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"""Square-free decomposition algorithms and related tools. """
from sympy.polys.densearith import (
dup_neg, dmp_neg,
dup_sub, dmp_sub,
dup_mul, dmp_mul,
dup_quo, dmp_quo,
dup_mul_ground, dmp_mul_ground)
from sympy.polys.densebasic import (
dup_strip,
dup_LC, dmp_ground_LC,
dmp_zero_p,
dmp_ground,
dup_degree, dmp_degree, dmp_degree_in, dmp_degree_list,
dmp_raise, dmp_inject,
dup_convert)
from sympy.polys.densetools import (
dup_diff, dmp_diff, dmp_diff_in,
dup_shift, dmp_shift,
dup_monic, dmp_ground_monic,
dup_primitive, dmp_ground_primitive)
from sympy.polys.euclidtools import (
dup_inner_gcd, dmp_inner_gcd,
dup_gcd, dmp_gcd,
dmp_resultant, dmp_primitive)
from sympy.polys.galoistools import (
gf_sqf_list, gf_sqf_part)
from sympy.polys.polyerrors import (
MultivariatePolynomialError,
DomainError)
def _dup_check_degrees(f, result):
"""Sanity check the degrees of a computed factorization in K[x]."""
deg = sum(k * dup_degree(fac) for (fac, k) in result)
assert deg == dup_degree(f)
def _dmp_check_degrees(f, u, result):
"""Sanity check the degrees of a computed factorization in K[X]."""
degs = [0] * (u + 1)
for fac, k in result:
degs_fac = dmp_degree_list(fac, u)
degs = [d1 + k * d2 for d1, d2 in zip(degs, degs_fac)]
assert tuple(degs) == dmp_degree_list(f, u)
def dup_sqf_p(f, K):
"""
Return ``True`` if ``f`` is a square-free polynomial in ``K[x]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x = ring("x", ZZ)
>>> R.dup_sqf_p(x**2 - 2*x + 1)
False
>>> R.dup_sqf_p(x**2 - 1)
True
"""
if not f:
return True
else:
return not dup_degree(dup_gcd(f, dup_diff(f, 1, K), K))
def dmp_sqf_p(f, u, K):
"""
Return ``True`` if ``f`` is a square-free polynomial in ``K[X]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_sqf_p(x**2 + 2*x*y + y**2)
False
>>> R.dmp_sqf_p(x**2 + y**2)
True
"""
if dmp_zero_p(f, u):
return True
for i in range(u+1):
fp = dmp_diff_in(f, 1, i, u, K)
if dmp_zero_p(fp, u):
continue
gcd = dmp_gcd(f, fp, u, K)
if dmp_degree_in(gcd, i, u) != 0:
return False
return True
def dup_sqf_norm(f, K):
r"""
Find a shift of `f` in `K[x]` that has square-free norm.
The domain `K` must be an algebraic number field `k(a)` (see :ref:`QQ(a)`).
Returns `(s,g,r)`, such that `g(x)=f(x-sa)`, `r(x)=\text{Norm}(g(x))` and
`r` is a square-free polynomial over `k`.
Examples
========
We first create the algebraic number field `K=k(a)=\mathbb{Q}(\sqrt{3})`
and rings `K[x]` and `k[x]`:
>>> from sympy.polys import ring, QQ
>>> from sympy import sqrt
>>> K = QQ.algebraic_field(sqrt(3))
>>> R, x = ring("x", K)
>>> _, X = ring("x", QQ)
We can now find a square free norm for a shift of `f`:
>>> f = x**2 - 1
>>> s, g, r = R.dup_sqf_norm(f)
The choice of shift `s` is arbitrary and the particular values returned for
`g` and `r` are determined by `s`.
>>> s == 1
True
>>> g == x**2 - 2*sqrt(3)*x + 2
True
>>> r == X**4 - 8*X**2 + 4
True
The invariants are:
>>> g == f.shift(-s*K.unit)
True
>>> g.norm() == r
True
>>> r.is_squarefree
True
Explanation
===========
This is part of Trager's algorithm for factorizing polynomials over
algebraic number fields. In particular this function is algorithm
``sqfr_norm`` from [Trager76]_.
See Also
========
dmp_sqf_norm:
Analogous function for multivariate polynomials over ``k(a)``.
dmp_norm:
Computes the norm of `f` directly without any shift.
dup_ext_factor:
Function implementing Trager's algorithm that uses this.
sympy.polys.polytools.sqf_norm:
High-level interface for using this function.
"""
if not K.is_Algebraic:
raise DomainError("ground domain must be algebraic")
s, g = 0, dmp_raise(K.mod.to_list(), 1, 0, K.dom)
while True:
h, _ = dmp_inject(f, 0, K, front=True)
r = dmp_resultant(g, h, 1, K.dom)
if dup_sqf_p(r, K.dom):
break
else:
f, s = dup_shift(f, -K.unit, K), s + 1
return s, f, r
def _dmp_sqf_norm_shifts(f, u, K):
"""Generate a sequence of candidate shifts for dmp_sqf_norm."""
#
# We want to find a minimal shift if possible because shifting high degree
# variables can be expensive e.g. x**10 -> (x + 1)**10. We try a few easy
# cases first before the final infinite loop that is guaranteed to give
# only finitely many bad shifts (see Trager76 for proof of this in the
# univariate case).
#
# First the trivial shift [0, 0, ...]
n = u + 1
s0 = [0] * n
yield s0, f
# Shift in multiples of the generator of the extension field K
a = K.unit
# Variables of degree > 0 ordered by increasing degree
d = dmp_degree_list(f, u)
var_indices = [i for di, i in sorted(zip(d, range(u+1))) if di > 0]
# Now try [1, 0, 0, ...], [0, 1, 0, ...]
for i in var_indices:
s1 = s0.copy()
s1[i] = 1
a1 = [-a*s1i for s1i in s1]
f1 = dmp_shift(f, a1, u, K)
yield s1, f1
# Now try [1, 1, 1, ...], [2, 2, 2, ...]
j = 0
while True:
j += 1
sj = [j] * n
aj = [-a*j] * n
fj = dmp_shift(f, aj, u, K)
yield sj, fj
def dmp_sqf_norm(f, u, K):
r"""
Find a shift of ``f`` in ``K[X]`` that has square-free norm.
The domain `K` must be an algebraic number field `k(a)` (see :ref:`QQ(a)`).
Returns `(s,g,r)`, such that `g(x_1,x_2,\cdots)=f(x_1-s_1 a, x_2 - s_2 a,
\cdots)`, `r(x)=\text{Norm}(g(x))` and `r` is a square-free polynomial over
`k`.
Examples
========
We first create the algebraic number field `K=k(a)=\mathbb{Q}(i)` and rings
`K[x,y]` and `k[x,y]`:
>>> from sympy.polys import ring, QQ
>>> from sympy import I
>>> K = QQ.algebraic_field(I)
>>> R, x, y = ring("x,y", K)
>>> _, X, Y = ring("x,y", QQ)
We can now find a square free norm for a shift of `f`:
>>> f = x*y + y**2
>>> s, g, r = R.dmp_sqf_norm(f)
The choice of shifts ``s`` is arbitrary and the particular values returned
for ``g`` and ``r`` are determined by ``s``.
>>> s
[0, 1]
>>> g == x*y - I*x + y**2 - 2*I*y - 1
True
>>> r == X**2*Y**2 + X**2 + 2*X*Y**3 + 2*X*Y + Y**4 + 2*Y**2 + 1
True
The required invariants are:
>>> g == f.shift_list([-si*K.unit for si in s])
True
>>> g.norm() == r
True
>>> r.is_squarefree
True
Explanation
===========
This is part of Trager's algorithm for factorizing polynomials over
algebraic number fields. In particular this function is a multivariate
generalization of algorithm ``sqfr_norm`` from [Trager76]_.
See Also
========
dup_sqf_norm:
Analogous function for univariate polynomials over ``k(a)``.
dmp_norm:
Computes the norm of `f` directly without any shift.
dmp_ext_factor:
Function implementing Trager's algorithm that uses this.
sympy.polys.polytools.sqf_norm:
High-level interface for using this function.
"""
if not u:
s, g, r = dup_sqf_norm(f, K)
return [s], g, r
if not K.is_Algebraic:
raise DomainError("ground domain must be algebraic")
g = dmp_raise(K.mod.to_list(), u + 1, 0, K.dom)
for s, f in _dmp_sqf_norm_shifts(f, u, K):
h, _ = dmp_inject(f, u, K, front=True)
r = dmp_resultant(g, h, u + 1, K.dom)
if dmp_sqf_p(r, u, K.dom):
break
return s, f, r
def dmp_norm(f, u, K):
r"""
Norm of ``f`` in ``K[X]``, often not square-free.
The domain `K` must be an algebraic number field `k(a)` (see :ref:`QQ(a)`).
Examples
========
We first define the algebraic number field `K = k(a) = \mathbb{Q}(\sqrt{2})`:
>>> from sympy import QQ, sqrt
>>> from sympy.polys.sqfreetools import dmp_norm
>>> k = QQ
>>> K = k.algebraic_field(sqrt(2))
We can now compute the norm of a polynomial `p` in `K[x,y]`:
>>> p = [[K(1)], [K(1),K.unit]] # x + y + sqrt(2)
>>> N = [[k(1)], [k(2),k(0)], [k(1),k(0),k(-2)]] # x**2 + 2*x*y + y**2 - 2
>>> dmp_norm(p, 1, K) == N
True
In higher level functions that is:
>>> from sympy import expand, roots, minpoly
>>> from sympy.abc import x, y
>>> from math import prod
>>> a = sqrt(2)
>>> e = (x + y + a)
>>> e.as_poly([x, y], extension=a).norm()
Poly(x**2 + 2*x*y + y**2 - 2, x, y, domain='QQ')
This is equal to the product of the expressions `x + y + a_i` where the
`a_i` are the conjugates of `a`:
>>> pa = minpoly(a)
>>> pa
_x**2 - 2
>>> rs = roots(pa, multiple=True)
>>> rs
[sqrt(2), -sqrt(2)]
>>> n = prod(e.subs(a, r) for r in rs)
>>> n
(x + y - sqrt(2))*(x + y + sqrt(2))
>>> expand(n)
x**2 + 2*x*y + y**2 - 2
Explanation
===========
Given an algebraic number field `K = k(a)` any element `b` of `K` can be
represented as polynomial function `b=g(a)` where `g` is in `k[x]`. If the
minimal polynomial of `a` over `k` is `p_a` then the roots `a_1`, `a_2`,
`\cdots` of `p_a(x)` are the conjugates of `a`. The norm of `b` is the
product `g(a1) \times g(a2) \times \cdots` and is an element of `k`.
As in [Trager76]_ we extend this norm to multivariate polynomials over `K`.
If `b(x)` is a polynomial in `k(a)[X]` then we can think of `b` as being
alternately a function `g_X(a)` where `g_X` is an element of `k[X][y]` i.e.
a polynomial function with coefficients that are elements of `k[X]`. Then
the norm of `b` is the product `g_X(a1) \times g_X(a2) \times \cdots` and
will be an element of `k[X]`.
See Also
========
dmp_sqf_norm:
Compute a shift of `f` so that the `\text{Norm}(f)` is square-free.
sympy.polys.polytools.Poly.norm:
Higher-level function that calls this.
"""
if not K.is_Algebraic:
raise DomainError("ground domain must be algebraic")
g = dmp_raise(K.mod.to_list(), u + 1, 0, K.dom)
h, _ = dmp_inject(f, u, K, front=True)
return dmp_resultant(g, h, u + 1, K.dom)
def dup_gf_sqf_part(f, K):
"""Compute square-free part of ``f`` in ``GF(p)[x]``. """
f = dup_convert(f, K, K.dom)
g = gf_sqf_part(f, K.mod, K.dom)
return dup_convert(g, K.dom, K)
def dmp_gf_sqf_part(f, u, K):
"""Compute square-free part of ``f`` in ``GF(p)[X]``. """
raise NotImplementedError('multivariate polynomials over finite fields')
def dup_sqf_part(f, K):
"""
Returns square-free part of a polynomial in ``K[x]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x = ring("x", ZZ)
>>> R.dup_sqf_part(x**3 - 3*x - 2)
x**2 - x - 2
See Also
========
sympy.polys.polytools.Poly.sqf_part
"""
if K.is_FiniteField:
return dup_gf_sqf_part(f, K)
if not f:
return f
if K.is_negative(dup_LC(f, K)):
f = dup_neg(f, K)
gcd = dup_gcd(f, dup_diff(f, 1, K), K)
sqf = dup_quo(f, gcd, K)
if K.is_Field:
return dup_monic(sqf, K)
else:
return dup_primitive(sqf, K)[1]
def dmp_sqf_part(f, u, K):
"""
Returns square-free part of a polynomial in ``K[X]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_sqf_part(x**3 + 2*x**2*y + x*y**2)
x**2 + x*y
"""
if not u:
return dup_sqf_part(f, K)
if K.is_FiniteField:
return dmp_gf_sqf_part(f, u, K)
if dmp_zero_p(f, u):
return f
if K.is_negative(dmp_ground_LC(f, u, K)):
f = dmp_neg(f, u, K)
gcd = f
for i in range(u+1):
gcd = dmp_gcd(gcd, dmp_diff_in(f, 1, i, u, K), u, K)
sqf = dmp_quo(f, gcd, u, K)
if K.is_Field:
return dmp_ground_monic(sqf, u, K)
else:
return dmp_ground_primitive(sqf, u, K)[1]
def dup_gf_sqf_list(f, K, all=False):
"""Compute square-free decomposition of ``f`` in ``GF(p)[x]``. """
f_orig = f
f = dup_convert(f, K, K.dom)
coeff, factors = gf_sqf_list(f, K.mod, K.dom, all=all)
for i, (f, k) in enumerate(factors):
factors[i] = (dup_convert(f, K.dom, K), k)
_dup_check_degrees(f_orig, factors)
return K.convert(coeff, K.dom), factors
def dmp_gf_sqf_list(f, u, K, all=False):
"""Compute square-free decomposition of ``f`` in ``GF(p)[X]``. """
raise NotImplementedError('multivariate polynomials over finite fields')
def dup_sqf_list(f, K, all=False):
"""
Return square-free decomposition of a polynomial in ``K[x]``.
Uses Yun's algorithm from [Yun76]_.
Examples
========
>>> from sympy.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(f)
(2, [(x + 1, 2), (x + 2, 3)])
>>> R.dup_sqf_list(f, all=True)
(2, [(1, 1), (x + 1, 2), (x + 2, 3)])
See Also
========
dmp_sqf_list:
Corresponding function for multivariate polynomials.
sympy.polys.polytools.sqf_list:
High-level function for square-free factorization of expressions.
sympy.polys.polytools.Poly.sqf_list:
Analogous method on :class:`~.Poly`.
References
==========
[Yun76]_
"""
if K.is_FiniteField:
return dup_gf_sqf_list(f, K, all=all)
f_orig = f
if K.is_Field:
coeff = dup_LC(f, K)
f = dup_monic(f, K)
else:
coeff, f = dup_primitive(f, K)
if K.is_negative(dup_LC(f, K)):
f = dup_neg(f, K)
coeff = -coeff
if dup_degree(f) <= 0:
return coeff, []
result, i = [], 1
h = dup_diff(f, 1, K)
g, p, q = dup_inner_gcd(f, h, K)
while True:
d = dup_diff(p, 1, K)
h = dup_sub(q, d, K)
if not h:
result.append((p, i))
break
g, p, q = dup_inner_gcd(p, h, K)
if all or dup_degree(g) > 0:
result.append((g, i))
i += 1
_dup_check_degrees(f_orig, result)
return coeff, result
def dup_sqf_list_include(f, K, all=False):
"""
Return square-free decomposition of a polynomial in ``K[x]``.
Examples
========
>>> from sympy.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 dmp_sqf_list(f, u, K, all=False):
"""
Return square-free decomposition of a polynomial in `K[X]`.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> f = x**5 + 2*x**4*y + x**3*y**2
>>> R.dmp_sqf_list(f)
(1, [(x + y, 2), (x, 3)])
>>> R.dmp_sqf_list(f, all=True)
(1, [(1, 1), (x + y, 2), (x, 3)])
Explanation
===========
Uses Yun's algorithm for univariate polynomials from [Yun76]_ recrusively.
The multivariate polynomial is treated as a univariate polynomial in its
leading variable. Then Yun's algorithm computes the square-free
factorization of the primitive and the content is factored recursively.
It would be better to use a dedicated algorithm for multivariate
polynomials instead.
See Also
========
dup_sqf_list:
Corresponding function for univariate polynomials.
sympy.polys.polytools.sqf_list:
High-level function for square-free factorization of expressions.
sympy.polys.polytools.Poly.sqf_list:
Analogous method on :class:`~.Poly`.
"""
if not u:
return dup_sqf_list(f, K, all=all)
if K.is_FiniteField:
return dmp_gf_sqf_list(f, u, K, all=all)
f_orig = f
if K.is_Field:
coeff = dmp_ground_LC(f, u, K)
f = dmp_ground_monic(f, u, K)
else:
coeff, f = dmp_ground_primitive(f, u, K)
if K.is_negative(dmp_ground_LC(f, u, K)):
f = dmp_neg(f, u, K)
coeff = -coeff
deg = dmp_degree(f, u)
if deg < 0:
return coeff, []
# Yun's algorithm requires the polynomial to be primitive as a univariate
# polynomial in its main variable.
content, f = dmp_primitive(f, u, K)
result = {}
if deg != 0:
h = dmp_diff(f, 1, u, K)
g, p, q = dmp_inner_gcd(f, h, u, K)
i = 1
while True:
d = dmp_diff(p, 1, u, K)
h = dmp_sub(q, d, u, K)
if dmp_zero_p(h, u):
result[i] = p
break
g, p, q = dmp_inner_gcd(p, h, u, K)
if all or dmp_degree(g, u) > 0:
result[i] = g
i += 1
coeff_content, result_content = dmp_sqf_list(content, u-1, K, all=all)
coeff *= coeff_content
# Combine factors of the content and primitive part that have the same
# multiplicity to produce a list in ascending order of multiplicity.
for fac, i in result_content:
fac = [fac]
if i in result:
result[i] = dmp_mul(result[i], fac, u, K)
else:
result[i] = fac
result = [(result[i], i) for i in sorted(result)]
_dmp_check_degrees(f_orig, u, result)
return coeff, result
def dmp_sqf_list_include(f, u, K, all=False):
"""
Return square-free decomposition of a polynomial in ``K[x]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> f = x**5 + 2*x**4*y + x**3*y**2
>>> R.dmp_sqf_list_include(f)
[(1, 1), (x + y, 2), (x, 3)]
>>> R.dmp_sqf_list_include(f, all=True)
[(1, 1), (x + y, 2), (x, 3)]
"""
if not u:
return dup_sqf_list_include(f, K, all=all)
coeff, factors = dmp_sqf_list(f, u, K, all=all)
if factors and factors[0][1] == 1:
g = dmp_mul_ground(factors[0][0], coeff, u, K)
return [(g, 1)] + factors[1:]
else:
g = dmp_ground(coeff, u)
return [(g, 1)] + factors
def dup_gff_list(f, K):
"""
Compute greatest factorial factorization of ``f`` in ``K[x]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x = ring("x", ZZ)
>>> R.dup_gff_list(x**5 + 2*x**4 - x**3 - 2*x**2)
[(x, 1), (x + 2, 4)]
"""
if not f:
raise ValueError("greatest factorial factorization doesn't exist for a zero polynomial")
f = dup_monic(f, K)
if not dup_degree(f):
return []
else:
g = dup_gcd(f, dup_shift(f, K.one, K), K)
H = dup_gff_list(g, K)
for i, (h, k) in enumerate(H):
g = dup_mul(g, dup_shift(h, -K(k), K), K)
H[i] = (h, k + 1)
f = dup_quo(f, g, K)
if not dup_degree(f):
return H
else:
return [(f, 1)] + H
def dmp_gff_list(f, u, K):
"""
Compute greatest factorial factorization of ``f`` in ``K[X]``.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
"""
if not u:
return dup_gff_list(f, K)
else:
raise MultivariatePolynomialError(f)
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