def descendant_subgroups(S, C, R1_c_list, x, R2, N, Y):
A_dict = C.A_dict
A_dict_inv = C.A_dict_inv
if C.is_complete():
# if C is complete then it only needs to test
# whether the relators in R2 are satisfied
for w, alpha in product(R2, C.omega):
if not C.scan_check(alpha, w):
return
# relators in R2 are satisfied, append the table to list
S.append(C)
else:
# find the first undefined entry in Coset Table
for alpha, x in product(range(len(C.table)), C.A):
if C.table[alpha][A_dict[x]] is None:
# this is "x" in pseudo-code (using "y" makes it clear)
undefined_coset, undefined_gen = alpha, x
break
# for filling up the undefine entry we try all possible values
# of β ∈ Ω or β = n where β^(undefined_gen^-1) is undefined
reach = C.omega + [C.n]
for beta in reach:
if beta < N:
if beta == C.n or C.table[beta][A_dict_inv[undefined_gen]] is None:
try_descendant(S, C, R1_c_list, R2, N, undefined_coset, \
undefined_gen, beta, Y)
def test_function_subs():
f = Function("f")
S = Sum(x*f(y),(x,0,oo),(y,0,oo))
assert S.subs(f(y),y) == Sum(x*y,(x,0,oo),(y,0,oo))
assert S.subs(f(x),x) == S
raises(ValueError, lambda: S.subs(f(y),x+y) )
S = Sum(x*log(y),(x,0,oo),(y,0,oo))
assert S.subs(log(y),y) == S
S = Sum(x*f(y),(x,0,oo),(y,0,oo))
assert S.subs(f(y),y) == Sum(x*y,(x,0,oo),(y,0,oo))
def test_exceptions():
S = Sum(x, (x, a, b))
raises(ValueError, lambda: S.change_index(x, x**2, y))
S = Sum(x, (x, a, b), (x, 1, 4))
raises(ValueError, lambda: S.index(x))
S = Sum(x, (x, a, b), (y, 1, 4))
raises(ValueError, lambda: S.reorder([x]))
S = Sum(x, (x, y, b), (y, 1, 4))
raises(ReorderError, lambda: S.reorder_limit(0, 1))
S = Sum(x*y, (x, a, b), (y, 1, 4))
raises(NotImplementedError, lambda: S.is_convergent())
def test_permutation_methods():
from sympy.combinatorics.fp_groups import FpSubgroup
F, x, y = free_group("x, y")
# DihedralGroup(8)
G = FpGroup(F, [x**2, y**8, x*y*x**-1*y])
T = G._to_perm_group()[1]
assert T.is_isomorphism()
assert G.center() == [y**4]
# DiheadralGroup(4)
G = FpGroup(F, [x**2, y**4, x*y*x**-1*y])
S = FpSubgroup(G, G.normal_closure([x]))
assert x in S
assert y**-1*x*y in S
# Z_5xZ_4
G = FpGroup(F, [x*y*x**-1*y**-1, y**5, x**4])
assert G.is_abelian
assert G.is_solvable
# AlternatingGroup(5)
G = FpGroup(F, [x**3, y**2, (x*y)**5])
assert not G.is_solvable
# AlternatingGroup(4)
G = FpGroup(F, [x**3, y**2, (x*y)**3])
assert len(G.derived_series()) == 3
S = FpSubgroup(G, G.derived_subgroup())
assert S.order() == 4
def test_Sum_doit():
assert Sum(n * Integral(a ** 2), (n, 0, 2)).doit() == a ** 3
assert Sum(n * Integral(a ** 2), (n, 0, 2)).doit(deep=False) == 3 * Integral(a ** 2)
assert summation(n * Integral(a ** 2), (n, 0, 2)) == 3 * Integral(a ** 2)
# test nested sum evaluation
S = Sum(Sum(Sum(2, (z, 1, n + 1)), (y, x + 1, n)), (x, 1, n))
assert 0 == (S.doit() - n * (n + 1) * (n - 1)).factor()
def test_PQ_f7(self):
S = QQ['t']
t = S.gen()
r0,r1,r2 = (t**3 - t**2 + 1).roots(QQbar, multiplicities=False)
series = self.get_PQ(self.f7)
x,y = self.f7.parent().gens()
x = QQbar['x,y'](x)
y = QQbar['x,y'](y)
self.assertItemsEqual(
series,
[(x, y + r0),
(x, y + r1),
(x, y + r2)])
def update(f, sugar, P):
"""Add f with sugar ``sugar`` to S, update P."""
if not f:
return P
k = len(S)
S.append(f)
Sugars.append(sugar)
LMf = sdm_LM(f)
def removethis(pair):
i, j, s, t = pair
if LMf[0] != t[0]:
return False
tik = sdm_monomial_lcm(LMf, sdm_LM(S[i]))
tjk = sdm_monomial_lcm(LMf, sdm_LM(S[j]))
return tik != t and tjk != t and sdm_monomial_divides(tik, t) and \
sdm_monomial_divides(tjk, t)
# apply the chain criterion
P = [p for p in P if not removethis(p)]
# new-pair set
N = [(i, k, Ssugar(i, k), sdm_monomial_lcm(LMf, sdm_LM(S[i])))
for i in range(k) if LMf[0] == sdm_LM(S[i])[0]]
# TODO apply the product criterion?
N.sort(key=ourkey)
remove = set()
for i, p in enumerate(N):
for j in range(i + 1, len(N)):
if sdm_monomial_divides(p[3], N[j][3]):
remove.add(j)
# TODO mergesort?
P.extend(reversed([p for i, p in enumerate(N) if not i in remove]))
P.sort(key=ourkey, reverse=True)
# NOTE reverse-sort, because we want to pop from the end
return P
def test_PQ_f27(self):
S = QQ['t']
t = S.gen()
sqrt2 = (t**2 - 2).roots(QQbar, multiplicities=False)[0]
series = self.get_PQ(self.f27)
x,y = self.f27.parent().gens()
x = QQbar['x,y'](x)
y = QQbar['x,y'](y)
self.assertItemsEqual(
series,
[(x, x*(y + sqrt2)),
(x, x*(y - sqrt2)),
(x**2/2, x**3*(y + 1)/2),
(x**3/2, x*(y + 1))])
def test_hyperexpand_parametric():
assert hyperexpand(hyper([a, S(1)/2 + a], [S(1)/2], z)) \
== (1 + sqrt(z))**(-2*a)/2 + (1 - sqrt(z))**(-2*a)/2
assert hyperexpand(hyper([a, -S(1)/2 + a], [2*a], z)) \
== 2**(2*a - 1)*(sqrt(-z + 1) + 1)**(-2*a + 1)
def test_geometric_sums():
assert summation(pi**n, (n, 0, b)) == (1 - pi**(b + 1)) / (1 - pi)
assert summation(2 * 3**n, (n, 0, b)) == 3**(b + 1) - 1
assert summation(Rational(1, 2)**n, (n, 1, oo)) == 1
assert summation(2**n, (n, 0, b)) == 2**(b + 1) - 1
assert summation(2**n, (n, 1, oo)) == oo
assert summation(2**(-n), (n, 1, oo)) == 1
assert summation(3**(-n), (n, 4, oo)) == Rational(1, 54)
assert summation(2**(-4 * n + 3), (n, 1, oo)) == Rational(8, 15)
assert summation(2**(n + 1), (n, 1, b)).expand() == 4 * (2**b - 1)
# issue 6664:
assert summation(x**n, (n, 0, oo)) == \
Piecewise((1/(-x + 1), Abs(x) < 1), (Sum(x**n, (n, 0, oo)), True))
assert summation(-2**n, (n, 0, oo)) == -oo
assert summation(I**n, (n, 0, oo)) == Sum(I**n, (n, 0, oo))
# issue 6802:
assert summation((-1)**(2 * x + 2), (x, 0, n)) == n + 1
assert summation((-2)**(2 * x + 2),
(x, 0, n)) == 4 * 4**(n + 1) / S(3) - S(4) / 3
assert summation((-1)**x, (x, 0, n)) == -(-1)**(n + 1) / S(2) + S(1) / 2
assert summation(y**x, (x, a, b)) == \
Piecewise((-a + b + 1, Eq(y, 1)), ((y**a - y**(b + 1))/(-y + 1), True))
assert summation((-2)**(y*x + 2), (x, 0, n)) == \
4*Piecewise((n + 1, Eq((-2)**y, 1)),
((-(-2)**(y*(n + 1)) + 1)/(-(-2)**y + 1), True))
# issue 8251:
assert summation((1 / (n + 1)**2) * n**2, (n, 0, oo)) == oo
#issue 9908:
assert Sum(1 / (n**3 - 1),
(n, -oo, -2)).doit() == summation(1 / (n**3 - 1), (n, -oo, -2))
#issue 11642:
result = Sum(0.5**n, (n, 1, oo)).doit()
assert result == 1
assert result.is_Float
result = Sum(0.25**n, (n, 1, oo)).doit()
assert result == S(1) / 3
assert result.is_Float
result = Sum(0.99999**n, (n, 1, oo)).doit()
assert result == 99999
assert result.is_Float
result = Sum(Rational(1, 2)**n, (n, 1, oo)).doit()
assert result == 1
assert not result.is_Float
result = Sum(Rational(3, 5)**n, (n, 1, oo)).doit()
assert result == S(3) / 2
assert not result.is_Float
assert Sum(1.0**n, (n, 1, oo)).doit() == oo
assert Sum(2.43**n, (n, 1, oo)).doit() == oo
# Issue 13979:
i, k, q = symbols('i k q', integer=True)
result = summation(
exp(-2 * I * pi * k * i / n) * exp(2 * I * pi * q * i / n) / n,
(i, 0, n - 1))
assert result.simplify() == Piecewise(
(1, Eq(exp(2 * I * pi * (-k + q) / n), 1)), (0, True))
def test_inverse_mellin_transform():
from sympy import (sin, simplify, expand_func, powsimp, Max, Min, expand,
powdenest, powsimp, exp_polar, combsimp, cos, cot)
IMT = inverse_mellin_transform
assert IMT(gamma(s), s, x, (0, oo)) == exp(-x)
assert IMT(gamma(-s), s, x, (-oo, 0)) == exp(-1 / x)
assert simplify(IMT(s/(2*s**2 - 2), s, x, (2, oo))) == \
(x**2 + 1)*Heaviside(1 - x)/(4*x)
# test passing "None"
assert IMT(1/(s**2 - 1), s, x, (-1, None)) == \
-x*Heaviside(-x + 1)/2 - Heaviside(x - 1)/(2*x)
assert IMT(1/(s**2 - 1), s, x, (None, 1)) == \
-x*Heaviside(-x + 1)/2 - Heaviside(x - 1)/(2*x)
# test expansion of sums
assert IMT(gamma(s) + gamma(s - 1), s, x, (1, oo)) == (x + 1) * exp(-x) / x
# test factorisation of polys
r = symbols('r', real=True)
assert IMT(1/(s**2 + 1), s, exp(-x), (None, oo)
).subs(x, r).rewrite(sin).simplify() \
== sin(r)*Heaviside(1 - exp(-r))
# test multiplicative substitution
_a, _b = symbols('a b', positive=True)
assert IMT(_b**(-s / _a) * factorial(s / _a) / s, s, x,
(0, oo)) == exp(-_b * x**_a)
assert IMT(factorial(_a / _b + s / _b) / (_a + s), s, x,
(-_a, oo)) == x**_a * exp(-x**_b)
def simp_pows(expr):
return simplify(powsimp(expand_mul(expr, deep=False),
force=True)).replace(exp_polar, exp)
# Now test the inverses of all direct transforms tested above
# Section 8.4.2
assert IMT(-1 / (nu + s), s, x, (-oo, None)) == x**nu * Heaviside(x - 1)
assert IMT(1 / (nu + s), s, x, (None, oo)) == x**nu * Heaviside(1 - x)
assert simp_pows(IMT(gamma(beta)*gamma(s)/gamma(s + beta), s, x, (0, oo))) \
== (1 - x)**(beta - 1)*Heaviside(1 - x)
assert simp_pows(IMT(gamma(beta)*gamma(1 - beta - s)/gamma(1 - s),
s, x, (-oo, None))) \
== (x - 1)**(beta - 1)*Heaviside(x - 1)
assert simp_pows(IMT(gamma(s)*gamma(rho - s)/gamma(rho), s, x, (0, None))) \
== (1/(x + 1))**rho
assert simp_pows(IMT(d**c*d**(s - 1)*sin(pi*c)
*gamma(s)*gamma(s + c)*gamma(1 - s)*gamma(1 - s - c)/pi,
s, x, (Max(-re(c), 0), Min(1 - re(c), 1)))) \
== (x**c - d**c)/(x - d)
assert simplify(IMT(1/sqrt(pi)*(-c/2)*gamma(s)*gamma((1 - c)/2 - s)
*gamma(-c/2 - s)/gamma(1 - c - s),
s, x, (0, -re(c)/2))) == \
(1 + sqrt(x + 1))**c
assert simplify(IMT(2**(a + 2*s)*b**(a + 2*s - 1)*gamma(s)*gamma(1 - a - 2*s)
/gamma(1 - a - s), s, x, (0, (-re(a) + 1)/2))) == \
b**(a - 1)*(sqrt(1 + x/b**2) + 1)**(a - 1)*(b**2*sqrt(1 + x/b**2) +
b**2 + x)/(b**2 + x)
assert simplify(IMT(-2**(c + 2*s)*c*b**(c + 2*s)*gamma(s)*gamma(-c - 2*s)
/ gamma(-c - s + 1), s, x, (0, -re(c)/2))) == \
b**c*(sqrt(1 + x/b**2) + 1)**c
# Section 8.4.5
assert IMT(24 / s**5, s, x, (0, oo)) == log(x)**4 * Heaviside(1 - x)
assert expand(IMT(6/s**4, s, x, (-oo, 0)), force=True) == \
log(x)**3*Heaviside(x - 1)
assert IMT(pi / (s * sin(pi * s)), s, x, (-1, 0)) == log(x + 1)
assert IMT(pi / (s * sin(pi * s / 2)), s, x, (-2, 0)) == log(x**2 + 1)
assert IMT(pi / (s * sin(2 * pi * s)), s, x,
(-S(1) / 2, 0)) == log(sqrt(x) + 1)
assert IMT(pi / (s * sin(pi * s)), s, x, (0, 1)) == log(1 + 1 / x)
# TODO
def mysimp(expr):
from sympy import expand, logcombine, powsimp
return expand(powsimp(logcombine(expr, force=True),
force=True,
deep=True),
force=True).replace(exp_polar, exp)
assert mysimp(mysimp(IMT(pi / (s * tan(pi * s)), s, x, (-1, 0)))) in [
log(1 - x) * Heaviside(1 - x) + log(x - 1) * Heaviside(x - 1),
log(x) * Heaviside(x - 1) + log(1 - 1 / x) * Heaviside(x - 1) +
log(-x + 1) * Heaviside(-x + 1)
]
# test passing cot
assert mysimp(IMT(pi * cot(pi * s) / s, s, x, (0, 1))) in [
log(1 / x - 1) * Heaviside(1 - x) + log(1 - 1 / x) * Heaviside(x - 1),
-log(x) * Heaviside(-x + 1) + log(1 - 1 / x) * Heaviside(x - 1) +
log(-x + 1) * Heaviside(-x + 1),
]
# 8.4.14
assert IMT(-gamma(s + S(1)/2)/(sqrt(pi)*s), s, x, (-S(1)/2, 0)) == \
erf(sqrt(x))
# 8.4.19
assert simplify(IMT(gamma(a/2 + s)/gamma(a/2 - s + 1), s, x, (-re(a)/2, S(3)/4))) \
== besselj(a, 2*sqrt(x))
assert simplify(IMT(2**a*gamma(S(1)/2 - 2*s)*gamma(s + (a + 1)/2)
/ (gamma(1 - s - a/2)*gamma(1 - 2*s + a)),
s, x, (-(re(a) + 1)/2, S(1)/4))) == \
sin(sqrt(x))*besselj(a, sqrt(x))
assert simplify(IMT(2**a*gamma(a/2 + s)*gamma(S(1)/2 - 2*s)
/ (gamma(S(1)/2 - s - a/2)*gamma(1 - 2*s + a)),
s, x, (-re(a)/2, S(1)/4))) == \
cos(sqrt(x))*besselj(a, sqrt(x))
# TODO this comes out as an amazing mess, but simplifies nicely
assert simplify(IMT(gamma(a + s)*gamma(S(1)/2 - s)
/ (sqrt(pi)*gamma(1 - s)*gamma(1 + a - s)),
s, x, (-re(a), S(1)/2))) == \
besselj(a, sqrt(x))**2
assert simplify(IMT(gamma(s)*gamma(S(1)/2 - s)
/ (sqrt(pi)*gamma(1 - s - a)*gamma(1 + a - s)),
s, x, (0, S(1)/2))) == \
besselj(-a, sqrt(x))*besselj(a, sqrt(x))
assert simplify(IMT(4**s*gamma(-2*s + 1)*gamma(a/2 + b/2 + s)
/ (gamma(-a/2 + b/2 - s + 1)*gamma(a/2 - b/2 - s + 1)
*gamma(a/2 + b/2 - s + 1)),
s, x, (-(re(a) + re(b))/2, S(1)/2))) == \
besselj(a, sqrt(x))*besselj(b, sqrt(x))
# Section 8.4.20
# TODO this can be further simplified!
assert simplify(IMT(-2**(2*s)*cos(pi*a/2 - pi*b/2 + pi*s)*gamma(-2*s + 1) *
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)),
s, x,
(Max(-re(a)/2 - re(b)/2, -re(a)/2 + re(b)/2), S(1)/2))) == \
besselj(a, sqrt(x))*-(besselj(-b, sqrt(x)) -
besselj(b, sqrt(x))*cos(pi*b))/sin(pi*b)
# TODO more
# for coverage
assert IMT(pi / cos(pi * s), s, x, (0, S(1) / 2)) == sqrt(x) / (x + 1)
from sage.all import SR
from sage.calculus.functional import taylor
from sage.calculus.var import var
from sage.rings.arith import xgcd
from sage.rings.laurent_series_ring import LaurentSeriesRing
from sage.rings.rational_field import QQ
from sage.rings.qqbar import QQbar
from sage.rings.infinity import infinity
from sympy import Poly, Point, Segment, Polygon, RootOf, sqrt, S
# every example will be over QQ[x,y]. consider putting in setup?
R = QQ['x,y']
S = QQ['t']
x,y = R.gens()
t = S.gens()
class TestNewtonPolygon(unittest.TestCase):
def test_segment(self):
H = y + x
self.assertEqual(newton_polygon(H),
[[(0,1),(1,0)]])
H = y**2 + x**2
self.assertEqual(newton_polygon(H),
[[(0,2),(2,0)]])
def test_general_segment(self):
H = y**2 + x**4
self.assertEqual(newton_polygon(H),
def test_cosine_transform():
from sympy import Si, Ci
t = symbols("t")
w = symbols("w")
a = symbols("a")
f = Function("f")
# Test unevaluated form
assert cosine_transform(f(t), t, w) == CosineTransform(f(t), t, w)
assert inverse_cosine_transform(
f(w), w, t) == InverseCosineTransform(f(w), w, t)
assert cosine_transform(1/sqrt(t), t, w) == 1/sqrt(w)
assert inverse_cosine_transform(1/sqrt(w), w, t) == 1/sqrt(t)
assert cosine_transform(1/(
a**2 + t**2), t, w) == sqrt(2)*sqrt(pi)*exp(-a*w)/(2*a)
assert cosine_transform(t**(
-a), t, w) == 2**(-a + S(1)/2)*w**(a - 1)*gamma((-a + 1)/2)/gamma(a/2)
assert inverse_cosine_transform(2**(-a + S(
1)/2)*w**(a - 1)*gamma(-a/2 + S(1)/2)/gamma(a/2), w, t) == t**(-a)
assert cosine_transform(
exp(-a*t), t, w) == sqrt(2)*a/(sqrt(pi)*(a**2 + w**2))
assert inverse_cosine_transform(
sqrt(2)*a/(sqrt(pi)*(a**2 + w**2)), w, t) == exp(-a*t)
assert cosine_transform(exp(-a*sqrt(t))*cos(a*sqrt(
t)), t, w) == a*exp(-a**2/(2*w))/(2*w**(S(3)/2))
assert cosine_transform(1/(a + t), t, w) == sqrt(2)*(
(-2*Si(a*w) + pi)*sin(a*w)/2 - cos(a*w)*Ci(a*w))/sqrt(pi)
assert inverse_cosine_transform(sqrt(2)*meijerg(((S(1)/2, 0), ()), (
(S(1)/2, 0, 0), (S(1)/2,)), a**2*w**2/4)/(2*pi), w, t) == 1/(a + t)
assert cosine_transform(1/sqrt(a**2 + t**2), t, w) == sqrt(2)*meijerg(
((S(1)/2,), ()), ((0, 0), (S(1)/2,)), a**2*w**2/4)/(2*sqrt(pi))
assert inverse_cosine_transform(sqrt(2)*meijerg(((S(1)/2,), ()), ((0, 0), (S(1)/2,)), a**2*w**2/4)/(2*sqrt(pi)), w, t) == 1/(t*sqrt(a**2/t**2 + 1))
def test_issue_5164():
assert limit(x**0.5, x, oo) == oo**0.5 is oo
assert limit(x**0.5, x, 16) == S(16)**0.5
assert limit(x**0.5, x, 0) == 0
assert limit(x**(-0.5), x, oo) == 0
assert limit(x**(-0.5), x, 4) == S(4)**(-0.5)
def test_roach_fail():
assert can_do([
-S(3) / 2,
], [-S(1) / 2, S(1) / 2]) # shine-integral
assert can_do([-S(3) / 2, -S(1) / 2], [2]) # elliptic integrals
assert can_do([-S(1) / 2, 1], [S(1) / 4, S(1) / 2, S(3) / 4]) # PFDD
assert can_do([S(3) / 2], [S(5) / 2, 5]) # polylog
assert can_do([-S(1) / 2, S(1) / 2, 1],
[S(3) / 2, S(5) / 2]) # polylog, pfdd
assert can_do([1, 2, 3], [S(1) / 2, 4]) # XXX ?
assert can_do([S(1) / 2], [-S(1) / 3, -S(1) / 2, -S(2) / 3]) # PFDD ?
def test_prudnikov_fail_3F2():
assert can_do([a, a + S(1) / 3, a + S(2) / 3], [S(1) / 3, S(2) / 3])
assert can_do([a, a + S(1) / 3, a + S(2) / 3], [S(2) / 3, S(4) / 3])
assert can_do([a, a + S(1) / 3, a + S(2) / 3], [S(4) / 3, S(5) / 3])
# page 421
assert can_do([a, a + S(1) / 3, a + S(2) / 3],
[3 * a / 2, (3 * a + 1) / 2])
# pages 422 ...
assert can_do([-S.Half, S.Half, S.Half], [1, 1]) # elliptic integrals
assert can_do([-S.Half, S.Half, 1], [S(3) / 2, S(3) / 2])
# TODO LOTS more
# PFDD
assert can_do([S(1) / 8, S(3) / 8, 1], [S(9) / 8, S(11) / 8])
assert can_do([S(1) / 8, S(5) / 8, 1], [S(9) / 8, S(13) / 8])
assert can_do([S(1) / 8, S(7) / 8, 1], [S(9) / 8, S(15) / 8])
assert can_do([S(1) / 6, S(1) / 3, 1], [S(7) / 6, S(4) / 3])
assert can_do([S(1) / 6, S(2) / 3, 1], [S(7) / 6, S(5) / 3])
assert can_do([S(1) / 6, S(2) / 3, 1], [S(5) / 3, S(13) / 6])
assert can_do([S.Half, 1, 1], [S(1) / 4, S(3) / 4])
def test_prudnikov_11():
# 7.15
assert can_do([a, a + S.Half], [2 * a, b, 2 * a - b])
assert can_do([a, a + S.Half], [S(3) / 2, 2 * a, 2 * a - S(1) / 2])
assert can_do([S(1) / 4, S(3) / 4], [S(1) / 2, S(1) / 2, 1])
assert can_do([S(5) / 4, S(3) / 4], [S(3) / 2, S(1) / 2, 2])
assert can_do([S(5) / 4, S(3) / 4], [S(3) / 2, S(3) / 2, 1])
assert can_do([S(5) / 4, S(7) / 4], [S(3) / 2, S(5) / 2, 2])
def test_prudnikov_12():
# 7.16
assert can_do([], [a, a + S.Half, 2 * a],
False) # branches only agree for some z!
assert can_do([], [a, a + S.Half, 2 * a + 1], False) # dito
assert can_do([], [S.Half, a, a + S.Half])
assert can_do([], [S(3) / 2, a, a + S.Half])
assert can_do([], [S(1) / 4, S(1) / 2, S(3) / 4])
assert can_do([], [S(1) / 2, S(1) / 2, 1])
assert can_do([], [S(1) / 2, S(3) / 2, 1])
assert can_do([], [S(3) / 4, S(3) / 2, S(5) / 4])
assert can_do([], [1, 1, S(3) / 2])
assert can_do([], [1, 2, S(3) / 2])
assert can_do([], [1, S(3) / 2, S(3) / 2])
assert can_do([], [S(5) / 4, S(3) / 2, S(7) / 4])
assert can_do([], [2, S(3) / 2, S(3) / 2])
def test_prudnikov_9():
# 7.13.1 [we have a general formula ... so this is a bit pointless]
for i in range(9):
assert can_do([], [(S(i) + 1) / 2])
for i in range(5):
assert can_do([], [-(2 * S(i) + 1) / 2])
def randrat():
""" Steer clear of integers. """
return S(randrange(25) + 10) / 50
def test_shifted_sum():
from sympy import simplify
assert simplify(hyperexpand(z**4*hyper([2], [3, S('3/2')], -z**2))) \
== -S(1)/2 + cos(2*z)/2 + z*sin(2*z) - z**2*cos(2*z)
def test_to_mpmath():
assert sqrt(3)._to_mpmath(20)._mpf_ == (0, long(908093), -19, 20)
assert S(3.2)._to_mpmath(20)._mpf_ == (0, long(838861), -18, 20)
def test_prudnikov_fail_other():
# 7.11.2
assert can_do([a], [a + 1]) # lowergamma ... why??
# 7.12.1
assert can_do([1, a], [b, 1 - 2 * a + b]) # ???
# 7.14.2
assert can_do([-S(1) / 2], [S(1) / 2, S(1) / 2]) # shine-integral shi
assert can_do([-S(1) / 2], [S(1) / 2, 1]) # poly-log
assert can_do([1], [S(1) / 2, S(1) / 2]) # poly-log
assert can_do([S(1) / 4], [S(1) / 2, S(5) / 4]) # PFDD
assert can_do([S(3) / 4], [S(3) / 2, S(7) / 4]) # PFDD
assert can_do([1], [S(1) / 4, S(3) / 4]) # PFDD
assert can_do([1], [S(3) / 4, S(5) / 4]) # PFDD
assert can_do([1], [S(5) / 4, S(7) / 4]) # PFDD
# TODO LOTS more
# 7.15.2
assert can_do([S(1) / 2, 1], [S(3) / 4, S(5) / 4, S(3) / 2]) # PFDD
assert can_do([S(1) / 2, 1], [S(7) / 4, S(5) / 4, S(3) / 2]) # PFDD
assert can_do([1, 1], [S(3) / 2, 2, 2]) # cosh-integral chi
# 7.16.1
assert can_do([], [S(1) / 3, S(2 / 3)]) # PFDD
assert can_do([], [S(2) / 3, S(4 / 3)]) # PFDD
assert can_do([], [S(5) / 3, S(4 / 3)]) # PFDD
# XXX this does not *evaluate* right??
assert can_do([], [a, a + S.Half, 2 * a - 1])
def test_plane():
x, y, z, u, v = symbols("x y z u v", real=True)
p1 = Point3D(0, 0, 0)
p2 = Point3D(1, 1, 1)
p3 = Point3D(1, 2, 3)
pl3 = Plane(p1, p2, p3)
pl4 = Plane(p1, normal_vector=(1, 1, 1))
pl4b = Plane(p1, p2)
pl5 = Plane(p3, normal_vector=(1, 2, 3))
pl6 = Plane(Point3D(2, 3, 7), normal_vector=(2, 2, 2))
pl7 = Plane(Point3D(1, -5, -6), normal_vector=(1, -2, 1))
pl8 = Plane(p1, normal_vector=(0, 0, 1))
pl9 = Plane(p1, normal_vector=(0, 12, 0))
pl10 = Plane(p1, normal_vector=(-2, 0, 0))
pl11 = Plane(p2, normal_vector=(0, 0, 1))
l1 = Line3D(Point3D(5, 0, 0), Point3D(1, -1, 1))
l2 = Line3D(Point3D(0, -2, 0), Point3D(3, 1, 1))
l3 = Line3D(Point3D(0, -1, 0), Point3D(5, -1, 9))
assert Plane(p1, p2, p3) != Plane(p1, p3, p2)
assert Plane(p1, p2, p3).is_coplanar(Plane(p1, p3, p2))
assert pl3 == Plane(Point3D(0, 0, 0), normal_vector=(1, -2, 1))
assert pl3 != pl4
assert pl4 == pl4b
assert pl5 == Plane(Point3D(1, 2, 3), normal_vector=(1, 2, 3))
assert pl5.equation(x, y, z) == x + 2 * y + 3 * z - 14
assert pl3.equation(x, y, z) == x - 2 * y + z
assert pl3.p1 == p1
assert pl4.p1 == p1
assert pl5.p1 == p3
assert pl4.normal_vector == (1, 1, 1)
assert pl5.normal_vector == (1, 2, 3)
assert p1 in pl3
assert p1 in pl4
assert p3 in pl5
assert pl3.projection(Point(0, 0)) == p1
p = pl3.projection(Point3D(1, 1, 0))
assert p == Point3D(Rational(7, 6), Rational(2, 3), Rational(1, 6))
assert p in pl3
l = pl3.projection_line(Line(Point(0, 0), Point(1, 1)))
assert l == Line3D(
Point3D(0, 0, 0), Point3D(Rational(7, 6), Rational(2, 3), Rational(1, 6))
)
assert l in pl3
# get a segment that does not intersect the plane which is also
# parallel to pl3's normal veector
t = Dummy()
r = pl3.random_point()
a = pl3.perpendicular_line(r).arbitrary_point(t)
s = Segment3D(a.subs(t, 1), a.subs(t, 2))
assert s.p1 not in pl3 and s.p2 not in pl3
assert pl3.projection_line(s).equals(r)
assert pl3.projection_line(Segment(Point(1, 0), Point(1, 1))) == Segment3D(
Point3D(Rational(5, 6), Rational(1, 3), Rational(-1, 6)),
Point3D(Rational(7, 6), Rational(2, 3), Rational(1, 6)),
)
assert pl6.projection_line(Ray(Point(1, 0), Point(1, 1))) == Ray3D(
Point3D(Rational(14, 3), Rational(11, 3), Rational(11, 3)),
Point3D(Rational(13, 3), Rational(13, 3), Rational(10, 3)),
)
assert pl3.perpendicular_line(r.args) == pl3.perpendicular_line(r)
assert pl3.is_parallel(pl6) is False
assert pl4.is_parallel(pl6)
assert pl6.is_parallel(l1) is False
assert pl3.is_perpendicular(pl6)
assert pl4.is_perpendicular(pl7)
assert pl6.is_perpendicular(pl7)
assert pl6.is_perpendicular(l1) is False
assert pl6.distance(pl6.arbitrary_point(u, v)) == 0
assert pl7.distance(pl7.arbitrary_point(u, v)) == 0
assert pl6.distance(pl6.arbitrary_point(t)) == 0
assert pl7.distance(pl7.arbitrary_point(t)) == 0
assert pl6.p1.distance(pl6.arbitrary_point(t)).simplify() == 1
assert pl7.p1.distance(pl7.arbitrary_point(t)).simplify() == 1
assert pl3.arbitrary_point(t) == Point3D(
-sqrt(30) * sin(t) / 30 + 2 * sqrt(5) * cos(t) / 5,
sqrt(30) * sin(t) / 15 + sqrt(5) * cos(t) / 5,
sqrt(30) * sin(t) / 6,
)
assert pl3.arbitrary_point(u, v) == Point3D(2 * u - v, u + 2 * v, 5 * v)
assert pl7.distance(Point3D(1, 3, 5)) == 5 * sqrt(6) / 6
assert pl6.distance(Point3D(0, 0, 0)) == 4 * sqrt(3)
assert pl6.distance(pl6.p1) == 0
assert pl7.distance(pl6) == 0
assert pl7.distance(l1) == 0
assert (
pl6.distance(Segment3D(Point3D(2, 3, 1), Point3D(1, 3, 4)))
== pl6.distance(Point3D(1, 3, 4))
== 4 * sqrt(3) / 3
)
assert (
pl6.distance(Segment3D(Point3D(1, 3, 4), Point3D(0, 3, 7)))
== pl6.distance(Point3D(0, 3, 7))
== 2 * sqrt(3) / 3
)
assert pl6.distance(Segment3D(Point3D(0, 3, 7), Point3D(-1, 3, 10))) == 0
assert pl6.distance(Segment3D(Point3D(-1, 3, 10), Point3D(-2, 3, 13))) == 0
assert (
pl6.distance(Segment3D(Point3D(-2, 3, 13), Point3D(-3, 3, 16)))
== pl6.distance(Point3D(-2, 3, 13))
== 2 * sqrt(3) / 3
)
assert pl6.distance(Plane(Point3D(5, 5, 5), normal_vector=(8, 8, 8))) == sqrt(3)
assert (
pl6.distance(Ray3D(Point3D(1, 3, 4), direction_ratio=[1, 0, -3]))
== 4 * sqrt(3) / 3
)
assert pl6.distance(Ray3D(Point3D(2, 3, 1), direction_ratio=[-1, 0, 3])) == 0
assert pl6.angle_between(pl3) == pi / 2
assert pl6.angle_between(pl6) == 0
assert pl6.angle_between(pl4) == 0
assert pl7.angle_between(Line3D(Point3D(2, 3, 5), Point3D(2, 4, 6))) == -asin(
sqrt(3) / 6
)
assert pl6.angle_between(Ray3D(Point3D(2, 4, 1), Point3D(6, 5, 3))) == asin(
sqrt(7) / 3
)
assert pl7.angle_between(Segment3D(Point3D(5, 6, 1), Point3D(1, 2, 4))) == asin(
7 * sqrt(246) / 246
)
assert are_coplanar(l1, l2, l3) is False
assert are_coplanar(l1) is False
assert are_coplanar(
Point3D(2, 7, 2), Point3D(0, 0, 2), Point3D(1, 1, 2), Point3D(1, 2, 2)
)
assert are_coplanar(Plane(p1, p2, p3), Plane(p1, p3, p2))
assert Plane.are_concurrent(pl3, pl4, pl5) is False
assert Plane.are_concurrent(pl6) is False
raises(ValueError, lambda: Plane.are_concurrent(Point3D(0, 0, 0)))
raises(ValueError, lambda: Plane((1, 2, 3), normal_vector=(0, 0, 0)))
assert pl3.parallel_plane(Point3D(1, 2, 5)) == Plane(
Point3D(1, 2, 5), normal_vector=(1, -2, 1)
)
# perpendicular_plane
p = Plane((0, 0, 0), (1, 0, 0))
# default
assert p.perpendicular_plane() == Plane(Point3D(0, 0, 0), (0, 1, 0))
# 1 pt
assert p.perpendicular_plane(Point3D(1, 0, 1)) == Plane(Point3D(1, 0, 1), (0, 1, 0))
# pts as tuples
assert p.perpendicular_plane((1, 0, 1), (1, 1, 1)) == Plane(
Point3D(1, 0, 1), (0, 0, -1)
)
a, b = Point3D(0, 0, 0), Point3D(0, 1, 0)
Z = (0, 0, 1)
p = Plane(a, normal_vector=Z)
# case 4
assert p.perpendicular_plane(a, b) == Plane(a, (1, 0, 0))
n = Point3D(*Z)
# case 1
assert p.perpendicular_plane(a, n) == Plane(a, (-1, 0, 0))
# case 2
assert Plane(a, normal_vector=b.args).perpendicular_plane(a, a + b) == Plane(
Point3D(0, 0, 0), (1, 0, 0)
)
# case 1&3
assert Plane(b, normal_vector=Z).perpendicular_plane(b, b + n) == Plane(
Point3D(0, 1, 0), (-1, 0, 0)
)
# case 2&3
assert Plane(b, normal_vector=b.args).perpendicular_plane(n, n + b) == Plane(
Point3D(0, 0, 1), (1, 0, 0)
)
assert pl6.intersection(pl6) == [pl6]
assert pl4.intersection(pl4.p1) == [pl4.p1]
assert pl3.intersection(pl6) == [Line3D(Point3D(8, 4, 0), Point3D(2, 4, 6))]
assert pl3.intersection(Line3D(Point3D(1, 2, 4), Point3D(4, 4, 2))) == [
Point3D(2, Rational(8, 3), Rational(10, 3))
]
assert pl3.intersection(Plane(Point3D(6, 0, 0), normal_vector=(2, -5, 3))) == [
Line3D(Point3D(-24, -12, 0), Point3D(-25, -13, -1))
]
assert pl6.intersection(Ray3D(Point3D(2, 3, 1), Point3D(1, 3, 4))) == [
Point3D(-1, 3, 10)
]
assert pl6.intersection(Segment3D(Point3D(2, 3, 1), Point3D(1, 3, 4))) == []
assert pl7.intersection(Line(Point(2, 3), Point(4, 2))) == [
Point3D(Rational(13, 2), Rational(3, 4), 0)
]
r = Ray(Point(2, 3), Point(4, 2))
assert Plane((1, 2, 0), normal_vector=(0, 0, 1)).intersection(r) == [
Ray3D(Point(2, 3), Point(4, 2))
]
assert pl9.intersection(pl8) == [Line3D(Point3D(0, 0, 0), Point3D(12, 0, 0))]
assert pl10.intersection(pl11) == [Line3D(Point3D(0, 0, 1), Point3D(0, 2, 1))]
assert pl4.intersection(pl8) == [Line3D(Point3D(0, 0, 0), Point3D(1, -1, 0))]
assert pl11.intersection(pl8) == []
assert pl9.intersection(pl11) == [Line3D(Point3D(0, 0, 1), Point3D(12, 0, 1))]
assert pl9.intersection(pl4) == [Line3D(Point3D(0, 0, 0), Point3D(12, 0, -12))]
assert pl3.random_point() in pl3
# test geometrical entity using equals
assert pl4.intersection(pl4.p1)[0].equals(pl4.p1)
assert pl3.intersection(pl6)[0].equals(Line3D(Point3D(8, 4, 0), Point3D(2, 4, 6)))
pl8 = Plane((1, 2, 0), normal_vector=(0, 0, 1))
assert pl8.intersection(Line3D(p1, (1, 12, 0)))[0].equals(
Line((0, 0, 0), (0.1, 1.2, 0))
)
assert pl8.intersection(Ray3D(p1, (1, 12, 0)))[0].equals(Ray((0, 0, 0), (1, 12, 0)))
assert pl8.intersection(Segment3D(p1, (21, 1, 0)))[0].equals(
Segment3D(p1, (21, 1, 0))
)
assert pl8.intersection(Plane(p1, normal_vector=(0, 0, 112)))[0].equals(pl8)
assert pl8.intersection(Plane(p1, normal_vector=(0, 12, 0)))[0].equals(
Line3D(p1, direction_ratio=(112 * pi, 0, 0))
)
assert pl8.intersection(Plane(p1, normal_vector=(11, 0, 1)))[0].equals(
Line3D(p1, direction_ratio=(0, -11, 0))
)
assert pl8.intersection(Plane(p1, normal_vector=(1, 0, 11)))[0].equals(
Line3D(p1, direction_ratio=(0, 11, 0))
)
assert pl8.intersection(Plane(p1, normal_vector=(-1, -1, -11)))[0].equals(
Line3D(p1, direction_ratio=(1, -1, 0))
)
assert pl3.random_point() in pl3
assert len(pl8.intersection(Ray3D(Point3D(0, 2, 3), Point3D(1, 0, 3)))) == 0
# check if two plane are equals
assert pl6.intersection(pl6)[0].equals(pl6)
assert pl8.equals(Plane(p1, normal_vector=(0, 12, 0))) is False
assert pl8.equals(pl8)
assert pl8.equals(Plane(p1, normal_vector=(0, 0, -12)))
assert pl8.equals(Plane(p1, normal_vector=(0, 0, -12 * sqrt(3))))
# issue 8570
l2 = Line3D(
Point3D(
Rational(50000004459633, 5000000000000),
Rational(-891926590718643, 1000000000000000),
Rational(231800966893633, 100000000000000),
),
Point3D(
Rational(50000004459633, 50000000000000),
Rational(-222981647679771, 250000000000000),
Rational(231800966893633, 100000000000000),
),
)
p2 = Plane(
Point3D(
Rational(402775636372767, 100000000000000),
Rational(-97224357654973, 100000000000000),
Rational(216793600814789, 100000000000000),
),
(-S("9.00000087501922"), -S("4.81170658872543e-13"), S("0.0")),
)
assert str([i.n(2) for i in p2.intersection(l2)]) == "[Point3D(4.0, -0.89, 2.3)]"
def test_nan_inequality_raise_errors():
# See discussion in pull request #7776. We test inequalities with
# a set including examples of various classes.
for q in (x, S(0), S(10), S(1) / 3, pi, S(1.3), oo, -oo, nan):
assert_all_ineq_raise_TypeError(q, nan)
def test_mellin_transform():
from sympy import Max, Min
MT = mellin_transform
bpos = symbols('b', positive=True)
# 8.4.2
assert MT(x**nu*Heaviside(x - 1), x, s) == \
(-1/(nu + s), (-oo, -re(nu)), True)
assert MT(x**nu*Heaviside(1 - x), x, s) == \
(1/(nu + s), (-re(nu), oo), True)
assert MT((1 - x)**(beta - 1)*Heaviside(1 - x), x, s) == \
(gamma(beta)*gamma(s)/gamma(beta + s), (0, oo), re(-beta) < 0)
assert MT((x - 1)**(beta - 1)*Heaviside(x - 1), x, s) == \
(gamma(beta)*gamma(1 - beta - s)/gamma(1 - s),
(-oo, -re(beta) + 1), re(-beta) < 0)
assert MT((1 + x)**(-rho), x, s) == \
(gamma(s)*gamma(rho - s)/gamma(rho), (0, re(rho)), True)
# TODO also the conditions should be simplified
assert MT(abs(1 - x)**(-rho), x, s) == (
2*sin(pi*rho/2)*gamma(1 - rho)*
cos(pi*(rho/2 - s))*gamma(s)*gamma(rho-s)/pi,
(0, re(rho)), And(re(rho) - 1 < 0, re(rho) < 1))
mt = MT((1 - x)**(beta - 1)*Heaviside(1 - x)
+ a*(x - 1)**(beta - 1)*Heaviside(x - 1), x, s)
assert mt[1], mt[2] == ((0, -re(beta) + 1), True)
assert MT((x**a - b**a)/(x - b), x, s)[0] == \
pi*b**(a + s - 1)*sin(pi*a)/(sin(pi*s)*sin(pi*(a + s)))
assert MT((x**a - bpos**a)/(x - bpos), x, s) == \
(pi*bpos**(a + s - 1)*sin(pi*a)/(sin(pi*s)*sin(pi*(a + s))),
(Max(-re(a), 0), Min(1 - re(a), 1)), True)
expr = (sqrt(x + b**2) + b)**a
assert MT(expr.subs(b, bpos), x, s) == \
(-a*(2*bpos)**(a + 2*s)*gamma(s)*gamma(-a - 2*s)/gamma(-a - s + 1),
(0, -re(a)/2), True)
expr = (sqrt(x + b**2) + b)**a/sqrt(x + b**2)
assert MT(expr.subs(b, bpos), x, s) == \
(2**(a + 2*s)*bpos**(a + 2*s - 1)*gamma(s)
*gamma(1 - a - 2*s)/gamma(1 - a - s),
(0, -re(a)/2 + S(1)/2), True)
# 8.4.2
assert MT(exp(-x), x, s) == (gamma(s), (0, oo), True)
assert MT(exp(-1/x), x, s) == (gamma(-s), (-oo, 0), True)
# 8.4.5
assert MT(log(x)**4*Heaviside(1 - x), x, s) == (24/s**5, (0, oo), True)
assert MT(log(x)**3*Heaviside(x - 1), x, s) == (6/s**4, (-oo, 0), True)
assert MT(log(x + 1), x, s) == (pi/(s*sin(pi*s)), (-1, 0), True)
assert MT(log(1/x + 1), x, s) == (pi/(s*sin(pi*s)), (0, 1), True)
assert MT(log(abs(1 - x)), x, s) == (pi/(s*tan(pi*s)), (-1, 0), True)
assert MT(log(abs(1 - 1/x)), x, s) == (pi/(s*tan(pi*s)), (0, 1), True)
# TODO we cannot currently do these (needs summation of 3F2(-1))
# this also implies that they cannot be written as a single g-function
# (although this is possible)
mt = MT(log(x)/(x + 1), x, s)
assert mt[1:] == ((0, 1), True)
assert not hyperexpand(mt[0], allow_hyper=True).has(meijerg)
mt = MT(log(x)**2/(x + 1), x, s)
assert mt[1:] == ((0, 1), True)
assert not hyperexpand(mt[0], allow_hyper=True).has(meijerg)
mt = MT(log(x)/(x + 1)**2, x, s)
assert mt[1:] == ((0, 2), True)
assert not hyperexpand(mt[0], allow_hyper=True).has(meijerg)
# 8.4.14
assert MT(erf(sqrt(x)), x, s) == \
(-gamma(s + S(1)/2)/(sqrt(pi)*s), (-S(1)/2, 0), True)
def sdm_groebner(G, NF, O, K, extended=False):
"""
Compute a minimal standard basis of ``G`` with respect to order ``O``.
The algorithm uses a normal form ``NF``, for example ``sdm_nf_mora``.
The ground field is assumed to be ``K``, and monomials ordered according
to ``O``.
Let `N` denote the submodule generated by elements of `G`. A standard
basis for `N` is a subset `S` of `N`, such that `in(S) = in(N)`, where for
any subset `X` of `F`, `in(X)` denotes the submodule generated by the
initial forms of elements of `X`. [SCA, defn 2.3.2]
A standard basis is called minimal if no subset of it is a standard basis.
One may show that standard bases are always generating sets.
Minimal standard bases are not unique. This algorithm computes a
deterministic result, depending on the particular order of `G`.
If ``extended=True``, also compute the transition matrix from the initial
generators to the groebner basis. That is, return a list of coefficient
vectors, expressing the elements of the groebner basis in terms of the
elements of ``G``.
This functions implements the "sugar" strategy, see
Giovini et al: "One sugar cube, please" OR Selection strategies in
Buchberger algorithm.
"""
# The critical pair set.
# A critical pair is stored as (i, j, s, t) where (i, j) defines the pair
# (by indexing S), s is the sugar of the pair, and t is the lcm of their
# leading monomials.
P = []
# The eventual standard basis.
S = []
Sugars = []
def Ssugar(i, j):
"""Compute the sugar of the S-poly corresponding to (i, j)."""
LMi = sdm_LM(S[i])
LMj = sdm_LM(S[j])
return max(Sugars[i] - sdm_monomial_deg(LMi),
Sugars[j] - sdm_monomial_deg(LMj)) \
+ sdm_monomial_deg(sdm_monomial_lcm(LMi, LMj))
ourkey = lambda p: (p[2], O(p[3]), p[1])
def update(f, sugar, P):
"""Add f with sugar ``sugar`` to S, update P."""
if not f:
return P
k = len(S)
S.append(f)
Sugars.append(sugar)
LMf = sdm_LM(f)
def removethis(pair):
i, j, s, t = pair
if LMf[0] != t[0]:
return False
tik = sdm_monomial_lcm(LMf, sdm_LM(S[i]))
tjk = sdm_monomial_lcm(LMf, sdm_LM(S[j]))
return tik != t and tjk != t and sdm_monomial_divides(tik, t) and \
sdm_monomial_divides(tjk, t)
# apply the chain criterion
P = [p for p in P if not removethis(p)]
# new-pair set
N = [(i, k, Ssugar(i, k), sdm_monomial_lcm(LMf, sdm_LM(S[i])))
for i in range(k) if LMf[0] == sdm_LM(S[i])[0]]
# TODO apply the product criterion?
N.sort(key=ourkey)
remove = set()
for i, p in enumerate(N):
for j in range(i + 1, len(N)):
if sdm_monomial_divides(p[3], N[j][3]):
remove.add(j)
# TODO mergesort?
P.extend(reversed([p for i, p in enumerate(N) if not i in remove]))
P.sort(key=ourkey, reverse=True)
# NOTE reverse-sort, because we want to pop from the end
return P
# Figure out the number of generators in the ground ring.
try:
# NOTE: we look for the first non-zero vector, take its first monomial
# the number of generators in the ring is one less than the length
# (since the zeroth entry is for the module generators)
numgens = len(next(x[0] for x in G if x)[0]) - 1
except StopIteration:
# No non-zero elements in G ...
if extended:
return [], []
return []
# This list will store expressions of the elements of S in terms of the
# initial generators
coefficients = []
# First add all the elements of G to S
for i, f in enumerate(G):
P = update(f, sdm_deg(f), P)
if extended and f:
coefficients.append(sdm_from_dict({(i,) + (0,)*numgens: K(1)}, O))
# Now carry out the buchberger algorithm.
while P:
i, j, s, t = P.pop()
f, sf, g, sg = S[i], Sugars[i], S[j], Sugars[j]
if extended:
sp, coeff = sdm_spoly(f, g, O, K,
phantom=(coefficients[i], coefficients[j]))
h, hcoeff = NF(sp, S, O, K, phantom=(coeff, coefficients))
if h:
coefficients.append(hcoeff)
else:
h = NF(sdm_spoly(f, g, O, K), S, O, K)
P = update(h, Ssugar(i, j), P)
# Finally interreduce the standard basis.
# (TODO again, better data structures)
S = set((tuple(f), i) for i, f in enumerate(S))
for (a, ai), (b, bi) in permutations(S, 2):
A = sdm_LM(a)
B = sdm_LM(b)
if sdm_monomial_divides(A, B) and (b, bi) in S and (a, ai) in S:
S.remove((b, bi))
L = sorted(((list(f), i) for f, i in S), key=lambda p: O(sdm_LM(p[0])),
reverse=True)
res = [x[0] for x in L]
if extended:
return res, [coefficients[i] for _, i in L]
return res
def test_mellin_transform_bessel():
from sympy import Max, Min, hyper, meijerg
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, S(3)/4), True)
assert MT(sin(sqrt(x))*besselj(a, sqrt(x)), x, s) == \
(2**a*gamma(-2*s + S(1)/2)*gamma(a/2 + s + S(1)/2)/(
gamma(-a/2 - s + 1)*gamma(a - 2*s + 1)), (
-re(a)/2 - S(1)/2, S(1)/4), True)
assert MT(cos(sqrt(x))*besselj(a, sqrt(x)), x, s) == \
(2**a*gamma(a/2 + s)*gamma(-2*s + S(1)/2)/(
gamma(-a/2 - s + S(1)/2)*gamma(a - 2*s + 1)), (
-re(a)/2, S(1)/4), True)
assert MT(besselj(a, sqrt(x))**2, x, s) == \
(gamma(a + s)*gamma(S(1)/2 - s)
/ (sqrt(pi)*gamma(1 - s)*gamma(1 + a - s)),
(-re(a), S(1)/2), True)
assert MT(besselj(a, sqrt(x))*besselj(-a, sqrt(x)), x, s) == \
(gamma(s)*gamma(S(1)/2 - s)
/ (sqrt(pi)*gamma(1 - a - s)*gamma(1 + a - s)),
(0, S(1)/2), 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(1)/2)
/ (sqrt(pi)*gamma(S(3)/2 - s)*gamma(a - s + S(1)/2)),
(S(1)/2 - re(a), S(1)/2), 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(1)/2), True)
assert MT(besselj(a, sqrt(x))**2 + besselj(-a, sqrt(x))**2, x, s)[1:] == \
((Max(re(a), -re(a)), S(1)/2), 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), S(3)/4), True)
assert MT(sin(sqrt(x))*bessely(a, sqrt(x)), x, s) == \
(-4**s*sin(pi*(a/2 - s))*gamma(S(1)/2 - 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), S(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(1)/2 - 2*s)
/ (sqrt(pi)*gamma(S(1)/2 - s - a/2)*gamma(S(1)/2 - s + a/2)),
(Max(-re(a)/2, re(a)/2), S(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(1)/2 - s)
/ (pi**S('3/2')*gamma(1 + a - s)),
(Max(-re(a), 0), S(1)/2), 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(1)/2), 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(1)/2), 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(1)/2)/(2*sqrt(pi)*gamma(a - s + 1)),
(Max(-re(a), 0), S(1)/2), 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(1)/2), True)
# TODO products of besselk are a mess
mt = MT(exp(-x / 2) * besselk(a, x / 2), x, s)
mt0 = combsimp((trigsimp(combsimp(mt[0].expand(func=True)))))
assert mt0 == 2 * pi**(S(3) / 2) * cos(pi * s) * gamma(-s + S(1) / 2) / (
(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_union():
N = Normal('N', 3, 2)
assert simplify(P(N**2 - N > 2)) == \
-erf(sqrt(2))/2 - erfc(sqrt(2)/4)/2 + S(3)/2
assert simplify(P(N**2 - 4 > 0)) == \
-erf(5*sqrt(2)/4)/2 - erfc(sqrt(2)/4)/2 + S(3)/2
def setup(self):
super().setup()
speed = min(150, 25 * self.level)
self.fy += S('%d * t' % speed)
def setup(self):
super().setup()
speed = min(50, 10 * self.level)
self.fy += S('%d * t' % speed)
self.fx += S('%d * t' % speed)
def test_factorial2():
n = Symbol('n', integer=True)
assert factorial2(-1) == 1
assert factorial2(0) == 1
assert factorial2(7) == 105
assert factorial2(8) == 384
# The following is exhaustive
tt = Symbol('tt', integer=True, nonnegative=True)
tte = Symbol('tte', even=True, nonnegative=True)
tpe = Symbol('tpe', even=True, positive=True)
tto = Symbol('tto', odd=True, nonnegative=True)
tf = Symbol('tf', integer=True, nonnegative=False)
tfe = Symbol('tfe', even=True, nonnegative=False)
tfo = Symbol('tfo', odd=True, nonnegative=False)
ft = Symbol('ft', integer=False, nonnegative=True)
ff = Symbol('ff', integer=False, nonnegative=False)
fn = Symbol('fn', integer=False)
nt = Symbol('nt', nonnegative=True)
nf = Symbol('nf', nonnegative=False)
nn = Symbol('nn')
#Solves and Fixes Issue #10388 - This is the updated test for the same solved issue
raises (ValueError, lambda: factorial2(oo))
raises (ValueError, lambda: factorial2(S(5)/2))
assert factorial2(n).is_integer is None
assert factorial2(tt - 1).is_integer
assert factorial2(tte - 1).is_integer
assert factorial2(tpe - 3).is_integer
assert factorial2(tto - 4).is_integer
assert factorial2(tto - 2).is_integer
assert factorial2(tf).is_integer is None
assert factorial2(tfe).is_integer is None
assert factorial2(tfo).is_integer is None
assert factorial2(ft).is_integer is None
assert factorial2(ff).is_integer is None
assert factorial2(fn).is_integer is None
assert factorial2(nt).is_integer is None
assert factorial2(nf).is_integer is None
assert factorial2(nn).is_integer is None
assert factorial2(n).is_positive is None
assert factorial2(tt - 1).is_positive is True
assert factorial2(tte - 1).is_positive is True
assert factorial2(tpe - 3).is_positive is True
assert factorial2(tpe - 1).is_positive is True
assert factorial2(tto - 2).is_positive is True
assert factorial2(tto - 1).is_positive is True
assert factorial2(tf).is_positive is None
assert factorial2(tfe).is_positive is None
assert factorial2(tfo).is_positive is None
assert factorial2(ft).is_positive is None
assert factorial2(ff).is_positive is None
assert factorial2(fn).is_positive is None
assert factorial2(nt).is_positive is None
assert factorial2(nf).is_positive is None
assert factorial2(nn).is_positive is None
assert factorial2(tt).is_even is None
assert factorial2(tt).is_odd is None
assert factorial2(tte).is_even is None
assert factorial2(tte).is_odd is None
assert factorial2(tte + 2).is_even is True
assert factorial2(tpe).is_even is True
assert factorial2(tto).is_odd is True
assert factorial2(tf).is_even is None
assert factorial2(tf).is_odd is None
assert factorial2(tfe).is_even is None
assert factorial2(tfe).is_odd is None
assert factorial2(tfo).is_even is False
assert factorial2(tfo).is_odd is None
def test_factor_and_dimension_with_Abs():
v_w1 = Quantity('v_w1', length / time, S(3) / 2 * meter / second)
expr = v_w1 - Abs(v_w1)
assert (0, length / time) == Quantity._collect_factor_and_dimension(expr)
def sdm_groebner(G, NF, O, K):
"""
Compute a minimal standard basis of ``G`` with respect to order ``O``.
The algorithm uses a normal form ``NF``, for example ``sdm_nf_mora``.
The ground field is assumed to be ``K``, and monomials ordered according
to ``O``.
Let `N` denote the submodule generated by elements of `G`. A standard
basis for `N` is a subset `S` of `N`, such that `in(S) = in(N)`, where for
any subset `X` of `F`, `in(X)` denotes the submodule generated by the
initial forms of elements of `X`. [SCA, defn 2.3.2]
A standard basis is called minimal if no subset of it is a standard basis.
One may show that standard bases are always generating sets.
Minimal standard bases are not unique. This algorithm computes a
deterministic result, depending on the particular order of `G`.
See [SCA, algorithm 2.3.8, and remark 1.6.3].
"""
# First compute a standard basis
S = [f for f in G if f]
P = list(combinations(S, 2))
def prune(P, S, h):
"""
Prune the pair-set by applying the chain criterion
[SCA, remark 2.5.11].
"""
remove = set()
retain = set()
for (a, b, c) in permutations(S, 3):
A = sdm_LM(a)
B = sdm_LM(b)
C = sdm_LM(c)
if len(set([A[0], B[0], C[0]])) != 1 or not h in [a, b, c] or \
any(tuple(x) in retain for x in [a, b, c]):
continue
if monomial_divides(B[1:], monomial_lcm(A[1:], C[1:])):
remove.add((tuple(a), tuple(c)))
retain.update([tuple(b), tuple(c), tuple(a)])
return [(f, g) for (f, g) in P if (h not in [f, g]) or \
((tuple(f), tuple(g)) not in remove and \
(tuple(g), tuple(f)) not in remove)]
while P:
# TODO better data structures!!!
#print len(P), len(S)
# Use the "normal selection strategy"
lcms = [(i, sdm_LM(f)[:1] + monomial_lcm(sdm_LM(f)[1:], sdm_LM(g)[1:])) for \
i, (f, g) in enumerate(P)]
i = min(lcms, key=lambda x: O(x[1]))[0]
f, g = P.pop(i)
h = NF(sdm_spoly(f, g, O, K), S, O, K)
if h:
S.append(h)
P.extend((h, f) for f in S if sdm_LM(h)[0] == sdm_LM(f)[0])
P = prune(P, S, h)
# Now interreduce it. (TODO again, better data structures)
S = set(tuple(f) for f in S)
for a, b in permutations(S, 2):
A = sdm_LM(list(a))
B = sdm_LM(list(b))
if sdm_monomial_divides(A, B) and b in S and a in S:
S.remove(b)
return sorted((list(f) for f in S), key=lambda f: O(sdm_LM(f)),
reverse=True)
def test_probability():
# various integrals from probability theory
from sympy.abc import x, y
from sympy import symbols, Symbol, Abs, expand_mul, gammasimp, powsimp, sin
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] == (1 < beta - 1)
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 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_simplify():
assert simplify(x * (y + 1) - x * y - x + 1 < x) == (x > 1)
assert simplify(S(1) < -x) == (x < -1)
def test_Or():
N = Normal('N', 0, 1)
assert simplify(P(Or(N > 2, N < 1))) == \
-erf(sqrt(2))/2 - erfc(sqrt(2)/2)/2 + S(3)/2
assert P(Or(N < 0, N < 1)) == P(N < 1)
assert P(Or(N > 0, N < 0)) == 1
def t(m, n):
x = S(m) / n
r = polygamma(0, x)
if r.has(polygamma):
return False
return abs(polygamma(0, x.n()).n() - r.n()).n() < 1e-10
def test_loggamma():
raises(TypeError, lambda: loggamma(2, 3))
raises(ArgumentIndexError, lambda: loggamma(x).fdiff(2))
assert loggamma(-1) == oo
assert loggamma(-2) == oo
assert loggamma(0) == oo
assert loggamma(1) == 0
assert loggamma(2) == 0
assert loggamma(3) == log(2)
assert loggamma(4) == log(6)
n = Symbol("n", integer=True, positive=True)
assert loggamma(n) == log(gamma(n))
assert loggamma(-n) == oo
assert loggamma(n / 2) == log(2**(-n + 1) * sqrt(pi) * gamma(n) /
gamma(n / 2 + S.Half))
from sympy import I
assert loggamma(oo) == oo
assert loggamma(-oo) == zoo
assert loggamma(I * oo) == zoo
assert loggamma(-I * oo) == zoo
assert loggamma(zoo) == zoo
assert loggamma(nan) == nan
L = loggamma(S(16) / 3)
E = -5 * log(3) + loggamma(S(1) / 3) + log(4) + log(7) + log(10) + log(13)
assert expand_func(L).doit() == E
assert L.n() == E.n()
L = loggamma(19 / S(4))
E = -4 * log(4) + loggamma(S(3) / 4) + log(3) + log(7) + log(11) + log(15)
assert expand_func(L).doit() == E
assert L.n() == E.n()
L = loggamma(S(23) / 7)
E = -3 * log(7) + log(2) + loggamma(S(2) / 7) + log(9) + log(16)
assert expand_func(L).doit() == E
assert L.n() == E.n()
L = loggamma(19 / S(4) - 7)
E = -log(9) - log(5) + loggamma(S(3) / 4) + 3 * log(4) - 3 * I * pi
assert expand_func(L).doit() == E
assert L.n() == E.n()
L = loggamma(23 / S(7) - 6)
E = -log(19) - log(12) - log(5) + loggamma(
S(2) / 7) + 3 * log(7) - 3 * I * pi
assert expand_func(L).doit() == E
assert L.n() == E.n()
assert loggamma(x).diff(x) == polygamma(0, x)
s1 = loggamma(1 / (x + sin(x)) + cos(x)).nseries(x, n=4)
s2 = (-log(2*x) - 1)/(2*x) - log(x/pi)/2 + (4 - log(2*x))*x/24 + O(x**2) + \
log(x)*x**2/2
assert (s1 - s2).expand(force=True).removeO() == 0
s1 = loggamma(1 / x).series(x)
s2 = (1/x - S(1)/2)*log(1/x) - 1/x + log(2*pi)/2 + \
x/12 - x**3/360 + x**5/1260 + O(x**7)
assert ((s1 - s2).expand(force=True)).removeO() == 0
assert loggamma(x).rewrite('intractable') == log(gamma(x))
s1 = loggamma(x).series(x)
assert s1 == -log(x) - EulerGamma*x + pi**2*x**2/12 + x**3*polygamma(2, 1)/6 + \
pi**4*x**4/360 + x**5*polygamma(4, 1)/120 + O(x**6)
assert s1 == loggamma(x).rewrite('intractable').series(x)
assert conjugate(loggamma(x)) == loggamma(conjugate(x))
assert conjugate(loggamma(0)) == conjugate(loggamma(0))
assert conjugate(loggamma(1)) == loggamma(conjugate(1))
assert conjugate(loggamma(-oo)) == conjugate(loggamma(-oo))
assert loggamma(x).is_real is None
y, z = Symbol('y', real=True), Symbol('z', imaginary=True)
assert loggamma(y).is_real
assert loggamma(z).is_real is False
def tN(N, M):
assert loggamma(1 / x)._eval_nseries(x, n=N).getn() == M
tN(0, 0)
tN(1, 1)
tN(2, 3)
tN(3, 3)
tN(4, 5)
tN(5, 5)
def _test_subgroup(K, T, S):
_gens = T(K.generators)
assert all(elem in S for elem in _gens)
assert T.is_injective()
assert T.image().order() == S.order()
def test_issue_14450():
assert uppergamma(3 / 8, x).evalf() == uppergamma(0.375, x)
assert lowergamma(x, 3 / 8).evalf() == lowergamma(x, 0.375)
# some values from Wolfram Alpha for comparison
assert abs(uppergamma(S(3) / 8, 2).evalf() - 0.07105675881) < 1e-9
assert abs(lowergamma(S(3) / 8, 2).evalf() - 2.2993794256) < 1e-9
def test_sparse_matrix():
def sparse_eye(n):
return SparseMatrix.eye(n)
def sparse_zeros(n):
return SparseMatrix.zeros(n)
# creation args
raises(TypeError, lambda: SparseMatrix(1, 2))
a = SparseMatrix((
(1, 0),
(0, 1)
))
assert SparseMatrix(a) == a
from sympy.matrices import MutableSparseMatrix, MutableDenseMatrix
a = MutableSparseMatrix([])
b = MutableDenseMatrix([1, 2])
assert a.row_join(b) == b
assert a.col_join(b) == b
assert type(a.row_join(b)) == type(a)
assert type(a.col_join(b)) == type(a)
# make sure 0 x n matrices get stacked correctly
sparse_matrices = [SparseMatrix.zeros(0, n) for n in range(4)]
assert SparseMatrix.hstack(*sparse_matrices) == Matrix(0, 6, [])
sparse_matrices = [SparseMatrix.zeros(n, 0) for n in range(4)]
assert SparseMatrix.vstack(*sparse_matrices) == Matrix(6, 0, [])
# test element assignment
a = SparseMatrix((
(1, 0),
(0, 1)
))
a[3] = 4
assert a[1, 1] == 4
a[3] = 1
a[0, 0] = 2
assert a == SparseMatrix((
(2, 0),
(0, 1)
))
a[1, 0] = 5
assert a == SparseMatrix((
(2, 0),
(5, 1)
))
a[1, 1] = 0
assert a == SparseMatrix((
(2, 0),
(5, 0)
))
assert a._smat == {(0, 0): 2, (1, 0): 5}
# test_multiplication
a = SparseMatrix((
(1, 2),
(3, 1),
(0, 6),
))
b = SparseMatrix((
(1, 2),
(3, 0),
))
c = a*b
assert c[0, 0] == 7
assert c[0, 1] == 2
assert c[1, 0] == 6
assert c[1, 1] == 6
assert c[2, 0] == 18
assert c[2, 1] == 0
try:
eval('c = a @ b')
except SyntaxError:
pass
else:
assert c[0, 0] == 7
assert c[0, 1] == 2
assert c[1, 0] == 6
assert c[1, 1] == 6
assert c[2, 0] == 18
assert c[2, 1] == 0
x = Symbol("x")
c = b * Symbol("x")
assert isinstance(c, SparseMatrix)
assert c[0, 0] == x
assert c[0, 1] == 2*x
assert c[1, 0] == 3*x
assert c[1, 1] == 0
c = 5 * b
assert isinstance(c, SparseMatrix)
assert c[0, 0] == 5
assert c[0, 1] == 2*5
assert c[1, 0] == 3*5
assert c[1, 1] == 0
#test_power
A = SparseMatrix([[2, 3], [4, 5]])
assert (A**5)[:] == [6140, 8097, 10796, 14237]
A = SparseMatrix([[2, 1, 3], [4, 2, 4], [6, 12, 1]])
assert (A**3)[:] == [290, 262, 251, 448, 440, 368, 702, 954, 433]
# test_creation
x = Symbol("x")
a = SparseMatrix([[x, 0], [0, 0]])
m = a
assert m.cols == m.rows
assert m.cols == 2
assert m[:] == [x, 0, 0, 0]
b = SparseMatrix(2, 2, [x, 0, 0, 0])
m = b
assert m.cols == m.rows
assert m.cols == 2
assert m[:] == [x, 0, 0, 0]
assert a == b
S = sparse_eye(3)
S.row_del(1)
assert S == SparseMatrix([
[1, 0, 0],
[0, 0, 1]])
S = sparse_eye(3)
S.col_del(1)
assert S == SparseMatrix([
[1, 0],
[0, 0],
[0, 1]])
S = SparseMatrix.eye(3)
S[2, 1] = 2
S.col_swap(1, 0)
assert S == SparseMatrix([
[0, 1, 0],
[1, 0, 0],
[2, 0, 1]])
a = SparseMatrix(1, 2, [1, 2])
b = a.copy()
c = a.copy()
assert a[0] == 1
a.row_del(0)
assert a == SparseMatrix(0, 2, [])
b.col_del(1)
assert b == SparseMatrix(1, 1, [1])
# test_determinant
x, y = Symbol('x'), Symbol('y')
assert SparseMatrix(1, 1, [0]).det() == 0
assert SparseMatrix([[1]]).det() == 1
assert SparseMatrix(((-3, 2), (8, -5))).det() == -1
assert SparseMatrix(((x, 1), (y, 2*y))).det() == 2*x*y - y
assert SparseMatrix(( (1, 1, 1),
(1, 2, 3),
(1, 3, 6) )).det() == 1
assert SparseMatrix(( ( 3, -2, 0, 5),
(-2, 1, -2, 2),
( 0, -2, 5, 0),
( 5, 0, 3, 4) )).det() == -289
assert SparseMatrix(( ( 1, 2, 3, 4),
( 5, 6, 7, 8),
( 9, 10, 11, 12),
(13, 14, 15, 16) )).det() == 0
assert SparseMatrix(( (3, 2, 0, 0, 0),
(0, 3, 2, 0, 0),
(0, 0, 3, 2, 0),
(0, 0, 0, 3, 2),
(2, 0, 0, 0, 3) )).det() == 275
assert SparseMatrix(( (1, 0, 1, 2, 12),
(2, 0, 1, 1, 4),
(2, 1, 1, -1, 3),
(3, 2, -1, 1, 8),
(1, 1, 1, 0, 6) )).det() == -55
assert SparseMatrix(( (-5, 2, 3, 4, 5),
( 1, -4, 3, 4, 5),
( 1, 2, -3, 4, 5),
( 1, 2, 3, -2, 5),
( 1, 2, 3, 4, -1) )).det() == 11664
assert SparseMatrix(( ( 2, 7, -1, 3, 2),
( 0, 0, 1, 0, 1),
(-2, 0, 7, 0, 2),
(-3, -2, 4, 5, 3),
( 1, 0, 0, 0, 1) )).det() == 123
# test_slicing
m0 = sparse_eye(4)
assert m0[:3, :3] == sparse_eye(3)
assert m0[2:4, 0:2] == sparse_zeros(2)
m1 = SparseMatrix(3, 3, lambda i, j: i + j)
assert m1[0, :] == SparseMatrix(1, 3, (0, 1, 2))
assert m1[1:3, 1] == SparseMatrix(2, 1, (2, 3))
m2 = SparseMatrix(
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [12, 13, 14, 15]])
assert m2[:, -1] == SparseMatrix(4, 1, [3, 7, 11, 15])
assert m2[-2:, :] == SparseMatrix([[8, 9, 10, 11], [12, 13, 14, 15]])
assert SparseMatrix([[1, 2], [3, 4]])[[1], [1]] == Matrix([[4]])
# test_submatrix_assignment
m = sparse_zeros(4)
m[2:4, 2:4] = sparse_eye(2)
assert m == SparseMatrix([(0, 0, 0, 0),
(0, 0, 0, 0),
(0, 0, 1, 0),
(0, 0, 0, 1)])
assert len(m._smat) == 2
m[:2, :2] = sparse_eye(2)
assert m == sparse_eye(4)
m[:, 0] = SparseMatrix(4, 1, (1, 2, 3, 4))
assert m == SparseMatrix([(1, 0, 0, 0),
(2, 1, 0, 0),
(3, 0, 1, 0),
(4, 0, 0, 1)])
m[:, :] = sparse_zeros(4)
assert m == sparse_zeros(4)
m[:, :] = ((1, 2, 3, 4), (5, 6, 7, 8), (9, 10, 11, 12), (13, 14, 15, 16))
assert m == SparseMatrix((( 1, 2, 3, 4),
( 5, 6, 7, 8),
( 9, 10, 11, 12),
(13, 14, 15, 16)))
m[:2, 0] = [0, 0]
assert m == SparseMatrix((( 0, 2, 3, 4),
( 0, 6, 7, 8),
( 9, 10, 11, 12),
(13, 14, 15, 16)))
# test_reshape
m0 = sparse_eye(3)
assert m0.reshape(1, 9) == SparseMatrix(1, 9, (1, 0, 0, 0, 1, 0, 0, 0, 1))
m1 = SparseMatrix(3, 4, lambda i, j: i + j)
assert m1.reshape(4, 3) == \
SparseMatrix([(0, 1, 2), (3, 1, 2), (3, 4, 2), (3, 4, 5)])
assert m1.reshape(2, 6) == \
SparseMatrix([(0, 1, 2, 3, 1, 2), (3, 4, 2, 3, 4, 5)])
# test_applyfunc
m0 = sparse_eye(3)
assert m0.applyfunc(lambda x: 2*x) == sparse_eye(3)*2
assert m0.applyfunc(lambda x: 0 ) == sparse_zeros(3)
# test__eval_Abs
assert abs(SparseMatrix(((x, 1), (y, 2*y)))) == SparseMatrix(((Abs(x), 1), (Abs(y), 2*Abs(y))))
# test_LUdecomp
testmat = SparseMatrix([[ 0, 2, 5, 3],
[ 3, 3, 7, 4],
[ 8, 4, 0, 2],
[-2, 6, 3, 4]])
L, U, p = testmat.LUdecomposition()
assert L.is_lower
assert U.is_upper
assert (L*U).permute_rows(p, 'backward') - testmat == sparse_zeros(4)
testmat = SparseMatrix([[ 6, -2, 7, 4],
[ 0, 3, 6, 7],
[ 1, -2, 7, 4],
[-9, 2, 6, 3]])
L, U, p = testmat.LUdecomposition()
assert L.is_lower
assert U.is_upper
assert (L*U).permute_rows(p, 'backward') - testmat == sparse_zeros(4)
x, y, z = Symbol('x'), Symbol('y'), Symbol('z')
M = Matrix(((1, x, 1), (2, y, 0), (y, 0, z)))
L, U, p = M.LUdecomposition()
assert L.is_lower
assert U.is_upper
assert (L*U).permute_rows(p, 'backward') - M == sparse_zeros(3)
# test_LUsolve
A = SparseMatrix([[2, 3, 5],
[3, 6, 2],
[8, 3, 6]])
x = SparseMatrix(3, 1, [3, 7, 5])
b = A*x
soln = A.LUsolve(b)
assert soln == x
A = SparseMatrix([[0, -1, 2],
[5, 10, 7],
[8, 3, 4]])
x = SparseMatrix(3, 1, [-1, 2, 5])
b = A*x
soln = A.LUsolve(b)
assert soln == x
# test_inverse
A = sparse_eye(4)
assert A.inv() == sparse_eye(4)
assert A.inv(method="CH") == sparse_eye(4)
assert A.inv(method="LDL") == sparse_eye(4)
A = SparseMatrix([[2, 3, 5],
[3, 6, 2],
[7, 2, 6]])
Ainv = SparseMatrix(Matrix(A).inv())
assert A*Ainv == sparse_eye(3)
assert A.inv(method="CH") == Ainv
assert A.inv(method="LDL") == Ainv
A = SparseMatrix([[2, 3, 5],
[3, 6, 2],
[5, 2, 6]])
Ainv = SparseMatrix(Matrix(A).inv())
assert A*Ainv == sparse_eye(3)
assert A.inv(method="CH") == Ainv
assert A.inv(method="LDL") == Ainv
# test_cross
v1 = Matrix(1, 3, [1, 2, 3])
v2 = Matrix(1, 3, [3, 4, 5])
assert v1.cross(v2) == Matrix(1, 3, [-2, 4, -2])
assert v1.norm(2)**2 == 14
# conjugate
a = SparseMatrix(((1, 2 + I), (3, 4)))
assert a.C == SparseMatrix([
[1, 2 - I],
[3, 4]
])
# mul
assert a*Matrix(2, 2, [1, 0, 0, 1]) == a
assert a + Matrix(2, 2, [1, 1, 1, 1]) == SparseMatrix([
[2, 3 + I],
[4, 5]
])
# col join
assert a.col_join(sparse_eye(2)) == SparseMatrix([
[1, 2 + I],
[3, 4],
[1, 0],
[0, 1]
])
# symmetric
assert not a.is_symmetric(simplify=False)
# test_cofactor
assert sparse_eye(3) == sparse_eye(3).cofactor_matrix()
test = SparseMatrix([[1, 3, 2], [2, 6, 3], [2, 3, 6]])
assert test.cofactor_matrix() == \
SparseMatrix([[27, -6, -6], [-12, 2, 3], [-3, 1, 0]])
test = SparseMatrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
assert test.cofactor_matrix() == \
SparseMatrix([[-3, 6, -3], [6, -12, 6], [-3, 6, -3]])
# test_jacobian
x = Symbol('x')
y = Symbol('y')
L = SparseMatrix(1, 2, [x**2*y, 2*y**2 + x*y])
syms = [x, y]
assert L.jacobian(syms) == Matrix([[2*x*y, x**2], [y, 4*y + x]])
L = SparseMatrix(1, 2, [x, x**2*y**3])
assert L.jacobian(syms) == SparseMatrix([[1, 0], [2*x*y**3, x**2*3*y**2]])
# test_QR
A = Matrix([[1, 2], [2, 3]])
Q, S = A.QRdecomposition()
R = Rational
assert Q == Matrix([
[ 5**R(-1, 2), (R(2)/5)*(R(1)/5)**R(-1, 2)],
[2*5**R(-1, 2), (-R(1)/5)*(R(1)/5)**R(-1, 2)]])
assert S == Matrix([
[5**R(1, 2), 8*5**R(-1, 2)],
[ 0, (R(1)/5)**R(1, 2)]])
assert Q*S == A
assert Q.T * Q == sparse_eye(2)
R = Rational
# test nullspace
# first test reduced row-ech form
M = SparseMatrix([[5, 7, 2, 1],
[1, 6, 2, -1]])
out, tmp = M.rref()
assert out == Matrix([[1, 0, -R(2)/23, R(13)/23],
[0, 1, R(8)/23, R(-6)/23]])
M = SparseMatrix([[ 1, 3, 0, 2, 6, 3, 1],
[-2, -6, 0, -2, -8, 3, 1],
[ 3, 9, 0, 0, 6, 6, 2],
[-1, -3, 0, 1, 0, 9, 3]])
out, tmp = M.rref()
assert out == Matrix([[1, 3, 0, 0, 2, 0, 0],
[0, 0, 0, 1, 2, 0, 0],
[0, 0, 0, 0, 0, 1, R(1)/3],
[0, 0, 0, 0, 0, 0, 0]])
# now check the vectors
basis = M.nullspace()
assert basis[0] == Matrix([-3, 1, 0, 0, 0, 0, 0])
assert basis[1] == Matrix([0, 0, 1, 0, 0, 0, 0])
assert basis[2] == Matrix([-2, 0, 0, -2, 1, 0, 0])
assert basis[3] == Matrix([0, 0, 0, 0, 0, R(-1)/3, 1])
# test eigen
x = Symbol('x')
y = Symbol('y')
sparse_eye3 = sparse_eye(3)
assert sparse_eye3.charpoly(x) == PurePoly(((x - 1)**3))
assert sparse_eye3.charpoly(y) == PurePoly(((y - 1)**3))
# test values
M = Matrix([( 0, 1, -1),
( 1, 1, 0),
(-1, 0, 1)])
vals = M.eigenvals()
assert sorted(vals.keys()) == [-1, 1, 2]
R = Rational
M = Matrix([[1, 0, 0],
[0, 1, 0],
[0, 0, 1]])
assert M.eigenvects() == [(1, 3, [
Matrix([1, 0, 0]),
Matrix([0, 1, 0]),
Matrix([0, 0, 1])])]
M = Matrix([[5, 0, 2],
[3, 2, 0],
[0, 0, 1]])
assert M.eigenvects() == [(1, 1, [Matrix([R(-1)/2, R(3)/2, 1])]),
(2, 1, [Matrix([0, 1, 0])]),
(5, 1, [Matrix([1, 1, 0])])]
assert M.zeros(3, 5) == SparseMatrix(3, 5, {})
A = SparseMatrix(10, 10, {(0, 0): 18, (0, 9): 12, (1, 4): 18, (2, 7): 16, (3, 9): 12, (4, 2): 19, (5, 7): 16, (6, 2): 12, (9, 7): 18})
assert A.row_list() == [(0, 0, 18), (0, 9, 12), (1, 4, 18), (2, 7, 16), (3, 9, 12), (4, 2, 19), (5, 7, 16), (6, 2, 12), (9, 7, 18)]
assert A.col_list() == [(0, 0, 18), (4, 2, 19), (6, 2, 12), (1, 4, 18), (2, 7, 16), (5, 7, 16), (9, 7, 18), (0, 9, 12), (3, 9, 12)]
assert SparseMatrix.eye(2).nnz() == 2
def test_issue_4511():
# This works, but gives a complicated answer. The correct answer is x - cos(x).
# The last one is what Maple gives. It is also quite slow.
assert integrate(cos(x)**2 / (1 - sin(x))) in [x - cos(x), 1 - cos(x) + x,
-2/(tan((S(1)/2)*x)**2 + 1) + x]
