u), sin(u + 1))
assert unpolarify(uppergamma(polar_lift(0), 2*exp_polar(0))) == \
uppergamma(0, 2)
assert unpolarify(Eq(p, 0)) == Eq(u, 0)
assert unpolarify(Ne(p, 0)) == Ne(u, 0)
assert unpolarify(polar_lift(x) > 0) == (x > 0)
# Test bools
assert unpolarify(True) is True
def _eval_expand_log(self, deep=True, **hints):
from sympy import unpolarify, expand_log, factorint
from sympy.concrete import Sum, Product
from sympy.functions.elementary.complexes import Abs
force = hints.get('force', False)
factor = hints.get('factor', False)
if (len(self.args) == 2):
return expand_log(self.func(*self.args), deep=deep, force=force)
arg = self.args[0]
if arg.is_Integer:
# remove perfect powers
p = perfect_power(arg)
logarg = None
coeff = 1
if p is not False:
arg, coeff = p
logarg = self.func(arg)
# expand as product of its prime factors if factor=True
if factor:
p = factorint(arg)
if arg not in p.keys():
logarg = sum(n * log(val) for val, n in p.items())
if logarg is not None:
return coeff * logarg
elif arg.is_Rational:
return log(arg.p) - log(arg.q)
elif arg.is_Mul:
expr = []
nonpos = []
for x in arg.args:
if force or (x.is_real and not x.is_negative) or x.is_polar:
a = self.func(x)
if isinstance(a, log):
expr.append(self.func(x)._eval_expand_log(**hints))
else:
expr.append(a)
elif x.is_negative:
a = self.func(-x)
expr.append(a)
nonpos.append(S.NegativeOne)
else:
nonpos.append(x)
return Add(*expr) + log(Mul(*nonpos))
elif arg.is_Pow or isinstance(arg, exp):
# expanding log(b^e)
b = arg.base
e = arg.exp
if e % 2 == 0 and b.is_real:
# even power and real base obeys the power rule: log(b^e) = e log(Abs(b))
return e * self.func(Abs(b))
elif e % 2 == 1 and b.is_real:
# odd power and real base obeys the power rule: log(b^e) = e log(b)
return e * self.func(b)
elif force or (e.is_extended_real and
(b.is_positive or
((e + 1).is_positive and
(e - 1).is_nonpositive))) or b.is_polar:
a = self.func(b)
if isinstance(a, log):
return unpolarify(e) * a._eval_expand_log(**hints)
else:
return unpolarify(e) * a
elif isinstance(arg, Product):
if force or arg.function.is_positive:
return Sum(log(arg.function), *arg.limits)
return self.func(arg)
def eval(cls, arg, base=None):
from sympy import unpolarify
arg = sympify(arg)
if base is not None:
base = sympify(base)
if base == 1:
if arg == 1:
return S.NaN
else:
return S.ComplexInfinity
try:
# handle extraction of powers of the base now
# or else expand_log in Mul would have to handle this
n = multiplicity(base, arg)
if n:
den = base**n
if den.is_Integer:
return n + log(arg // den) / log(base)
else:
return n + log(arg / den) / log(base)
else:
return log(arg)/log(base)
except ValueError:
pass
if base is not S.Exp1:
return cls(arg)/cls(base)
else:
return cls(arg)
if arg.is_Number:
if arg is S.Zero:
return S.ComplexInfinity
elif arg is S.One:
return S.Zero
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Infinity
elif arg is S.NaN:
return S.NaN
elif arg.is_negative:
return S.Pi * S.ImaginaryUnit + cls(-arg)
elif arg.is_Rational:
if arg.q != 1:
return cls(arg.p) - cls(arg.q)
elif arg is S.ComplexInfinity:
return S.ComplexInfinity
elif arg is S.Exp1:
return S.One
elif arg.func is exp and arg.args[0].is_real:
return arg.args[0]
elif arg.func is exp_polar:
return unpolarify(arg.exp)
#don't autoexpand Pow or Mul (see the issue 252):
elif not arg.is_Add:
coeff = arg.as_coefficient(S.ImaginaryUnit)
if coeff is not None:
if coeff is S.Infinity:
return S.Infinity
elif coeff is S.NegativeInfinity:
return S.Infinity
elif coeff.is_Rational:
if coeff.is_nonnegative:
return S.Pi * S.ImaginaryUnit * S.Half + cls(coeff)
else:
return -S.Pi * S.ImaginaryUnit * S.Half + cls(-coeff)
def test_unpolarify():
from sympy import (exp_polar, polar_lift, exp, unpolarify,
principal_branch)
from sympy import gamma, erf, sin, tanh, uppergamma, Eq, Ne
from sympy.abc import x
p = exp_polar(7*I) + 1
u = exp(7*I) + 1
assert unpolarify(1) == 1
assert unpolarify(p) == u
assert unpolarify(p**2) == u**2
assert unpolarify(p**x) == p**x
assert unpolarify(p*x) == u*x
assert unpolarify(p + x) == u + x
assert unpolarify(sqrt(sin(p))) == sqrt(sin(u))
# Test reduction to principal branch 2*pi.
t = principal_branch(x, 2*pi)
assert unpolarify(t) == x
assert unpolarify(sqrt(t)) == sqrt(t)
# Test exponents_only.
assert unpolarify(p**p, exponents_only=True) == p**u
assert unpolarify(uppergamma(x, p**p)) == uppergamma(x, p**u)
# Test functions.
assert unpolarify(sin(p)) == sin(u)
assert unpolarify(tanh(p)) == tanh(u)
assert unpolarify(gamma(p)) == gamma(u)
assert unpolarify(erf(p)) == erf(u)
assert unpolarify(uppergamma(x, p)) == uppergamma(x, p)
assert unpolarify(uppergamma(sin(p), sin(p + exp_polar(0)))) == \
uppergamma(sin(u), sin(u + 1))
assert unpolarify(uppergamma(polar_lift(0), 2*exp_polar(0))) == \
uppergamma(0, 2)
assert unpolarify(Eq(p, 0)) == Eq(u, 0)
assert unpolarify(Ne(p, 0)) == Ne(u, 0)
assert unpolarify(polar_lift(x) > 0) == (x > 0)
# Test bools
assert unpolarify(True) is True
def _eval_expand_func(self, **hints):
from sympy import exp, I, floor, Add, Poly, Dummy, exp_polar, unpolarify
z, s, a = self.args
if z == 1:
return zeta(s, a)
if s.is_Integer and s <= 0:
t = Dummy("t")
p = Poly((t + a) ** (-s), t)
start = 1 / (1 - t)
res = S.Zero
for c in reversed(p.all_coeffs()):
res += c * start
start = t * start.diff(t)
return res.subs(t, z)
if a.is_Rational:
# See section 18 of
# Kelly B. Roach. Hypergeometric Function Representations.
# In: Proceedings of the 1997 International Symposium on Symbolic and
# Algebraic Computation, pages 205-211, New York, 1997. ACM.
# TODO should something be polarified here?
add = S.Zero
mul = S.One
# First reduce a to the interaval (0, 1]
if a > 1:
n = floor(a)
if n == a:
n -= 1
a -= n
mul = z ** (-n)
add = Add(*[-(z ** (k - n)) / (a + k) ** s for k in range(n)])
elif a <= 0:
n = floor(-a) + 1
a += n
mul = z ** n
add = Add(*[z ** (n - 1 - k) / (a - k - 1) ** s for k in range(n)])
m, n = S([a.p, a.q])
zet = exp_polar(2 * pi * I / n)
root = z ** (1 / n)
return add + mul * n ** (s - 1) * Add(
*[
polylog(s, zet ** k * root)._eval_expand_func(**hints)
/ (unpolarify(zet) ** k * root) ** m
for k in range(n)
]
)
# TODO use minpoly instead of ad-hoc methods when issue 5888 is fixed
if (
isinstance(z, exp)
and (z.args[0] / (pi * I)).is_Rational
or z in [-1, I, -I]
):
# TODO reference?
if z == -1:
p, q = S([1, 2])
elif z == I:
p, q = S([1, 4])
elif z == -I:
p, q = S([-1, 4])
else:
arg = z.args[0] / (2 * pi * I)
p, q = S([arg.p, arg.q])
return Add(
*[
exp(2 * pi * I * k * p / q) / q ** s * zeta(s, (k + a) / q)
for k in range(q)
]
)
return lerchphi(z, s, a)
def eval(cls, arg, base=None):
from sympy import unpolarify
from sympy.calculus import AccumBounds
from sympy.sets.setexpr import SetExpr
arg = sympify(arg)
if base is not None:
base = sympify(base)
if base == 1:
if arg == 1:
return S.NaN
else:
return S.ComplexInfinity
try:
# handle extraction of powers of the base now
# or else expand_log in Mul would have to handle this
n = multiplicity(base, arg)
if n:
den = base**n
if den.is_Integer:
return n + log(arg // den) / log(base)
else:
return n + log(arg / den) / log(base)
else:
return log(arg)/log(base)
except ValueError:
pass
if base is not S.Exp1:
return cls(arg)/cls(base)
else:
return cls(arg)
if arg.is_Number:
if arg is S.Zero:
return S.ComplexInfinity
elif arg is S.One:
return S.Zero
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Infinity
elif arg is S.NaN:
return S.NaN
elif arg.is_Rational and arg.p == 1:
return -cls(arg.q)
if arg is S.ComplexInfinity:
return S.ComplexInfinity
if isinstance(arg, exp) and arg.args[0].is_real:
return arg.args[0]
elif isinstance(arg, exp_polar):
return unpolarify(arg.exp)
elif isinstance(arg, AccumBounds):
if arg.min.is_positive:
return AccumBounds(log(arg.min), log(arg.max))
else:
return
elif isinstance(arg, SetExpr):
return arg._eval_func(cls)
if arg.is_number:
if arg.is_negative:
return S.Pi * S.ImaginaryUnit + cls(-arg)
elif arg is S.ComplexInfinity:
return S.ComplexInfinity
elif arg is S.Exp1:
return S.One
# don't autoexpand Pow or Mul (see the issue 3351):
if not arg.is_Add:
coeff = arg.as_coefficient(S.ImaginaryUnit)
if coeff is not None:
if coeff is S.Infinity:
return S.Infinity
elif coeff is S.NegativeInfinity:
return S.Infinity
elif coeff.is_Rational:
if coeff.is_nonnegative:
return S.Pi * S.ImaginaryUnit * S.Half + cls(coeff)
else:
return -S.Pi * S.ImaginaryUnit * S.Half + cls(-coeff)
def fdiff(self, argindex=1):
from sympy import unpolarify
arg = unpolarify(self.args[0])
if argindex == 1:
return self._trigfunc(arg)/arg
def eval(cls, ap, bq, z):
from sympy import unpolarify
if len(ap) <= len(bq) or (len(ap) == len(bq) + 1 and (Abs(z) <= 1) == True):
nz = unpolarify(z)
if z != nz:
return hyper(ap, bq, nz)
def eval(cls, arg, base=None):
from sympy import unpolarify
arg = sympify(arg)
if base is not None:
base = sympify(base)
if base == 1:
if arg == 1:
return S.NaN
else:
return S.ComplexInfinity
try:
if not (base.is_positive and arg.is_positive):
raise ValueError
n = multiplicity(base, arg)
if n:
den = base**n
if den.is_Integer:
return n + log(arg // den) / log(base)
else:
return n + log(arg / den) / log(base)
else:
return log(arg)/log(base)
except ValueError:
pass
if base is not S.Exp1:
return cls(arg)/cls(base)
else:
return cls(arg)
if arg.is_Number:
if arg is S.Zero:
return S.ComplexInfinity
elif arg is S.One:
return S.Zero
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Infinity
elif arg is S.NaN:
return S.NaN
elif arg.is_negative:
return S.Pi * S.ImaginaryUnit + cls(-arg)
elif arg.is_Rational:
if arg.q != 1:
return cls(arg.p) - cls(arg.q)
# remove perfect powers automatically
p = perfect_power(int(arg))
if p is not False:
return p[1]*cls(p[0])
elif arg is S.ComplexInfinity:
return S.ComplexInfinity
elif arg is S.Exp1:
return S.One
elif arg.func is exp and arg.args[0].is_real:
return arg.args[0]
elif arg.func is exp_polar:
return unpolarify(arg.exp)
#don't autoexpand Pow or Mul (see the issue 252):
elif not arg.is_Add:
coeff = arg.as_coefficient(S.ImaginaryUnit)
if coeff is not None:
if coeff is S.Infinity:
return S.Infinity
elif coeff is S.NegativeInfinity:
return S.Infinity
elif coeff.is_Rational:
if coeff.is_nonnegative:
return S.Pi * S.ImaginaryUnit * S.Half + cls(coeff)
else:
return -S.Pi * S.ImaginaryUnit * S.Half + cls(-coeff)
def fdiff(self, argindex=1):
from sympy import unpolarify
arg = unpolarify(self.args[0])
if argindex == 1:
return self._trigfunc(arg)/arg
def mysimp(expr):
return expand(
unpolarify(simplify(expand(expand_func(expr.rewrite(besselj))))))
def unpolarify(x):
return diffify(sympy.unpolarify(x))
def eval(cls, ap, bq, z):
from sympy import unpolarify
if len(ap) <= len(bq) or (len(ap) == len(bq) + 1 and (Abs(z) <= 1) == True):
nz = unpolarify(z)
if z != nz:
return hyper(ap, bq, nz)
def eval(cls, a, z):
from sympy import unpolarify, I, expint
if z.is_Number:
if z is S.NaN:
return S.NaN
elif z is S.Infinity:
return S.Zero
elif z.is_zero:
if re(a).is_positive:
return gamma(a)
# We extract branching information here. C/f lowergamma.
nx, n = z.extract_branch_factor()
if a.is_integer and a.is_positive:
nx = unpolarify(z)
if z != nx:
return uppergamma(a, nx)
elif a.is_integer and a.is_nonpositive:
if n != 0:
return -2 * pi * I * n * (-1) ** (-a) / factorial(-a) + uppergamma(
a, nx
)
elif n != 0:
return gamma(a) * (1 - exp(2 * pi * I * n * a)) + exp(
2 * pi * I * n * a
) * uppergamma(a, nx)
# Special values.
if a.is_Number:
if a is S.Zero and z.is_positive:
return -Ei(-z)
elif a is S.One:
return exp(-z)
elif a is S.Half:
return sqrt(pi) * erfc(sqrt(z))
elif a.is_Integer or (2 * a).is_Integer:
b = a - 1
if b.is_positive:
if a.is_integer:
return (
exp(-z)
* factorial(b)
* Add(*[z ** k / factorial(k) for k in range(a)])
)
else:
return gamma(a) * erfc(sqrt(z)) + (-1) ** (a - S(3) / 2) * exp(
-z
) * sqrt(z) * Add(
*[
gamma(-S.Half - k) * (-z) ** k / gamma(1 - a)
for k in range(a - S.Half)
]
)
elif b.is_Integer:
return expint(-b, z) * unpolarify(z) ** (b + 1)
if not a.is_Integer:
return (-1) ** (S.Half - a) * pi * erfc(sqrt(z)) / gamma(
1 - a
) - z ** a * exp(-z) * Add(
*[
z ** k * gamma(a) / gamma(a + k + 1)
for k in range(S.Half - a)
]
)
if a.is_zero and z.is_positive:
return -Ei(-z)
if z.is_zero and re(a).is_positive:
return gamma(a)
def test_issue_14216():
from sympy.functions.elementary.complexes import unpolarify
A = MatrixSymbol("A", 2, 2)
assert unpolarify(A[0, 0]) == A[0, 0]
assert unpolarify(A[0, 0] * A[1, 0]) == A[0, 0] * A[1, 0]
def test_expint():
""" Test various exponential integrals. """
from sympy import (
expint,
unpolarify,
Symbol,
Ci,
Si,
Shi,
Chi,
sin,
cos,
sinh,
cosh,
Ei,
)
assert simplify(
unpolarify(
integrate(exp(-z * x) / x ** y, (x, 1, oo), meijerg=True, conds="none")
.rewrite(expint)
.expand(func=True)
)
) == expint(y, z)
assert integrate(exp(-z * x) / x, (x, 1, oo), meijerg=True, conds="none").rewrite(
expint
).expand() == expint(1, z)
assert integrate(
exp(-z * x) / x ** 2, (x, 1, oo), meijerg=True, conds="none"
).rewrite(expint).expand() == expint(2, z).rewrite(Ei).rewrite(expint)
assert (
integrate(exp(-z * x) / x ** 3, (x, 1, oo), meijerg=True, conds="none")
.rewrite(expint)
.expand()
== expint(3, z).rewrite(Ei).rewrite(expint).expand()
)
t = Symbol("t", positive=True)
assert integrate(-cos(x) / x, (x, t, oo), meijerg=True).expand() == Ci(t)
assert integrate(-sin(x) / x, (x, t, oo), meijerg=True).expand() == Si(t) - pi / 2
assert integrate(sin(x) / x, (x, 0, z), meijerg=True) == Si(z)
assert integrate(sinh(x) / x, (x, 0, z), meijerg=True) == Shi(z)
assert integrate(exp(-x) / x, x, meijerg=True).expand().rewrite(
expint
) == I * pi - expint(1, x)
assert (
integrate(exp(-x) / x ** 2, x, meijerg=True).rewrite(expint).expand()
== expint(1, x) - exp(-x) / x - I * pi
)
u = Symbol("u", polar=True)
assert integrate(cos(u) / u, u, meijerg=True).expand().as_independent(u)[1] == Ci(u)
assert integrate(cosh(u) / u, u, meijerg=True).expand().as_independent(u)[1] == Chi(
u
)
assert integrate(expint(1, x), x, meijerg=True).rewrite(
expint
).expand() == x * expint(1, x) - exp(-x)
assert (
integrate(expint(2, x), x, meijerg=True).rewrite(expint).expand()
== -(x ** 2) * expint(1, x) / 2 + x * exp(-x) / 2 - exp(-x) / 2
)
assert simplify(
unpolarify(
integrate(expint(y, x), x, meijerg=True).rewrite(expint).expand(func=True)
)
) == -expint(y + 1, x)
assert integrate(Si(x), x, meijerg=True) == x * Si(x) + cos(x)
assert integrate(Ci(u), u, meijerg=True).expand() == u * Ci(u) - sin(u)
assert integrate(Shi(x), x, meijerg=True) == x * Shi(x) - cosh(x)
assert integrate(Chi(u), u, meijerg=True).expand() == u * Chi(u) - sinh(u)
assert integrate(Si(x) * exp(-x), (x, 0, oo), meijerg=True) == pi / 4
assert integrate(expint(1, x) * sin(x), (x, 0, oo), meijerg=True) == log(2) / 2
def eval(cls, arg, base=None):
from sympy import unpolarify
from sympy.calculus import AccumBounds
from sympy.sets.setexpr import SetExpr
from sympy.functions.elementary.complexes import Abs
arg = sympify(arg)
if base is not None:
base = sympify(base)
if base == 1:
if arg == 1:
return S.NaN
else:
return S.ComplexInfinity
try:
# handle extraction of powers of the base now
# or else expand_log in Mul would have to handle this
n = multiplicity(base, arg)
if n:
return n + log(arg / base**n) / log(base)
else:
return log(arg) / log(base)
except ValueError:
pass
if base is not S.Exp1:
return cls(arg) / cls(base)
else:
return cls(arg)
if arg.is_Number:
if arg.is_zero:
return S.ComplexInfinity
elif arg is S.One:
return S.Zero
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Infinity
elif arg is S.NaN:
return S.NaN
elif arg.is_Rational and arg.p == 1:
return -cls(arg.q)
if arg.is_Pow and arg.base is S.Exp1 and arg.exp.is_extended_real:
return arg.exp
I = S.ImaginaryUnit
if isinstance(arg, exp) and arg.exp.is_extended_real:
return arg.exp
elif isinstance(arg, exp) and arg.exp.is_number:
r_, i_ = match_real_imag(arg.exp)
if i_ and i_.is_comparable:
i_ %= 2 * S.Pi
if i_ > S.Pi:
i_ -= 2 * S.Pi
return r_ + expand_mul(i_ * I, deep=False)
elif isinstance(arg, exp_polar):
return unpolarify(arg.exp)
elif isinstance(arg, AccumBounds):
if arg.min.is_positive:
return AccumBounds(log(arg.min), log(arg.max))
else:
return
elif isinstance(arg, SetExpr):
return arg._eval_func(cls)
if arg.is_number:
if arg.is_negative:
return S.Pi * I + cls(-arg)
elif arg is S.ComplexInfinity:
return S.ComplexInfinity
elif arg is S.Exp1:
return S.One
if arg.is_zero:
return S.ComplexInfinity
# don't autoexpand Pow or Mul (see the issue 3351):
if not arg.is_Add:
coeff = arg.as_coefficient(I)
if coeff is not None:
if coeff is S.Infinity:
return S.Infinity
elif coeff is S.NegativeInfinity:
return S.Infinity
elif coeff.is_Rational:
if coeff.is_nonnegative:
return S.Pi * I * S.Half + cls(coeff)
else:
return -S.Pi * I * S.Half + cls(-coeff)
if arg.is_number and arg.is_algebraic:
# Match arg = coeff*(r_ + i_*I) with coeff>0, r_ and i_ real.
coeff, arg_ = arg.as_independent(I, as_Add=False)
if coeff.is_negative:
coeff *= -1
arg_ *= -1
arg_ = expand_mul(arg_, deep=False)
r_, i_ = arg_.as_independent(I, as_Add=True)
i_ = i_.as_coefficient(I)
if coeff.is_real and i_ and i_.is_real and r_.is_real:
if r_.is_zero:
if i_.is_positive:
return S.Pi * I * S.Half + cls(coeff * i_)
elif i_.is_negative:
return -S.Pi * I * S.Half + cls(coeff * -i_)
else:
from sympy.simplify import ratsimp
# Check for arguments involving rational multiples of pi
t = (i_ / r_).cancel()
t1 = (-t).cancel()
atan_table = {
# first quadrant only
sqrt(3):
S.Pi / 3,
1:
S.Pi / 4,
sqrt(5 - 2 * sqrt(5)):
S.Pi / 5,
sqrt(2) * sqrt(5 - sqrt(5)) / (1 + sqrt(5)):
S.Pi / 5,
sqrt(5 + 2 * sqrt(5)):
S.Pi * Rational(2, 5),
sqrt(2) * sqrt(sqrt(5) + 5) / (-1 + sqrt(5)):
S.Pi * Rational(2, 5),
sqrt(3) / 3:
S.Pi / 6,
sqrt(2) - 1:
S.Pi / 8,
sqrt(2 - sqrt(2)) / sqrt(sqrt(2) + 2):
S.Pi / 8,
sqrt(2) + 1:
S.Pi * Rational(3, 8),
sqrt(sqrt(2) + 2) / sqrt(2 - sqrt(2)):
S.Pi * Rational(3, 8),
sqrt(1 - 2 * sqrt(5) / 5):
S.Pi / 10,
(-sqrt(2) + sqrt(10)) / (2 * sqrt(sqrt(5) + 5)):
S.Pi / 10,
sqrt(1 + 2 * sqrt(5) / 5):
S.Pi * Rational(3, 10),
(sqrt(2) + sqrt(10)) / (2 * sqrt(5 - sqrt(5))):
S.Pi * Rational(3, 10),
2 - sqrt(3):
S.Pi / 12,
(-1 + sqrt(3)) / (1 + sqrt(3)):
S.Pi / 12,
2 + sqrt(3):
S.Pi * Rational(5, 12),
(1 + sqrt(3)) / (-1 + sqrt(3)):
S.Pi * Rational(5, 12)
}
if t in atan_table:
modulus = ratsimp(coeff * Abs(arg_))
if r_.is_positive:
return cls(modulus) + I * atan_table[t]
else:
return cls(modulus) + I * (atan_table[t] - S.Pi)
elif t1 in atan_table:
modulus = ratsimp(coeff * Abs(arg_))
if r_.is_positive:
return cls(modulus) + I * (-atan_table[t1])
else:
return cls(modulus) + I * (S.Pi - atan_table[t1])
def eval(cls, ap, bq, z):
from sympy import unpolarify
if len(ap) <= len(bq):
nz = unpolarify(z)
if z != nz:
return hyper(ap, bq, nz)
def eval(cls, ap, bq, z):
from sympy import unpolarify
if len(ap) <= len(bq):
nz = unpolarify(z)
if z != nz:
return hyper(ap, bq, nz)
def eval(cls, arg, base=None):
from sympy import unpolarify
from sympy.calculus import AccumBounds
from sympy.sets.setexpr import SetExpr
arg = sympify(arg)
if base is not None:
base = sympify(base)
if base == 1:
if arg == 1:
return S.NaN
else:
return S.ComplexInfinity
try:
# handle extraction of powers of the base now
# or else expand_log in Mul would have to handle this
n = multiplicity(base, arg)
if n:
den = base**n
if den.is_Integer:
return n + log(arg // den) / log(base)
else:
return n + log(arg / den) / log(base)
else:
return log(arg) / log(base)
except ValueError:
pass
if base is not S.Exp1:
return cls(arg) / cls(base)
else:
return cls(arg)
if arg.is_Number:
if arg is S.Zero:
return S.ComplexInfinity
elif arg is S.One:
return S.Zero
elif arg is S.Infinity:
return S.Infinity
elif arg is S.NegativeInfinity:
return S.Infinity
elif arg is S.NaN:
return S.NaN
elif arg.is_Rational and arg.p == 1:
return -cls(arg.q)
if arg is S.ComplexInfinity:
return S.ComplexInfinity
if isinstance(arg, exp) and arg.args[0].is_real:
return arg.args[0]
elif isinstance(arg, exp_polar):
return unpolarify(arg.exp)
elif isinstance(arg, AccumBounds):
if arg.min.is_positive:
return AccumBounds(log(arg.min), log(arg.max))
else:
return
elif isinstance(arg, SetExpr):
return arg._eval_func(cls)
if arg.is_number:
if arg.is_negative:
return S.Pi * S.ImaginaryUnit + cls(-arg)
elif arg is S.ComplexInfinity:
return S.ComplexInfinity
elif arg is S.Exp1:
return S.One
# don't autoexpand Pow or Mul (see the issue 3351):
if not arg.is_Add:
coeff = arg.as_coefficient(S.ImaginaryUnit)
if coeff is not None:
if coeff is S.Infinity:
return S.Infinity
elif coeff is S.NegativeInfinity:
return S.Infinity
elif coeff.is_Rational:
if coeff.is_nonnegative:
return S.Pi * S.ImaginaryUnit * S.Half + cls(coeff)
else:
return -S.Pi * S.ImaginaryUnit * S.Half + cls(-coeff)