本文整理汇总了Python中sympy.polys.distributedpolys.sdp_LM函数的典型用法代码示例。如果您正苦于以下问题:Python sdp_LM函数的具体用法?Python sdp_LM怎么用?Python sdp_LM使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了sdp_LM函数的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的Python代码示例。
示例1: matrix_fglm
def matrix_fglm(F, u, O_from, O_to, K):
"""
Converts the reduced Groebner basis ``F`` of a zero-dimensional
ideal w.r.t. ``O_from`` to a reduced Groebner basis
w.r.t. ``O_to``.
**References**
J.C. Faugere, P. Gianni, D. Lazard, T. Mora (1994). Efficient
Computation of Zero-dimensional Groebner Bases by Change of
Ordering
J.C. Faugere's lecture notes:
http://www-salsa.lip6.fr/~jcf/Papers/2010_MPRI5e.pdf
"""
old_basis = _basis(F, u, O_from, K)
M = _representing_matrices(old_basis, F, u, O_from, K)
# V contains the normalforms (wrt O_from) of S
S = [(0,) * (u + 1)]
V = [[K.one] + [K.zero] * (len(old_basis) - 1)]
G = []
L = [(i, 0) for i in xrange(u + 1)] # (i, j) corresponds to x_i * S[j]
L.sort(key=lambda (k, l): O_to(_incr_k(S[l], k)), reverse=True)
t = L.pop()
P = _identity_matrix(len(old_basis), K)
while True:
s = len(S)
v = _matrix_mul(M[t[0]], V[t[1]], K)
_lambda = _matrix_mul(P, v, K)
if all(_lambda[i] == K.zero for i in xrange(s, len(old_basis))):
# there is a linear combination of v by V
lt = [(_incr_k(S[t[1]], t[0]), K.one)]
rest = sdp_strip(sdp_sort([(S[i], _lambda[i]) for i in xrange(s)], O_to))
g = sdp_sub(lt, rest, u, O_to, K)
if g != []:
G.append(g)
else:
# v is linearly independant from V
P = _update(s, _lambda, P, K)
S.append(_incr_k(S[t[1]], t[0]))
V.append(v)
L.extend([(i, s) for i in xrange(u + 1)])
L = list(set(L))
L.sort(key=lambda (k, l): O_to(_incr_k(S[l], k)), reverse=True)
L = [(k, l) for (k, l) in L if all(monomial_div(_incr_k(S[l], k), sdp_LM(g, u)) is None for g in G)]
if not L:
G = [sdp_monic(g, K) for g in G]
return sorted(G, key=lambda g: O_to(sdp_LM(g, u)), reverse=True)
t = L.pop()
开发者ID:nvlrules,项目名称:sympy,代码行数:60,代码来源:groebnertools.py
示例2: red_groebner
def red_groebner(G, u, O, K):
"""
Compute reduced Groebner basis, from BeckerWeispfenning93, p. 216
Selects a subset of generators, that already generate the ideal
and computes a reduced Groebner basis for them.
"""
def reduction(P, u, O, K):
"""
The actual reduction algorithm.
"""
Q = []
for i, p in enumerate(P):
h = sdp_rem(p, P[:i] + P[i + 1 :], u, O, K)
if h != []:
Q.append(h)
return [sdp_monic(p, K) for p in Q]
F = G
H = []
while F:
f0 = F.pop()
if not any(monomial_divides(sdp_LM(f0, u), sdp_LM(f, u)) for f in F + H):
H.append(f0)
# Becker, Weispfenning, p. 217: H is Groebner basis of the ideal generated by G.
return reduction(H, u, O, K)
开发者ID:nvlrules,项目名称:sympy,代码行数:31,代码来源:groebnertools.py
示例3: is_zero_dimensional
def is_zero_dimensional(F, u, O, K):
"""
Checks if the ideal generated by ``F`` is zero-dimensional.
The algorithm checks if the set of monomials not divisible by a
leading monomial of any element of ``F`` is bounded. In general
``F`` has to be a Groebner basis w.r.t. ``O`` but if ``True``
is returned, then the ideal is zero-dimensional.
**References**
David A. Cox, John B. Little, Donal O'Shea. Ideals, Varieties
and Algorithms, 3rd edition, p. 234
"""
def single_var(m):
n = 0
for e in m:
if e != 0:
n += 1
return n == 1
exponents = (0,) * (u + 1)
for f in F:
if single_var(sdp_LM(f, u)):
exponents = monomial_mul(exponents, sdp_LM(f, O)) # == sum of exponent vectors
product = 1
for e in exponents:
product *= e
# If product == 0, then there's a variable for which there's
# no degree bound.
return product != 0
开发者ID:lazovich,项目名称:sympy,代码行数:33,代码来源:groebnertools.py
示例4: f5_reduce
def f5_reduce(f, B, u, O, K):
"""
F5-reduce a labeled polynomial f by B.
Continously searches for non-zero labeled polynomial h in B, such
that the leading term lt_h of h divides the leading term lt_f of
f and Sign(lt_h * h) < Sign(f). If such a labeled polynomial h is
found, f gets replaced by f - lt_f / lt_h * h. If no such h can be
found or f is 0, f is no further F5-reducible and f gets returned.
A polynomial that is reducible in the usual sense (sdp_rem)
need not be F5-reducible, e.g.:
>>> from sympy.polys.groebnertools import lbp, sig, f5_reduce, Polyn
>>> from sympy.polys.distributedpolys import sdp_rem
>>> from sympy.polys.monomialtools import lex
>>> from sympy import QQ
>>> f = lbp(sig((1, 1, 1), 4), [((1, 0, 0), QQ(1))], 3)
>>> g = lbp(sig((0, 0, 0), 2), [((1, 0, 0), QQ(1))], 2)
>>> sdp_rem(Polyn(f), [Polyn(g)], 2, lex, QQ)
[]
>>> f5_reduce(f, [g], 2, lex, QQ)
(((1, 1, 1), 4), [((1, 0, 0), 1/1)], 3)
"""
if Polyn(f) == []:
return f
if K.has_Field:
term_div = _term_ff_div
else:
term_div = _term_rr_div
while True:
g = f
for h in B:
if Polyn(h) != []:
if monomial_divides(sdp_LM(Polyn(f), u), sdp_LM(Polyn(h), u)):
t = term_div(
sdp_LT(Polyn(f), u, K), sdp_LT(Polyn(h), u, K), K)
if sig_cmp(sig_mult(Sign(h), t[0]), Sign(f), O) < 0:
# The following check need not be done and is in general slower than without.
#if not is_rewritable_or_comparable(Sign(gp), Num(gp), B, u, K):
hp = lbp_mul_term(h, t, u, O, K)
f = lbp_sub(f, hp, u, O, K)
break
if g == f or Polyn(f) == []:
return f
开发者ID:FireJade,项目名称:sympy,代码行数:52,代码来源:groebnertools.py
示例5: is_minimal
def is_minimal(G, u, O, K):
"""
Checks if G is a minimal Groebner basis.
"""
G.sort(key=lambda g: O(sdp_LM(g, u)))
for i, g in enumerate(G):
if sdp_LC(g, K) != K.one:
return False
for h in G[:i] + G[i + 1 :]:
if monomial_divides(sdp_LM(g, u), sdp_LM(h, u)):
return False
return True
开发者ID:nvlrules,项目名称:sympy,代码行数:14,代码来源:groebnertools.py
示例6: sdp_spoly
def sdp_spoly(p1, p2, u, O, K):
"""
Compute LCM(LM(p1), LM(p2))/LM(p1)*p1 - LCM(LM(p1), LM(p2))/LM(p2)*p2
This is the S-poly provided p1 and p2 are monic
"""
LM1 = sdp_LM(p1, u)
LM2 = sdp_LM(p2, u)
LCM12 = monomial_lcm(LM1, LM2)
m1 = monomial_div(LCM12, LM1)
m2 = monomial_div(LCM12, LM2)
s1 = sdp_mul_term(p1, (m1, K.one), u, O, K)
s2 = sdp_mul_term(p2, (m2, K.one), u, O, K)
s = sdp_sub(s1, s2, u, O, K)
return s
开发者ID:nvlrules,项目名称:sympy,代码行数:14,代码来源:groebnertools.py
示例7: _basis
def _basis(G, u, O, K):
"""
Computes a list of monomials which are not divisible by the leading
monomials wrt to ``O`` of ``G``. These monomials are a basis of
`K[X_1, \ldots, X_n]/(G)`.
"""
leading_monomials = [sdp_LM(g, u) for g in G]
candidates = [(0,) * (u + 1)]
basis = []
while candidates:
t = candidates.pop()
basis.append(t)
new_candidates = [
_incr_k(t, k)
for k in xrange(u + 1)
if all(monomial_div(_incr_k(t, k), lmg) is None for lmg in leading_monomials)
]
candidates.extend(new_candidates)
candidates.sort(key=lambda m: O(m), reverse=True)
basis = list(set(basis))
return sorted(basis, key=lambda m: O(m))
开发者ID:nvlrules,项目名称:sympy,代码行数:25,代码来源:groebnertools.py
示例8: is_rewritable_or_comparable
def is_rewritable_or_comparable(sign, num, B, u, K):
"""
Check if a labeled polynomial is redundant by checking if its
signature and number imply rewritability or comparability.
(sign, num) is comparable if there exists a labeled polynomial
h in B, such that sign[1] (the index) is less than Sign(h)[1]
and sign[0] is divisible by the leading monomial of h.
(sign, num) is rewritable if there exists a labeled polynomial
h in B, such thatsign[1] is equal to Sign(h)[1], num < Num(h)
and sign[0] is divisible by Sign(h)[0].
"""
for h in B:
# comparable
if sign[1] < Sign(h)[1]:
if monomial_divides(sign[0], sdp_LM(Polyn(h), u)):
return True
# rewritable
if sign[1] == Sign(h)[1]:
if num < Num(h):
if monomial_divides(sign[0], Sign(h)[0]):
return True
return False
开发者ID:nvlrules,项目名称:sympy,代码行数:25,代码来源:groebnertools.py
示例9: normal
def normal(g, J):
h = sdp_rem(g, [f[j] for j in J], u, O, K)
if not h:
return None
else:
h = sdp_monic(h, K)
h = tuple(h)
if not h in I:
I[h] = len(f)
f.append(h)
return sdp_LM(h, u), I[h]
开发者ID:nvlrules,项目名称:sympy,代码行数:14,代码来源:groebnertools.py
示例10: test_sdp_LM
def test_sdp_LM():
assert sdp_LM([], 1) == (0, 0)
assert sdp_LM([((1, 0), QQ(1, 2))], 1) == (1, 0)
assert sdp_LM([((1, 1), QQ(1, 4)), ((1, 0), QQ(1, 2))], 1) == (1, 1)
开发者ID:FireJade,项目名称:sympy,代码行数:4,代码来源:test_distributedpolys.py
示例11: select
def select(P):
# normal selection strategy
# select the pair with minimum LCM(LM(f), LM(g))
pr = min(P, key=lambda pair: O(monomial_lcm(sdp_LM(f[pair[0]], u), sdp_LM(f[pair[1]], u))))
return pr
开发者ID:nvlrules,项目名称:sympy,代码行数:5,代码来源:groebnertools.py
示例12: f5b
def f5b(F, u, O, K, gens="", verbose=False):
"""
Computes a reduced Groebner basis for the ideal generated by F.
f5b is an implementation of the F5B algorithm by Yao Sun and
Dingkang Wang. Similarly to Buchberger's algorithm, the algorithm
proceeds by computing critical pairs, computing the S-polynomial,
reducing it and adjoining the reduced S-polynomial if it is not 0.
Unlike Buchberger's algorithm, each polynomial contains additional
information, namely a signature and a number. The signature
specifies the path of computation (i.e. from which polynomial in
the original basis was it derived and how), the number says when
the polynomial was added to the basis. With this information it
is (often) possible to decide if an S-polynomial will reduce to
0 and can be discarded.
Optimizations include: Reducing the generators before computing
a Groebner basis, removing redundant critical pairs when a new
polynomial enters the basis and sorting the critical pairs and
the current basis.
Once a Groebner basis has been found, it gets reduced.
** References **
Yao Sun, Dingkang Wang: "A New Proof for the Correctness of F5
(F5-Like) Algorithm", http://arxiv.org/abs/1004.0084 (specifically
v4)
Thomas Becker, Volker Weispfenning, Groebner bases: A computational
approach to commutative algebra, 1993, p. 203, 216
"""
if not K.has_Field:
raise DomainError("can't compute a Groebner basis over %s" % K)
# reduce polynomials (like in Mario Pernici's implementation) (Becker, Weispfenning, p. 203)
B = F
while True:
F = B
B = []
for i in xrange(len(F)):
p = F[i]
r = sdp_rem(p, F[:i], u, O, K)
if r != []:
B.append(r)
if F == B:
break
# basis
B = [lbp(sig((0,) * (u + 1), i + 1), F[i], i + 1) for i in xrange(len(F))]
B.sort(key=lambda f: O(sdp_LM(Polyn(f), u)), reverse=True)
# critical pairs
CP = [critical_pair(B[i], B[j], u, O, K) for i in xrange(len(B)) for j in xrange(i + 1, len(B))]
CP.sort(key=lambda cp: cp_key(cp, O), reverse=True)
k = len(B)
reductions_to_zero = 0
while len(CP):
cp = CP.pop()
# discard redundant critical pairs:
if is_rewritable_or_comparable(cp[0], Num(cp[2]), B, u, K):
continue
if is_rewritable_or_comparable(cp[3], Num(cp[5]), B, u, K):
continue
s = s_poly(cp, u, O, K)
p = f5_reduce(s, B, u, O, K)
p = lbp(Sign(p), sdp_monic(Polyn(p), K), k + 1)
if Polyn(p) != []:
# remove old critical pairs, that become redundant when adding p:
indices = []
for i, cp in enumerate(CP):
if is_rewritable_or_comparable(cp[0], Num(cp[2]), [p], u, K):
indices.append(i)
elif is_rewritable_or_comparable(cp[3], Num(cp[5]), [p], u, K):
indices.append(i)
for i in reversed(indices):
del CP[i]
# only add new critical pairs that are not made redundant by p:
for g in B:
if Polyn(g) != []:
cp = critical_pair(p, g, u, O, K)
if is_rewritable_or_comparable(cp[0], Num(cp[2]), [p], u, K):
continue
elif is_rewritable_or_comparable(cp[3], Num(cp[5]), [p], u, K):
continue
CP.append(cp)
#.........这里部分代码省略.........
开发者ID:nvlrules,项目名称:sympy,代码行数:101,代码来源:groebnertools.py
示例13: buchberger
def buchberger(f, u, O, K, gens="", verbose=False):
"""
Computes Groebner basis for a set of polynomials in `K[X]`.
Given a set of multivariate polynomials `F`, finds another
set `G`, such that Ideal `F = Ideal G` and `G` is a reduced
Groebner basis.
The resulting basis is unique and has monic generators if the
ground domains is a field. Otherwise the result is non-unique
but Groebner bases over e.g. integers can be computed (if the
input polynomials are monic).
Groebner bases can be used to choose specific generators for a
polynomial ideal. Because these bases are unique you can check
for ideal equality by comparing the Groebner bases. To see if
one polynomial lies in an ideal, divide by the elements in the
base and see if the remainder vanishes.
They can also be used to solve systems of polynomial equations
as, by choosing lexicographic ordering, you can eliminate one
variable at a time, provided that the ideal is zero-dimensional
(finite number of solutions).
**References**
1. [Bose03]_
2. [Giovini91]_
3. [Ajwa95]_
4. [Cox97]_
Algorithm used: an improved version of Buchberger's algorithm
as presented in T. Becker, V. Weispfenning, Groebner Bases: A
Computational Approach to Commutative Algebra, Springer, 1993,
page 232.
Added optional ``gens`` argument to apply :func:`sdp_str` for
the purpose of debugging the algorithm.
"""
if not K.has_Field:
raise DomainError("can't compute a Groebner basis over %s" % K)
def select(P):
# normal selection strategy
# select the pair with minimum LCM(LM(f), LM(g))
pr = min(P, key=lambda pair: O(monomial_lcm(sdp_LM(f[pair[0]], u), sdp_LM(f[pair[1]], u))))
return pr
def normal(g, J):
h = sdp_rem(g, [f[j] for j in J], u, O, K)
if not h:
return None
else:
h = sdp_monic(h, K)
h = tuple(h)
if not h in I:
I[h] = len(f)
f.append(h)
return sdp_LM(h, u), I[h]
def update(G, B, ih):
# update G using the set of critical pairs B and h
# [BW] page 230
h = f[ih]
mh = sdp_LM(h, u)
# filter new pairs (h, g), g in G
C = G.copy()
D = set()
while C:
# select a pair (h, g) by popping an element from C
ig = C.pop()
g = f[ig]
mg = sdp_LM(g, u)
LCMhg = monomial_lcm(mh, mg)
def lcm_divides(ip):
# LCM(LM(h), LM(p)) divides LCM(LM(h), LM(g))
m = monomial_lcm(mh, sdp_LM(f[ip], u))
return monomial_div(LCMhg, m)
# HT(h) and HT(g) disjoint: mh*mg == LCMhg
if monomial_mul(mh, mg) == LCMhg or (
not any(lcm_divides(ipx) for ipx in C) and not any(lcm_divides(pr[1]) for pr in D)
):
D.add((ih, ig))
E = set()
while D:
# select h, g from D (h the same as above)
ih, ig = D.pop()
mg = sdp_LM(f[ig], u)
LCMhg = monomial_lcm(mh, mg)
#.........这里部分代码省略.........
开发者ID:nvlrules,项目名称:sympy,代码行数:101,代码来源:groebnertools.py
示例14: lcm_divides
def lcm_divides(ip):
# LCM(LM(h), LM(p)) divides LCM(LM(h), LM(g))
m = monomial_lcm(mh, sdp_LM(f[ip], u))
return monomial_div(LCMhg, m)
开发者ID:nvlrules,项目名称:sympy,代码行数:4,代码来源:groebnertools.py
示例15: update
def update(G, B, ih):
# update G using the set of critical pairs B and h
# [BW] page 230
h = f[ih]
mh = sdp_LM(h, u)
# filter new pairs (h, g), g in G
C = G.copy()
D = set()
while C:
# select a pair (h, g) by popping an element from C
ig = C.pop()
g = f[ig]
mg = sdp_LM(g, u)
LCMhg = monomial_lcm(mh, mg)
def lcm_divides(ip):
# LCM(LM(h), LM(p)) divides LCM(LM(h), LM(g))
m = monomial_lcm(mh, sdp_LM(f[ip], u))
return monomial_div(LCMhg, m)
# HT(h) and HT(g) disjoint: mh*mg == LCMhg
if monomial_mul(mh, mg) == LCMhg or (
not any(lcm_divides(ipx) for ipx in C) and not any(lcm_divides(pr[1]) for pr in D)
):
D.add((ih, ig))
E = set()
while D:
# select h, g from D (h the same as above)
ih, ig = D.pop()
mg = sdp_LM(f[ig], u)
LCMhg = monomial_lcm(mh, mg)
if not monomial_mul(mh, mg) == LCMhg:
E.add((ih, ig))
# filter old pairs
B_new = set()
while B:
# select g1, g2 from B (-> CP)
ig1, ig2 = B.pop()
mg1 = sdp_LM(f[ig1], u)
mg2 = sdp_LM(f[ig2], u)
LCM12 = monomial_lcm(mg1, mg2)
# if HT(h) does not divide lcm(HT(g1), HT(g2))
if not monomial_div(LCM12, mh) or monomial_lcm(mg1, mh) == LCM12 or monomial_lcm(mg2, mh) == LCM12:
B_new.add((ig1, ig2))
B_new |= E
# filter polynomials
G_new = set()
while G:
ig = G.pop()
mg = sdp_LM(f[ig], u)
if not monomial_div(mg, mh):
G_new.add(ig)
G_new.add(ih)
return G_new, B_new
开发者ID:nvlrules,项目名称:sympy,代码行数:68,代码来源:groebnertools.py
注:本文中的sympy.polys.distributedpolys.sdp_LM函数示例由纯净天空整理自Github/MSDocs等源码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。 |
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