def dup_zz_hensel_step(m, f, g, h, s, t, K):
"""
One step in Hensel lifting in `Z[x]`.
Given positive integer `m` and `Z[x]` polynomials `f`, `g`, `h`, `s`
and `t` such that::
f == g*h (mod m)
s*g + t*h == 1 (mod m)
lc(f) is not a zero divisor (mod m)
lc(h) == 1
deg(f) == deg(g) + deg(h)
deg(s) < deg(h)
deg(t) < deg(g)
returns polynomials `G`, `H`, `S` and `T`, such that::
f == G*H (mod m**2)
S*G + T**H == 1 (mod m**2)
References
==========
1. [Gathen99]_
"""
M = m**2
e = dup_sub_mul(f, g, h, K)
e = dup_trunc(e, M, K)
q, r = dup_div(dup_mul(s, e, K), h, K)
q = dup_trunc(q, M, K)
r = dup_trunc(r, M, K)
u = dup_add(dup_mul(t, e, K), dup_mul(q, g, K), K)
G = dup_trunc(dup_add(g, u, K), M, K)
H = dup_trunc(dup_add(h, r, K), M, K)
u = dup_add(dup_mul(s, G, K), dup_mul(t, H, K), K)
b = dup_trunc(dup_sub(u, [K.one], K), M, K)
c, d = dup_div(dup_mul(s, b, K), H, K)
c = dup_trunc(c, M, K)
d = dup_trunc(d, M, K)
u = dup_add(dup_mul(t, b, K), dup_mul(c, G, K), K)
S = dup_trunc(dup_sub(s, d, K), M, K)
T = dup_trunc(dup_sub(t, u, K), M, K)
return G, H, S, T
def dup_zz_hensel_step(m, f, g, h, s, t, K):
"""
One step in Hensel lifting in `Z[x]`.
Given positive integer `m` and `Z[x]` polynomials `f`, `g`, `h`, `s`
and `t` such that::
f == g*h (mod m)
s*g + t*h == 1 (mod m)
lc(f) is not a zero divisor (mod m)
lc(h) == 1
deg(f) == deg(g) + deg(h)
deg(s) < deg(h)
deg(t) < deg(g)
returns polynomials `G`, `H`, `S` and `T`, such that::
f == G*H (mod m**2)
S*G + T**H == 1 (mod m**2)
References
==========
1. [Gathen99]_
"""
M = m**2
e = dup_sub_mul(f, g, h, K)
e = dup_trunc(e, M, K)
q, r = dup_div(dup_mul(s, e, K), h, K)
q = dup_trunc(q, M, K)
r = dup_trunc(r, M, K)
u = dup_add(dup_mul(t, e, K), dup_mul(q, g, K), K)
G = dup_trunc(dup_add(g, u, K), M, K)
H = dup_trunc(dup_add(h, r, K), M, K)
u = dup_add(dup_mul(s, G, K), dup_mul(t, H, K), K)
b = dup_trunc(dup_sub(u, [K.one], K), M, K)
c, d = dup_div(dup_mul(s, b, K), H, K)
c = dup_trunc(c, M, K)
d = dup_trunc(d, M, K)
u = dup_add(dup_mul(t, b, K), dup_mul(c, G, K), K)
S = dup_trunc(dup_sub(s, d, K), M, K)
T = dup_trunc(dup_sub(t, u, K), M, K)
return G, H, S, T
def dup_half_gcdex(f, g, K):
"""
Half extended Euclidean algorithm in ``F[x]``.
Returns ``(s, h)`` such that ``h = gcd(f, g)`` and ``s*f = h (mod g)``.
**Examples**
>>> from sympy.polys.domains import QQ
>>> from sympy.polys.euclidtools import dup_half_gcdex
>>> f = QQ.map([1, -2, -6, 12, 15])
>>> g = QQ.map([1, 1, -4, -4])
>>> dup_half_gcdex(f, g, QQ)
([-1/5, 3/5], [1/1, 1/1])
"""
if not (K.has_Field or not K.is_Exact):
raise DomainError("can't compute half extended GCD over %s" % K)
a, b = [K.one], []
while g:
q, r = dup_div(f, g, K)
f, g = g, r
a, b = b, dup_sub_mul(a, q, b, K)
a = dup_exquo_ground(a, dup_LC(f, K), K)
f = dup_monic(f, K)
return a, f
def test_dup_div():
f, g, q, r = [5,4,3,2,1], [1,2,3], [5,-6,0], [20,1]
assert dup_div(f, g, ZZ) == (q, r)
assert dup_quo(f, g, ZZ) == q
assert dup_rem(f, g, ZZ) == r
raises(ExactQuotientFailed, lambda: dup_exquo(f, g, ZZ))
f, g, q, r = [5,4,3,2,1,0], [1,2,0,0,9], [5,-6], [15,2,-44,54]
assert dup_div(f, g, ZZ) == (q, r)
assert dup_quo(f, g, ZZ) == q
assert dup_rem(f, g, ZZ) == r
raises(ExactQuotientFailed, lambda: dup_exquo(f, g, ZZ))
def dup_half_gcdex(f, g, K):
"""
Half extended Euclidean algorithm in `F[x]`.
Returns ``(s, h)`` such that ``h = gcd(f, g)`` and ``s*f = h (mod g)``.
Examples
========
>>> from sympy.polys import ring, QQ
>>> R, x = ring("x", QQ)
>>> f = x**4 - 2*x**3 - 6*x**2 + 12*x + 15
>>> g = x**3 + x**2 - 4*x - 4
>>> R.dup_half_gcdex(f, g)
(-1/5*x + 3/5, x + 1)
"""
if not K.has_Field:
raise DomainError("can't compute half extended GCD over %s" % K)
a, b = [K.one], []
while g:
q, r = dup_div(f, g, K)
f, g = g, r
a, b = b, dup_sub_mul(a, q, b, K)
a = dup_quo_ground(a, dup_LC(f, K), K)
f = dup_monic(f, K)
return a, f
def dup_half_gcdex(f, g, K):
"""
Half extended Euclidean algorithm in `F[x]`.
Returns ``(s, h)`` such that ``h = gcd(f, g)`` and ``s*f = h (mod g)``.
Examples
========
>>> from sympy.polys import ring, QQ
>>> R, x = ring("x", QQ)
>>> f = x**4 - 2*x**3 - 6*x**2 + 12*x + 15
>>> g = x**3 + x**2 - 4*x - 4
>>> R.dup_half_gcdex(f, g)
(-1/5*x + 3/5, x + 1)
"""
if not K.has_Field:
raise DomainError("can't compute half extended GCD over %s" % K)
a, b = [K.one], []
while g:
q, r = dup_div(f, g, K)
f, g = g, r
a, b = b, dup_sub_mul(a, q, b, K)
a = dup_quo_ground(a, dup_LC(f, K), K)
f = dup_monic(f, K)
return a, f
def dup_half_gcdex(f, g, K):
"""
Half extended Euclidean algorithm in `F[x]`.
Returns ``(s, h)`` such that ``h = gcd(f, g)`` and ``s*f = h (mod g)``.
Examples
========
>>> from sympy.polys.domains import QQ
>>> from sympy.polys.euclidtools import dup_half_gcdex
>>> f = QQ.map([1, -2, -6, 12, 15])
>>> g = QQ.map([1, 1, -4, -4])
>>> dup_half_gcdex(f, g, QQ)
([-1/5, 3/5], [1/1, 1/1])
"""
if not (K.has_Field or not K.is_Exact):
raise DomainError("can't compute half extended GCD over %s" % K)
a, b = [K.one], []
while g:
q, r = dup_div(f, g, K)
f, g = g, r
a, b = b, dup_sub_mul(a, q, b, K)
a = dup_quo_ground(a, dup_LC(f, K), K)
f = dup_monic(f, K)
return a, f
def _dup_left_decompose(f, h, K):
"""Helper function for :func:`_dup_decompose`."""
g, i = {}, 0
while f:
q, r = dup_div(f, h, K)
if dup_degree(r) > 0:
return None
else:
g[i] = dup_LC(r, K)
f, i = q, i + 1
return dup_from_raw_dict(g, K)
def _dup_left_decompose(f, h, K):
"""Helper function for :func:`_dup_decompose`."""
g, i = {}, 0
while f:
q, r = dup_div(f, h, K)
if dup_degree(r) > 0:
return None
else:
g[i] = dup_LC(r, K)
f, i = q, i + 1
return dup_from_raw_dict(g, K)
def dup_trial_division(f, factors, K):
"""Determine multiplicities of factors using trial division. """
result = []
for factor in factors:
k = 0
while True:
q, r = dup_div(f, factor, K)
if not r:
f, k = q, k + 1
else:
break
result.append((factor, k))
return _sort_factors(result)
def dup_trial_division(f, factors, K):
"""Determine multiplicities of factors using trial division. """
result = []
for factor in factors:
k = 0
while True:
q, r = dup_div(f, factor, K)
if not r:
f, k = q, k+1
else:
break
result.append((factor, k))
return _sort_factors(result)
def dup_zz_factor(f, K):
"""
Factor (non square-free) polynomials in `Z[x]`.
Given a univariate polynomial `f` in `Z[x]` computes its complete
factorization `f_1, ..., f_n` into irreducibles over integers::
f = content(f) f_1**k_1 ... f_n**k_n
The factorization is computed by reducing the input polynomial
into a primitive square-free polynomial and factoring it using
Zassenhaus algorithm. Trial division is used to recover the
multiplicities of factors.
The result is returned as a tuple consisting of::
(content(f), [(f_1, k_1), ..., (f_n, k_n))
Consider polynomial `f = 2*x**4 - 2`::
>>> from sympy.polys.factortools import dup_zz_factor
>>> from sympy.polys.domains import ZZ
>>> dup_zz_factor([2, 0, 0, 0, -2], ZZ)
(2, [([1, -1], 1), ([1, 1], 1), ([1, 0, 1], 1)])
In result we got the following factorization::
f = 2 (x - 1) (x + 1) (x**2 + 1)
Note that this is a complete factorization over integers,
however over Gaussian integers we can factor the last term.
By default, polynomials `x**n - 1` and `x**n + 1` are factored
using cyclotomic decomposition to speedup computations. To
disable this behaviour set cyclotomic=False.
References
==========
1. [Gathen99]_
"""
cont, g = dup_primitive(f, K)
n = dup_degree(g)
if dup_LC(g, K) < 0:
cont, g = -cont, dup_neg(g, K)
if n <= 0:
return cont, []
elif n == 1:
return cont, [(g, 1)]
if query('USE_IRREDUCIBLE_IN_FACTOR'):
if dup_zz_irreducible_p(g, K):
return cont, [(g, 1)]
g = dup_sqf_part(g, K)
H, factors = None, []
if query('USE_CYCLOTOMIC_FACTOR'):
H = dup_zz_cyclotomic_factor(g, K)
if H is None:
H = dup_zz_zassenhaus(g, K)
for h in H:
k = 0
while True:
q, r = dup_div(f, h, K)
if not r:
f, k = q, k + 1
else:
break
factors.append((h, k))
return cont, _sort_factors(factors)
def dup_zz_factor(f, K):
"""
Factor (non square-free) polynomials in `Z[x]`.
Given a univariate polynomial `f` in `Z[x]` computes its complete
factorization `f_1, ..., f_n` into irreducibles over integers::
f = content(f) f_1**k_1 ... f_n**k_n
The factorization is computed by reducing the input polynomial
into a primitive square-free polynomial and factoring it using
Zassenhaus algorithm. Trial division is used to recover the
multiplicities of factors.
The result is returned as a tuple consisting of::
(content(f), [(f_1, k_1), ..., (f_n, k_n))
Consider polynomial `f = 2*x**4 - 2`::
>>> from sympy.polys.factortools import dup_zz_factor
>>> from sympy.polys.domains import ZZ
>>> dup_zz_factor([2, 0, 0, 0, -2], ZZ)
(2, [([1, -1], 1), ([1, 1], 1), ([1, 0, 1], 1)])
In result we got the following factorization::
f = 2 (x - 1) (x + 1) (x**2 + 1)
Note that this is a complete factorization over integers,
however over Gaussian integers we can factor the last term.
By default, polynomials `x**n - 1` and `x**n + 1` are factored
using cyclotomic decomposition to speedup computations. To
disable this behaviour set cyclotomic=False.
**References**
1. [Gathen99]_
"""
cont, g = dup_primitive(f, K)
n = dup_degree(g)
if dup_LC(g, K) < 0:
cont, g = -cont, dup_neg(g, K)
if n <= 0:
return cont, []
elif n == 1:
return cont, [(g, 1)]
if query('USE_IRREDUCIBLE_IN_FACTOR'):
if dup_zz_irreducible_p(g, K):
return cont, [(g, 1)]
g = dup_sqf_part(g, K)
H, factors = None, []
if query('USE_CYCLOTOMIC_FACTOR'):
H = dup_zz_cyclotomic_factor(g, K)
if H is None:
H = dup_zz_zassenhaus(g, K)
for h in H:
k = 0
while True:
q, r = dup_div(f, h, K)
if not r:
f, k = q, k+1
else:
break
factors.append((h, k))
return cont, _sort_factors(factors)
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 sympy.polys.domains import ZZ
>>> from sympy.polys.euclidtools import dup_zz_heu_gcd
>>> f = ZZ.map([1, 0, -1])
>>> g = ZZ.map([1, -3, 2])
>>> dup_zz_heu_gcd(f, g, ZZ)
([1, -1], [1, 1], [1, -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 = 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 xrange(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_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 sympy.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 xrange(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')
