def test_lerchphi_expansion():
assert myexpand(lerchphi(1, s, a), zeta(s, a))
assert myexpand(lerchphi(z, s, 1), polylog(s, z) / z)
# direct summation
assert myexpand(lerchphi(z, -1, a), a / (1 - z) + z / (1 - z)**2)
assert myexpand(lerchphi(z, -3, a), None)
# polylog reduction
assert myexpand(
lerchphi(z, s, Rational(1, 2)),
2**(s - 1) * (polylog(s, sqrt(z)) / sqrt(z) -
polylog(s,
polar_lift(-1) * sqrt(z)) / sqrt(z)))
assert myexpand(lerchphi(z, s, 2), -1 / z + polylog(s, z) / z**2)
assert myexpand(lerchphi(z, s, Rational(3, 2)), None)
assert myexpand(lerchphi(z, s, Rational(7, 3)), None)
assert myexpand(lerchphi(z, s, -Rational(1, 3)), None)
assert myexpand(lerchphi(z, s, -Rational(5, 2)), None)
# hurwitz zeta reduction
assert myexpand(lerchphi(-1, s, a),
2**(-s) * zeta(s, a / 2) - 2**(-s) * zeta(s, (a + 1) / 2))
assert myexpand(lerchphi(I, s, a), None)
assert myexpand(lerchphi(-I, s, a), None)
assert myexpand(lerchphi(exp(2 * I * pi / 5), s, a), None)
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_derivatives():
assert zeta(x, a).diff(x) == Derivative(zeta(x, a), x)
assert zeta(x, a).diff(a) == -x*zeta(x + 1, a)
assert lerchphi(
z, s, a).diff(z) == (lerchphi(z, s - 1, a) - a*lerchphi(z, s, a))/z
assert lerchphi(z, s, a).diff(a) == -s*lerchphi(z, s + 1, a)
assert polylog(s, z).diff(z) == polylog(s - 1, z)/z
b = randcplx()
c = randcplx()
assert td(zeta(b, x), x)
assert td(polylog(b, z), z)
assert td(lerchphi(c, b, x), x)
assert td(lerchphi(x, b, c), x)
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 zeta(z, 2).rewrite(dirichlet_eta) == zeta(z, 2)
assert zeta(z, 2).rewrite('tractable') == zeta(z, 2)
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)
assert lerchphi(z, s, a).rewrite(zeta) == lerchphi(z, s, a)
def test_lerchphi():
from diofant import combsimp, exp_polar, polylog, log, lerchphi
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 combsimp(
hyperexpand(meijerg([0, 1 - a], [], [0], [-a],
exp_polar(-I * pi) * z))) == lerchphi(z, 1, a)
assert combsimp(
hyperexpand(
meijerg([0, 1 - a, 1 - a], [], [0], [-a, -a],
exp_polar(-I * pi) * z))) == lerchphi(z, 2, a)
assert combsimp(
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 + Rational(1, 2)], [a + 1, Rational(1, 2)], 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 diofant import Abs
assert hyperexpand(hyper([Rational(1, 2), Rational(1, 2), Rational(1, 2), 1],
[Rational(3, 2), Rational(3, 2), Rational(3, 2)], Rational(1, 4))) == \
Abs(-polylog(3, exp_polar(I*pi)/2) + polylog(3, Rational(1, 2)))
def test_derivatives():
assert zeta(x, a).diff(x) == Derivative(zeta(x, a), x)
assert zeta(x, a).diff(a) == -x * zeta(x + 1, a)
assert zeta(z).diff(z) == Derivative(zeta(z), z)
assert lerchphi(
z, s, a).diff(z) == (lerchphi(z, s - 1, a) - a * lerchphi(z, s, a)) / z
pytest.raises(ArgumentIndexError, lambda: lerchphi(z, s, a).fdiff(4))
assert lerchphi(z, s, a).diff(a) == -s * lerchphi(z, s + 1, a)
assert polylog(s, z).diff(z) == polylog(s - 1, z) / z
pytest.raises(ArgumentIndexError, lambda: polylog(s, z).fdiff(3))
b = randcplx()
c = randcplx()
assert td(zeta(b, x), x)
assert td(polylog(b, z), z)
assert td(lerchphi(c, b, x), x)
assert td(lerchphi(x, b, c), x)
def test_derivatives():
assert zeta(x, a).diff(x) == Derivative(zeta(x, a), x)
assert zeta(x, a).diff(a) == -x*zeta(x + 1, a)
assert zeta(z).diff(z) == Derivative(zeta(z), z)
assert lerchphi(
z, s, a).diff(z) == (lerchphi(z, s - 1, a) - a*lerchphi(z, s, a))/z
pytest.raises(ArgumentIndexError, lambda: lerchphi(z, s, a).fdiff(4))
assert lerchphi(z, s, a).diff(a) == -s*lerchphi(z, s + 1, a)
assert polylog(s, z).diff(z) == polylog(s - 1, z)/z
pytest.raises(ArgumentIndexError, lambda: polylog(s, z).fdiff(3))
b = randcplx()
c = randcplx()
assert td(zeta(b, x), x)
assert td(polylog(b, z), z)
assert td(lerchphi(c, b, x), x)
assert td(lerchphi(x, b, c), x)
def test_polylog_eval():
assert polylog(s, 0) == 0
assert polylog(s, 1) == zeta(s)
assert polylog(s, -1) == -dirichlet_eta(s)
assert polylog(s, exp_polar(I * pi)) == polylog(s, -1)
assert polylog(s, 2 * exp_polar(2 * I * pi)) == polylog(
s, 2 * exp_polar(2 * I * pi), evaluate=False)
def test_lerchphi():
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 combsimp(hyperexpand(meijerg([0, 1 - a], [], [0],
[-a], exp_polar(-I*pi)*z))) == lerchphi(z, 1, a)
assert combsimp(hyperexpand(meijerg([0, 1 - a, 1 - a], [], [0],
[-a, -a], exp_polar(-I*pi)*z))) == lerchphi(z, 2, a)
assert combsimp(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 + Rational(1, 2)], [a + 1, Rational(1, 2)], 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
assert hyperexpand(hyper([Rational(1, 2), Rational(1, 2), Rational(1, 2), 1],
[Rational(3, 2), Rational(3, 2), Rational(3, 2)], Rational(1, 4))) == \
abs(-polylog(3, exp_polar(I*pi)/2) + polylog(3, Rational(1, 2)))
def test_lerchphi_expansion():
assert myexpand(lerchphi(1, s, a), zeta(s, a))
assert myexpand(lerchphi(z, s, 1), polylog(s, z)/z)
# direct summation
assert myexpand(lerchphi(z, -1, a), a/(1 - z) + z/(1 - z)**2)
assert myexpand(lerchphi(z, -3, a), None)
# polylog reduction
assert myexpand(lerchphi(z, s, Rational(1, 2)),
2**(s - 1)*(polylog(s, sqrt(z))/sqrt(z)
- polylog(s, polar_lift(-1)*sqrt(z))/sqrt(z)))
assert myexpand(lerchphi(z, s, 2), -1/z + polylog(s, z)/z**2)
assert myexpand(lerchphi(z, s, Rational(3, 2)), None)
assert myexpand(lerchphi(z, s, Rational(7, 3)), None)
assert myexpand(lerchphi(z, s, -Rational(1, 3)), None)
assert myexpand(lerchphi(z, s, -Rational(5, 2)), None)
# hurwitz zeta reduction
assert myexpand(lerchphi(-1, s, a),
2**(-s)*zeta(s, a/2) - 2**(-s)*zeta(s, (a + 1)/2))
assert myexpand(lerchphi(I, s, a), None)
assert myexpand(lerchphi(-I, s, a), None)
assert myexpand(lerchphi(exp(2*I*pi/5), s, a), None)
def test_polylog_expansion():
assert myexpand(polylog(1, z), -log(1 - z))
assert myexpand(polylog(0, z), z / (1 - z))
assert myexpand(polylog(-1, z), z**2 / (1 - z)**2 + z / (1 - z))
assert myexpand(polylog(-5, z), None)
def test_Function():
assert mathematica_code(f(x, y, z)) == 'f[x, y, z]'
assert mathematica_code(sin(x)**cos(x)) == 'Sin[x]^Cos[x]'
assert mathematica_code(sign(x)) == 'Sign[x]'
assert mathematica_code(atanh(x),
user_functions={'atanh':
'ArcTanh'}) == 'ArcTanh[x]'
assert (mathematica_code(meijerg(
((1, 1), (3, 4)), ((1, ), ()),
x)) == 'MeijerG[{{1, 1}, {3, 4}}, {{1}, {}}, x]')
assert (mathematica_code(hyper(
(1, 2, 3), (3, 4), x)) == 'HypergeometricPFQ[{1, 2, 3}, {3, 4}, x]')
assert mathematica_code(Min(x, y)) == 'Min[x, y]'
assert mathematica_code(Max(x, y)) == 'Max[x, y]'
assert mathematica_code(Max(x,
2)) == 'Max[2, x]' # issue sympy/sympy#15344
assert mathematica_code(binomial(x, y)) == 'Binomial[x, y]'
assert mathematica_code(log(x)) == 'Log[x]'
assert mathematica_code(tan(x)) == 'Tan[x]'
assert mathematica_code(cot(x)) == 'Cot[x]'
assert mathematica_code(asin(x)) == 'ArcSin[x]'
assert mathematica_code(acos(x)) == 'ArcCos[x]'
assert mathematica_code(atan(x)) == 'ArcTan[x]'
assert mathematica_code(acot(x)) == 'ArcCot[x]'
assert mathematica_code(sinh(x)) == 'Sinh[x]'
assert mathematica_code(cosh(x)) == 'Cosh[x]'
assert mathematica_code(tanh(x)) == 'Tanh[x]'
assert mathematica_code(coth(x)) == 'Coth[x]'
assert mathematica_code(asinh(x)) == 'ArcSinh[x]'
assert mathematica_code(acosh(x)) == 'ArcCosh[x]'
assert mathematica_code(atanh(x)) == 'ArcTanh[x]'
assert mathematica_code(acoth(x)) == 'ArcCoth[x]'
assert mathematica_code(sech(x)) == 'Sech[x]'
assert mathematica_code(csch(x)) == 'Csch[x]'
assert mathematica_code(erf(x)) == 'Erf[x]'
assert mathematica_code(erfi(x)) == 'Erfi[x]'
assert mathematica_code(erfc(x)) == 'Erfc[x]'
assert mathematica_code(conjugate(x)) == 'Conjugate[x]'
assert mathematica_code(re(x)) == 'Re[x]'
assert mathematica_code(im(x)) == 'Im[x]'
assert mathematica_code(polygamma(x, y)) == 'PolyGamma[x, y]'
assert mathematica_code(factorial(x)) == 'Factorial[x]'
assert mathematica_code(factorial2(x)) == 'Factorial2[x]'
assert mathematica_code(rf(x, y)) == 'Pochhammer[x, y]'
assert mathematica_code(gamma(x)) == 'Gamma[x]'
assert mathematica_code(zeta(x)) == 'Zeta[x]'
assert mathematica_code(Heaviside(x)) == 'UnitStep[x]'
assert mathematica_code(fibonacci(x)) == 'Fibonacci[x]'
assert mathematica_code(polylog(x, y)) == 'PolyLog[x, y]'
assert mathematica_code(loggamma(x)) == 'LogGamma[x]'
assert mathematica_code(uppergamma(x, y)) == 'Gamma[x, y]'
class MyFunc1(Function):
@classmethod
def eval(cls, x):
pass
class MyFunc2(Function):
@classmethod
def eval(cls, x, y):
pass
pytest.raises(
ValueError,
lambda: mathematica_code(MyFunc1(x),
user_functions={'MyFunc1': ['Myfunc1']}))
assert mathematica_code(MyFunc1(x),
user_functions={'MyFunc1':
'Myfunc1'}) == 'Myfunc1[x]'
assert mathematica_code(
MyFunc2(x, y),
user_functions={'MyFunc2':
[(lambda *x: False, 'Myfunc2')]}) == 'MyFunc2[x, y]'
def test_polylog_expansion():
assert myexpand(polylog(1, z), -log(1 - z))
assert myexpand(polylog(0, z), z/(1 - z))
assert myexpand(polylog(-1, z), z**2/(1 - z)**2 + z/(1 - z))
assert myexpand(polylog(-5, z), None)
def test_polylog_eval():
assert polylog(s, 0) == 0
assert polylog(s, 1) == zeta(s)
assert polylog(s, -1) == -dirichlet_eta(s)
assert polylog(s, exp_polar(I*pi)) == polylog(s, -1)
assert polylog(s, 2*exp_polar(2*I*pi)) == polylog(s, 2*exp_polar(2*I*pi), evaluate=False)
def compute_moment(self, k):
if self.distribution == 'finite':
return sum([p * (b**k) for b, p in self.parameters])
if self.distribution == 'uniform':
l, u = self.parameters
return (u**(k + 1) - l**(k + 1)) / ((k + 1) * (u - l))
if self.distribution == 'gauss' or self.distribution == 'normal':
mu, sigma_squared = self.parameters
# For low moments avoid scipy.stats.moments as it does not support
# parametric parameters. In the future get all moments directly,
# using the following properties:
# https://math.stackexchange.com/questions/1945448/methods-for-finding-raw-moments-of-the-normal-distribution
if k == 0:
return 1
elif k == 1:
return mu
elif k == 2:
return mu**2 + sigma_squared
elif k == 3:
return mu * (mu**2 + 3 * sigma_squared)
elif k == 4:
return mu**4 + 6 * mu**2 * sigma_squared + 3 * sigma_squared**2
moment = norm(loc=mu, scale=sqrt(sigma_squared)).moment(k)
return Rational(moment)
if self.distribution == 'bernoulli':
return sympify(self.parameters[0])
if self.distribution == 'geometric':
p = sympify(self.parameters[0])
return p * polylog(-k, 1 - p)
if self.distribution == 'exponential':
lambd = sympify(self.parameters[0])
return factorial(k) / (lambd**k)
if self.distribution == 'beta':
alpha, beta = self.parameters
alpha = sympify(alpha)
beta = sympify(beta)
r = symbols('r')
return product((alpha + r) / (alpha + beta + r), (r, 0, k - 1))
if self.distribution == 'chi-squared':
n = sympify(self.parameters[0])
i = symbols('i')
return product(n + 2 * i, (i, 0, k - 1))
if self.distribution == 'rayleigh':
s = sympify(self.parameters[0])
return (2**(k / 2)) * (s**k) * gamma(1 + k / 2)
if self.distribution == 'unknown':
return sympify(f"{self.var_name}(0)^{k}")
if self.distribution == 'laplace':
mu, b = self.parameters
mu = sympify(mu)
b = sympify(b)
x = Laplace("x", mu, b)
return E(x**k)
if self.distribution == 'binomial':
n, p = self.parameters
n = sympify(n)
p = sympify(p)
x = Binomial("x", n, p)
return E(x**k)
if self.distribution == 'hypergeometric':
N, K, n = self.parameters
N = sympify(N)
K = sympify(K)
n = sympify(n)
x = Hypergeometric("x", N, K, n)
return E(x**k)
