def test_hyper():
raises(TypeError, 'hyper(1, 2, z)')
assert hyper((1, 2),(1,), z) == hyper(Tuple(1, 2), Tuple(1), z)
h = hyper((1, 2), (3, 4, 5), z)
assert h.ap == Tuple(1, 2)
assert h.bq == Tuple(3, 4, 5)
assert h.argument == z
assert h.is_commutative is True
# just a few checks to make sure that all arguments go where they should
assert tn(hyper(Tuple(), Tuple(), z), exp(z), z)
assert tn(z*hyper((1, 1), Tuple(2), -z), log(1 + z), z)
# differentiation
h = hyper((randcplx(), randcplx(), randcplx()), (randcplx(), randcplx()), z)
assert td(h, z)
a1, a2, b1, b2, b3 = symbols('a1:3, b1:4')
assert hyper((a1, a2), (b1, b2, b3), z).diff(z) == \
a1*a2/(b1*b2*b3) * hyper((a1+1, a2+1), (b1+1, b2+1, b3+1), z)
# differentiation wrt parameters is not supported
raises(NotImplementedError, 'hyper((z,), (), z).diff(z)')
def test_partial_simp():
# First test that hypergeometric function formulae work.
a, b, c, d, e = map(lambda _: randcplx(), range(5))
for func in [Hyper_Function([a, b, c], [d, e]),
Hyper_Function([], [a, b, c, d, e])]:
f = build_hypergeometric_formula(func)
z = f.z
assert f.closed_form == func(z)
deriv1 = f.B.diff(z)*z
deriv2 = f.M*f.B
for func1, func2 in zip(deriv1, deriv2):
assert tn(func1, func2, z)
# Now test that formulae are partially simplified.
from sympy.abc import a, b, z
assert hyperexpand(hyper([3, a], [1, b], z)) == \
(-a*b/2 + a*z/2 + 2*a)*hyper([a + 1], [b], z) \
+ (a*b/2 - 2*a + 1)*hyper([a], [b], z)
assert tn(
hyperexpand(hyper([3, d], [1, e], z)), hyper([3, d], [1, e], z), z)
assert hyperexpand(hyper([3], [1, a, b], z)) == \
hyper((), (a, b), z) \
+ z*hyper((), (a + 1, b), z)/(2*a) \
- z*(b - 4)*hyper((), (a + 1, b + 1), z)/(2*a*b)
assert tn(
hyperexpand(hyper([3], [1, d, e], z)), hyper([3], [1, d, e], z), z)
def test_K():
assert K(0) == pi/2
assert K(S(1)/2) == 8*pi**(S(3)/2)/gamma(-S(1)/4)**2
assert K(1) == zoo
assert K(-1) == gamma(S(1)/4)**2/(4*sqrt(2*pi))
assert K(oo) == 0
assert K(-oo) == 0
assert K(I*oo) == 0
assert K(-I*oo) == 0
assert K(zoo) == 0
assert K(z).diff(z) == (E(z) - (1 - z)*K(z))/(2*z*(1 - z))
assert td(K(z), z)
zi = Symbol('z', real=False)
assert K(zi).conjugate() == K(zi.conjugate())
zr = Symbol('z', real=True, negative=True)
assert K(zr).conjugate() == K(zr)
assert K(z).rewrite(hyper) == \
(pi/2)*hyper((S.Half, S.Half), (S.One,), z)
assert tn(K(z), (pi/2)*hyper((S.Half, S.Half), (S.One,), z))
assert K(z).rewrite(meijerg) == \
meijerg(((S.Half, S.Half), []), ((S.Zero,), (S.Zero,)), -z)/2
assert tn(K(z), meijerg(((S.Half, S.Half), []), ((S.Zero,), (S.Zero,)), -z)/2)
def test_conjugate():
from sympy import conjugate, I, Symbol
n, z, x = Symbol('n'), Symbol('z', real=False), Symbol('x', real=True)
y, t = Symbol('y', real=True, positive=True), Symbol('t', negative=True)
for f in [besseli, besselj, besselk, bessely, hankel1, hankel2]:
assert f(n, -1).conjugate() != f(conjugate(n), -1)
assert f(n, x).conjugate() != f(conjugate(n), x)
assert f(n, t).conjugate() != f(conjugate(n), t)
rz = randcplx(b=0.5)
for f in [besseli, besselj, besselk, bessely]:
assert f(n, 1 + I).conjugate() == f(conjugate(n), 1 - I)
assert f(n, 0).conjugate() == f(conjugate(n), 0)
assert f(n, 1).conjugate() == f(conjugate(n), 1)
assert f(n, z).conjugate() == f(conjugate(n), conjugate(z))
assert f(n, y).conjugate() == f(conjugate(n), y)
assert tn(f(n, rz).conjugate(), f(conjugate(n), conjugate(rz)))
assert hankel1(n, 1 + I).conjugate() == hankel2(conjugate(n), 1 - I)
assert hankel1(n, 0).conjugate() == hankel2(conjugate(n), 0)
assert hankel1(n, 1).conjugate() == hankel2(conjugate(n), 1)
assert hankel1(n, y).conjugate() == hankel2(conjugate(n), y)
assert hankel1(n, z).conjugate() == hankel2(conjugate(n), conjugate(z))
assert tn(hankel1(n, rz).conjugate(), hankel2(conjugate(n), conjugate(rz)))
assert hankel2(n, 1 + I).conjugate() == hankel1(conjugate(n), 1 - I)
assert hankel2(n, 0).conjugate() == hankel1(conjugate(n), 0)
assert hankel2(n, 1).conjugate() == hankel1(conjugate(n), 1)
assert hankel2(n, y).conjugate() == hankel1(conjugate(n), y)
assert hankel2(n, z).conjugate() == hankel1(conjugate(n), conjugate(z))
assert tn(hankel2(n, rz).conjugate(), hankel1(conjugate(n), conjugate(rz)))
def test_E():
assert E(z, 0) == z
assert E(0, m) == 0
assert E(i*pi/2, m) == i*E(m)
assert E(z, oo) == zoo
assert E(z, -oo) == zoo
assert E(0) == pi/2
assert E(1) == 1
assert E(oo) == I*oo
assert E(-oo) == oo
assert E(zoo) == zoo
assert E(-z, m) == -E(z, m)
assert E(z, m).diff(z) == sqrt(1 - m*sin(z)**2)
assert E(z, m).diff(m) == (E(z, m) - F(z, m))/(2*m)
assert E(z).diff(z) == (E(z) - K(z))/(2*z)
r = randcplx()
assert td(E(r, m), m)
assert td(E(z, r), z)
assert td(E(z), z)
mi = Symbol('m', real=False)
assert E(z, mi).conjugate() == E(z.conjugate(), mi.conjugate())
mr = Symbol('m', real=True, negative=True)
assert E(z, mr).conjugate() == E(z.conjugate(), mr)
assert E(z).rewrite(hyper) == (pi/2)*hyper((-S.Half, S.Half), (S.One,), z)
assert tn(E(z), (pi/2)*hyper((-S.Half, S.Half), (S.One,), z))
assert E(z).rewrite(meijerg) == \
-meijerg(((S.Half, S(3)/2), []), ((S.Zero,), (S.Zero,)), -z)/4
assert tn(E(z), -meijerg(((S.Half, S(3)/2), []), ((S.Zero,), (S.Zero,)), -z)/4)
def test_meijerg_formulae():
from sympy.simplify.hyperexpand import MeijerFormulaCollection
formulae = MeijerFormulaCollection().formulae
for sig in formulae:
for formula in formulae[sig]:
g = meijerg(formula.func.an, formula.func.ap,
formula.func.bm, formula.func.bq,
formula.z)
rep = {}
for sym in formula.symbols:
rep[sym] = randcplx()
# first test if the closed-form is actually correct
g = g.subs(rep)
closed_form = formula.closed_form.subs(rep)
z = formula.z
assert tn(g, closed_form, z)
# now test the computed matrix
cl = (formula.C * formula.B)[0].subs(rep)
assert tn(closed_form, cl, z)
deriv1 = z*formula.B.diff(z)
deriv2 = formula.M * formula.B
for d1, d2 in zip(deriv1, deriv2):
assert tn(d1.subs(rep), d2.subs(rep), z)
def test_lowergamma():
from sympy import meijerg, exp_polar, I, expint
assert lowergamma(x, y).diff(y) == y**(x-1)*exp(-y)
assert td(lowergamma(randcplx(), y), y)
assert lowergamma(x, y).diff(x) == \
gamma(x)*polygamma(0, x) - uppergamma(x, y)*log(y) \
+ meijerg([], [1, 1], [0, 0, x], [], y)
assert lowergamma(S.Half, x) == sqrt(pi)*erf(sqrt(x))
assert not lowergamma(S.Half - 3, x).has(lowergamma)
assert not lowergamma(S.Half + 3, x).has(lowergamma)
assert lowergamma(S.Half, x, evaluate=False).has(lowergamma)
assert tn(lowergamma(S.Half + 3, x, evaluate=False),
lowergamma(S.Half + 3, x), x)
assert tn(lowergamma(S.Half - 3, x, evaluate=False),
lowergamma(S.Half - 3, x), x)
assert lowergamma(x, y).rewrite(uppergamma) == gamma(x) - uppergamma(x, y)
assert tn_branch(-3, lowergamma)
assert tn_branch(-4, lowergamma)
assert tn_branch(S(1)/3, lowergamma)
assert tn_branch(pi, lowergamma)
assert lowergamma(3, exp_polar(4*pi*I)*x) == lowergamma(3, x)
assert lowergamma(y, exp_polar(5*pi*I)*x) == \
exp(4*I*pi*y)*lowergamma(y, x*exp_polar(pi*I))
assert lowergamma(-2, exp_polar(5*pi*I)*x) == \
lowergamma(-2, x*exp_polar(I*pi)) + 2*pi*I
assert lowergamma(x, y).rewrite(expint) == -y**x*expint(-x + 1, y) + gamma(x)
k = Symbol('k', integer=True)
assert lowergamma(k, y).rewrite(expint) == -y**k*expint(-k + 1, y) + gamma(k)
k = Symbol('k', integer=True, positive=False)
assert lowergamma(k, y).rewrite(expint) == lowergamma(k, y)
def test_uppergamma():
from sympy import meijerg, exp_polar, I, expint
assert uppergamma(4, 0) == 6
assert uppergamma(x, y).diff(y) == -y**(x-1)*exp(-y)
assert td(uppergamma(randcplx(), y), y)
assert uppergamma(x, y).diff(x) == \
uppergamma(x, y)*log(y) + meijerg([], [1, 1], [0, 0, x], [], y)
assert td(uppergamma(x, randcplx()), x)
assert uppergamma(S.Half, x) == sqrt(pi)*(1 - erf(sqrt(x)))
assert not uppergamma(S.Half - 3, x).has(uppergamma)
assert not uppergamma(S.Half + 3, x).has(uppergamma)
assert uppergamma(S.Half, x, evaluate=False).has(uppergamma)
assert tn(uppergamma(S.Half + 3, x, evaluate=False),
uppergamma(S.Half + 3, x), x)
assert tn(uppergamma(S.Half - 3, x, evaluate=False),
uppergamma(S.Half - 3, x), x)
assert uppergamma(x, y).rewrite(lowergamma) == gamma(x) - lowergamma(x, y)
assert tn_branch(-3, uppergamma)
assert tn_branch(-4, uppergamma)
assert tn_branch(S(1)/3, uppergamma)
assert tn_branch(pi, uppergamma)
assert uppergamma(3, exp_polar(4*pi*I)*x) == uppergamma(3, x)
assert uppergamma(y, exp_polar(5*pi*I)*x) == \
exp(4*I*pi*y)*uppergamma(y, x*exp_polar(pi*I)) + gamma(y)*(1-exp(4*pi*I*y))
assert uppergamma(-2, exp_polar(5*pi*I)*x) == \
uppergamma(-2, x*exp_polar(I*pi)) - 2*pi*I
assert uppergamma(-2, x) == expint(3, x)/x**2
assert uppergamma(x, y).rewrite(expint) == y**x*expint(-x + 1, y)
def test_hyper():
raises(TypeError, lambda: hyper(1, 2, z))
assert hyper((1, 2), (1,), z) == hyper(Tuple(1, 2), Tuple(1), z)
h = hyper((1, 2), (3, 4, 5), z)
assert h.ap == Tuple(1, 2)
assert h.bq == Tuple(3, 4, 5)
assert h.argument == z
assert h.is_commutative is True
# just a few checks to make sure that all arguments go where they should
assert tn(hyper(Tuple(), Tuple(), z), exp(z), z)
assert tn(z*hyper((1, 1), Tuple(2), -z), log(1 + z), z)
# differentiation
h = hyper(
(randcplx(), randcplx(), randcplx()), (randcplx(), randcplx()), z)
assert td(h, z)
a1, a2, b1, b2, b3 = symbols('a1:3, b1:4')
assert hyper((a1, a2), (b1, b2, b3), z).diff(z) == \
a1*a2/(b1*b2*b3) * hyper((a1 + 1, a2 + 1), (b1 + 1, b2 + 1, b3 + 1), z)
# differentiation wrt parameters is not supported
assert hyper([z], [], z).diff(z) == Derivative(hyper([z], [], z), z)
# hyper is unbranched wrt parameters
from sympy import polar_lift
assert hyper([polar_lift(z)], [polar_lift(k)], polar_lift(x)) == \
hyper([z], [k], polar_lift(x))
def test_formulae():
from sympy.simplify.hyperexpand import FormulaCollection
formulae = FormulaCollection().formulae
for formula in formulae:
h = formula.func(formula.z)
rep = {}
for n, sym in enumerate(formula.symbols):
rep[sym] = randcplx(n)
# NOTE hyperexpand returns truly branched functions. We know we are
# on the main sheet, but numerical evaluation can still go wrong
# (e.g. if exp_polar cannot be evalf'd).
# Just replace all exp_polar by exp, this usually works.
# first test if the closed-form is actually correct
h = h.subs(rep)
closed_form = formula.closed_form.subs(rep).rewrite('nonrepsmall')
z = formula.z
assert tn(h, closed_form.replace(exp_polar, exp), z)
# now test the computed matrix
cl = (formula.C * formula.B)[0].subs(rep).rewrite('nonrepsmall')
assert tn(closed_form.replace(
exp_polar, exp), cl.replace(exp_polar, exp), z)
deriv1 = z*formula.B.applyfunc(lambda t: t.rewrite(
'nonrepsmall')).diff(z)
deriv2 = formula.M * formula.B
for d1, d2 in zip(deriv1, deriv2):
assert tn(d1.subs(rep).replace(exp_polar, exp),
d2.subs(rep).rewrite('nonrepsmall').replace(exp_polar, exp), z)
def test_K():
assert K(0) == pi / 2
assert K(S(1) / 2) == 8 * pi ** (S(3) / 2) / gamma(-S(1) / 4) ** 2
assert K(1) == zoo
assert K(-1) == gamma(S(1) / 4) ** 2 / (4 * sqrt(2 * pi))
assert K(oo) == 0
assert K(-oo) == 0
assert K(I * oo) == 0
assert K(-I * oo) == 0
assert K(zoo) == 0
assert K(z).diff(z) == (E(z) - (1 - z) * K(z)) / (2 * z * (1 - z))
assert td(K(z), z)
zi = Symbol("z", real=False)
assert K(zi).conjugate() == K(zi.conjugate())
zr = Symbol("z", real=True, negative=True)
assert K(zr).conjugate() == K(zr)
assert K(z).rewrite(hyper) == (pi / 2) * hyper((S.Half, S.Half), (S.One,), z)
assert tn(K(z), (pi / 2) * hyper((S.Half, S.Half), (S.One,), z))
assert K(z).rewrite(meijerg) == meijerg(((S.Half, S.Half), []), ((S.Zero,), (S.Zero,)), -z) / 2
assert tn(K(z), meijerg(((S.Half, S.Half), []), ((S.Zero,), (S.Zero,)), -z) / 2)
assert K(z).series(
z
) == pi / 2 + pi * z / 8 + 9 * pi * z ** 2 / 128 + 25 * pi * z ** 3 / 512 + 1225 * pi * z ** 4 / 32768 + 3969 * pi * z ** 5 / 131072 + O(
z ** 6
)
def t(func, hyp, z):
""" Test that func is a valid representation of hyp. """
# First test that func agrees with hyp for small z
if not tn(func.rewrite('nonrepsmall'), hyp, z,
a=S(-1)/2, b=S(-1)/2, c=S(1)/2, d=S(1)/2):
return False
# Next check that the two small representations agree.
if not tn(
func.rewrite('nonrepsmall').subs(
z, exp_polar(I*pi)*z).replace(exp_polar, exp),
func.subs(z, exp_polar(I*pi)*z).rewrite('nonrepsmall'),
z, a=S(-1)/2, b=S(-1)/2, c=S(1)/2, d=S(1)/2):
return False
# Next check continuity along exp_polar(I*pi)*t
expr = func.subs(z, exp_polar(I*pi)*z).rewrite('nonrep')
if abs(expr.subs(z, 1 + 1e-15).n() - expr.subs(z, 1 - 1e-15).n()) > 1e-10:
return False
# Finally check continuity of the big reps.
def dosubs(func, a, b):
rv = func.subs(z, exp_polar(a)*z).rewrite('nonrep')
return rv.subs(z, exp_polar(b)*z).replace(exp_polar, exp)
for n in [0, 1, 2, 3, 4, -1, -2, -3, -4]:
expr1 = dosubs(func, 2*I*pi*n, I*pi/2)
expr2 = dosubs(func, 2*I*pi*n + I*pi, -I*pi/2)
if not tn(expr1, expr2, z):
return False
expr1 = dosubs(func, 2*I*pi*(n + 1), -I*pi/2)
expr2 = dosubs(func, 2*I*pi*n + I*pi, I*pi/2)
if not tn(expr1, expr2, z):
return False
return True
def test_meijerg():
# carefully set up the parameters.
# NOTE: this used to fail sometimes. I believe it is fixed, but if you
# hit an inexplicable test failure here, please let me know the seed.
a1, a2 = map(lambda n: randcplx() - 5*I - n*I, range(2))
b1, b2 = map(lambda n: randcplx() + 5*I + n*I, range(2))
b3, b4, b5, a3, a4, a5 = map(lambda n: randcplx(), range(6))
g = meijerg([a1], [a3, a4], [b1], [b3, b4], z)
assert ReduceOrder.meijer_minus(3, 4) is None
assert ReduceOrder.meijer_plus(4, 3) is None
g2 = meijerg([a1, a2], [a3, a4], [b1], [b3, b4, a2], z)
assert tn(ReduceOrder.meijer_plus(a2, a2).apply(g, op), g2, z)
g2 = meijerg([a1, a2], [a3, a4], [b1], [b3, b4, a2 + 1], z)
assert tn(ReduceOrder.meijer_plus(a2, a2 + 1).apply(g, op), g2, z)
g2 = meijerg([a1, a2 - 1], [a3, a4], [b1], [b3, b4, a2 + 2], z)
assert tn(ReduceOrder.meijer_plus(a2 - 1, a2 + 2).apply(g, op), g2, z)
g2 = meijerg([a1], [a3, a4, b2 - 1], [b1, b2 + 2], [b3, b4], z)
assert tn(ReduceOrder.meijer_minus(b2 + 2, b2 - 1).apply(g, op), g2, z, tol=1e-6)
# test several-step reduction
an = [a1, a2]
bq = [b3, b4, a2 + 1]
ap = [a3, a4, b2 - 1]
bm = [b1, b2 + 1]
niq, ops = reduce_order_meijer(IndexQuadruple(an, ap, bm, bq))
assert niq.an == (a1,)
assert set(niq.ap) == set([a3, a4])
assert niq.bm == (b1,)
assert set(niq.bq) == set([b3, b4])
assert tn(apply_operators(g, ops, op), meijerg(an, ap, bm, bq, z), z)
def test_plan():
assert devise_plan(Hyper_Function([0], ()),
Hyper_Function([0], ()), z) == []
with raises(ValueError):
devise_plan(Hyper_Function([1], ()), Hyper_Function((), ()), z)
with raises(ValueError):
devise_plan(Hyper_Function([2], [1]), Hyper_Function([2], [2]), z)
with raises(ValueError):
devise_plan(Hyper_Function([2], []), Hyper_Function([S("1/2")], []), z)
# We cannot use pi/(10000 + n) because polys is insanely slow.
a1, a2, b1 = map(lambda n: randcplx(n), range(3))
b1 += 2*I
h = hyper([a1, a2], [b1], z)
h2 = hyper((a1 + 1, a2), [b1], z)
assert tn(apply_operators(h,
devise_plan(Hyper_Function((a1 + 1, a2), [b1]),
Hyper_Function((a1, a2), [b1]), z), op),
h2, z)
h2 = hyper((a1 + 1, a2 - 1), [b1], z)
assert tn(apply_operators(h,
devise_plan(Hyper_Function((a1 + 1, a2 - 1), [b1]),
Hyper_Function((a1, a2), [b1]), z), op),
h2, z)
def test_rewrite():
from sympy import polar_lift, exp, I
assert besselj(n, z).rewrite(jn) == sqrt(2*z/pi)*jn(n - S(1)/2, z)
assert bessely(n, z).rewrite(yn) == sqrt(2*z/pi)*yn(n - S(1)/2, z)
assert besseli(n, z).rewrite(besselj) == \
exp(-I*n*pi/2)*besselj(n, polar_lift(I)*z)
assert besselj(n, z).rewrite(besseli) == \
exp(I*n*pi/2)*besseli(n, polar_lift(-I)*z)
nu = randcplx()
assert tn(besselj(nu, z), besselj(nu, z).rewrite(besseli), z)
assert tn(besselj(nu, z), besselj(nu, z).rewrite(bessely), z)
assert tn(besseli(nu, z), besseli(nu, z).rewrite(besselj), z)
assert tn(besseli(nu, z), besseli(nu, z).rewrite(bessely), z)
assert tn(bessely(nu, z), bessely(nu, z).rewrite(besselj), z)
assert tn(bessely(nu, z), bessely(nu, z).rewrite(besseli), z)
assert tn(besselk(nu, z), besselk(nu, z).rewrite(besselj), z)
assert tn(besselk(nu, z), besselk(nu, z).rewrite(besseli), z)
assert tn(besselk(nu, z), besselk(nu, z).rewrite(bessely), z)
# check that a rewrite was triggered, when the order is set to a generic
# symbol 'nu'
assert yn(nu, z) != yn(nu, z).rewrite(jn)
assert hn1(nu, z) != hn1(nu, z).rewrite(jn)
assert hn2(nu, z) != hn2(nu, z).rewrite(jn)
assert jn(nu, z) != jn(nu, z).rewrite(yn)
assert hn1(nu, z) != hn1(nu, z).rewrite(yn)
assert hn2(nu, z) != hn2(nu, z).rewrite(yn)
# rewriting spherical bessel functions (SBFs) w.r.t. besselj, bessely is
# not allowed if a generic symbol 'nu' is used as the order of the SBFs
# to avoid inconsistencies (the order of bessel[jy] is allowed to be
# complex-valued, whereas SBFs are defined only for integer orders)
order = nu
for f in (besselj, bessely):
assert hn1(order, z) == hn1(order, z).rewrite(f)
assert hn2(order, z) == hn2(order, z).rewrite(f)
assert jn(order, z).rewrite(besselj) == sqrt(2)*sqrt(pi)*sqrt(1/z)*besselj(order + S(1)/2, z)/2
assert jn(order, z).rewrite(bessely) == (-1)**nu*sqrt(2)*sqrt(pi)*sqrt(1/z)*bessely(-order - S(1)/2, z)/2
# for integral orders rewriting SBFs w.r.t bessel[jy] is allowed
N = Symbol('n', integer=True)
ri = randint(-11, 10)
for order in (ri, N):
for f in (besselj, bessely):
assert yn(order, z) != yn(order, z).rewrite(f)
assert jn(order, z) != jn(order, z).rewrite(f)
assert hn1(order, z) != hn1(order, z).rewrite(f)
assert hn2(order, z) != hn2(order, z).rewrite(f)
for func, refunc in product((yn, jn, hn1, hn2),
(jn, yn, besselj, bessely)):
assert tn(func(ri, z), func(ri, z).rewrite(refunc), z)
def test_meijer():
raises(TypeError, lambda: meijerg(1, z))
raises(TypeError, lambda: meijerg(((1,), (2,)), (3,), (4,), z))
assert meijerg(((1, 2), (3,)), ((4,), (5,)), z) == \
meijerg(Tuple(1, 2), Tuple(3), Tuple(4), Tuple(5), z)
g = meijerg((1, 2), (3, 4, 5), (6, 7, 8, 9), (10, 11, 12, 13, 14), z)
assert g.an == Tuple(1, 2)
assert g.ap == Tuple(1, 2, 3, 4, 5)
assert g.aother == Tuple(3, 4, 5)
assert g.bm == Tuple(6, 7, 8, 9)
assert g.bq == Tuple(6, 7, 8, 9, 10, 11, 12, 13, 14)
assert g.bother == Tuple(10, 11, 12, 13, 14)
assert g.argument == z
assert g.nu == 75
assert g.delta == -1
assert g.is_commutative is True
assert meijerg([1, 2], [3], [4], [5], z).delta == S(1)/2
# just a few checks to make sure that all arguments go where they should
assert tn(meijerg(Tuple(), Tuple(), Tuple(0), Tuple(), -z), exp(z), z)
assert tn(sqrt(pi)*meijerg(Tuple(), Tuple(),
Tuple(0), Tuple(S(1)/2), z**2/4), cos(z), z)
assert tn(meijerg(Tuple(1, 1), Tuple(), Tuple(1), Tuple(0), z),
log(1 + z), z)
# differentiation
g = meijerg((randcplx(),), (randcplx() + 2*I,), Tuple(),
(randcplx(), randcplx()), z)
assert td(g, z)
g = meijerg(Tuple(), (randcplx(),), Tuple(),
(randcplx(), randcplx()), z)
assert td(g, z)
g = meijerg(Tuple(), Tuple(), Tuple(randcplx()),
Tuple(randcplx(), randcplx()), z)
assert td(g, z)
a1, a2, b1, b2, c1, c2, d1, d2 = symbols('a1:3, b1:3, c1:3, d1:3')
assert meijerg((a1, a2), (b1, b2), (c1, c2), (d1, d2), z).diff(z) == \
(meijerg((a1 - 1, a2), (b1, b2), (c1, c2), (d1, d2), z)
+ (a1 - 1)*meijerg((a1, a2), (b1, b2), (c1, c2), (d1, d2), z))/z
assert meijerg([z, z], [], [], [], z).diff(z) == \
Derivative(meijerg([z, z], [], [], [], z), z)
# meijerg is unbranched wrt parameters
from sympy import polar_lift as pl
assert meijerg([pl(a1)], [pl(a2)], [pl(b1)], [pl(b2)], pl(z)) == \
meijerg([a1], [a2], [b1], [b2], pl(z))
# integrand
from sympy.abc import a, b, c, d, s
assert meijerg([a], [b], [c], [d], z).integrand(s) == \
z**s*gamma(c - s)*gamma(-a + s + 1)/(gamma(b - s)*gamma(-d + s + 1))
def test_rewriting():
assert dirichlet_eta(x).rewrite(zeta) == (1 - 2 ** (1 - x)) * zeta(x)
assert zeta(x).rewrite(dirichlet_eta) == dirichlet_eta(x) / (1 - 2 ** (1 - x))
assert tn(dirichlet_eta(x), dirichlet_eta(x).rewrite(zeta), x)
assert tn(zeta(x), zeta(x).rewrite(dirichlet_eta), x)
assert zeta(x, a).rewrite(lerchphi) == lerchphi(1, x, a)
assert polylog(s, z).rewrite(lerchphi) == lerchphi(z, s, 1) * z
assert lerchphi(1, x, a).rewrite(zeta) == zeta(x, a)
assert z * lerchphi(z, s, 1).rewrite(polylog) == polylog(s, z)
def test_rewrite():
from sympy import polar_lift, exp, I
assert besselj(n, z).rewrite(jn) == sqrt(2*z/pi)*jn(n - S(1)/2, z)
assert bessely(n, z).rewrite(yn) == sqrt(2*z/pi)*yn(n - S(1)/2, z)
assert besseli(n, z).rewrite(besselj) == \
exp(-I*n*pi/2)*besselj(n, polar_lift(I)*z)
assert besselj(n, z).rewrite(besseli) == \
exp(I*n*pi/2)*besseli(n, polar_lift(-I)*z)
nu = randcplx()
assert tn(besselj(nu, z), besselj(nu, z).rewrite(besseli), z)
assert tn(besseli(nu, z), besseli(nu, z).rewrite(besselj), z)
def test_shift_operators():
a1, a2, b1, b2, b3 = map(lambda n: randcplx(n), range(5))
h = hyper((a1, a2), (b1, b2, b3), z)
raises(ValueError, lambda: ShiftA(0))
raises(ValueError, lambda: ShiftB(1))
assert tn(ShiftA(a1).apply(h, op), hyper((a1 + 1, a2), (b1, b2, b3), z), z)
assert tn(ShiftA(a2).apply(h, op), hyper((a1, a2 + 1), (b1, b2, b3), z), z)
assert tn(ShiftB(b1).apply(h, op), hyper((a1, a2), (b1 - 1, b2, b3), z), z)
assert tn(ShiftB(b2).apply(h, op), hyper((a1, a2), (b1, b2 - 1, b3), z), z)
assert tn(ShiftB(b3).apply(h, op), hyper((a1, a2), (b1, b2, b3 - 1), z), z)
def test_plan_derivatives():
a1, a2, a3 = 1, 2, S("1/2")
b1, b2 = 3, S("5/2")
h = hyper((a1, a2, a3), (b1, b2), z)
h2 = hyper((a1 + 1, a2 + 1, a3 + 2), (b1 + 1, b2 + 1), z)
ops = devise_plan(IndexPair((a1 + 1, a2 + 1, a3 + 2), (b1 + 1, b2 + 1)), IndexPair((a1, a2, a3), (b1, b2)), z)
f = Formula((a1, a2, a3), (b1, b2), z, h, [])
deriv = make_derivative_operator(f.M, z)
assert tn((apply_operators(f.C, ops, deriv) * f.B)[0], h2, z)
h2 = hyper((a1, a2 - 1, a3 - 2), (b1 - 1, b2 - 1), z)
ops = devise_plan(IndexPair((a1, a2 - 1, a3 - 2), (b1 - 1, b2 - 1)), IndexPair((a1, a2, a3), (b1, b2)), z)
assert tn((apply_operators(f.C, ops, deriv) * f.B)[0], h2, z)
def test_polylog_values():
from sympy.utilities.randtest import verify_numerically as tn
assert polylog(2, 2) == pi**2/4 - I*pi*log(2)
assert polylog(2, S.Half) == pi**2/12 - log(2)**2/2
for z in [S.Half, 2, (sqrt(5)-1)/2, -(sqrt(5)-1)/2, -(sqrt(5)+1)/2, (3-sqrt(5))/2]:
assert Abs(polylog(2, z).evalf() - polylog(2, z, evaluate=False).evalf()) < 1e-15
z = Symbol("z")
for s in [-1, 0]:
for _ in range(10):
assert tn(polylog(s, z), polylog(s, z, evaluate=False), z,
a=-3, b=-2, c=S.Half, d=2)
assert tn(polylog(s, z), polylog(s, z, evaluate=False), z,
a=2, b=-2, c=5, d=2)
def test_plan_derivatives():
a1, a2, a3 = 1, 2, S('1/2')
b1, b2 = 3, S('5/2')
h = Hyper_Function((a1, a2, a3), (b1, b2))
h2 = Hyper_Function((a1 + 1, a2 + 1, a3 + 2), (b1 + 1, b2 + 1))
ops = devise_plan(h2, h, z)
f = Formula(h, z, h(z), [])
deriv = make_derivative_operator(f.M, z)
assert tn((apply_operators(f.C, ops, deriv)*f.B)[0], h2(z), z)
h2 = Hyper_Function((a1, a2 - 1, a3 - 2), (b1 - 1, b2 - 1))
ops = devise_plan(h2, h, z)
assert tn((apply_operators(f.C, ops, deriv)*f.B)[0], h2(z), z)
def test_solve_quintics():
skip("This test is too slow")
f = x**5 - 110*x**3 - 55*x**2 + 2310*x + 979
s = solveset_complex(f, x)
for root in s:
res = f.subs(x, root.n()).n()
assert tn(res, 0)
f = x**5 + 15*x + 12
s = solveset_complex(f, x)
for root in s:
res = f.subs(x, root.n()).n()
assert tn(res, 0)
def test_meijerg_shift_operators():
# carefully set up the parameters. XXX this still fails sometimes
a1, a2, a3, a4, a5, b1, b2, b3, b4, b5 = \
map(lambda n: randcplx(n), range(10))
g = meijerg([a1], [a3, a4], [b1], [b3, b4], z)
assert tn(MeijerShiftA(b1).apply(g, op),
meijerg([a1], [a3, a4], [b1 + 1], [b3, b4], z), z)
assert tn(MeijerShiftB(a1).apply(g, op),
meijerg([a1 - 1], [a3, a4], [b1], [b3, b4], z), z)
assert tn(MeijerShiftC(b3).apply(g, op),
meijerg([a1], [a3, a4], [b1], [b3 + 1, b4], z), z)
assert tn(MeijerShiftD(a3).apply(g, op),
meijerg([a1], [a3 - 1, a4], [b1], [b3, b4], z), z)
s = MeijerUnShiftA([a1], [a3, a4], [b1], [b3, b4], 0, z)
assert tn(
s.apply(g, op), meijerg([a1], [a3, a4], [b1 - 1], [b3, b4], z), z)
s = MeijerUnShiftC([a1], [a3, a4], [b1], [b3, b4], 0, z)
assert tn(
s.apply(g, op), meijerg([a1], [a3, a4], [b1], [b3 - 1, b4], z), z)
s = MeijerUnShiftB([a1], [a3, a4], [b1], [b3, b4], 0, z)
assert tn(
s.apply(g, op), meijerg([a1 + 1], [a3, a4], [b1], [b3, b4], z), z)
s = MeijerUnShiftD([a1], [a3, a4], [b1], [b3, b4], 0, z)
assert tn(
s.apply(g, op), meijerg([a1], [a3 + 1, a4], [b1], [b3, b4], z), z)
def test_uppergamma():
from sympy import meijerg
assert uppergamma(4, 0) == 6
assert uppergamma(x, y).diff(y) == -y ** (x - 1) * exp(-y)
assert td(uppergamma(randcplx(), y), y)
assert uppergamma(x, y).diff(x) == uppergamma(x, y) * log(y) + meijerg([], [1, 1], [0, 0, x], [], y)
assert td(uppergamma(x, randcplx()), x)
assert uppergamma(S.Half, x) == sqrt(pi) * (1 - erf(sqrt(x)))
assert not uppergamma(S.Half - 3, x).has(uppergamma)
assert not uppergamma(S.Half + 3, x).has(uppergamma)
assert uppergamma(S.Half, x, evaluate=False).has(uppergamma)
assert tn(uppergamma(S.Half + 3, x, evaluate=False), uppergamma(S.Half + 3, x), x)
assert tn(uppergamma(S.Half - 3, x, evaluate=False), uppergamma(S.Half - 3, x), x)
def test_lowergamma():
from sympy import meijerg
assert lowergamma(x, y).diff(y) == y ** (x - 1) * exp(-y)
assert td(lowergamma(randcplx(), y), y)
assert lowergamma(x, y).diff(x) == gamma(x) * polygamma(0, x) - uppergamma(x, y) * log(y) + meijerg(
[], [1, 1], [0, 0, x], [], y
)
assert lowergamma(S.Half, x) == sqrt(pi) * erf(sqrt(x))
assert not lowergamma(S.Half - 3, x).has(lowergamma)
assert not lowergamma(S.Half + 3, x).has(lowergamma)
assert lowergamma(S.Half, x, evaluate=False).has(lowergamma)
assert tn(lowergamma(S.Half + 3, x, evaluate=False), lowergamma(S.Half + 3, x), x)
assert tn(lowergamma(S.Half - 3, x, evaluate=False), lowergamma(S.Half - 3, x), x)
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 test_meijer():
raises(TypeError, 'meijerg(1, z)')
raises(TypeError, 'meijerg(((1,), (2,)), (3,), (4,), z)')
assert meijerg(((1, 2), (3,)), ((4,), (5,)), z) == \
meijerg(Tuple(1, 2), Tuple(3), Tuple(4), Tuple(5), z)
g = meijerg((1, 2), (3, 4, 5), (6, 7, 8, 9), (10, 11, 12, 13, 14), z)
assert g.an == Tuple(1, 2)
assert g.ap == Tuple(1, 2, 3, 4, 5)
assert g.aother == Tuple(3, 4, 5)
assert g.bm == Tuple(6, 7, 8, 9)
assert g.bq == Tuple(6, 7, 8, 9, 10, 11, 12, 13, 14)
assert g.bother == Tuple(10, 11, 12, 13, 14)
assert g.argument == z
assert g.nu == 75
assert g.delta == -1
assert g.is_commutative is True
assert meijerg([1, 2], [3], [4], [5], z).delta == S(1)/2
# just a few checks to make sure that all arguments go where they should
assert tn(meijerg(Tuple(), Tuple(), Tuple(0), Tuple(), -z), exp(z), z)
assert tn(sqrt(pi)*meijerg(Tuple(), Tuple(),
Tuple(0), Tuple(S(1)/2), z**2/4), cos(z), z)
assert tn(meijerg(Tuple(1, 1),Tuple(), Tuple(1), Tuple(0), z),
log(1 + z), z)
# differentiation
g = meijerg((randcplx(),), (randcplx() + 2*I,), Tuple(),
(randcplx(), randcplx()), z)
assert td(g, z)
g = meijerg(Tuple(), (randcplx(),), Tuple(),
(randcplx(), randcplx()), z)
assert td(g, z)
g = meijerg(Tuple(), Tuple(), Tuple(randcplx()),
Tuple(randcplx(), randcplx()), z)
assert td(g, z)
a1, a2, b1, b2, c1, c2, d1, d2 = symbols('a1:3, b1:3, c1:3, d1:3')
assert meijerg((a1, a2), (b1, b2), (c1, c2), (d1, d2), z).diff(z) == \
(meijerg((a1-1, a2), (b1, b2), (c1, c2), (d1, d2), z) \
+ (a1 - 1)*meijerg((a1, a2), (b1, b2), (c1, c2), (d1, d2), z))/z
raises(NotImplementedError, 'meijerg((z,), (), (), (), z).diff(z)')
def test_lowergamma():
from sympy import meijerg, exp_polar, I, expint
assert lowergamma(x, 0) == 0
assert lowergamma(x, y).diff(y) == y**(x - 1)*exp(-y)
assert td(lowergamma(randcplx(), y), y)
assert td(lowergamma(x, randcplx()), x)
assert lowergamma(x, y).diff(x) == \
gamma(x)*polygamma(0, x) - uppergamma(x, y)*log(y) \
- meijerg([], [1, 1], [0, 0, x], [], y)
assert lowergamma(S.Half, x) == sqrt(pi)*erf(sqrt(x))
assert not lowergamma(S.Half - 3, x).has(lowergamma)
assert not lowergamma(S.Half + 3, x).has(lowergamma)
assert lowergamma(S.Half, x, evaluate=False).has(lowergamma)
assert tn(lowergamma(S.Half + 3, x, evaluate=False),
lowergamma(S.Half + 3, x), x)
assert tn(lowergamma(S.Half - 3, x, evaluate=False),
lowergamma(S.Half - 3, x), x)
assert tn_branch(-3, lowergamma)
assert tn_branch(-4, lowergamma)
assert tn_branch(S(1)/3, lowergamma)
assert tn_branch(pi, lowergamma)
assert lowergamma(3, exp_polar(4*pi*I)*x) == lowergamma(3, x)
assert lowergamma(y, exp_polar(5*pi*I)*x) == \
exp(4*I*pi*y)*lowergamma(y, x*exp_polar(pi*I))
assert lowergamma(-2, exp_polar(5*pi*I)*x) == \
lowergamma(-2, x*exp_polar(I*pi)) + 2*pi*I
assert conjugate(lowergamma(x, y)) == lowergamma(conjugate(x), conjugate(y))
assert conjugate(lowergamma(x, 0)) == conjugate(lowergamma(x, 0))
assert conjugate(lowergamma(x, -oo)) == conjugate(lowergamma(x, -oo))
assert lowergamma(
x, y).rewrite(expint) == -y**x*expint(-x + 1, y) + gamma(x)
k = Symbol('k', integer=True)
assert lowergamma(
k, y).rewrite(expint) == -y**k*expint(-k + 1, y) + gamma(k)
k = Symbol('k', integer=True, positive=False)
assert lowergamma(k, y).rewrite(expint) == lowergamma(k, y)
assert lowergamma(x, y).rewrite(uppergamma) == gamma(x) - uppergamma(x, y)
assert lowergamma(70, 6) == factorial(69) - 69035724522603011058660187038367026272747334489677105069435923032634389419656200387949342530805432320 * exp(-6)
assert (lowergamma(S(77) / 2, 6) - lowergamma(S(77) / 2, 6, evaluate=False)).evalf() < 1e-16
assert (lowergamma(-S(77) / 2, 6) - lowergamma(-S(77) / 2, 6, evaluate=False)).evalf() < 1e-16
def test_plan():
assert devise_plan(IndexPair([0], ()), IndexPair([0], ()), z) == []
raises(ValueError, "devise_plan(IndexPair([1], ()), IndexPair((), ()), z)")
raises(ValueError, "devise_plan(IndexPair([2], [1]), IndexPair([2], [2]), z)")
raises(KeyError, 'devise_plan(IndexPair([2], []), IndexPair([S("1/2")], []), z)')
# We cannot use pi/(10000 + n) because polys is insanely slow.
a1, a2, b1 = map(lambda n: randcplx(n), range(3))
b1 += 2 * I
h = hyper([a1, a2], [b1], z)
h2 = hyper((a1 + 1, a2), [b1], z)
assert tn(apply_operators(h, devise_plan(IndexPair((a1 + 1, a2), [b1]), IndexPair((a1, a2), [b1]), z), op), h2, z)
h2 = hyper((a1 + 1, a2 - 1), [b1], z)
assert tn(
apply_operators(h, devise_plan(IndexPair((a1 + 1, a2 - 1), [b1]), IndexPair((a1, a2), [b1]), z), op), h2, z
)
def test_rewrite():
from sympy import polar_lift, exp, I
assert besselj(n, z).rewrite(jn) == sqrt(2 * z / pi) * jn(n - S.Half, z)
assert bessely(n, z).rewrite(yn) == sqrt(2 * z / pi) * yn(n - S.Half, z)
assert besseli(n, z).rewrite(besselj) == \
exp(-I*n*pi/2)*besselj(n, polar_lift(I)*z)
assert besselj(n, z).rewrite(besseli) == \
exp(I*n*pi/2)*besseli(n, polar_lift(-I)*z)
nu = randcplx()
assert tn(besselj(nu, z), besselj(nu, z).rewrite(besseli), z)
assert tn(besselj(nu, z), besselj(nu, z).rewrite(bessely), z)
assert tn(besseli(nu, z), besseli(nu, z).rewrite(besselj), z)
assert tn(besseli(nu, z), besseli(nu, z).rewrite(bessely), z)
assert tn(bessely(nu, z), bessely(nu, z).rewrite(besselj), z)
assert tn(bessely(nu, z), bessely(nu, z).rewrite(besseli), z)
assert tn(besselk(nu, z), besselk(nu, z).rewrite(besselj), z)
assert tn(besselk(nu, z), besselk(nu, z).rewrite(besseli), z)
assert tn(besselk(nu, z), besselk(nu, z).rewrite(bessely), z)
# check that a rewrite was triggered, when the order is set to a generic
# symbol 'nu'
assert yn(nu, z) != yn(nu, z).rewrite(jn)
assert hn1(nu, z) != hn1(nu, z).rewrite(jn)
assert hn2(nu, z) != hn2(nu, z).rewrite(jn)
assert jn(nu, z) != jn(nu, z).rewrite(yn)
assert hn1(nu, z) != hn1(nu, z).rewrite(yn)
assert hn2(nu, z) != hn2(nu, z).rewrite(yn)
# rewriting spherical bessel functions (SBFs) w.r.t. besselj, bessely is
# not allowed if a generic symbol 'nu' is used as the order of the SBFs
# to avoid inconsistencies (the order of bessel[jy] is allowed to be
# complex-valued, whereas SBFs are defined only for integer orders)
order = nu
for f in (besselj, bessely):
assert hn1(order, z) == hn1(order, z).rewrite(f)
assert hn2(order, z) == hn2(order, z).rewrite(f)
assert jn(order, z).rewrite(besselj) == sqrt(2) * sqrt(pi) * sqrt(
1 / z) * besselj(order + S.Half, z) / 2
assert jn(order,
z).rewrite(bessely) == (-1)**nu * sqrt(2) * sqrt(pi) * sqrt(
1 / z) * bessely(-order - S.Half, z) / 2
# for integral orders rewriting SBFs w.r.t bessel[jy] is allowed
N = Symbol('n', integer=True)
ri = randint(-11, 10)
for order in (ri, N):
for f in (besselj, bessely):
assert yn(order, z) != yn(order, z).rewrite(f)
assert jn(order, z) != jn(order, z).rewrite(f)
assert hn1(order, z) != hn1(order, z).rewrite(f)
assert hn2(order, z) != hn2(order, z).rewrite(f)
for func, refunc in product((yn, jn, hn1, hn2),
(jn, yn, besselj, bessely)):
assert tn(func(ri, z), func(ri, z).rewrite(refunc), z)
def test_expand():
from sympy import besselsimp, Symbol, exp, exp_polar, I
assert expand_func(besselj(S(1)/2, z).rewrite(jn)) == \
sqrt(2)*sin(z)/(sqrt(pi)*sqrt(z))
assert expand_func(bessely(S(1)/2, z).rewrite(yn)) == \
-sqrt(2)*cos(z)/(sqrt(pi)*sqrt(z))
# XXX: teach sin/cos to work around arguments like
# x*exp_polar(I*pi*n/2). Then change besselsimp -> expand_func
assert besselsimp(besselj(S(1)/2, z)) == sqrt(2)*sin(z)/(sqrt(pi)*sqrt(z))
assert besselsimp(besselj(S(-1)/2, z)) == sqrt(2)*cos(z)/(sqrt(pi)*sqrt(z))
assert besselsimp(besselj(S(5)/2, z)) == \
-sqrt(2)*(z**2*sin(z) + 3*z*cos(z) - 3*sin(z))/(sqrt(pi)*z**(S(5)/2))
assert besselsimp(besselj(-S(5)/2, z)) == \
-sqrt(2)*(z**2*cos(z) - 3*z*sin(z) - 3*cos(z))/(sqrt(pi)*z**(S(5)/2))
assert besselsimp(bessely(S(1)/2, z)) == \
-(sqrt(2)*cos(z))/(sqrt(pi)*sqrt(z))
assert besselsimp(bessely(S(-1)/2, z)) == sqrt(2)*sin(z)/(sqrt(pi)*sqrt(z))
assert besselsimp(bessely(S(5)/2, z)) == \
sqrt(2)*(z**2*cos(z) - 3*z*sin(z) - 3*cos(z))/(sqrt(pi)*z**(S(5)/2))
assert besselsimp(bessely(S(-5)/2, z)) == \
-sqrt(2)*(z**2*sin(z) + 3*z*cos(z) - 3*sin(z))/(sqrt(pi)*z**(S(5)/2))
assert besselsimp(besseli(S(1)/2, z)) == sqrt(2)*sinh(z)/(sqrt(pi)*sqrt(z))
assert besselsimp(besseli(S(-1)/2, z)) == \
sqrt(2)*cosh(z)/(sqrt(pi)*sqrt(z))
assert besselsimp(besseli(S(5)/2, z)) == \
sqrt(2)*(z**2*sinh(z) - 3*z*cosh(z) + 3*sinh(z))/(sqrt(pi)*z**(S(5)/2))
assert besselsimp(besseli(S(-5)/2, z)) == \
sqrt(2)*(z**2*cosh(z) - 3*z*sinh(z) + 3*cosh(z))/(sqrt(pi)*z**(S(5)/2))
assert besselsimp(besselk(S(1)/2, z)) == \
besselsimp(besselk(S(-1)/2, z)) == sqrt(pi)*exp(-z)/(sqrt(2)*sqrt(z))
assert besselsimp(besselk(S(5)/2, z)) == \
besselsimp(besselk(S(-5)/2, z)) == \
sqrt(2)*sqrt(pi)*(z**2 + 3*z + 3)*exp(-z)/(2*z**(S(5)/2))
def check(eq, ans):
return tn(eq, ans) and eq == ans
rn = randcplx(a=1, b=0, d=0, c=2)
for besselx in [besselj, bessely, besseli, besselk]:
ri = S(2*randint(-11, 10) + 1) / 2 # half integer in [-21/2, 21/2]
assert tn(besselsimp(besselx(ri, z)), besselx(ri, z))
assert check(expand_func(besseli(rn, x)), \
besseli(rn - 2, x) - 2*(rn - 1)*besseli(rn - 1, x)/x)
assert check(expand_func(besseli(-rn, x)), \
besseli(-rn + 2, x) + 2*(-rn + 1)*besseli(-rn + 1, x)/x)
assert check(expand_func(besselj(rn, x)), \
-besselj(rn - 2, x) + 2*(rn - 1)*besselj(rn - 1, x)/x)
assert check(expand_func(besselj(-rn, x)), \
-besselj(-rn + 2, x) + 2*(-rn + 1)*besselj(-rn + 1, x)/x)
assert check(expand_func(besselk(rn, x)), \
besselk(rn - 2, x) + 2*(rn - 1)*besselk(rn - 1, x)/x)
assert check(expand_func(besselk(-rn, x)), \
besselk(-rn + 2, x) - 2*(-rn + 1)*besselk(-rn + 1, x)/x)
assert check(expand_func(bessely(rn, x)), \
-bessely(rn - 2, x) + 2*(rn - 1)*bessely(rn - 1, x)/x)
assert check(expand_func(bessely(-rn, x)), \
-bessely(-rn + 2, x) + 2*(-rn + 1)*bessely(-rn + 1, x)/x)
n = Symbol('n', integer=True, positive=True)
assert expand_func(besseli(n + 2, z)) == \
besseli(n, z) + (-2*n - 2)*(-2*n*besseli(n, z)/z + besseli(n - 1, z))/z
assert expand_func(besselj(n + 2, z)) == \
-besselj(n, z) + (2*n + 2)*(2*n*besselj(n, z)/z - besselj(n - 1, z))/z
assert expand_func(besselk(n + 2, z)) == \
besselk(n, z) + (2*n + 2)*(2*n*besselk(n, z)/z + besselk(n - 1, z))/z
assert expand_func(bessely(n + 2, z)) == \
-bessely(n, z) + (2*n + 2)*(2*n*bessely(n, z)/z - bessely(n - 1, z))/z
assert expand_func(besseli(n + S(1)/2, z).rewrite(jn)) == \
sqrt(2)*sqrt(z)*exp(-I*pi*(n + S(1)/2)/2)* \
exp_polar(I*pi/4)*jn(n, z*exp_polar(I*pi/2))/sqrt(pi)
assert expand_func(besselj(n + S(1)/2, z).rewrite(jn)) == \
sqrt(2)*sqrt(z)*jn(n, z)/sqrt(pi)
r = Symbol('r', real=True)
p = Symbol('p', positive=True)
i = Symbol('i', integer=True)
for besselx in [besselj, bessely, besseli, besselk]:
assert besselx(i, p).is_real
assert besselx(i, x).is_real is None
assert besselx(x, z).is_real is None
for besselx in [besselj, besseli]:
assert besselx(i, r).is_real
for besselx in [bessely, besselk]:
assert besselx(i, r).is_real is None
def check(eq, ans):
return tn(eq, ans) and eq == ans
def u(an, ap, bm, bq):
m = meijerg(an, ap, bm, bq, z)
m2 = hyperexpand(m, allow_hyper=True)
if m2.has(meijerg) and not (m2.is_Piecewise and len(m2.args) == 3):
return False
return tn(m, m2, z)
def valid(a, b):
from sympy.utilities.randtest import verify_numerically as tn
if not (tn(a, b) and a == b):
return False
return True
def test_meijer():
raises(TypeError, lambda: meijerg(1, z))
raises(TypeError, lambda: meijerg(((1,), (2,)), (3,), (4,), z))
assert meijerg(((1, 2), (3,)), ((4,), (5,)), z) == \
meijerg(Tuple(1, 2), Tuple(3), Tuple(4), Tuple(5), z)
g = meijerg((1, 2), (3, 4, 5), (6, 7, 8, 9), (10, 11, 12, 13, 14), z)
assert g.an == Tuple(1, 2)
assert g.ap == Tuple(1, 2, 3, 4, 5)
assert g.aother == Tuple(3, 4, 5)
assert g.bm == Tuple(6, 7, 8, 9)
assert g.bq == Tuple(6, 7, 8, 9, 10, 11, 12, 13, 14)
assert g.bother == Tuple(10, 11, 12, 13, 14)
assert g.argument == z
assert g.nu == 75
assert g.delta == -1
assert g.is_commutative is True
assert g.is_number is False
#issue 13071
assert meijerg([[],[]], [[S(1)/2],[0]], 1).is_number is True
assert meijerg([1, 2], [3], [4], [5], z).delta == S(1)/2
# just a few checks to make sure that all arguments go where they should
assert tn(meijerg(Tuple(), Tuple(), Tuple(0), Tuple(), -z), exp(z), z)
assert tn(sqrt(pi)*meijerg(Tuple(), Tuple(),
Tuple(0), Tuple(S(1)/2), z**2/4), cos(z), z)
assert tn(meijerg(Tuple(1, 1), Tuple(), Tuple(1), Tuple(0), z),
log(1 + z), z)
# test exceptions
raises(ValueError, lambda: meijerg(((3, 1), (2,)), ((oo,), (2, 0)), x))
raises(ValueError, lambda: meijerg(((3, 1), (2,)), ((1,), (2, 0)), x))
# differentiation
g = meijerg((randcplx(),), (randcplx() + 2*I,), Tuple(),
(randcplx(), randcplx()), z)
assert td(g, z)
g = meijerg(Tuple(), (randcplx(),), Tuple(),
(randcplx(), randcplx()), z)
assert td(g, z)
g = meijerg(Tuple(), Tuple(), Tuple(randcplx()),
Tuple(randcplx(), randcplx()), z)
assert td(g, z)
a1, a2, b1, b2, c1, c2, d1, d2 = symbols('a1:3, b1:3, c1:3, d1:3')
assert meijerg((a1, a2), (b1, b2), (c1, c2), (d1, d2), z).diff(z) == \
(meijerg((a1 - 1, a2), (b1, b2), (c1, c2), (d1, d2), z)
+ (a1 - 1)*meijerg((a1, a2), (b1, b2), (c1, c2), (d1, d2), z))/z
assert meijerg([z, z], [], [], [], z).diff(z) == \
Derivative(meijerg([z, z], [], [], [], z), z)
# meijerg is unbranched wrt parameters
from sympy import polar_lift as pl
assert meijerg([pl(a1)], [pl(a2)], [pl(b1)], [pl(b2)], pl(z)) == \
meijerg([a1], [a2], [b1], [b2], pl(z))
# integrand
from sympy.abc import a, b, c, d, s
assert meijerg([a], [b], [c], [d], z).integrand(s) == \
z**s*gamma(c - s)*gamma(-a + s + 1)/(gamma(b - s)*gamma(-d + s + 1))
