def test_issue_22606():
fx = Function('f')(x)
eq = x + gamma(y)
# seems like ans should be `eq`, not `(x*y + gamma(y + 1))/y`
ans = gammasimp(eq)
assert gammasimp(eq.subs(x, fx)).subs(fx, x) == ans
assert gammasimp(eq.subs(x, cos(x))).subs(cos(x), x) == ans
assert 1 / gammasimp(1 / eq) == ans
assert gammasimp(fx.subs(x, eq)).args[0] == ans
def test_lerchphi():
from sympy.functions.special.zeta_functions import (lerchphi, polylog)
from sympy.simplify.gammasimp import gammasimp
assert hyperexpand(hyper([1, a], [a + 1], z)/a) == lerchphi(z, 1, a)
assert hyperexpand(
hyper([1, a, a], [a + 1, a + 1], z)/a**2) == lerchphi(z, 2, a)
assert hyperexpand(hyper([1, a, a, a], [a + 1, a + 1, a + 1], z)/a**3) == \
lerchphi(z, 3, a)
assert hyperexpand(hyper([1] + [a]*10, [a + 1]*10, z)/a**10) == \
lerchphi(z, 10, a)
assert gammasimp(hyperexpand(meijerg([0, 1 - a], [], [0],
[-a], exp_polar(-I*pi)*z))) == lerchphi(z, 1, a)
assert gammasimp(hyperexpand(meijerg([0, 1 - a, 1 - a], [], [0],
[-a, -a], exp_polar(-I*pi)*z))) == lerchphi(z, 2, a)
assert gammasimp(hyperexpand(meijerg([0, 1 - a, 1 - a, 1 - a], [], [0],
[-a, -a, -a], exp_polar(-I*pi)*z))) == lerchphi(z, 3, a)
assert hyperexpand(z*hyper([1, 1], [2], z)) == -log(1 + -z)
assert hyperexpand(z*hyper([1, 1, 1], [2, 2], z)) == polylog(2, z)
assert hyperexpand(z*hyper([1, 1, 1, 1], [2, 2, 2], z)) == polylog(3, z)
assert hyperexpand(hyper([1, a, 1 + S.Half], [a + 1, S.Half], z)) == \
-2*a/(z - 1) + (-2*a**2 + a)*lerchphi(z, 1, a)
# Now numerical tests. These make sure reductions etc are carried out
# correctly
# a rational function (polylog at negative integer order)
assert can_do([2, 2, 2], [1, 1])
# NOTE these contain log(1-x) etc ... better make sure we have |z| < 1
# reduction of order for polylog
assert can_do([1, 1, 1, b + 5], [2, 2, b], div=10)
# reduction of order for lerchphi
# XXX lerchphi in mpmath is flaky
assert can_do(
[1, a, a, a, b + 5], [a + 1, a + 1, a + 1, b], numerical=False)
# test a bug
from sympy.functions.elementary.complexes import Abs
assert hyperexpand(hyper([S.Half, S.Half, S.Half, 1],
[Rational(3, 2), Rational(3, 2), Rational(3, 2)], Rational(1, 4))) == \
Abs(-polylog(3, exp_polar(I*pi)/2) + polylog(3, S.Half))
def combsimp(expr):
r"""
Simplify combinatorial expressions.
Explanation
===========
This function takes as input an expression containing factorials,
binomials, Pochhammer symbol and other "combinatorial" functions,
and tries to minimize the number of those functions and reduce
the size of their arguments.
The algorithm works by rewriting all combinatorial functions as
gamma functions and applying gammasimp() except simplification
steps that may make an integer argument non-integer. See docstring
of gammasimp for more information.
Then it rewrites expression in terms of factorials and binomials by
rewriting gammas as factorials and converting (a+b)!/a!b! into
binomials.
If expression has gamma functions or combinatorial functions
with non-integer argument, it is automatically passed to gammasimp.
Examples
========
>>> from sympy.simplify import combsimp
>>> from sympy import factorial, binomial, symbols
>>> n, k = symbols('n k', integer = True)
>>> combsimp(factorial(n)/factorial(n - 3))
n*(n - 2)*(n - 1)
>>> combsimp(binomial(n+1, k+1)/binomial(n, k))
(n + 1)/(k + 1)
"""
expr = expr.rewrite(gamma, piecewise=False)
if any(
isinstance(node, gamma) and not node.args[0].is_integer
for node in preorder_traversal(expr)):
return gammasimp(expr)
expr = _gammasimp(expr, as_comb=True)
expr = _gamma_as_comb(expr)
return expr
def combsimp(expr):
r"""
Simplify combinatorial expressions.
This function takes as input an expression containing factorials,
binomials, Pochhammer symbol and other "combinatorial" functions,
and tries to minimize the number of those functions and reduce
the size of their arguments.
The algorithm works by rewriting all combinatorial functions as
gamma functions and applying gammasimp() except simplification
steps that may make an integer argument non-integer. See docstring
of gammasimp for more information.
Then it rewrites expression in terms of factorials and binomials by
rewriting gammas as factorials and converting (a+b)!/a!b! into
binomials.
If expression has gamma functions or combinatorial functions
with non-integer argument, it is automatically passed to gammasimp.
Examples
========
>>> from sympy.simplify import combsimp
>>> from sympy import factorial, binomial, symbols
>>> n, k = symbols('n k', integer = True)
>>> combsimp(factorial(n)/factorial(n - 3))
n*(n - 2)*(n - 1)
>>> combsimp(binomial(n+1, k+1)/binomial(n, k))
(n + 1)/(k + 1)
"""
expr = expr.rewrite(gamma)
if any(isinstance(node, gamma) and not node.args[0].is_integer
for node in preorder_traversal(expr)):
return gammasimp(expr);
expr = _gammasimp(expr, as_comb = True)
expr = _gamma_as_comb(expr)
return expr
def test_probability():
# various integrals from probability theory
from sympy.core.function import expand_mul
from sympy.core.symbol import (Symbol, symbols)
from sympy.functions.elementary.complexes import Abs
from sympy.simplify.gammasimp import gammasimp
from sympy.simplify.powsimp import powsimp
mu1, mu2 = symbols('mu1 mu2', nonzero=True)
sigma1, sigma2 = symbols('sigma1 sigma2', positive=True)
rate = Symbol('lambda', positive=True)
def normal(x, mu, sigma):
return 1 / sqrt(2 * pi * sigma**2) * exp(-(x - mu)**2 / 2 / sigma**2)
def exponential(x, rate):
return rate * exp(-rate * x)
assert integrate(normal(x, mu1, sigma1), (x, -oo, oo), meijerg=True) == 1
assert integrate(x*normal(x, mu1, sigma1), (x, -oo, oo), meijerg=True) == \
mu1
assert integrate(x**2*normal(x, mu1, sigma1), (x, -oo, oo), meijerg=True) \
== mu1**2 + sigma1**2
assert integrate(x**3*normal(x, mu1, sigma1), (x, -oo, oo), meijerg=True) \
== mu1**3 + 3*mu1*sigma1**2
assert integrate(normal(x, mu1, sigma1) * normal(y, mu2, sigma2),
(x, -oo, oo), (y, -oo, oo),
meijerg=True) == 1
assert integrate(x * normal(x, mu1, sigma1) * normal(y, mu2, sigma2),
(x, -oo, oo), (y, -oo, oo),
meijerg=True) == mu1
assert integrate(y * normal(x, mu1, sigma1) * normal(y, mu2, sigma2),
(x, -oo, oo), (y, -oo, oo),
meijerg=True) == mu2
assert integrate(x * y * normal(x, mu1, sigma1) * normal(y, mu2, sigma2),
(x, -oo, oo), (y, -oo, oo),
meijerg=True) == mu1 * mu2
assert integrate(
(x + y + 1) * normal(x, mu1, sigma1) * normal(y, mu2, sigma2),
(x, -oo, oo), (y, -oo, oo),
meijerg=True) == 1 + mu1 + mu2
assert integrate((x + y - 1)*normal(x, mu1, sigma1)*normal(y, mu2, sigma2),
(x, -oo, oo), (y, -oo, oo), meijerg=True) == \
-1 + mu1 + mu2
i = integrate(x**2 * normal(x, mu1, sigma1) * normal(y, mu2, sigma2),
(x, -oo, oo), (y, -oo, oo),
meijerg=True)
assert not i.has(Abs)
assert simplify(i) == mu1**2 + sigma1**2
assert integrate(y**2*normal(x, mu1, sigma1)*normal(y, mu2, sigma2),
(x, -oo, oo), (y, -oo, oo), meijerg=True) == \
sigma2**2 + mu2**2
assert integrate(exponential(x, rate), (x, 0, oo), meijerg=True) == 1
assert integrate(x*exponential(x, rate), (x, 0, oo), meijerg=True) == \
1/rate
assert integrate(x**2*exponential(x, rate), (x, 0, oo), meijerg=True) == \
2/rate**2
def E(expr):
res1 = integrate(expr * exponential(x, rate) * normal(y, mu1, sigma1),
(x, 0, oo), (y, -oo, oo),
meijerg=True)
res2 = integrate(expr * exponential(x, rate) * normal(y, mu1, sigma1),
(y, -oo, oo), (x, 0, oo),
meijerg=True)
assert expand_mul(res1) == expand_mul(res2)
return res1
assert E(1) == 1
assert E(x * y) == mu1 / rate
assert E(x * y**2) == mu1**2 / rate + sigma1**2 / rate
ans = sigma1**2 + 1 / rate**2
assert simplify(E((x + y + 1)**2) - E(x + y + 1)**2) == ans
assert simplify(E((x + y - 1)**2) - E(x + y - 1)**2) == ans
assert simplify(E((x + y)**2) - E(x + y)**2) == ans
# Beta' distribution
alpha, beta = symbols('alpha beta', positive=True)
betadist = x**(alpha - 1)*(1 + x)**(-alpha - beta)*gamma(alpha + beta) \
/gamma(alpha)/gamma(beta)
assert integrate(betadist, (x, 0, oo), meijerg=True) == 1
i = integrate(x * betadist, (x, 0, oo), meijerg=True, conds='separate')
assert (gammasimp(i[0]), i[1]) == (alpha / (beta - 1), 1 < beta)
j = integrate(x**2 * betadist, (x, 0, oo), meijerg=True, conds='separate')
assert j[1] == (beta > 2)
assert gammasimp(j[0] - i[0]**2) == (alpha + beta - 1)*alpha \
/(beta - 2)/(beta - 1)**2
# Beta distribution
# NOTE: this is evaluated using antiderivatives. It also tests that
# meijerint_indefinite returns the simplest possible answer.
a, b = symbols('a b', positive=True)
betadist = x**(a - 1) * (-x + 1)**(b - 1) * gamma(a + b) / (gamma(a) *
gamma(b))
assert simplify(integrate(betadist, (x, 0, 1), meijerg=True)) == 1
assert simplify(integrate(x*betadist, (x, 0, 1), meijerg=True)) == \
a/(a + b)
assert simplify(integrate(x**2*betadist, (x, 0, 1), meijerg=True)) == \
a*(a + 1)/(a + b)/(a + b + 1)
assert simplify(integrate(x**y*betadist, (x, 0, 1), meijerg=True)) == \
gamma(a + b)*gamma(a + y)/gamma(a)/gamma(a + b + y)
# Chi distribution
k = Symbol('k', integer=True, positive=True)
chi = 2**(1 - k / 2) * x**(k - 1) * exp(-x**2 / 2) / gamma(k / 2)
assert powsimp(integrate(chi, (x, 0, oo), meijerg=True)) == 1
assert simplify(integrate(x*chi, (x, 0, oo), meijerg=True)) == \
sqrt(2)*gamma((k + 1)/2)/gamma(k/2)
assert simplify(integrate(x**2 * chi, (x, 0, oo), meijerg=True)) == k
# Chi^2 distribution
chisquared = 2**(-k / 2) / gamma(k / 2) * x**(k / 2 - 1) * exp(-x / 2)
assert powsimp(integrate(chisquared, (x, 0, oo), meijerg=True)) == 1
assert simplify(integrate(x * chisquared, (x, 0, oo), meijerg=True)) == k
assert simplify(integrate(x**2*chisquared, (x, 0, oo), meijerg=True)) == \
k*(k + 2)
assert gammasimp(
integrate(((x - k) / sqrt(2 * k))**3 * chisquared, (x, 0, oo),
meijerg=True)) == 2 * sqrt(2) / sqrt(k)
# Dagum distribution
a, b, p = symbols('a b p', positive=True)
# XXX (x/b)**a does not work
dagum = a * p / x * (x / b)**(a * p) / (1 + x**a / b**a)**(p + 1)
assert simplify(integrate(dagum, (x, 0, oo), meijerg=True)) == 1
# XXX conditions are a mess
arg = x * dagum
assert simplify(integrate(
arg, (x, 0, oo), meijerg=True,
conds='none')) == a * b * gamma(1 - 1 / a) * gamma(p + 1 + 1 / a) / (
(a * p + 1) * gamma(p))
assert simplify(integrate(
x * arg, (x, 0, oo), meijerg=True,
conds='none')) == a * b**2 * gamma(1 -
2 / a) * gamma(p + 1 + 2 / a) / (
(a * p + 2) * gamma(p))
# F-distribution
d1, d2 = symbols('d1 d2', positive=True)
f = sqrt(((d1*x)**d1 * d2**d2)/(d1*x + d2)**(d1 + d2))/x \
/gamma(d1/2)/gamma(d2/2)*gamma((d1 + d2)/2)
assert simplify(integrate(f, (x, 0, oo), meijerg=True)) == 1
# TODO conditions are a mess
assert simplify(integrate(x * f, (x, 0, oo), meijerg=True,
conds='none')) == d2 / (d2 - 2)
assert simplify(
integrate(x**2 * f, (x, 0, oo), meijerg=True,
conds='none')) == d2**2 * (d1 + 2) / d1 / (d2 - 4) / (d2 - 2)
# TODO gamma, rayleigh
# inverse gaussian
lamda, mu = symbols('lamda mu', positive=True)
dist = sqrt(lamda / 2 / pi) * x**(Rational(-3, 2)) * exp(
-lamda * (x - mu)**2 / x / 2 / mu**2)
mysimp = lambda expr: simplify(expr.rewrite(exp))
assert mysimp(integrate(dist, (x, 0, oo))) == 1
assert mysimp(integrate(x * dist, (x, 0, oo))) == mu
assert mysimp(integrate((x - mu)**2 * dist, (x, 0, oo))) == mu**3 / lamda
assert mysimp(integrate((x - mu)**3 * dist,
(x, 0, oo))) == 3 * mu**5 / lamda**2
# Levi
c = Symbol('c', positive=True)
assert integrate(
sqrt(c / 2 / pi) * exp(-c / 2 / (x - mu)) / (x - mu)**S('3/2'),
(x, mu, oo)) == 1
# higher moments oo
# log-logistic
alpha, beta = symbols('alpha beta', positive=True)
distn = (beta/alpha)*x**(beta - 1)/alpha**(beta - 1)/ \
(1 + x**beta/alpha**beta)**2
# FIXME: If alpha, beta are not declared as finite the line below hangs
# after the changes in:
# https://github.com/sympy/sympy/pull/16603
assert simplify(integrate(distn, (x, 0, oo))) == 1
# NOTE the conditions are a mess, but correctly state beta > 1
assert simplify(integrate(x*distn, (x, 0, oo), conds='none')) == \
pi*alpha/beta/sin(pi/beta)
# (similar comment for conditions applies)
assert simplify(integrate(x**y*distn, (x, 0, oo), conds='none')) == \
pi*alpha**y*y/beta/sin(pi*y/beta)
# weibull
k = Symbol('k', positive=True)
n = Symbol('n', positive=True)
distn = k / lamda * (x / lamda)**(k - 1) * exp(-(x / lamda)**k)
assert simplify(integrate(distn, (x, 0, oo))) == 1
assert simplify(integrate(x**n*distn, (x, 0, oo))) == \
lamda**n*gamma(1 + n/k)
# rice distribution
from sympy.functions.special.bessel import besseli
nu, sigma = symbols('nu sigma', positive=True)
rice = x / sigma**2 * exp(-(x**2 + nu**2) / 2 / sigma**2) * besseli(
0, x * nu / sigma**2)
assert integrate(rice, (x, 0, oo), meijerg=True) == 1
# can someone verify higher moments?
# Laplace distribution
mu = Symbol('mu', real=True)
b = Symbol('b', positive=True)
laplace = exp(-abs(x - mu) / b) / 2 / b
assert integrate(laplace, (x, -oo, oo), meijerg=True) == 1
assert integrate(x * laplace, (x, -oo, oo), meijerg=True) == mu
assert integrate(x**2*laplace, (x, -oo, oo), meijerg=True) == \
2*b**2 + mu**2
# TODO are there other distributions supported on (-oo, oo) that we can do?
# misc tests
k = Symbol('k', positive=True)
assert gammasimp(
expand_mul(
integrate(log(x) * x**(k - 1) * exp(-x) / gamma(k),
(x, 0, oo)))) == polygamma(0, k)
def test_gammasimp():
R = Rational
# was part of test_combsimp_gamma() in test_combsimp.py
assert gammasimp(gamma(x)) == gamma(x)
assert gammasimp(gamma(x + 1) / x) == gamma(x)
assert gammasimp(gamma(x) / (x - 1)) == gamma(x - 1)
assert gammasimp(x * gamma(x)) == gamma(x + 1)
assert gammasimp((x + 1) * gamma(x + 1)) == gamma(x + 2)
assert gammasimp(gamma(x + y) * (x + y)) == gamma(x + y + 1)
assert gammasimp(x / gamma(x + 1)) == 1 / gamma(x)
assert gammasimp((x + 1)**2 / gamma(x + 2)) == (x + 1) / gamma(x + 1)
assert gammasimp(x*gamma(x) + gamma(x + 3)/(x + 2)) == \
(x + 2)*gamma(x + 1)
assert gammasimp(gamma(2 * x) * x) == gamma(2 * x + 1) / 2
assert gammasimp(gamma(2 * x) / (x - S.Half)) == 2 * gamma(2 * x - 1)
assert gammasimp(gamma(x) * gamma(1 - x)) == pi / sin(pi * x)
assert gammasimp(gamma(x) * gamma(-x)) == -pi / (x * sin(pi * x))
assert gammasimp(1/gamma(x + 3)/gamma(1 - x)) == \
sin(pi*x)/(pi*x*(x + 1)*(x + 2))
assert gammasimp(factorial(n + 2)) == gamma(n + 3)
assert gammasimp(binomial(n, k)) == \
gamma(n + 1)/(gamma(k + 1)*gamma(-k + n + 1))
assert powsimp(gammasimp(
gamma(x)*gamma(x + S.Half)*gamma(y)/gamma(x + y))) == \
2**(-2*x + 1)*sqrt(pi)*gamma(2*x)*gamma(y)/gamma(x + y)
assert gammasimp(1/gamma(x)/gamma(x - Rational(1, 3))/gamma(x + Rational(1, 3))) == \
3**(3*x - Rational(3, 2))/(2*pi*gamma(3*x - 1))
assert simplify(
gamma(S.Half + x / 2) * gamma(1 + x / 2) / gamma(1 + x) / sqrt(pi) *
2**x) == 1
assert gammasimp(gamma(Rational(-1, 4)) *
gamma(Rational(-3, 4))) == 16 * sqrt(2) * pi / 3
assert powsimp(gammasimp(gamma(2*x)/gamma(x))) == \
2**(2*x - 1)*gamma(x + S.Half)/sqrt(pi)
# issue 6792
e = (-gamma(k) * gamma(k + 2) + gamma(k + 1)**2) / gamma(k)**2
assert gammasimp(e) == -k
assert gammasimp(1 / e) == -1 / k
e = (gamma(x) + gamma(x + 1)) / gamma(x)
assert gammasimp(e) == x + 1
assert gammasimp(1 / e) == 1 / (x + 1)
e = (gamma(x) + gamma(x + 2)) * (gamma(x - 1) + gamma(x)) / gamma(x)
assert gammasimp(e) == (x**2 + x + 1) * gamma(x + 1) / (x - 1)
e = (-gamma(k) * gamma(k + 2) + gamma(k + 1)**2) / gamma(k)**2
assert gammasimp(e**2) == k**2
assert gammasimp(e**2 / gamma(k + 1)) == k / gamma(k)
a = R(1, 2) + R(1, 3)
b = a + R(1, 3)
assert gammasimp(gamma(2 * k) / gamma(k) * gamma(k + a) *
gamma(k + b)) == 3 * 2**(2 * k + 1) * 3**(
-3 * k - 2) * sqrt(pi) * gamma(3 * k + R(3, 2)) / 2
# issue 9699
assert gammasimp(
(x + 1) * factorial(x) / gamma(y)) == gamma(x + 2) / gamma(y)
assert gammasimp(rf(x + n, k) * binomial(n, k)).simplify() == Piecewise(
(gamma(n + 1) * gamma(k + n + x) /
(gamma(k + 1) * gamma(n + x) * gamma(-k + n + 1)), n > -x),
((-1)**k * gamma(n + 1) * gamma(-n - x + 1) /
(gamma(k + 1) * gamma(-k + n + 1) * gamma(-k - n - x + 1)), True))
A, B = symbols('A B', commutative=False)
assert gammasimp(e * B * A) == gammasimp(e) * B * A
# check iteration
assert gammasimp(gamma(2 * k) / gamma(k) *
gamma(-k - R(1, 2))) == (-2**(2 * k + 1) * sqrt(pi) /
(2 *
((2 * k + 1) * cos(pi * k))))
assert gammasimp(
gamma(k) * gamma(k + R(1, 3)) * gamma(k + R(2, 3)) /
gamma(k * R(3, 2))) == (3 * 2**(3 * k + 1) * 3**(-3 * k - S.Half) *
sqrt(pi) * gamma(k * R(3, 2) + S.Half) / 2)
# issue 6153
assert gammasimp(gamma(Rational(1, 4)) / gamma(Rational(5, 4))) == 4
# was part of test_combsimp() in test_combsimp.py
assert gammasimp(binomial(n + 2, k + S.Half)) == gamma(n + 3)/ \
(gamma(k + R(3, 2))*gamma(-k + n + R(5, 2)))
assert gammasimp(binomial(n + 2, k + 2.0)) == \
gamma(n + 3)/(gamma(k + 3.0)*gamma(-k + n + 1))
# issue 11548
assert gammasimp(binomial(0, x)) == sin(pi * x) / (pi * x)
e = gamma(n + Rational(1, 3)) * gamma(n + R(2, 3))
assert gammasimp(e) == e
assert gammasimp(gamma(4*n + S.Half)/gamma(2*n - R(3, 4))) == \
2**(4*n - R(5, 2))*(8*n - 3)*gamma(2*n + R(3, 4))/sqrt(pi)
i, m = symbols('i m', integer=True)
e = gamma(exp(i))
assert gammasimp(e) == e
e = gamma(m + 3)
assert gammasimp(e) == e
e = gamma(m + 1) / (gamma(i + 1) * gamma(-i + m + 1))
assert gammasimp(e) == e
p = symbols("p", integer=True, positive=True)
assert gammasimp(gamma(-p + 4)) == gamma(-p + 4)
def test_meijerg_expand():
from sympy.simplify.gammasimp import gammasimp
from sympy.simplify.simplify import simplify
# from mpmath docs
assert hyperexpand(meijerg([[], []], [[0], []], -z)) == exp(z)
assert hyperexpand(meijerg([[1, 1], []], [[1], [0]], z)) == \
log(z + 1)
assert hyperexpand(meijerg([[1, 1], []], [[1], [1]], z)) == \
z/(z + 1)
assert hyperexpand(meijerg([[], []], [[S.Half], [0]], (z/2)**2)) \
== sin(z)/sqrt(pi)
assert hyperexpand(meijerg([[], []], [[0], [S.Half]], (z/2)**2)) \
== cos(z)/sqrt(pi)
assert can_do_meijer([], [a], [a - 1, a - S.Half], [])
assert can_do_meijer([], [], [a/2], [-a/2], False) # branches...
assert can_do_meijer([a], [b], [a], [b, a - 1])
# wikipedia
assert hyperexpand(meijerg([1], [], [], [0], z)) == \
Piecewise((0, abs(z) < 1), (1, abs(1/z) < 1),
(meijerg([1], [], [], [0], z), True))
assert hyperexpand(meijerg([], [1], [0], [], z)) == \
Piecewise((1, abs(z) < 1), (0, abs(1/z) < 1),
(meijerg([], [1], [0], [], z), True))
# The Special Functions and their Approximations
assert can_do_meijer([], [], [a + b/2], [a, a - b/2, a + S.Half])
assert can_do_meijer(
[], [], [a], [b], False) # branches only agree for small z
assert can_do_meijer([], [S.Half], [a], [-a])
assert can_do_meijer([], [], [a, b], [])
assert can_do_meijer([], [], [a, b], [])
assert can_do_meijer([], [], [a, a + S.Half], [b, b + S.Half])
assert can_do_meijer([], [], [a, -a], [0, S.Half], False) # dito
assert can_do_meijer([], [], [a, a + S.Half, b, b + S.Half], [])
assert can_do_meijer([S.Half], [], [0], [a, -a])
assert can_do_meijer([S.Half], [], [a], [0, -a], False) # dito
assert can_do_meijer([], [a - S.Half], [a, b], [a - S.Half], False)
assert can_do_meijer([], [a + S.Half], [a + b, a - b, a], [], False)
assert can_do_meijer([a + S.Half], [], [b, 2*a - b, a], [], False)
# This for example is actually zero.
assert can_do_meijer([], [], [], [a, b])
# Testing a bug:
assert hyperexpand(meijerg([0, 2], [], [], [-1, 1], z)) == \
Piecewise((0, abs(z) < 1),
(z*(1 - 1/z**2)/2, abs(1/z) < 1),
(meijerg([0, 2], [], [], [-1, 1], z), True))
# Test that the simplest possible answer is returned:
assert gammasimp(simplify(hyperexpand(
meijerg([1], [1 - a], [-a/2, -a/2 + S.Half], [], 1/z)))) == \
-2*sqrt(pi)*(sqrt(z + 1) + 1)**a/a
# Test that hyper is returned
assert hyperexpand(meijerg([1], [], [a], [0, 0], z)) == hyper(
(a,), (a + 1, a + 1), z*exp_polar(I*pi))*z**a*gamma(a)/gamma(a + 1)**2
# Test place option
f = meijerg(((0, 1), ()), ((S.Half,), (0,)), z**2)
assert hyperexpand(f) == sqrt(pi)/sqrt(1 + z**(-2))
assert hyperexpand(f, place=0) == sqrt(pi)*z/sqrt(z**2 + 1)
def test_mellin_transform_bessel():
from sympy.functions.elementary.miscellaneous import Max
MT = mellin_transform
# 8.4.19
assert MT(besselj(a, 2*sqrt(x)), x, s) == \
(gamma(a/2 + s)/gamma(a/2 - s + 1), (-re(a)/2, Rational(3, 4)), True)
assert MT(sin(sqrt(x))*besselj(a, sqrt(x)), x, s) == \
(2**a*gamma(-2*s + S.Half)*gamma(a/2 + s + S.Half)/(
gamma(-a/2 - s + 1)*gamma(a - 2*s + 1)), (
-re(a)/2 - S.Half, Rational(1, 4)), True)
assert MT(cos(sqrt(x))*besselj(a, sqrt(x)), x, s) == \
(2**a*gamma(a/2 + s)*gamma(-2*s + S.Half)/(
gamma(-a/2 - s + S.Half)*gamma(a - 2*s + 1)), (
-re(a)/2, Rational(1, 4)), True)
assert MT(besselj(a, sqrt(x))**2, x, s) == \
(gamma(a + s)*gamma(S.Half - s)
/ (sqrt(pi)*gamma(1 - s)*gamma(1 + a - s)),
(-re(a), S.Half), True)
assert MT(besselj(a, sqrt(x))*besselj(-a, sqrt(x)), x, s) == \
(gamma(s)*gamma(S.Half - s)
/ (sqrt(pi)*gamma(1 - a - s)*gamma(1 + a - s)),
(0, S.Half), True)
# NOTE: prudnikov gives the strip below as (1/2 - re(a), 1). As far as
# I can see this is wrong (since besselj(z) ~ 1/sqrt(z) for z large)
assert MT(besselj(a - 1, sqrt(x))*besselj(a, sqrt(x)), x, s) == \
(gamma(1 - s)*gamma(a + s - S.Half)
/ (sqrt(pi)*gamma(Rational(3, 2) - s)*gamma(a - s + S.Half)),
(S.Half - re(a), S.Half), True)
assert MT(besselj(a, sqrt(x))*besselj(b, sqrt(x)), x, s) == \
(4**s*gamma(1 - 2*s)*gamma((a + b)/2 + s)
/ (gamma(1 - s + (b - a)/2)*gamma(1 - s + (a - b)/2)
*gamma( 1 - s + (a + b)/2)),
(-(re(a) + re(b))/2, S.Half), True)
assert MT(besselj(a, sqrt(x))**2 + besselj(-a, sqrt(x))**2, x, s)[1:] == \
((Max(re(a), -re(a)), S.Half), True)
# Section 8.4.20
assert MT(bessely(a, 2*sqrt(x)), x, s) == \
(-cos(pi*(a/2 - s))*gamma(s - a/2)*gamma(s + a/2)/pi,
(Max(-re(a)/2, re(a)/2), Rational(3, 4)), True)
assert MT(sin(sqrt(x))*bessely(a, sqrt(x)), x, s) == \
(-4**s*sin(pi*(a/2 - s))*gamma(S.Half - 2*s)
* gamma((1 - a)/2 + s)*gamma((1 + a)/2 + s)
/ (sqrt(pi)*gamma(1 - s - a/2)*gamma(1 - s + a/2)),
(Max(-(re(a) + 1)/2, (re(a) - 1)/2), Rational(1, 4)), True)
assert MT(cos(sqrt(x))*bessely(a, sqrt(x)), x, s) == \
(-4**s*cos(pi*(a/2 - s))*gamma(s - a/2)*gamma(s + a/2)*gamma(S.Half - 2*s)
/ (sqrt(pi)*gamma(S.Half - s - a/2)*gamma(S.Half - s + a/2)),
(Max(-re(a)/2, re(a)/2), Rational(1, 4)), True)
assert MT(besselj(a, sqrt(x))*bessely(a, sqrt(x)), x, s) == \
(-cos(pi*s)*gamma(s)*gamma(a + s)*gamma(S.Half - s)
/ (pi**S('3/2')*gamma(1 + a - s)),
(Max(-re(a), 0), S.Half), True)
assert MT(besselj(a, sqrt(x))*bessely(b, sqrt(x)), x, s) == \
(-4**s*cos(pi*(a/2 - b/2 + s))*gamma(1 - 2*s)
* gamma(a/2 - b/2 + s)*gamma(a/2 + b/2 + s)
/ (pi*gamma(a/2 - b/2 - s + 1)*gamma(a/2 + b/2 - s + 1)),
(Max((-re(a) + re(b))/2, (-re(a) - re(b))/2), S.Half), True)
# NOTE bessely(a, sqrt(x))**2 and bessely(a, sqrt(x))*bessely(b, sqrt(x))
# are a mess (no matter what way you look at it ...)
assert MT(bessely(a, sqrt(x))**2, x, s)[1:] == \
((Max(-re(a), 0, re(a)), S.Half), True)
# Section 8.4.22
# TODO we can't do any of these (delicate cancellation)
# Section 8.4.23
assert MT(besselk(a, 2*sqrt(x)), x, s) == \
(gamma(
s - a/2)*gamma(s + a/2)/2, (Max(-re(a)/2, re(a)/2), oo), True)
assert MT(besselj(a, 2*sqrt(2*sqrt(x)))*besselk(
a, 2*sqrt(2*sqrt(x))), x, s) == (4**(-s)*gamma(2*s)*
gamma(a/2 + s)/(2*gamma(a/2 - s + 1)), (Max(0, -re(a)/2), oo), True)
# TODO bessely(a, x)*besselk(a, x) is a mess
assert MT(besseli(a, sqrt(x))*besselk(a, sqrt(x)), x, s) == \
(gamma(s)*gamma(
a + s)*gamma(-s + S.Half)/(2*sqrt(pi)*gamma(a - s + 1)),
(Max(-re(a), 0), S.Half), True)
assert MT(besseli(b, sqrt(x))*besselk(a, sqrt(x)), x, s) == \
(2**(2*s - 1)*gamma(-2*s + 1)*gamma(-a/2 + b/2 + s)* \
gamma(a/2 + b/2 + s)/(gamma(-a/2 + b/2 - s + 1)* \
gamma(a/2 + b/2 - s + 1)), (Max(-re(a)/2 - re(b)/2, \
re(a)/2 - re(b)/2), S.Half), True)
# TODO products of besselk are a mess
mt = MT(exp(-x/2)*besselk(a, x/2), x, s)
mt0 = gammasimp(trigsimp(gammasimp(mt[0].expand(func=True))))
assert mt0 == 2*pi**Rational(3, 2)*cos(pi*s)*gamma(S.Half - s)/(
(cos(2*pi*a) - cos(2*pi*s))*gamma(-a - s + 1)*gamma(a - s + 1))
assert mt[1:] == ((Max(-re(a), re(a)), oo), True)
def test_gammasimp():
assert gammasimp(A*B - B*A) == A*B - B*A
