def test_dup_mul_ground():
f = dup_normal([], ZZ)
assert dup_mul_ground(f, ZZ(2), ZZ) == dup_normal([], ZZ)
f = dup_normal([1, 2, 3], ZZ)
assert dup_mul_ground(f, ZZ(0), ZZ) == dup_normal([], ZZ)
assert dup_mul_ground(f, ZZ(2), ZZ) == dup_normal([2, 4, 6], ZZ)
def dup_legendre(n, K):
"""Low-level implementation of Legendre polynomials. """
seq = [[K.one], [K.one, K.zero]]
for i in range(2, n + 1):
a = dup_mul_ground(dup_lshift(seq[-1], 1, K), K(2 * i - 1, i), K)
b = dup_mul_ground(seq[-2], K(i - 1, i), K)
seq.append(dup_sub(a, b, K))
return seq[n]
def dup_gegenbauer(n, a, K):
"""Low-level implementation of Gegenbauer polynomials. """
seq = [[K.one], [K(2) * a, K.zero]]
for i in range(2, n + 1):
f1 = K(2) * (i + a - K.one) / i
f2 = (i + K(2) * a - K(2)) / i
p1 = dup_mul_ground(dup_lshift(seq[-1], 1, K), f1, K)
p2 = dup_mul_ground(seq[-2], f2, K)
seq.append(dup_sub(p1, p2, K))
return seq[n]
def dup_hermite(n, K):
"""Low-level implementation of Hermite polynomials. """
seq = [[K.one], [K(2), K.zero]]
for i in range(2, n + 1):
a = dup_lshift(seq[-1], 1, K)
b = dup_mul_ground(seq[-2], K(i - 1), K)
c = dup_mul_ground(dup_sub(a, b, K), K(2), K)
seq.append(c)
return seq[n]
def dup_revert(f, n, K):
"""
Compute ``f**(-1)`` mod ``x**n`` using Newton iteration.
This function computes first ``2**n`` terms of a polynomial that
is a result of inversion of a polynomial modulo ``x**n``. This is
useful to efficiently compute series expansion of ``1/f``.
Examples
========
>>> from diofant.polys import ring, QQ
>>> R, x = ring("x", QQ)
>>> f = -QQ(1,720)*x**6 + QQ(1,24)*x**4 - QQ(1,2)*x**2 + 1
>>> R.dup_revert(f, 8)
61/720*x**6 + 5/24*x**4 + 1/2*x**2 + 1
"""
g = [K.revert(dup_TC(f, K))]
h = [K.one, K.zero, K.zero]
N = int(_ceil(_log(n, 2)))
for i in range(1, N + 1):
a = dup_mul_ground(g, K(2), K)
b = dup_mul(f, dup_sqr(g, K), K)
g = dup_rem(dup_sub(a, b, K), h, K)
h = dup_lshift(h, dup_degree(h), K)
return g
def dup_transform(f, p, q, K):
"""
Evaluate functional transformation ``q**n * f(p/q)`` in ``K[x]``.
Examples
========
>>> from diofant.polys import ring, ZZ
>>> R, x = ring("x", ZZ)
>>> R.dup_transform(x**2 - 2*x + 1, x**2 + 1, x - 1)
x**4 - 2*x**3 + 5*x**2 - 4*x + 4
"""
if not f:
return []
n = len(f) - 1
h, Q = [f[0]], [[K.one]]
for i in range(0, n):
Q.append(dup_mul(Q[-1], q, K))
for c, q in zip(f[1:], Q[1:]):
h = dup_mul(h, p, K)
q = dup_mul_ground(q, c, K)
h = dup_add(h, q, K)
return h
def dup_jacobi(n, a, b, K):
"""Low-level implementation of Jacobi polynomials. """
seq = [[K.one], [(a + b + K(2)) / K(2), (a - b) / K(2)]]
for i in range(2, n + 1):
den = K(i) * (a + b + i) * (a + b + K(2) * i - K(2))
f0 = (a + b + K(2) * i - K.one) * (a * a - b * b) / (K(2) * den)
f1 = (a + b + K(2) * i - K.one) * (a + b + K(2) * i - K(2)) * (
a + b + K(2) * i) / (K(2) * den)
f2 = (a + i - K.one) * (b + i - K.one) * (a + b + K(2) * i) / den
p0 = dup_mul_ground(seq[-1], f0, K)
p1 = dup_mul_ground(dup_lshift(seq[-1], 1, K), f1, K)
p2 = dup_mul_ground(seq[-2], f2, K)
seq.append(dup_sub(dup_add(p0, p1, K), p2, K))
return seq[n]
def dup_clear_denoms(f, K0, K1=None, convert=False):
"""
Clear denominators, i.e. transform ``K_0`` to ``K_1``.
Examples
========
>>> from diofant.polys import ring, QQ
>>> R, x = ring("x", QQ)
>>> f = QQ(1,2)*x + QQ(1,3)
>>> R.dup_clear_denoms(f, convert=False)
(6, 3*x + 2)
>>> R.dup_clear_denoms(f, convert=True)
(6, 3*x + 2)
"""
if K1 is None:
if K0.has_assoc_Ring:
K1 = K0.get_ring()
else:
K1 = K0
common = K1.one
for c in f:
common = K1.lcm(common, K0.denom(c))
if not K1.is_one(common):
f = dup_mul_ground(f, common, K0)
if not convert:
return common, f
else:
return common, dup_convert(f, K0, K1)
def dup_sqf_list_include(f, K, all=False):
"""
Return square-free decomposition of a polynomial in ``K[x]``.
Examples
========
>>> from diofant.polys import ring, ZZ
>>> R, x = ring("x", ZZ)
>>> f = 2*x**5 + 16*x**4 + 50*x**3 + 76*x**2 + 56*x + 16
>>> R.dup_sqf_list_include(f)
[(2, 1), (x + 1, 2), (x + 2, 3)]
>>> R.dup_sqf_list_include(f, all=True)
[(2, 1), (x + 1, 2), (x + 2, 3)]
"""
coeff, factors = dup_sqf_list(f, K, all=all)
if factors and factors[0][1] == 1:
g = dup_mul_ground(factors[0][0], coeff, K)
return [(g, 1)] + factors[1:]
else:
g = dup_strip([coeff])
return [(g, 1)] + factors
def dup_qq_heu_gcd(f, g, K0):
"""
Heuristic polynomial GCD in `Q[x]`.
Returns ``(h, cff, cfg)`` such that ``a = gcd(f, g)``,
``cff = quo(f, h)``, and ``cfg = quo(g, h)``.
Examples
========
>>> from diofant.polys import ring, QQ
>>> R, x = ring("x", QQ)
>>> f = QQ(1,2)*x**2 + QQ(7,4)*x + QQ(3,2)
>>> g = QQ(1,2)*x**2 + x
>>> R.dup_qq_heu_gcd(f, g)
(x + 2, 1/2*x + 3/4, 1/2*x)
"""
result = _dup_ff_trivial_gcd(f, g, K0)
if result is not None:
return result
K1 = K0.get_ring()
cf, f = dup_clear_denoms(f, K0, K1)
cg, g = dup_clear_denoms(g, K0, K1)
f = dup_convert(f, K0, K1)
g = dup_convert(g, K0, K1)
h, cff, cfg = dup_zz_heu_gcd(f, g, K1)
h = dup_convert(h, K1, K0)
c = dup_LC(h, K0)
h = dup_monic(h, K0)
cff = dup_convert(cff, K1, K0)
cfg = dup_convert(cfg, K1, K0)
cff = dup_mul_ground(cff, K0.quo(c, cf), K0)
cfg = dup_mul_ground(cfg, K0.quo(c, cg), K0)
return h, cff, cfg
def dup_chebyshevt(n, K):
"""Low-level implementation of Chebyshev polynomials of the 1st kind. """
seq = [[K.one], [K.one, K.zero]]
for i in range(2, n + 1):
a = dup_mul_ground(dup_lshift(seq[-1], 1, K), K(2), K)
seq.append(dup_sub(a, seq[-2], K))
return seq[n]
def dup_spherical_bessel_fn_minus(n, K):
""" Low-level implementation of fn(-n, x) """
seq = [[K.one, K.zero], [K.zero]]
for i in range(2, n + 1):
a = dup_mul_ground(dup_lshift(seq[-1], 1, K), K(3 - 2 * i), K)
seq.append(dup_sub(a, seq[-2], K))
return seq[n]
def dup_factor_list_include(f, K):
"""Factor polynomials into irreducibles in `K[x]`. """
coeff, factors = dup_factor_list(f, K)
if not factors:
return [(dup_strip([coeff]), 1)]
else:
g = dup_mul_ground(factors[0][0], coeff, K)
return [(g, factors[0][1])] + factors[1:]
def dup_zz_hensel_lift(p, f, f_list, l, K):
"""
Multifactor Hensel lifting in `Z[x]`.
Given a prime `p`, polynomial `f` over `Z[x]` such that `lc(f)`
is a unit modulo `p`, monic pair-wise coprime polynomials `f_i`
over `Z[x]` satisfying::
f = lc(f) f_1 ... f_r (mod p)
and a positive integer `l`, returns a list of monic polynomials
`F_1`, `F_2`, ..., `F_r` satisfying::
f = lc(f) F_1 ... F_r (mod p**l)
F_i = f_i (mod p), i = 1..r
References
==========
.. [1] [Gathen99]_
"""
r = len(f_list)
lc = dup_LC(f, K)
if r == 1:
F = dup_mul_ground(f, K.gcdex(lc, p**l)[0], K)
return [dup_trunc(F, p**l, K)]
m = p
k = r // 2
d = int(_ceil(_log(l, 2)))
g = gf_from_int_poly([lc], p)
for f_i in f_list[:k]:
g = gf_mul(g, gf_from_int_poly(f_i, p), p, K)
h = gf_from_int_poly(f_list[k], p)
for f_i in f_list[k + 1:]:
h = gf_mul(h, gf_from_int_poly(f_i, p), p, K)
s, t, _ = gf_gcdex(g, h, p, K)
g = gf_to_int_poly(g, p)
h = gf_to_int_poly(h, p)
s = gf_to_int_poly(s, p)
t = gf_to_int_poly(t, p)
for _ in range(1, d + 1):
(g, h, s, t), m = dup_zz_hensel_step(m, f, g, h, s, t, K), m**2
return dup_zz_hensel_lift(p, g, f_list[:k], l, K) \
+ dup_zz_hensel_lift(p, h, f_list[k:], l, K)
def dup_laguerre(n, alpha, K):
"""Low-level implementation of Laguerre polynomials. """
seq = [[K.zero], [K.one]]
for i in range(1, n + 1):
a = dup_mul(seq[-1], [-K.one / i, alpha / i + K(2 * i - 1) / i], K)
b = dup_mul_ground(seq[-2], alpha / i + K(i - 1) / i, K)
seq.append(dup_sub(a, b, K))
return seq[-1]
def dmp_zz_wang_lead_coeffs(f, T, cs, E, H, A, u, K):
"""Wang/EEZ: Compute correct leading coefficients. """
C, J, v = [], [0] * len(E), u - 1
for h in H:
c = dmp_one(v, K)
d = dup_LC(h, K) * cs
for i in reversed(range(len(E))):
k, e, (t, _) = 0, E[i], T[i]
while not (d % e):
d, k = d // e, k + 1
if k != 0:
c, J[i] = dmp_mul(c, dmp_pow(t, k, v, K), v, K), 1
C.append(c)
if any(not j for j in J):
raise ExtraneousFactors # pragma: no cover
CC, HH = [], []
for c, h in zip(C, H):
d = dmp_eval_tail(c, A, v, K)
lc = dup_LC(h, K)
if K.is_one(cs):
cc = lc // d
else:
g = K.gcd(lc, d)
d, cc = d // g, lc // g
h, cs = dup_mul_ground(h, d, K), cs // d
c = dmp_mul_ground(c, cc, v, K)
CC.append(c)
HH.append(h)
if K.is_one(cs):
return f, HH, CC
CCC, HHH = [], []
for c, h in zip(CC, HH):
CCC.append(dmp_mul_ground(c, cs, v, K))
HHH.append(dmp_mul_ground(h, cs, 0, K))
f = dmp_mul_ground(f, cs**(len(H) - 1), u, K)
return f, HHH, CCC
def dup_rr_lcm(f, g, K):
"""
Computes polynomial LCM over a ring in `K[x]`.
Examples
========
>>> from diofant.polys import ring, ZZ
>>> R, x = ring("x", ZZ)
>>> R.dup_rr_lcm(x**2 - 1, x**2 - 3*x + 2)
x**3 - 2*x**2 - x + 2
"""
fc, f = dup_primitive(f, K)
gc, g = dup_primitive(g, K)
c = K.lcm(fc, gc)
h = dup_quo(dup_mul(f, g, K), dup_gcd(f, g, K), K)
return dup_mul_ground(h, c, K)
def dup_rr_prs_gcd(f, g, K):
"""
Computes polynomial GCD using subresultants over a ring.
Returns ``(h, cff, cfg)`` such that ``a = gcd(f, g)``, ``cff = quo(f, h)``,
and ``cfg = quo(g, h)``.
Examples
========
>>> from diofant.polys import ring, ZZ
>>> R, x = ring("x", ZZ)
>>> R.dup_rr_prs_gcd(x**2 - 1, x**2 - 3*x + 2)
(x - 1, x + 1, x - 2)
"""
result = _dup_rr_trivial_gcd(f, g, K)
if result is not None:
return result
fc, F = dup_primitive(f, K)
gc, G = dup_primitive(g, K)
c = K.gcd(fc, gc)
h = dup_subresultants(F, G, K)[-1]
_, h = dup_primitive(h, K)
if K.is_negative(dup_LC(h, K)):
c = -c
h = dup_mul_ground(h, c, K)
cff = dup_quo(f, h, K)
cfg = dup_quo(g, h, K)
return h, cff, cfg
def dmp_zz_diophantine(F, c, A, d, p, u, K):
"""Wang/EEZ: Solve multivariate Diophantine equations. """
if not A:
S = [[] for _ in F]
n = dup_degree(c)
for i, coeff in enumerate(c):
if not coeff:
continue
T = dup_zz_diophantine(F, n - i, p, K)
for j, (s, t) in enumerate(zip(S, T)):
t = dup_mul_ground(t, coeff, K)
S[j] = dup_trunc(dup_add(s, t, K), p, K)
else:
n = len(A)
e = dmp_expand(F, u, K)
a, A = A[-1], A[:-1]
B, G = [], []
for f in F:
B.append(dmp_quo(e, f, u, K))
G.append(dmp_eval_in(f, a, n, u, K))
C = dmp_eval_in(c, a, n, u, K)
v = u - 1
S = dmp_zz_diophantine(G, C, A, d, p, v, K)
S = [dmp_raise(s, 1, v, K) for s in S]
for s, b in zip(S, B):
c = dmp_sub_mul(c, s, b, u, K)
c = dmp_ground_trunc(c, p, u, K)
m = dmp_nest([K.one, -a], n, K)
M = dmp_one(n, K)
for k in K.map(range(0, d)):
if dmp_zero_p(c, u):
break
M = dmp_mul(M, m, u, K)
C = dmp_diff_eval_in(c, k + 1, a, n, u, K)
if not dmp_zero_p(C, v):
C = dmp_quo_ground(C, K.factorial(k + 1), v, K)
T = dmp_zz_diophantine(G, C, A, d, p, v, K)
for i, t in enumerate(T):
T[i] = dmp_mul(dmp_raise(t, 1, v, K), M, u, K)
for i, (s, t) in enumerate(zip(S, T)):
S[i] = dmp_add(s, t, u, K)
for t, b in zip(T, B):
c = dmp_sub_mul(c, t, b, u, K)
c = dmp_ground_trunc(c, p, u, K)
S = [dmp_ground_trunc(s, p, u, K) for s in S]
return S
def dup_zz_heu_gcd(f, g, K):
"""
Heuristic polynomial GCD in `Z[x]`.
Given univariate polynomials `f` and `g` in `Z[x]`, returns
their GCD and cofactors, i.e. polynomials ``h``, ``cff`` and ``cfg``
such that::
h = gcd(f, g), cff = quo(f, h) and cfg = quo(g, h)
The algorithm is purely heuristic which means it may fail to compute
the GCD. This will be signaled by raising an exception. In this case
you will need to switch to another GCD method.
The algorithm computes the polynomial GCD by evaluating polynomials
f and g at certain points and computing (fast) integer GCD of those
evaluations. The polynomial GCD is recovered from the integer image
by interpolation. The final step is to verify if the result is the
correct GCD. This gives cofactors as a side effect.
Examples
========
>>> from diofant.polys import ring, ZZ
>>> R, x = ring("x", ZZ)
>>> R.dup_zz_heu_gcd(x**2 - 1, x**2 - 3*x + 2)
(x - 1, x + 1, x - 2)
References
==========
.. [1] [Liao95]_
"""
result = _dup_rr_trivial_gcd(f, g, K)
if result is not None:
return result
df = dup_degree(f)
dg = dup_degree(g)
gcd, f, g = dup_extract(f, g, K)
if df == 0 or dg == 0:
return [gcd], f, g
f_norm = dup_max_norm(f, K)
g_norm = dup_max_norm(g, K)
B = K(2 * min(f_norm, g_norm) + 29)
x = max(
min(B, 99 * K.sqrt(B)),
2 * min(f_norm // abs(dup_LC(f, K)), g_norm // abs(dup_LC(g, K))) + 2)
for i in range(0, HEU_GCD_MAX):
ff = dup_eval(f, x, K)
gg = dup_eval(g, x, K)
if ff and gg:
h = K.gcd(ff, gg)
cff = ff // h
cfg = gg // h
h = _dup_zz_gcd_interpolate(h, x, K)
h = dup_primitive(h, K)[1]
cff_, r = dup_div(f, h, K)
if not r:
cfg_, r = dup_div(g, h, K)
if not r:
h = dup_mul_ground(h, gcd, K)
return h, cff_, cfg_
cff = _dup_zz_gcd_interpolate(cff, x, K)
h, r = dup_div(f, cff, K)
if not r:
cfg_, r = dup_div(g, h, K)
if not r:
h = dup_mul_ground(h, gcd, K)
return h, cff, cfg_
cfg = _dup_zz_gcd_interpolate(cfg, x, K)
h, r = dup_div(g, cfg, K)
if not r:
cff_, r = dup_div(f, h, K)
if not r:
h = dup_mul_ground(h, gcd, K)
return h, cff_, cfg
x = 73794 * x * K.sqrt(K.sqrt(x)) // 27011
raise HeuristicGCDFailed('no luck')
def dup_inner_subresultants(f, g, K):
"""
Subresultant PRS algorithm in `K[x]`.
Computes the subresultant polynomial remainder sequence (PRS)
and the non-zero scalar subresultants of `f` and `g`.
By [1] Thm. 3, these are the constants '-c' (- to optimize
computation of sign).
The first subdeterminant is set to 1 by convention to match
the polynomial and the scalar subdeterminants.
If 'deg(f) < deg(g)', the subresultants of '(g,f)' are computed.
Examples
========
>>> from diofant.polys import ring, ZZ
>>> R, x = ring("x", ZZ)
>>> R.dup_inner_subresultants(x**2 + 1, x**2 - 1)
([x**2 + 1, x**2 - 1, -2], [1, 1, 4])
References
==========
.. [1] W.S. Brown, The Subresultant PRS Algorithm.
ACM Transaction of Mathematical Software 4 (1978) 237-249
"""
n = dup_degree(f)
m = dup_degree(g)
if n < m:
f, g = g, f
n, m = m, n
if not f:
return [], []
if not g:
return [f], [K.one]
R = [f, g]
d = n - m
b = (-K.one)**(d + 1)
h = dup_prem(f, g, K)
h = dup_mul_ground(h, b, K)
lc = dup_LC(g, K)
c = lc**d
# Conventional first scalar subdeterminant is 1
S = [K.one, c]
c = -c
while h:
k = dup_degree(h)
R.append(h)
f, g, m, d = g, h, k, m - k
b = -lc * c**d
h = dup_prem(f, g, K)
h = dup_quo_ground(h, b, K)
lc = dup_LC(g, K)
if d > 1: # abnormal case
q = c**(d - 1)
c = K.quo((-lc)**d, q)
else:
c = -lc
S.append(-c)
return R, S
def dmp_zz_modular_resultant(f, g, p, u, K):
"""
Compute resultant of `f` and `g` modulo a prime `p`.
Examples
========
>>> from diofant.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> f = x + y + 2
>>> g = 2*x*y + x + 3
>>> R.dmp_zz_modular_resultant(f, g, 5)
-2*y**2 + 1
"""
if not u:
return gf_int(dup_prs_resultant(f, g, K)[0] % p, p)
v = u - 1
n = dmp_degree(f, u)
m = dmp_degree(g, u)
N = dmp_degree_in(f, 1, u)
M = dmp_degree_in(g, 1, u)
B = n * M + m * N
D, a = [K.one], -K.one
r = dmp_zero(v)
while dup_degree(D) <= B:
while True:
a += K.one
if a == p:
raise HomomorphismFailed('no luck')
F = dmp_eval_in(f, gf_int(a, p), 1, u, K)
if dmp_degree(F, v) == n:
G = dmp_eval_in(g, gf_int(a, p), 1, u, K)
if dmp_degree(G, v) == m:
break
R = dmp_zz_modular_resultant(F, G, p, v, K)
e = dmp_eval(r, a, v, K)
if not v:
R = dup_strip([R])
e = dup_strip([e])
else:
R = [R]
e = [e]
d = K.invert(dup_eval(D, a, K), p)
d = dup_mul_ground(D, d, K)
d = dmp_raise(d, v, 0, K)
c = dmp_mul(d, dmp_sub(R, e, v, K), v, K)
r = dmp_add(r, c, v, K)
r = dmp_ground_trunc(r, p, v, K)
D = dup_mul(D, [K.one, -a], K)
D = dup_trunc(D, p, K)
return r