def _dmp_simplify_gcd(f, g, u, K):
"""Try to eliminate ``x_0`` from GCD computation in ``K[X]``. """
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if df > 0 and dg > 0:
return None
if not (df or dg):
F = dmp_LC(f, K)
G = dmp_LC(g, K)
else:
if not df:
F = dmp_LC(f, K)
G = dmp_content(g, u, K)
else:
F = dmp_content(f, u, K)
G = dmp_LC(g, K)
v = u - 1
h = dmp_gcd(F, G, v, K)
cff = [ dmp_exquo(cf, h, v, K) for cf in f ]
cfg = [ dmp_exquo(cg, h, v, K) for cg in g ]
return [h], cff, cfg
def dmp_prem(f, g, u, K):
"""Polynomial pseudo-remainder in `K[X]`. """
if not u:
return dup_prem(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
r = f
if df < dg:
return r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
j, N = dr - dg, N - 1
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
c = dmp_pow(lc_g, N, u - 1, K)
return dmp_mul_term(r, c, 0, u, K)
def dmp_prem(f, g, u, K):
"""Polynomial pseudo-remainder in `K[X]`. """
if not u:
return dup_prem(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
r = f
if df < dg:
return r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
j, N = dr-dg, N-1
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
c = dmp_pow(lc_g, N, u-1, K)
return dmp_mul_term(r, c, 0, u, K)
def _dmp_simplify_gcd(f, g, u, K):
"""Try to eliminate `x_0` from GCD computation in `K[X]`. """
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if df > 0 and dg > 0:
return None
if not (df or dg):
F = dmp_LC(f, K)
G = dmp_LC(g, K)
else:
if not df:
F = dmp_LC(f, K)
G = dmp_content(g, u, K)
else:
F = dmp_content(f, u, K)
G = dmp_LC(g, K)
v = u - 1
h = dmp_gcd(F, G, v, K)
cff = [ dmp_quo(cf, h, v, K) for cf in f ]
cfg = [ dmp_quo(cg, h, v, K) for cg in g ]
return [h], cff, cfg
def dmp_pdiv(f, g, u, K):
"""
Polynomial pseudo-division in ``K[X]``.
Examples
========
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.densearith import dmp_pdiv
>>> f = ZZ.map([[1], [1, 0], []])
>>> g = ZZ.map([[2], [2]])
>>> dmp_pdiv(f, g, 1, ZZ)
([[2], [2, -2]], [[-4, 4]])
"""
if not u:
return dup_pdiv(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
j, N = dr - dg, N - 1
Q = dmp_mul_term(q, lc_g, 0, u, K)
q = dmp_add_term(Q, lc_r, j, u, K)
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
c = dmp_pow(lc_g, N, u - 1, K)
q = dmp_mul_term(q, c, 0, u, K)
r = dmp_mul_term(r, c, 0, u, K)
return q, r
def dmp_pdiv(f, g, u, K):
"""
Polynomial pseudo-division in ``K[X]``.
Examples
========
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.densearith import dmp_pdiv
>>> f = ZZ.map([[1], [1, 0], []])
>>> g = ZZ.map([[2], [2]])
>>> dmp_pdiv(f, g, 1, ZZ)
([[2], [2, -2]], [[-4, 4]])
"""
if not u:
return dup_pdiv(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
j, N = dr-dg, N-1
Q = dmp_mul_term(q, lc_g, 0, u, K)
q = dmp_add_term(Q, lc_r, j, u, K)
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
c = dmp_pow(lc_g, N, u-1, K)
q = dmp_mul_term(q, c, 0, u, K)
r = dmp_mul_term(r, c, 0, u, K)
return q, r
def dmp_pdiv(f, g, u, K):
"""
Polynomial pseudo-division in ``K[X]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_pdiv(x**2 + x*y, 2*x + 2)
(2*x + 2*y - 2, -4*y + 4)
"""
if not u:
return dup_pdiv(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r, dr = dmp_zero(u), f, df
if df < dg:
return q, r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
lc_r = dmp_LC(r, K)
j, N = dr - dg, N - 1
Q = dmp_mul_term(q, lc_g, 0, u, K)
q = dmp_add_term(Q, lc_r, j, u, K)
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
_dr, dr = dr, dmp_degree(r, u)
if dr < dg:
break
elif not (dr < _dr):
raise PolynomialDivisionFailed(f, g, K)
c = dmp_pow(lc_g, N, u - 1, K)
q = dmp_mul_term(q, c, 0, u, K)
r = dmp_mul_term(r, c, 0, u, K)
return q, r
def dmp_pdiv(f, g, u, K):
"""
Polynomial pseudo-division in ``K[X]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_pdiv(x**2 + x*y, 2*x + 2)
(2*x + 2*y - 2, -4*y + 4)
"""
if not u:
return dup_pdiv(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r, dr = dmp_zero(u), f, df
if df < dg:
return q, r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
lc_r = dmp_LC(r, K)
j, N = dr - dg, N - 1
Q = dmp_mul_term(q, lc_g, 0, u, K)
q = dmp_add_term(Q, lc_r, j, u, K)
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
_dr, dr = dr, dmp_degree(r, u)
if dr < dg:
break
elif not (dr < _dr):
raise PolynomialDivisionFailed(f, g, K)
c = dmp_pow(lc_g, N, u - 1, K)
q = dmp_mul_term(q, c, 0, u, K)
r = dmp_mul_term(r, c, 0, u, K)
return q, r
def dmp_ff_div(f, g, u, K):
"""
Polynomial division with remainder over a field.
Examples
========
>>> from sympy.polys.domains import QQ
>>> from sympy.polys.densearith import dmp_ff_div
>>> f = QQ.map([[1], [1, 0], []])
>>> g = QQ.map([[2], [2]])
>>> dmp_ff_div(f, g, 1, QQ)
([[1/2], [1/2, -1/2]], [[-1/1, 1/1]])
"""
if not u:
return dup_ff_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u-1
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
c, R = dmp_ff_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
return q, r
def dmp_ff_div(f, g, u, K):
"""
Polynomial division with remainder over a field.
Examples
========
>>> from sympy.polys.domains import QQ
>>> from sympy.polys.densearith import dmp_ff_div
>>> f = QQ.map([[1], [1, 0], []])
>>> g = QQ.map([[2], [2]])
>>> dmp_ff_div(f, g, 1, QQ)
([[1/2], [1/2, -1/2]], [[-1/1, 1/1]])
"""
if not u:
return dup_ff_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u - 1
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
c, R = dmp_ff_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
return q, r
def dmp_rr_div(f, g, u, K):
"""
Multivariate division with remainder over a ring.
**Examples**
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.densearith import dmp_rr_div
>>> f = ZZ.map([[1], [1, 0], []])
>>> g = ZZ.map([[2], [2]])
>>> dmp_rr_div(f, g, 1, ZZ)
([[]], [[1], [1, 0], []])
"""
if not u:
return dup_rr_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u - 1
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
c, R = dmp_rr_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
return q, r
def dmp_rr_div(f, g, u, K):
"""
Multivariate division with remainder over a ring.
**Examples**
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.densearith import dmp_rr_div
>>> f = ZZ.map([[1], [1, 0], []])
>>> g = ZZ.map([[2], [2]])
>>> dmp_rr_div(f, g, 1, ZZ)
([[]], [[1], [1, 0], []])
"""
if not u:
return dup_rr_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u-1
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
c, R = dmp_rr_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
return q, r
def dmp_rr_div(f, g, u, K):
"""
Multivariate division with remainder over a ring.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_rr_div(x**2 + x*y, 2*x + 2)
(0, x**2 + x*y)
"""
if not u:
return dup_rr_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u - 1
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
c, R = dmp_rr_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
return q, r
def dmp_ff_div(f, g, u, K):
"""
Polynomial division with remainder over a field.
Examples
========
>>> from sympy.polys import ring, QQ
>>> R, x,y = ring("x,y", QQ)
>>> R.dmp_ff_div(x**2 + x*y, 2*x + 2)
(1/2*x + 1/2*y - 1/2, -y + 1)
"""
if not u:
return dup_ff_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r, dr = dmp_zero(u), f, df
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u - 1
while True:
lc_r = dmp_LC(r, K)
c, R = dmp_ff_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
_dr, dr = dr, dmp_degree(r, u)
if dr < dg:
break
elif not (dr < _dr):
raise PolynomialDivisionFailed(f, g, K)
return q, r
def dmp_ff_div(f, g, u, K):
"""
Polynomial division with remainder over a field.
Examples
========
>>> from sympy.polys import ring, QQ
>>> R, x,y = ring("x,y", QQ)
>>> R.dmp_ff_div(x**2 + x*y, 2*x + 2)
(1/2*x + 1/2*y - 1/2, -y + 1)
"""
if not u:
return dup_ff_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r, dr = dmp_zero(u), f, df
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u - 1
while True:
lc_r = dmp_LC(r, K)
c, R = dmp_ff_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
_dr, dr = dr, dmp_degree(r, u)
if dr < dg:
break
elif not (dr < _dr):
raise PolynomialDivisionFailed(f, g, K)
return q, r
def dmp_rr_div(f, g, u, K):
"""
Multivariate division with remainder over a ring.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_rr_div(x**2 + x*y, 2*x + 2)
(0, x**2 + x*y)
"""
if not u:
return dup_rr_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u - 1
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
c, R = dmp_rr_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
return q, r
def dmp_prem(f, g, u, K):
"""
Polynomial pseudo-remainder in ``K[X]``.
**Examples**
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.densearith import dmp_prem
>>> f = ZZ.map([[1], [1, 0], []])
>>> g = ZZ.map([[2], [2]])
>>> dmp_prem(f, g, 1, ZZ)
[[-4, 4]]
"""
if not u:
return dup_prem(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
r = f
if df < dg:
return r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
j, N = dr - dg, N - 1
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
c = dmp_pow(lc_g, N, u - 1, K)
return dmp_mul_term(r, c, 0, u, K)
def dmp_prem(f, g, u, K):
"""
Polynomial pseudo-remainder in ``K[X]``.
**Examples**
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.densearith import dmp_prem
>>> f = ZZ.map([[1], [1, 0], []])
>>> g = ZZ.map([[2], [2]])
>>> dmp_prem(f, g, 1, ZZ)
[[-4, 4]]
"""
if not u:
return dup_prem(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
r = f
if df < dg:
return r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
j, N = dr-dg, N-1
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
c = dmp_pow(lc_g, N, u-1, K)
return dmp_mul_term(r, c, 0, u, K)
def dmp_eval(f, a, u, K):
"""
Evaluate a polynomial at ``x_0 = a`` in ``K[X]`` using the Horner scheme.
Examples
========
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.densetools import dmp_eval
>>> f = ZZ.map([[2, 3], [1, 2]])
>>> dmp_eval(f, 2, 1, ZZ)
[5, 8]
"""
if not u:
return dup_eval(f, a, K)
if not a:
return dmp_TC(f, K)
result, v = dmp_LC(f, K), u - 1
for coeff in f[1:]:
result = dmp_mul_ground(result, a, v, K)
result = dmp_add(result, coeff, v, K)
return result
def dmp_content(f, u, K):
"""
Returns GCD of multivariate coefficients.
Examples
========
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.euclidtools import dmp_content
>>> f = ZZ.map([[2, 6], [4, 12]])
>>> dmp_content(f, 1, ZZ)
[2, 6]
"""
cont, v = dmp_LC(f, K), u - 1
if dmp_zero_p(f, u):
return cont
for c in f[1:]:
cont = dmp_gcd(cont, c, v, K)
if dmp_one_p(cont, v, K):
break
if K.is_negative(dmp_ground_LC(cont, v, K)):
return dmp_neg(cont, v, K)
else:
return cont
def dmp_discriminant(f, u, K):
"""
Computes discriminant of a polynomial in `K[X]`.
Examples
========
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.euclidtools import dmp_discriminant
>>> f = ZZ.map([[[[1]], [[]]], [[[1], []]], [[[1, 0]]]])
>>> dmp_discriminant(f, 3, ZZ)
[[[-4, 0]], [[1], [], []]]
"""
if not u:
return dup_discriminant(f, K)
d, v = dmp_degree(f, u), u - 1
if d <= 0:
return dmp_zero(v)
else:
s = (-1)**((d * (d - 1)) // 2)
c = dmp_LC(f, K)
r = dmp_resultant(f, dmp_diff(f, 1, u, K), u, K)
c = dmp_mul_ground(c, K(s), v, K)
return dmp_quo(r, c, v, K)
def dmp_discriminant(f, u, K):
"""
Computes discriminant of a polynomial in `K[X]`.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y,z,t = ring("x,y,z,t", ZZ)
>>> R.dmp_discriminant(x**2*y + x*z + t)
-4*y*t + z**2
"""
if not u:
return dup_discriminant(f, K)
d, v = dmp_degree(f, u), u - 1
if d <= 0:
return dmp_zero(v)
else:
s = (-1)**((d*(d - 1)) // 2)
c = dmp_LC(f, K)
r = dmp_resultant(f, dmp_diff(f, 1, u, K), u, K)
c = dmp_mul_ground(c, K(s), v, K)
return dmp_quo(r, c, v, K)
def dmp_content(f, u, K):
"""
Returns GCD of multivariate coefficients.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y, = ring("x,y", ZZ)
>>> R.dmp_content(2*x*y + 6*x + 4*y + 12)
2*y + 6
"""
cont, v = dmp_LC(f, K), u - 1
if dmp_zero_p(f, u):
return cont
for c in f[1:]:
cont = dmp_gcd(cont, c, v, K)
if dmp_one_p(cont, v, K):
break
if K.is_negative(dmp_ground_LC(cont, v, K)):
return dmp_neg(cont, v, K)
else:
return cont
def dmp_content(f, u, K):
"""
Returns GCD of multivariate coefficients.
**Examples**
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.euclidtools import dmp_content
>>> f = ZZ.map([[2, 6], [4, 12]])
>>> dmp_content(f, 1, ZZ)
[2, 6]
"""
cont, v = dmp_LC(f, K), u-1
if dmp_zero_p(f, u):
return cont
for c in f[1:]:
cont = dmp_gcd(cont, c, v, K)
if dmp_one_p(cont, v, K):
break
if K.is_negative(dmp_ground_LC(cont, v, K)):
return dmp_neg(cont, v, K)
else:
return cont
def dmp_eval(f, a, u, K):
"""
Evaluate a polynomial at ``x_0 = a`` in ``K[X]`` using the Horner scheme.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_eval(2*x*y + 3*x + y + 2, 2)
5*y + 8
"""
if not u:
return dup_eval(f, a, K)
if not a:
return dmp_TC(f, K)
result, v = dmp_LC(f, K), u - 1
for coeff in f[1:]:
result = dmp_mul_ground(result, a, v, K)
result = dmp_add(result, coeff, v, K)
return result
def dmp_eval(f, a, u, K):
"""
Evaluate a polynomial at ``x_0 = a`` in ``K[X]`` using the Horner scheme.
Examples
========
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.densetools import dmp_eval
>>> f = ZZ.map([[2, 3], [1, 2]])
>>> dmp_eval(f, 2, 1, ZZ)
[5, 8]
"""
if not u:
return dup_eval(f, a, K)
if not a:
return dmp_TC(f, K)
result, v = dmp_LC(f, K), u - 1
for coeff in f[1:]:
result = dmp_mul_ground(result, a, v, K)
result = dmp_add(result, coeff, v, K)
return result
def dmp_eval(f, a, u, K):
"""
Evaluate a polynomial at ``x_0 = a`` in ``K[X]`` using the Horner scheme.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_eval(2*x*y + 3*x + y + 2, 2)
5*y + 8
"""
if not u:
return dup_eval(f, a, K)
if not a:
return dmp_TC(f, K)
result, v = dmp_LC(f, K), u - 1
for coeff in f[1:]:
result = dmp_mul_ground(result, a, v, K)
result = dmp_add(result, coeff, v, K)
return result
def dmp_discriminant(f, u, K):
"""
Computes discriminant of a polynomial in ``K[X]``.
**Examples**
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.euclidtools import dmp_discriminant
>>> f = ZZ.map([[[[1]], [[]]], [[[1], []]], [[[1, 0]]]])
>>> dmp_discriminant(f, 3, ZZ)
[[[-4, 0]], [[1], [], []]]
"""
if not u:
return dup_discriminant(f, K)
d, v = dmp_degree(f, u), u-1
if d <= 0:
return dmp_zero(v)
else:
s = (-1)**((d*(d-1)) // 2)
c = dmp_LC(f, K)
r = dmp_resultant(f, dmp_diff(f, 1, u, K), u, K)
c = dmp_mul_ground(c, K(s), v, K)
return dmp_exquo(r, c, v, K)
def dmp_discriminant(f, u, K):
"""
Computes discriminant of a polynomial in `K[X]`.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y,z,t = ring("x,y,z,t", ZZ)
>>> R.dmp_discriminant(x**2*y + x*z + t)
-4*y*t + z**2
"""
if not u:
return dup_discriminant(f, K)
d, v = dmp_degree(f, u), u - 1
if d <= 0:
return dmp_zero(v)
else:
s = (-1)**((d*(d - 1)) // 2)
c = dmp_LC(f, K)
r = dmp_resultant(f, dmp_diff(f, 1, u, K), u, K)
c = dmp_mul_ground(c, K(s), v, K)
return dmp_quo(r, c, v, K)
def dmp_content(f, u, K):
"""
Returns GCD of multivariate coefficients.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y, = ring("x,y", ZZ)
>>> R.dmp_content(2*x*y + 6*x + 4*y + 12)
2*y + 6
"""
cont, v = dmp_LC(f, K), u - 1
if dmp_zero_p(f, u):
return cont
for c in f[1:]:
cont = dmp_gcd(cont, c, v, K)
if dmp_one_p(cont, v, K):
break
if K.is_negative(dmp_ground_LC(cont, v, K)):
return dmp_neg(cont, v, K)
else:
return cont
def dmp_prem(f, g, u, K):
"""
Polynomial pseudo-remainder in ``K[X]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_prem(x**2 + x*y, 2*x + 2)
-4*y + 4
"""
if not u:
return dup_prem(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
r = f
if df < dg:
return r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
j, N = dr - dg, N - 1
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
c = dmp_pow(lc_g, N, u - 1, K)
return dmp_mul_term(r, c, 0, u, K)
def dmp_prem(f, g, u, K):
"""
Polynomial pseudo-remainder in ``K[X]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_prem(x**2 + x*y, 2*x + 2)
-4*y + 4
"""
if not u:
return dup_prem(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
r = f
if df < dg:
return r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
j, N = dr - dg, N - 1
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
c = dmp_pow(lc_g, N, u - 1, K)
return dmp_mul_term(r, c, 0, u, K)
def dmp_pdiv(f, g, u, K):
"""Polynomial pseudo-division in `K[X]`. """
if not u:
return dup_pdiv(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
j, N = dr-dg, N-1
Q = dmp_mul_term(q, lc_g, 0, u, K)
q = dmp_add_term(Q, lc_r, j, u, K)
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
c = dmp_pow(lc_g, N, u-1, K)
q = dmp_mul_term(q, c, 0, u, K)
r = dmp_mul_term(r, c, 0, u, K)
return q, r
def dmp_pdiv(f, g, u, K):
"""Polynomial pseudo-division in `K[X]`. """
if not u:
return dup_pdiv(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
N = df - dg + 1
lc_g = dmp_LC(g, K)
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
j, N = dr - dg, N - 1
Q = dmp_mul_term(q, lc_g, 0, u, K)
q = dmp_add_term(Q, lc_r, j, u, K)
R = dmp_mul_term(r, lc_g, 0, u, K)
G = dmp_mul_term(g, lc_r, j, u, K)
r = dmp_sub(R, G, u, K)
c = dmp_pow(lc_g, N, u - 1, K)
q = dmp_mul_term(q, c, 0, u, K)
r = dmp_mul_term(r, c, 0, u, K)
return q, r
def dmp_ff_div(f, g, u, K):
"""Polynomial division with remainder over a field. """
if not u:
return dup_ff_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u - 1
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
c, R = dmp_ff_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
return q, r
def dmp_ff_div(f, g, u, K):
"""Polynomial division with remainder over a field. """
if not u:
return dup_ff_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r = dmp_zero(u), f
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u-1
while True:
dr = dmp_degree(r, u)
if dr < dg:
break
lc_r = dmp_LC(r, K)
c, R = dmp_ff_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
return q, r
def dmp_zz_wang_test_points(f, T, ct, A, u, K):
"""Wang/EEZ: Test evaluation points for suitability. """
if not dmp_eval_tail(dmp_LC(f, K), A, u - 1, K):
raise EvaluationFailed('no luck')
g = dmp_eval_tail(f, A, u, K)
if not dup_sqf_p(g, K):
raise EvaluationFailed('no luck')
c, h = dup_primitive(g, K)
if K.is_negative(dup_LC(h, K)):
c, h = -c, dup_neg(h, K)
v = u - 1
E = [dmp_eval_tail(t, A, v, K) for t, _ in T]
D = dmp_zz_wang_non_divisors(E, c, ct, K)
if D is not None:
return c, h, E
else:
raise EvaluationFailed('no luck')
def dmp_zz_wang_test_points(f, T, ct, A, u, K):
"""Wang/EEZ: Test evaluation points for suitability. """
if not dmp_eval_tail(dmp_LC(f, K), A, u-1, K):
raise EvaluationFailed('no luck')
g = dmp_eval_tail(f, A, u, K)
if not dup_sqf_p(g, K):
raise EvaluationFailed('no luck')
c, h = dup_primitive(g, K)
if K.is_negative(dup_LC(h, K)):
c, h = -c, dup_neg(h, K)
v = u-1
E = [ dmp_eval_tail(t, A, v, K) for t, _ in T ]
D = dmp_zz_wang_non_divisors(E, c, ct, K)
if D is not None:
return c, h, E
else:
raise EvaluationFailed('no luck')
def test_dmp_subresultants():
assert dmp_resultant([[]], [[]], 1, ZZ) == []
assert dmp_prs_resultant([[]], [[]], 1, ZZ)[0] == []
assert dmp_zz_collins_resultant([[]], [[]], 1, ZZ) == []
assert dmp_qq_collins_resultant([[]], [[]], 1, ZZ) == []
assert dmp_resultant([[ZZ(1)]], [[]], 1, ZZ) == []
assert dmp_resultant([[ZZ(1)]], [[]], 1, ZZ) == []
assert dmp_resultant([[ZZ(1)]], [[]], 1, ZZ) == []
assert dmp_resultant([[]], [[ZZ(1)]], 1, ZZ) == []
assert dmp_prs_resultant([[]], [[ZZ(1)]], 1, ZZ)[0] == []
assert dmp_zz_collins_resultant([[]], [[ZZ(1)]], 1, ZZ) == []
assert dmp_qq_collins_resultant([[]], [[ZZ(1)]], 1, ZZ) == []
f = dmp_normal([[3, 0], [], [-1, 0, 0, -4]], 1, ZZ)
g = dmp_normal([[1], [1, 0, 0, 0], [-9]], 1, ZZ)
a = dmp_normal([[3, 0, 0, 0, 0], [1, 0, -27, 4]], 1, ZZ)
b = dmp_normal([[-3, 0, 0, -12, 1, 0, -54, 8, 729, -216, 16]], 1, ZZ)
r = dmp_LC(b, ZZ)
assert dmp_subresultants(f, g, 1, ZZ) == [f, g, a, b]
assert dmp_resultant(f, g, 1, ZZ) == r
assert dmp_prs_resultant(f, g, 1, ZZ)[0] == r
assert dmp_zz_collins_resultant(f, g, 1, ZZ) == r
assert dmp_qq_collins_resultant(f, g, 1, ZZ) == r
f = dmp_normal([[-1], [], [], [5]], 1, ZZ)
g = dmp_normal([[3, 1], [], []], 1, ZZ)
a = dmp_normal([[45, 30, 5]], 1, ZZ)
b = dmp_normal([[675, 675, 225, 25]], 1, ZZ)
r = dmp_LC(b, ZZ)
assert dmp_subresultants(f, g, 1, ZZ) == [f, g, a]
assert dmp_resultant(f, g, 1, ZZ) == r
assert dmp_prs_resultant(f, g, 1, ZZ)[0] == r
assert dmp_zz_collins_resultant(f, g, 1, ZZ) == r
assert dmp_qq_collins_resultant(f, g, 1, ZZ) == r
f = [[[[[6]]]], [[[[-3]]], [[[-2]], [[]]]], [[[[1]], [[]]], [[[]]]]]
g = [[[[[1]]]], [[[[-1], [-1, 0]]]], [[[[1, 0], []]]]]
r = [[[[1]], [[-3], [-3, 0]], [[9, 0], []]],
[[[-2], [-2, 0]], [[6], [12, 0], [6, 0, 0]],
[[-18, 0], [-18, 0, 0], []]],
[[[4, 0], []], [[-12, 0], [-12, 0, 0], []], [[36, 0, 0], [], []]]]
assert dmp_zz_collins_resultant(f, g, 4, ZZ) == r
f = [[[[[QQ(1, 1)]]]], [[[[QQ(-1, 2)]]], [[[QQ(-1, 3)]], [[]]]],
[[[[QQ(1, 6)]], [[]]], [[[]]]]]
g = [[[[[QQ(1, 1)]]]], [[[[QQ(-1, 1)], [QQ(-1, 1), QQ(0, 1)]]]],
[[[[QQ(1, 1), QQ(0, 1)], []]]]]
r = [[[[QQ(1, 36)]], [[QQ(-1, 12)], [QQ(-1, 12), QQ(0, 1)]],
[[QQ(1, 4), QQ(0, 1)], []]],
[[[QQ(-1, 18)], [QQ(-1, 18), QQ(0, 1)]],
[[QQ(1, 6)], [QQ(1, 3), QQ(0, 1)], [QQ(1, 6),
QQ(0, 1),
QQ(0, 1)]],
[[QQ(-1, 2), QQ(0, 1)], [QQ(-1, 2), QQ(0, 1),
QQ(0, 1)], []]],
[[[QQ(1, 9), QQ(0, 1)], []],
[[QQ(-1, 3), QQ(0, 1)], [QQ(-1, 3), QQ(0, 1),
QQ(0, 1)], []],
[[QQ(1, 1), QQ(0, 1), QQ(0, 1)], [], []]]]
assert dmp_qq_collins_resultant(f, g, 4, QQ) == r
def dmp_inner_subresultants(f, g, u, K):
"""
Subresultant PRS algorithm in `K[X]`.
Examples
========
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.euclidtools import dmp_inner_subresultants
>>> f = ZZ.map([[3, 0], [], [-1, 0, 0, -4]])
>>> g = ZZ.map([[1], [1, 0, 0, 0], [-9]])
>>> a = [[3, 0, 0, 0, 0], [1, 0, -27, 4]]
>>> b = [[-3, 0, 0, -12, 1, 0, -54, 8, 729, -216, 16]]
>>> R = ZZ.map([f, g, a, b])
>>> B = ZZ.map([[-1], [1], [9, 0, 0, 0, 0, 0, 0, 0, 0]])
>>> D = ZZ.map([0, 1, 1])
>>> dmp_inner_subresultants(f, g, 1, ZZ) == (R, B, D)
True
"""
if not u:
return dup_inner_subresultants(f, g, K)
n = dmp_degree(f, u)
m = dmp_degree(g, u)
if n < m:
f, g = g, f
n, m = m, n
R = [f, g]
d = n - m
v = u - 1
b = dmp_pow(dmp_ground(-K.one, v), d + 1, v, K)
c = dmp_ground(-K.one, v)
B, D = [b], [d]
if dmp_zero_p(f, u) or dmp_zero_p(g, u):
return R, B, D
h = dmp_prem(f, g, u, K)
h = dmp_mul_term(h, b, 0, u, K)
while not dmp_zero_p(h, u):
k = dmp_degree(h, u)
R.append(h)
lc = dmp_LC(g, K)
p = dmp_pow(dmp_neg(lc, v, K), d, v, K)
if not d:
q = c
else:
q = dmp_pow(c, d - 1, v, K)
c = dmp_quo(p, q, v, K)
b = dmp_mul(dmp_neg(lc, v, K), dmp_pow(c, m - k, v, K), v, K)
f, g, m, d = g, h, k, m - k
B.append(b)
D.append(d)
h = dmp_prem(f, g, u, K)
h = [dmp_quo(ch, b, v, K) for ch in h]
return R, B, D
def dmp_inner_subresultants(f, g, u, K):
"""
Subresultant PRS algorithm in `K[X]`.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> f = 3*x**2*y - y**3 - 4
>>> g = x**2 + x*y**3 - 9
>>> a = 3*x*y**4 + y**3 - 27*y + 4
>>> b = -3*y**10 - 12*y**7 + y**6 - 54*y**4 + 8*y**3 + 729*y**2 - 216*y + 16
>>> prs = [f, g, a, b]
>>> beta = [[-1], [1], [9, 0, 0, 0, 0, 0, 0, 0, 0]]
>>> delta = [0, 1, 1]
>>> R.dmp_inner_subresultants(f, g) == (prs, beta, delta)
True
"""
if not u:
return dup_inner_subresultants(f, g, K)
n = dmp_degree(f, u)
m = dmp_degree(g, u)
if n < m:
f, g = g, f
n, m = m, n
R = [f, g]
d = n - m
v = u - 1
b = dmp_pow(dmp_ground(-K.one, v), d + 1, v, K)
c = dmp_ground(-K.one, v)
B, D = [b], [d]
if dmp_zero_p(f, u) or dmp_zero_p(g, u):
return R, B, D
h = dmp_prem(f, g, u, K)
h = dmp_mul_term(h, b, 0, u, K)
while not dmp_zero_p(h, u):
k = dmp_degree(h, u)
R.append(h)
lc = dmp_LC(g, K)
p = dmp_pow(dmp_neg(lc, v, K), d, v, K)
if not d:
q = c
else:
q = dmp_pow(c, d - 1, v, K)
c = dmp_quo(p, q, v, K)
b = dmp_mul(dmp_neg(lc, v, K),
dmp_pow(c, m - k, v, K), v, K)
f, g, m, d = g, h, k, m - k
B.append(b)
D.append(d)
h = dmp_prem(f, g, u, K)
h = [ dmp_quo(ch, b, v, K) for ch in h ]
return R, B, D
def dmp_zz_wang(f, u, K, mod=None):
"""
Factor primitive square-free polynomials in `Z[X]`.
Given a multivariate polynomial `f` in `Z[x_1,...,x_n]`, which
is primitive and square-free in `x_1`, computes factorization
of `f` into irreducibles over integers.
The procedure is based on Wang's Enhanced Extended Zassenhaus
algorithm. The algorithm works by viewing `f` as a univariate
polynomial in `Z[x_2,...,x_n][x_1]`, for which an evaluation
mapping is computed::
x_2 -> a_2, ..., x_n -> a_n
where `a_i`, for `i = 2, ..., n`, are carefully chosen integers.
The mapping is used to transform `f` into a univariate polynomial
in `Z[x_1]`, which can be factored efficiently using Zassenhaus
algorithm. The last step is to lift univariate factors to obtain
true multivariate factors. For this purpose a parallel Hensel
lifting procedure is used.
**References**
1. [Wang78]_
2. [Geddes92]_
"""
ct, T = dmp_zz_factor(dmp_LC(f, K), u-1, K)
b = dmp_zz_mignotte_bound(f, u, K)
p = K(nextprime(b))
if mod is None:
if u == 1:
mod = 2
else:
mod = 1
history, configs, A, r = set([]), [], [K.zero]*u, None
try:
cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K)
_, H = dup_zz_factor_sqf(s, K)
r = len(H)
if r == 1:
return [f]
bad_points = set([tuple(A)])
configs = [(s, cs, E, H, A)]
except EvaluationFailed:
pass
eez_num_configs = query('EEZ_NUMBER_OF_CONFIGS')
eez_num_tries = query('EEZ_NUMBER_OF_TRIES')
eez_mod_step = query('EEZ_MODULUS_STEP')
while len(configs) < eez_num_configs:
for _ in xrange(eez_num_tries):
A = [ K(randint(-mod, mod)) for _ in xrange(u) ]
if tuple(A) not in history:
history.add(tuple(A))
else:
continue
try:
cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K)
except EvaluationFailed:
continue
_, H = dup_zz_factor_sqf(s, K)
rr = len(H)
if r is not None:
if rr != r: # pragma: no cover
if rr < r:
configs, r = [], rr
else:
continue
else:
r = rr
if r == 1:
return [f]
configs.append((s, cs, E, H, A))
if len(configs) == eez_num_configs:
break
else:
mod += eez_mod_step
s_norm, s_arg, i = None, 0, 0
for s, _, _, _, _ in configs:
_s_norm = dup_max_norm(s, K)
if s_norm is not None:
if _s_norm < s_norm:
s_norm = _s_norm
s_arg = i
else:
s_norm = _s_norm
i += 1
_, cs, E, H, A = configs[s_arg]
try:
f, H, LC = dmp_zz_wang_lead_coeffs(f, T, cs, E, H, A, u, K)
factors = dmp_zz_wang_hensel_lifting(f, H, LC, A, p, u, K)
except ExtraneousFactors: # pragma: no cover
if query('EEZ_RESTART_IF_NEEDED'):
return dmp_zz_wang(f, u, K, mod+1)
else:
raise ExtraneousFactors("we need to restart algorithm with better parameters")
negative, result = 0, []
for f in factors:
_, f = dmp_ground_primitive(f, u, K)
if K.is_negative(dmp_ground_LC(f, u, K)):
f = dmp_neg(f, u, K)
result.append(f)
return result
def dmp_prs_resultant(f, g, u, K):
"""
Resultant algorithm in `K[X]` using subresultant PRS.
Examples
========
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.euclidtools import dmp_prs_resultant
>>> f = ZZ.map([[3, 0], [], [-1, 0, 0, -4]])
>>> g = ZZ.map([[1], [1, 0, 0, 0], [-9]])
>>> a = ZZ.map([[3, 0, 0, 0, 0], [1, 0, -27, 4]])
>>> b = ZZ.map([[-3, 0, 0, -12, 1, 0, -54, 8, 729, -216, 16]])
>>> dmp_prs_resultant(f, g, 1, ZZ) == (b[0], [f, g, a, b])
True
"""
if not u:
return dup_prs_resultant(f, g, K)
if dmp_zero_p(f, u) or dmp_zero_p(g, u):
return (dmp_zero(u - 1), [])
R, B, D = dmp_inner_subresultants(f, g, u, K)
if dmp_degree(R[-1], u) > 0:
return (dmp_zero(u - 1), R)
if dmp_one_p(R[-2], u, K):
return (dmp_LC(R[-1], K), R)
s, i, v = 1, 1, u - 1
p = dmp_one(v, K)
q = dmp_one(v, K)
for b, d in list(zip(B, D))[:-1]:
du = dmp_degree(R[i - 1], u)
dv = dmp_degree(R[i], u)
dw = dmp_degree(R[i + 1], u)
if du % 2 and dv % 2:
s = -s
lc, i = dmp_LC(R[i], K), i + 1
p = dmp_mul(dmp_mul(p, dmp_pow(b, dv, v, K), v, K),
dmp_pow(lc, du - dw, v, K), v, K)
q = dmp_mul(q, dmp_pow(lc, dv * (1 + d), v, K), v, K)
_, p, q = dmp_inner_gcd(p, q, v, K)
if s < 0:
p = dmp_neg(p, v, K)
i = dmp_degree(R[-2], u)
res = dmp_pow(dmp_LC(R[-1], K), i, v, K)
res = dmp_quo(dmp_mul(res, p, v, K), q, v, K)
return res, R
def dmp_inner_subresultants(f, g, u, K):
"""
Subresultant PRS algorithm in `K[X]`.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> f = 3*x**2*y - y**3 - 4
>>> g = x**2 + x*y**3 - 9
>>> a = 3*x*y**4 + y**3 - 27*y + 4
>>> b = -3*y**10 - 12*y**7 + y**6 - 54*y**4 + 8*y**3 + 729*y**2 - 216*y + 16
>>> prs = [f, g, a, b]
>>> sres = [[1], [1], [3, 0, 0, 0, 0], [-3, 0, 0, -12, 1, 0, -54, 8, 729, -216, 16]]
>>> R.dmp_inner_subresultants(f, g) == (prs, sres)
True
"""
if not u:
return dup_inner_subresultants(f, g, K)
n = dmp_degree(f, u)
m = dmp_degree(g, u)
if n < m:
f, g = g, f
n, m = m, n
if dmp_zero_p(f, u):
return [], []
v = u - 1
if dmp_zero_p(g, u):
return [f], [dmp_ground(K.one, v)]
R = [f, g]
d = n - m
b = dmp_pow(dmp_ground(-K.one, v), d + 1, v, K)
h = dmp_prem(f, g, u, K)
h = dmp_mul_term(h, b, 0, u, K)
lc = dmp_LC(g, K)
c = dmp_pow(lc, d, v, K)
S = [dmp_ground(K.one, v), c]
c = dmp_neg(c, v, K)
while not dmp_zero_p(h, u):
k = dmp_degree(h, u)
R.append(h)
f, g, m, d = g, h, k, m - k
b = dmp_mul(dmp_neg(lc, v, K),
dmp_pow(c, d, v, K), v, K)
h = dmp_prem(f, g, u, K)
h = [ dmp_quo(ch, b, v, K) for ch in h ]
lc = dmp_LC(g, K)
if d > 1:
p = dmp_pow(dmp_neg(lc, v, K), d, v, K)
q = dmp_pow(c, d - 1, v, K)
c = dmp_quo(p, q, v, K)
else:
c = dmp_neg(lc, v, K)
S.append(dmp_neg(c, v, K))
return R, S
def dmp_zz_wang(f, u, K, **args):
"""Factor primitive square-free polynomials in `Z[X]`.
Given a multivariate polynomial `f` in `Z[x_1,...,x_n]`, which
is primitive and square-free in `x_1`, computes factorization
of `f` into irreducibles over integers.
The procedure is based on Wang's Enhanced Extended Zassenhaus
algorithm. The algorithm works by viewing `f` as a univariate
polynomial in `Z[x_2,...,x_n][x_1]`, for which an evaluation
mapping is computed::
x_2 -> a_2, ..., x_n -> a_n
where `a_i`, for `i = 2, ..., n`, are carefully chosen integers.
The mapping is used to transform `f` into a univariate polynomial
in `Z[x_1]`, which can be factored efficiently using Zassenhaus
algorithm. The last step is to lift univariate factors to obtain
true multivariate factors. For this purpose a parallel Hensel
lifting procedure is used.
References
==========
.. [Wang78] P. S. Wang, An Improved Multivariate Polynomial Factoring
Algorithm, Math. of Computation 32, 1978, pp. 1215--1231
.. [Geddes92] K. Geddes, S. R. Czapor, G. Labahn, Algorithms for
Computer Algebra, Springer, 1992, pp. 264--272
"""
ct, T = dmp_zz_factor(dmp_LC(f, K), u - 1, K)
b = dmp_zz_mignotte_bound(f, u, K)
p = K(nextprime(b))
eez_mod = args.get('mod', None)
if eez_mod is None:
if u == 1:
eez_mod = 2
else:
eez_mod = 1
history, configs, A, r = set([]), [], [K.zero] * u, None
try:
cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K)
_, H = dup_zz_factor_sqf(s, K)
r = len(H)
if r == 1:
return [f]
bad_points = set([tuple(A)])
configs = [(s, cs, E, H, A)]
except EvaluationFailed:
pass
while len(configs) < EEZ_NUM_OK:
for _ in xrange(EEZ_NUM_TRY):
A = [K(randint(-eez_mod, eez_mod)) for _ in xrange(u)]
if tuple(A) not in history:
history.add(tuple(A))
else:
continue
try:
cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K)
except EvaluationFailed:
continue
_, H = dup_zz_factor_sqf(s, K)
rr = len(H)
if r is not None:
if rr != r: # pragma: no cover
if rr < r:
configs, r = [], rr
else:
continue
else:
r = rr
if r == 1:
return [f]
configs.append((s, cs, E, H, A))
if len(configs) == EEZ_NUM_OK:
break
else:
eez_mod += EEZ_MOD_STEP
s_norm, s_arg, i = None, 0, 0
for s, _, _, _, _ in configs:
_s_norm = dup_max_norm(s, K)
if s_norm is not None:
if _s_norm < s_norm:
s_norm = _s_norm
s_arg = i
else:
s_norm = _s_norm
i += 1
_, cs, E, H, A = configs[s_arg]
try:
f, H, LC = dmp_zz_wang_lead_coeffs(f, T, cs, E, H, A, u, K)
factors = dmp_zz_wang_hensel_lifting(f, H, LC, A, p, u, K)
except ExtraneousFactors: # pragma: no cover
if args.get('restart', True):
return dmp_zz_wang(f, u, K, mod=eez_mod + 1)
else:
raise ExtraneousFactors(
"we need to restart algorithm with better parameters")
negative, result = 0, []
for f in factors:
_, f = dmp_ground_primitive(f, u, K)
if K.is_negative(dmp_ground_LC(f, u, K)):
f = dmp_neg(f, u, K)
result.append(f)
return result
def dmp_inner_subresultants(f, g, u, K):
"""
Subresultant PRS algorithm in `K[X]`.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> f = 3*x**2*y - y**3 - 4
>>> g = x**2 + x*y**3 - 9
>>> a = 3*x*y**4 + y**3 - 27*y + 4
>>> b = -3*y**10 - 12*y**7 + y**6 - 54*y**4 + 8*y**3 + 729*y**2 - 216*y + 16
>>> prs = [f, g, a, b]
>>> sres = [[1], [1], [3, 0, 0, 0, 0], [-3, 0, 0, -12, 1, 0, -54, 8, 729, -216, 16]]
>>> R.dmp_inner_subresultants(f, g) == (prs, sres)
True
"""
if not u:
return dup_inner_subresultants(f, g, K)
n = dmp_degree(f, u)
m = dmp_degree(g, u)
if n < m:
f, g = g, f
n, m = m, n
if dmp_zero_p(f, u):
return [], []
v = u - 1
if dmp_zero_p(g, u):
return [f], [dmp_ground(K.one, v)]
R = [f, g]
d = n - m
b = dmp_pow(dmp_ground(-K.one, v), d + 1, v, K)
h = dmp_prem(f, g, u, K)
h = dmp_mul_term(h, b, 0, u, K)
lc = dmp_LC(g, K)
c = dmp_pow(lc, d, v, K)
S = [dmp_ground(K.one, v), c]
c = dmp_neg(c, v, K)
while not dmp_zero_p(h, u):
k = dmp_degree(h, u)
R.append(h)
f, g, m, d = g, h, k, m - k
b = dmp_mul(dmp_neg(lc, v, K),
dmp_pow(c, d, v, K), v, K)
h = dmp_prem(f, g, u, K)
h = [ dmp_quo(ch, b, v, K) for ch in h ]
lc = dmp_LC(g, K)
if d > 1:
p = dmp_pow(dmp_neg(lc, v, K), d, v, K)
q = dmp_pow(c, d - 1, v, K)
c = dmp_quo(p, q, v, K)
else:
c = dmp_neg(lc, v, K)
S.append(dmp_neg(c, v, K))
return R, S
def test_dmp_subresultants():
assert dmp_resultant([[]], [[]], 1, ZZ) == []
assert dmp_prs_resultant([[]], [[]], 1, ZZ)[0] == []
assert dmp_zz_collins_resultant([[]], [[]], 1, ZZ) == []
assert dmp_qq_collins_resultant([[]], [[]], 1, ZZ) == []
assert dmp_resultant([[ZZ(1)]], [[]], 1, ZZ) == []
assert dmp_resultant([[ZZ(1)]], [[]], 1, ZZ) == []
assert dmp_resultant([[ZZ(1)]], [[]], 1, ZZ) == []
assert dmp_resultant([[]], [[ZZ(1)]], 1, ZZ) == []
assert dmp_prs_resultant([[]], [[ZZ(1)]], 1, ZZ)[0] == []
assert dmp_zz_collins_resultant([[]], [[ZZ(1)]], 1, ZZ) == []
assert dmp_qq_collins_resultant([[]], [[ZZ(1)]], 1, ZZ) == []
f = dmp_normal([[3,0],[],[-1,0,0,-4]], 1, ZZ)
g = dmp_normal([[1],[1,0,0,0],[-9]], 1, ZZ)
a = dmp_normal([[3,0,0,0,0],[1,0,-27,4]], 1, ZZ)
b = dmp_normal([[-3,0,0,-12,1,0,-54,8,729,-216,16]], 1, ZZ)
r = dmp_LC(b, ZZ)
assert dmp_subresultants(f, g, 1, ZZ) == [f, g, a, b]
assert dmp_resultant(f, g, 1, ZZ) == r
assert dmp_prs_resultant(f, g, 1, ZZ)[0] == r
assert dmp_zz_collins_resultant(f, g, 1, ZZ) == r
assert dmp_qq_collins_resultant(f, g, 1, ZZ) == r
f = dmp_normal([[-1],[],[],[5]], 1, ZZ)
g = dmp_normal([[3,1],[],[]], 1, ZZ)
a = dmp_normal([[45,30,5]], 1, ZZ)
b = dmp_normal([[675,675,225,25]], 1, ZZ)
r = dmp_LC(b, ZZ)
assert dmp_subresultants(f, g, 1, ZZ) == [f, g, a]
assert dmp_resultant(f, g, 1, ZZ) == r
assert dmp_prs_resultant(f, g, 1, ZZ)[0] == r
assert dmp_zz_collins_resultant(f, g, 1, ZZ) == r
assert dmp_qq_collins_resultant(f, g, 1, ZZ) == r
f = [[[[[6]]]], [[[[-3]]], [[[-2]], [[]]]], [[[[1]], [[]]], [[[]]]]]
g = [[[[[1]]]], [[[[-1], [-1, 0]]]], [[[[1, 0], []]]]]
r = [[[[1]], [[-3], [-3, 0]], [[9, 0], []]], [[[-2], [-2, 0]], [[6],
[12, 0], [6, 0, 0]], [[-18, 0], [-18, 0, 0], []]], [[[4, 0],
[]], [[-12, 0], [-12, 0, 0], []], [[36, 0, 0], [], []]]]
assert dmp_zz_collins_resultant(f, g, 4, ZZ) == r
f = [[[[[QQ(1,1)]]]], [[[[QQ(-1,2)]]], [[[QQ(-1,3)]], [[]]]], [[[[QQ(1,6)]], [[]]], [[[]]]]]
g = [[[[[QQ(1,1)]]]], [[[[QQ(-1,1)], [QQ(-1,1), QQ(0, 1)]]]], [[[[QQ(1,1), QQ(0,1)], []]]]]
r = [[[[QQ(1,36)]], [[QQ(-1,12)], [QQ(-1,12), QQ(0,1)]], [[QQ(1,4), QQ(0,1)], []]],
[[[QQ(-1,18)], [QQ(-1,18), QQ(0,1)]], [[QQ(1,6)], [QQ(1,3), QQ(0,1)], [QQ(1,6),
QQ(0,1), QQ(0,1)]], [[QQ(-1,2), QQ(0,1)], [QQ(-1,2), QQ(0,1), QQ(0,1)], []]],
[[[QQ(1,9), QQ(0,1)], []], [[QQ(-1,3), QQ(0,1)], [QQ(-1,3), QQ(0,1), QQ(0,1)], []],
[[QQ(1,1), QQ(0,1), QQ(0,1)], [], []]]]
assert dmp_qq_collins_resultant(f, g, 4, QQ) == r
def test_dmp_LC():
assert dmp_LC([[]], ZZ) == []
assert dmp_LC([[2,3,4],[5]], ZZ) == [2,3,4]
assert dmp_LC([[[]]], ZZ) == [[]]
assert dmp_LC([[[2],[3,4]],[[5]]], ZZ) == [[2],[3,4]]
def dmp_prs_resultant(f, g, u, K):
"""
Resultant algorithm in ``K[X]`` using subresultant PRS.
**Examples**
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.euclidtools import dmp_prs_resultant
>>> f = ZZ.map([[3, 0], [], [-1, 0, 0, -4]])
>>> g = ZZ.map([[1], [1, 0, 0, 0], [-9]])
>>> a = ZZ.map([[3, 0, 0, 0, 0], [1, 0, -27, 4]])
>>> b = ZZ.map([[-3, 0, 0, -12, 1, 0, -54, 8, 729, -216, 16]])
>>> dmp_prs_resultant(f, g, 1, ZZ) == (b[0], [f, g, a, b])
True
"""
if not u:
return dup_prs_resultant(f, g, K)
if dmp_zero_p(f, u) or dmp_zero_p(g, u):
return (dmp_zero(u-1), [])
R, B, D = dmp_inner_subresultants(f, g, u, K)
if dmp_degree(R[-1], u) > 0:
return (dmp_zero(u-1), R)
if dmp_one_p(R[-2], u, K):
return (dmp_LC(R[-1], K), R)
s, i, v = 1, 1, u-1
p = dmp_one(v, K)
q = dmp_one(v, K)
for b, d in zip(B, D)[:-1]:
du = dmp_degree(R[i-1], u)
dv = dmp_degree(R[i ], u)
dw = dmp_degree(R[i+1], u)
if du % 2 and dv % 2:
s = -s
lc, i = dmp_LC(R[i], K), i+1
p = dmp_mul(dmp_mul(p, dmp_pow(b, dv, v, K), v, K),
dmp_pow(lc, du-dw, v, K), v, K)
q = dmp_mul(q, dmp_pow(lc, dv*(1+d), v, K), v, K)
_, p, q = dmp_inner_gcd(p, q, v, K)
if s < 0:
p = dmp_neg(p, v, K)
i = dmp_degree(R[-2], u)
res = dmp_pow(dmp_LC(R[-1], K), i, v, K)
res = dmp_exquo(dmp_mul(res, p, v, K), q, v, K)
return res, R
def dmp_inner_subresultants(f, g, u, K):
"""
Subresultant PRS algorithm in ``K[X]``.
**Examples**
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.euclidtools import dmp_inner_subresultants
>>> f = ZZ.map([[3, 0], [], [-1, 0, 0, -4]])
>>> g = ZZ.map([[1], [1, 0, 0, 0], [-9]])
>>> a = [[3, 0, 0, 0, 0], [1, 0, -27, 4]]
>>> b = [[-3, 0, 0, -12, 1, 0, -54, 8, 729, -216, 16]]
>>> R = ZZ.map([f, g, a, b])
>>> B = ZZ.map([[-1], [1], [9, 0, 0, 0, 0, 0, 0, 0, 0]])
>>> D = ZZ.map([0, 1, 1])
>>> dmp_inner_subresultants(f, g, 1, ZZ) == (R, B, D)
True
"""
if not u:
return dup_inner_subresultants(f, g, K)
n = dmp_degree(f, u)
m = dmp_degree(g, u)
if n < m:
f, g = g, f
n, m = m, n
R = [f, g]
d = n - m
v = u - 1
b = dmp_pow(dmp_ground(-K.one, v), d+1, v, K)
c = dmp_ground(-K.one, v)
B, D = [b], [d]
if dmp_zero_p(f, u) or dmp_zero_p(g, u):
return R, B, D
h = dmp_prem(f, g, u, K)
h = dmp_mul_term(h, b, 0, u, K)
while not dmp_zero_p(h, u):
k = dmp_degree(h, u)
R.append(h)
lc = dmp_LC(g, K)
p = dmp_pow(dmp_neg(lc, v, K), d, v, K)
if not d:
q = c
else:
q = dmp_pow(c, d-1, v, K)
c = dmp_exquo(p, q, v, K)
b = dmp_mul(dmp_neg(lc, v, K),
dmp_pow(c, m-k, v, K), v, K)
f, g, m, d = g, h, k, m-k
B.append(b)
D.append(d)
h = dmp_prem(f, g, u, K)
h = [ dmp_exquo(ch, b, v, K) for ch in h ]
return R, B, D
def dmp_inner_subresultants(f, g, u, K):
"""
Subresultant PRS algorithm in `K[X]`.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> f = 3*x**2*y - y**3 - 4
>>> g = x**2 + x*y**3 - 9
>>> a = 3*x*y**4 + y**3 - 27*y + 4
>>> b = -3*y**10 - 12*y**7 + y**6 - 54*y**4 + 8*y**3 + 729*y**2 - 216*y + 16
>>> prs = [f, g, a, b]
>>> beta = [[-1], [1], [9, 0, 0, 0, 0, 0, 0, 0, 0]]
>>> delta = [0, 1, 1]
>>> R.dmp_inner_subresultants(f, g) == (prs, beta, delta)
True
"""
if not u:
return dup_inner_subresultants(f, g, K)
n = dmp_degree(f, u)
m = dmp_degree(g, u)
if n < m:
f, g = g, f
n, m = m, n
R = [f, g]
d = n - m
v = u - 1
b = dmp_pow(dmp_ground(-K.one, v), d + 1, v, K)
c = dmp_ground(-K.one, v)
B, D = [b], [d]
if dmp_zero_p(f, u) or dmp_zero_p(g, u):
return R, B, D
h = dmp_prem(f, g, u, K)
h = dmp_mul_term(h, b, 0, u, K)
while not dmp_zero_p(h, u):
k = dmp_degree(h, u)
R.append(h)
lc = dmp_LC(g, K)
p = dmp_pow(dmp_neg(lc, v, K), d, v, K)
if not d:
q = c
else:
q = dmp_pow(c, d - 1, v, K)
c = dmp_quo(p, q, v, K)
b = dmp_mul(dmp_neg(lc, v, K),
dmp_pow(c, m - k, v, K), v, K)
f, g, m, d = g, h, k, m - k
B.append(b)
D.append(d)
h = dmp_prem(f, g, u, K)
h = [ dmp_quo(ch, b, v, K) for ch in h ]
return R, B, D
def dmp_prs_resultant(f, g, u, K):
"""
Resultant algorithm in `K[X]` using subresultant PRS.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> f = 3*x**2*y - y**3 - 4
>>> g = x**2 + x*y**3 - 9
>>> a = 3*x*y**4 + y**3 - 27*y + 4
>>> b = -3*y**10 - 12*y**7 + y**6 - 54*y**4 + 8*y**3 + 729*y**2 - 216*y + 16
>>> res, prs = R.dmp_prs_resultant(f, g)
>>> res == b # resultant has n-1 variables
False
>>> res == b.drop(x)
True
>>> prs == [f, g, a, b]
True
"""
if not u:
return dup_prs_resultant(f, g, K)
if dmp_zero_p(f, u) or dmp_zero_p(g, u):
return (dmp_zero(u - 1), [])
R, B, D = dmp_inner_subresultants(f, g, u, K)
if dmp_degree(R[-1], u) > 0:
return (dmp_zero(u - 1), R)
if dmp_one_p(R[-2], u, K):
return (dmp_LC(R[-1], K), R)
s, i, v = 1, 1, u - 1
p = dmp_one(v, K)
q = dmp_one(v, K)
for b, d in list(zip(B, D))[:-1]:
du = dmp_degree(R[i - 1], u)
dv = dmp_degree(R[i ], u)
dw = dmp_degree(R[i + 1], u)
if du % 2 and dv % 2:
s = -s
lc, i = dmp_LC(R[i], K), i + 1
p = dmp_mul(dmp_mul(p, dmp_pow(b, dv, v, K), v, K),
dmp_pow(lc, du - dw, v, K), v, K)
q = dmp_mul(q, dmp_pow(lc, dv*(1 + d), v, K), v, K)
_, p, q = dmp_inner_gcd(p, q, v, K)
if s < 0:
p = dmp_neg(p, v, K)
i = dmp_degree(R[-2], u)
res = dmp_pow(dmp_LC(R[-1], K), i, v, K)
res = dmp_quo(dmp_mul(res, p, v, K), q, v, K)
return res, R
def dmp_prs_resultant(f, g, u, K):
"""
Resultant algorithm in `K[X]` using subresultant PRS.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> f = 3*x**2*y - y**3 - 4
>>> g = x**2 + x*y**3 - 9
>>> a = 3*x*y**4 + y**3 - 27*y + 4
>>> b = -3*y**10 - 12*y**7 + y**6 - 54*y**4 + 8*y**3 + 729*y**2 - 216*y + 16
>>> res, prs = R.dmp_prs_resultant(f, g)
>>> res == b # resultant has n-1 variables
False
>>> res == b.drop(x)
True
>>> prs == [f, g, a, b]
True
"""
if not u:
return dup_prs_resultant(f, g, K)
if dmp_zero_p(f, u) or dmp_zero_p(g, u):
return (dmp_zero(u - 1), [])
R, B, D = dmp_inner_subresultants(f, g, u, K)
if dmp_degree(R[-1], u) > 0:
return (dmp_zero(u - 1), R)
if dmp_one_p(R[-2], u, K):
return (dmp_LC(R[-1], K), R)
s, i, v = 1, 1, u - 1
p = dmp_one(v, K)
q = dmp_one(v, K)
for b, d in list(zip(B, D))[:-1]:
du = dmp_degree(R[i - 1], u)
dv = dmp_degree(R[i ], u)
dw = dmp_degree(R[i + 1], u)
if du % 2 and dv % 2:
s = -s
lc, i = dmp_LC(R[i], K), i + 1
p = dmp_mul(dmp_mul(p, dmp_pow(b, dv, v, K), v, K),
dmp_pow(lc, du - dw, v, K), v, K)
q = dmp_mul(q, dmp_pow(lc, dv*(1 + d), v, K), v, K)
_, p, q = dmp_inner_gcd(p, q, v, K)
if s < 0:
p = dmp_neg(p, v, K)
i = dmp_degree(R[-2], u)
res = dmp_pow(dmp_LC(R[-1], K), i, v, K)
res = dmp_quo(dmp_mul(res, p, v, K), q, v, K)
return res, R
def dmp_zz_wang(f, u, K, mod=None):
"""
Factor primitive square-free polynomials in `Z[X]`.
Given a multivariate polynomial `f` in `Z[x_1,...,x_n]`, which
is primitive and square-free in `x_1`, computes factorization
of `f` into irreducibles over integers.
The procedure is based on Wang's Enhanced Extended Zassenhaus
algorithm. The algorithm works by viewing `f` as a univariate
polynomial in `Z[x_2,...,x_n][x_1]`, for which an evaluation
mapping is computed::
x_2 -> a_2, ..., x_n -> a_n
where `a_i`, for `i = 2, ..., n`, are carefully chosen integers.
The mapping is used to transform `f` into a univariate polynomial
in `Z[x_1]`, which can be factored efficiently using Zassenhaus
algorithm. The last step is to lift univariate factors to obtain
true multivariate factors. For this purpose a parallel Hensel
lifting procedure is used.
References
==========
1. [Wang78]_
2. [Geddes92]_
"""
ct, T = dmp_zz_factor(dmp_LC(f, K), u - 1, K)
b = dmp_zz_mignotte_bound(f, u, K)
p = K(nextprime(b))
if mod is None:
if u == 1:
mod = 2
else:
mod = 1
history, configs, A, r = set([]), [], [K.zero] * u, None
try:
cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K)
_, H = dup_zz_factor_sqf(s, K)
r = len(H)
if r == 1:
return [f]
configs = [(s, cs, E, H, A)]
except EvaluationFailed:
pass
eez_num_configs = query('EEZ_NUMBER_OF_CONFIGS')
eez_num_tries = query('EEZ_NUMBER_OF_TRIES')
eez_mod_step = query('EEZ_MODULUS_STEP')
while len(configs) < eez_num_configs:
for _ in xrange(eez_num_tries):
A = [K(randint(-mod, mod)) for _ in xrange(u)]
if tuple(A) not in history:
history.add(tuple(A))
else:
continue
try:
cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K)
except EvaluationFailed:
continue
_, H = dup_zz_factor_sqf(s, K)
rr = len(H)
if r is not None:
if rr != r: # pragma: no cover
if rr < r:
configs, r = [], rr
else:
continue
else:
r = rr
if r == 1:
return [f]
configs.append((s, cs, E, H, A))
if len(configs) == eez_num_configs:
break
else:
mod += eez_mod_step
s_norm, s_arg, i = None, 0, 0
for s, _, _, _, _ in configs:
_s_norm = dup_max_norm(s, K)
if s_norm is not None:
if _s_norm < s_norm:
s_norm = _s_norm
s_arg = i
else:
s_norm = _s_norm
i += 1
_, cs, E, H, A = configs[s_arg]
try:
f, H, LC = dmp_zz_wang_lead_coeffs(f, T, cs, E, H, A, u, K)
factors = dmp_zz_wang_hensel_lifting(f, H, LC, A, p, u, K)
except ExtraneousFactors: # pragma: no cover
if query('EEZ_RESTART_IF_NEEDED'):
return dmp_zz_wang(f, u, K, mod + 1)
else:
raise ExtraneousFactors(
"we need to restart algorithm with better parameters")
negative, result = 0, []
for f in factors:
_, f = dmp_ground_primitive(f, u, K)
if K.is_negative(dmp_ground_LC(f, u, K)):
f = dmp_neg(f, u, K)
result.append(f)
return result
def dmp_zz_wang(f, u, K, **args):
"""Factor primitive square-free polynomials in `Z[X]`.
Given a multivariate polynomial `f` in `Z[x_1,...,x_n]`, which
is primitive and square-free in `x_1`, computes factorization
of `f` into irreducibles over integers.
The procedure is based on Wang's Enhanced Extended Zassenhaus
algorithm. The algorithm works by viewing `f` as a univariate
polynomial in `Z[x_2,...,x_n][x_1]`, for which an evaluation
mapping is computed::
x_2 -> a_2, ..., x_n -> a_n
where `a_i`, for `i = 2, ..., n`, are carefully chosen integers.
The mapping is used to transform `f` into a univariate polynomial
in `Z[x_1]`, which can be factored efficiently using Zassenhaus
algorithm. The last step is to lift univariate factors to obtain
true multivariate factors. For this purpose a parallel Hensel
lifting procedure is used.
References
==========
.. [Wang78] P. S. Wang, An Improved Multivariate Polynomial Factoring
Algorithm, Math. of Computation 32, 1978, pp. 1215--1231
.. [Geddes92] K. Geddes, S. R. Czapor, G. Labahn, Algorithms for
Computer Algebra, Springer, 1992, pp. 264--272
"""
ct, T = dmp_zz_factor(dmp_LC(f, K), u-1, K)
b = dmp_zz_mignotte_bound(f, u, K)
p = K(nextprime(b))
eez_mod = args.get('mod', None)
if eez_mod is None:
if u == 1:
eez_mod = 2
else:
eez_mod = 1
history, configs, A, r = set([]), [], [K.zero]*u, None
try:
cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K)
_, H = dup_zz_factor_sqf(s, K)
r = len(H)
if r == 1:
return [f]
bad_points = set([tuple(A)])
configs = [(s, cs, E, H, A)]
except EvaluationFailed:
pass
while len(configs) < EEZ_NUM_OK:
for _ in xrange(EEZ_NUM_TRY):
A = [ K(randint(-eez_mod, eez_mod)) for _ in xrange(u) ]
if tuple(A) not in history:
history.add(tuple(A))
else:
continue
try:
cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K)
except EvaluationFailed:
continue
_, H = dup_zz_factor_sqf(s, K)
rr = len(H)
if r is not None:
if rr != r: # pragma: no cover
if rr < r:
configs, r = [], rr
else:
continue
else:
r = rr
if r == 1:
return [f]
configs.append((s, cs, E, H, A))
if len(configs) == EEZ_NUM_OK:
break
else:
eez_mod += EEZ_MOD_STEP
s_norm, s_arg, i = None, 0, 0
for s, _, _, _, _ in configs:
_s_norm = dup_max_norm(s, K)
if s_norm is not None:
if _s_norm < s_norm:
s_norm = _s_norm
s_arg = i
else:
s_norm = _s_norm
i += 1
_, cs, E, H, A = configs[s_arg]
try:
f, H, LC = dmp_zz_wang_lead_coeffs(f, T, cs, E, H, A, u, K)
factors = dmp_zz_wang_hensel_lifting(f, H, LC, A, p, u, K)
except ExtraneousFactors: # pragma: no cover
if args.get('restart', True):
return dmp_zz_wang(f, u, K, mod=eez_mod+1)
else:
raise ExtraneousFactors("we need to restart algorithm with better parameters")
negative, result = 0, []
for f in factors:
_, f = dmp_ground_primitive(f, u, K)
if K.is_negative(dmp_ground_LC(f, u, K)):
f = dmp_neg(f, u, K)
result.append(f)
return result