def polygon_values(vertices):
vertices = normalize_vertices(vertices)
vertices_str = ",".join(repr(pt).replace(" ", "") for pt in vertices)
polygon = Polyhedron(vertices)
volume = float(polygon.volume())
points = polygon.integral_points()
num_points = len(points)
num_interior = len([pt for pt in points if polygon.interior_contains(pt)])
length = int(max(x for x, y in vertices))
width = int(max(y for x, y in vertices))
SymmQQ = polygon.restricted_automorphism_group(output="matrixlist")
if len(SymmQQ) == 1:
# Fast path for trivial symmetry group
symm = 1
else:
# Restrict symmetries to symmetries in GL(3, ZZ)
Symm = [s for s in SymmQQ if abs(s.determinant()) == 1 and all(x in ZZ for x in s.list())]
if all(s.determinant() > 0 for s in Symm):
symm = len(Symm)
else:
symm = -len(Symm)
return (vertices_str, len(vertices), volume,
num_points, num_interior, num_points - num_interior,
width, length, symm)
def inner_open_normal_fan(N):
"""
Construct the relatively open, inner normal fan of a lattice
polytope.
We approximate 'x > 0' via 'x >= 1', see the part on 'models' of half-open
cones in the second paper.
"""
if N.is_empty():
raise ValueError('need a non-empty polytope')
V = [vector(QQ, v) for v in N.vertices()]
if len(V) == 1:
# Confusingly, given an empty list of (in)equalities, Sage
# returns the empty polyhedron instead of the whole space.
yield Polyhedron(eqns=[(N.ambient_dim() + 1) * (0, )])
return
for face in N.face_lattice():
if face.dim() == -1:
continue
W = [vector(QQ, w) for w in face.vertices()]
eqns = [vector(QQ, [0] + list(W[0] - W[i])) for i in range(1, len(W))]
idx = [i for i in range(len(V)) if V[i] not in W]
ieqs = [vector(QQ, [-1] + list(V[i] - W[0])) for i in idx]
yield Polyhedron(ieqs=ieqs, eqns=eqns)
def padically_evaluate_regular(self, datum):
# Our integral is
# |y|^(s-1) * prod_v ||x^(v + weight) : weight in wt(v); y||^(-1).
if not datum.is_regular():
raise ValueError('need a regular datum')
n = self.nvertices
RS = RationalSet([datum.polyhedron]) * RationalSet(PositiveOrthant(1))
polytopes = [Polyhedron(vertices=[vector(ZZ, n * [0] + [1])])]
I = identity_matrix(ZZ, n)
vertices = [[vector(ZZ, n * [0] + [1])]
for _ in range(n)] # y appears in each factor
for i, (u, v) in enumerate(datum.edges):
assert u == v and u in range(n)
vertices[u].append(vector(ZZ, list(I[u] + datum.weights[i]) + [0]))
for v in vertices:
polytopes.append(Polyhedron(vertices=v))
for z in padically_evaluate_monomial_integral(RS, polytopes,
[(1, ) + n * (0, ),
(n + 1) * (1, )]):
yield z
def relative_initial_forms(F, polyhedron=None, split=True):
if not F:
raise ValueError('need non-empty collection of polynomials')
if split:
G, d, A = split_off_torus(F)
N = sum(g.newton_polytope() for g in G)
n = A.nrows()
else:
N = sum(f.newton_polytope() for f in F)
n = N.ambient_dim()
if polyhedron is None:
polyhedron = Polyhedron(ieqs=[(n + 1) * (0, )])
for Q in inner_open_normal_fan(N):
if split:
Q = linear_image_of_polyhedron(
DirectProductOfPolyhedra(
Q, Polyhedron(ieqs=[(n - d + 1) * (0, )])), A.transpose())
Q &= polyhedron
if Q.dim() == -1:
continue
y = get_point_in_polyhedron(Q)
yield [initial_form_by_direction(f, y) for f in F], Q
def StrictlyPositiveOrthant(d):
if d == 0:
return Polyhedron(ambient_dim=0, vertices=[()], base_ring=QQ)
else:
return Polyhedron(ieqs=block_matrix([[
matrix(QQ, d, 1, [-1 for i in range(d)]),
identity_matrix(QQ, d)
]]))
def linear_image_of_polyhedron(P, A):
if A.nrows() != P.ambient_dim():
raise ValueError('matrix does not act on ambient space of polyhedra')
return Polyhedron(ambient_dim=P.ambient_dim(),
vertices=[vector(v) * A for v in P.vertices()],
rays=[vector(r) * A for r in P.rays()],
lines=[vector(l) * A for l in P.lines()])
def DirectProductOfPolyhedra(P, Q):
m = P.ambient_dim()
n = Q.ambient_dim()
ieqs = []
eqns = [(n + m + 1) * (0, )] # ensures correctness when P == RR^m, Q==RR^n
# [b | a] --> [b | a | 0]
def f(v):
return v + n * [0]
# [b | a] --> [b | 0 | a]
def g(v):
return [v[0]] + m * [0] + v[1:]
for i in P.inequalities():
ieqs.append(f(list(i)))
for i in Q.inequalities():
ieqs.append(g(list(i)))
for e in P.equations():
eqns.append(f(list(e)))
for e in Q.equations():
eqns.append(g(list(e)))
return Polyhedron(ieqs=ieqs, eqns=eqns, base_ring=QQ, ambient_dim=m + n)
def plot(self):
"""
EXAMPLES::
sage: UnitCubeTriangulation(3).plot()
"""
return sum(
Polyhedron(simplex).plot() for simplex in self.simplex_iter())
def padically_evaluate_regular(self, datum):
T = datum.toric_datum
if not T.is_regular():
raise ValueError('Can only processed regular toric data')
M = Set(range(T.length()))
q = SR.var('q')
alpha = {}
for I in Subsets(M):
F = [T.initials[i] for i in I]
V = SubvarietyOfTorus(F, torus_dim=T.ambient_dim)
alpha[I] = V.count()
def cat(u, v):
return vector(list(u) + list(v))
for I in Subsets(M):
cnt = sum((-1)**len(J) * alpha[I + J] for J in Subsets(M - I))
if not cnt:
continue
P = DirectProductOfPolyhedra(T.polyhedron,
StrictlyPositiveOrthant(len(I)))
it = iter(identity_matrix(ZZ, len(I)).rows())
ieqs = []
for i in M:
ieqs.append(
cat(
vector(ZZ, (0, )),
cat(
vector(ZZ, T.initials[i].exponents()[0]) -
vector(ZZ, T.lhs[i].exponents()[0]),
next(it) if i in I else zero_vector(ZZ, len(I)))))
if not ieqs:
ieqs = [vector(ZZ, (T.ambient_dim + len(I) + 1) * [0])]
Q = Polyhedron(ieqs=ieqs,
base_ring=QQ,
ambient_dim=T.ambient_dim + len(I))
foo, ring = symbolic_to_ratfun(
cnt * (q - 1)**len(I) / q**(T.ambient_dim),
[var('t'), var('q')])
corr_cnt = CyclotomicRationalFunction.from_laurent_polynomial(
foo, ring)
Phi = matrix([
cat(T.integrand[0], zero_vector(ZZ, len(I))),
cat(T.integrand[1], vector(ZZ,
len(I) * [-1]))
]).transpose()
sm = RationalSet([P.intersection(Q)]).generating_function()
for z in sm.monomial_substitution(QQ['t', 'q'], Phi):
yield corr_cnt * z
def dual_cone_as_polyhedron(rays, strict=False):
"""
Compute the polyhedron consisting of all y such that
r * y >= 0 (or r * y > 0 if strict=True) for r in rays.
"""
if not rays:
raise TypeError('Need at least one ray')
c = Integer(-1) if strict else ZZ.zero()
return Polyhedron(ieqs=[[c] + list(v) for v in rays], base_ring=QQ)
def solve(self):
"""
Builds a classic convex polyhedron over vts and
returns a set of constraints (i.e. the facets of the polyhedron)
"""
ts = [t for t in self.terms if t != 1]
logger.debug('Create vertices from {} traces'.format(len(self.tcs)))
vts = [[QQ(t.subs(tc)) for t in ts] for tc in self.tcs]
vts = map(list, set(map(tuple, vts))) # make these vts unique
logger.debug('Build (gen CL) poly from {} vts in {} dims: {}'.format(
len(vts), len(vts[0]), ts))
poly = Polyhedron(vertices=vts, base_ring=QQ)
try:
rs = [list(p.vector()) for p in poly.inequality_generator()]
logger.debug('Sage: found {} inequalities'.format(len(rs)))
# remove rs of form [const_c, 0 , ..., 0]
# because those translate to the trivial form 'const_c >= 0'
rs = [s for s in rs if any(x != 0 for x in s[1:])]
except AttributeError:
logger.warn('Sage: cannot construct polyhedron')
rs = []
if rs:
# parse the result
def _f(s):
return s[0] + sum(map(prod, zip(s[1:], ts)))
rs = [_f(s) >= 0 for s in rs]
# remove trivial (tautology) str(x) <=> str(x)
rs = [
s for s in rs
if not (s.is_relational() and str(s.lhs()) == str(s.rhs()))
]
self.sols = map(InvIeq, rs)
def topologically_evaluate_regular(self, datum):
if not datum.is_regular():
raise ValueError('need a regular datum')
euler_cap = {}
torus_factor_dim = {}
N = Set(range(len(datum.polynomials)))
_, d, _ = split_off_torus([datum.initials[i].num for i in N])
min_dim = datum.ambient_dim - d
# NOTE: triangulation/"topologisation" of RationalSet instances only
# considers cones of maximal dimension.
if datum.RS.dim() <= min_dim - 2:
return
yield
if datum.RS.dim() >= min_dim:
raise RuntimeError('this should be impossible')
for I in Subsets(N):
F = [datum.initials[i].num for i in I]
V = SubvarietyOfTorus(F, torus_dim=datum.ambient_dim)
U,W = V.split_off_torus()
torus_factor_dim[I] = W.torus_dim
assert torus_factor_dim[I] >= min_dim
if W.torus_dim > min_dim:
continue
euler_cap[I] = U.khovanskii_characteristic() if U.is_nondegenerate() else U.euler_characteristic()
for I in Subsets(N):
chi = sum((-1)**len(J) * euler_cap[I + J] for J in Subsets(N - I)
if torus_factor_dim[I + J] == min_dim)
if not chi:
continue
I = list(I)
id = identity_matrix(ZZ, len(I))
def vectorise(first, k, vec):
w = id[I.index(k)] if k in I else vector(ZZ,len(I))
return vector(ZZ, [first] + list(vec) + list(w))
polytopes = []
for (i, j) in self.pairs:
vertices = [vectorise(0, k, datum.ideals[i].initials[m].exponents()[0]) for m, k in enumerate(datum._ideal2poly[i])] +\
[vectorise(1, k, datum.ideals[j].initials[m].exponents()[0]) for m, k in enumerate(datum._ideal2poly[j])]
polytopes.append(Polyhedron(vertices=vertices, ambient_dim=1+datum.ambient_dim + len(I)))
extended_RS = (RationalSet(StrictlyPositiveOrthant(1)) * datum.RS *
RationalSet(StrictlyPositiveOrthant(len(I))))
for surf in topologically_evaluate_monomial_integral(extended_RS, polytopes,
self.integrand, dims=[min_dim+len(I)]):
yield SURF(scalar=chi*surf.scalar, rays=surf.rays)
def solve(self):
"""
Builds a classic convex polyhedron over vts and
returns a set of constraints (i.e. the facets of the polyhedron)
"""
ts = [t for t in self.terms if t != 1]
logger.debug('Create vertices from {} traces'
.format(len(self.tcs)))
vts = [[QQ(t.subs(tc)) for t in ts] for tc in self.tcs]
vts = map(list,set(map(tuple,vts))) #make these vts unique
logger.debug('Build (gen CL) poly from {} vts in {} dims: {}'
.format(len(vts),len(vts[0]),ts))
poly = Polyhedron(vertices=vts,base_ring=QQ)
try:
rs = [list(p.vector()) for p in poly.inequality_generator()]
logger.debug('Sage: found {} inequalities'.format(len(rs)))
#remove rs of form [const_c, 0 , ..., 0]
#because those translate to the trivial form 'const_c >= 0'
rs = [s for s in rs if any(x != 0 for x in s[1:])]
except AttributeError:
logger.warn('Sage: cannot construct polyhedron')
rs = []
if rs:
#parse the result
_f = lambda s: s[0] + sum(map(prod,zip(s[1:],ts)))
rs = [_f(s) >= 0 for s in rs]
#remove trivial (tautology) str(x) <=> str(x)
rs = [s for s in rs
if not (s.is_relational()
and str(s.lhs()) == str(s.rhs()))]
self.sols = map(InvIeq,rs)
def is_weak_fano(Delta):
"""
Check whether Delta is a (weak) Fano polytope.
OUTPUT:
- 2 if Fano
- 1 if weak Fano
- 0 if not weak Fano
"""
N = normal_vertices(Delta)
Normal = Polyhedron(vertices=N)
if len(interior_points(Normal)) == 1:
# Weak Fano => Fano iff all elements of N
# are vertices
if Normal.n_vertices() == len(N):
return 2
else:
return 1
return 0
def padically_evaluate_regular(self, datum):
A = self.A
n = self.nvertices
m = self.nedges
RS = RationalSet(PositiveOrthant(n + 1))
polytopes = [Polyhedron(vertices=[vector(ZZ, n * [0] + [1])])]
I = list(identity_matrix(ZZ, n + 1))
for j in range(m):
vertices = [vector(ZZ, n * [0] + [1])]
for i, a in enumerate(A.column(j)):
if a == 1:
vertices.append(I[i])
polytopes.append(Polyhedron(vertices=vertices))
for z in padically_evaluate_monomial_integral(RS, polytopes,
[(1, ) + m * (0, ),
(m + 1) * (1, )]):
yield z
def topologically_evaluate_regular(self, datum):
if not datum.is_regular():
raise ValueError('need a regular datum')
euler_cap = {}
torus_factor_dim = {}
N = Set(range(len(datum.polynomials)))
_, d, _ = split_off_torus([datum.initials[i].num for i in N])
min_dim = datum.ambient_dim - d
if datum.RS.dim() < min_dim:
logger.debug('Totally irrelevant datum')
return
yield
for I in Subsets(N):
F = [datum.initials[i].num for i in I]
V = SubvarietyOfTorus(F, torus_dim=datum.ambient_dim)
U,W = V.split_off_torus()
torus_factor_dim[I] = W.torus_dim
euler_cap[I] = U.khovanskii_characteristic() if U.is_nondegenerate() else U.euler_characteristic()
assert torus_factor_dim[I] >= min_dim
for I in Subsets(N):
chi = sum((-1)**len(J) * euler_cap[I+J] for J in Subsets(N-I) if torus_factor_dim[I+J] == min_dim)
if not chi:
logger.debug('Vanishing Euler characteristic: I = %s' % I)
continue
I = list(I)
polytopes = []
id = identity_matrix(ZZ, len(I))
def vectorise(k, vec):
w = id[I.index(k)] if k in I else vector(ZZ,len(I))
return vector(ZZ, list(vec) + list(w))
assert len(datum._ideal2poly[0]) == len(datum.ideals[0].gens)
polytopes = [Polyhedron(vertices=[vectorise(k, datum.ideals[0].initials[m].exponents()[0]) for m,k in enumerate(datum._ideal2poly[0])],
ambient_dim=datum.ambient_dim+len(I))]
extended_RS = datum.RS * RationalSet(StrictlyPositiveOrthant(len(I)))
assert all(extended_RS.ambient_dim == P.ambient_dim() for P in polytopes)
for surf in topologically_evaluate_monomial_integral(extended_RS, polytopes,
[ (1,), (0,) ],
dims=[min_dim + len(I)],
):
yield SURF(scalar=chi*surf.scalar, rays=surf.rays)
def dominating_cones(vectors):
assert vectors
for j, v in enumerate(vectors):
# 1st cone: v[0] * x < v[1] * x, ..., v[n] * x
# 2nd cone: v[1] * x < v[2] * x, ..., v[n] * n; v[1] <= v[0]
# ...
# In particular, in the i-th cone returned, vectors[i] dominates
# all others.
ieqs = []
for i, w in enumerate(vectors):
if i == j:
continue
ieqs.append([0 if i < j else -1] + list(w - v))
yield Polyhedron(eqns=[], ieqs=ieqs, base_ring=QQ)
def padically_evaluate_regular(self, datum, extra_RS=None):
if not datum.is_regular():
raise ValueError('need a regular datum')
# The extra variable's valuation is in extra_RS.
if extra_RS is None:
extra_RS = RationalSet(StrictlyPositiveOrthant(1))
q = var('q')
count_cap = {}
N = Set(range(len(datum.polynomials)))
for I in Subsets(N):
F = [datum.initials[i].num for i in I]
V = SubvarietyOfTorus(F, torus_dim=datum.ambient_dim)
count_cap[I] = V.count()
# BEGIN SANITY CHECK
# q = var('q')
# u, w = V.split_off_torus()
# assert ((count_cap[I]/(q-1)**w.torus_dim).simplify_full())(q=1) == u.euler_characteristic()
# END SANITY CHECK
for I in Subsets(N):
cnt = sum((-1)**len(J) * count_cap[I + J] for J in Subsets(N - I))
if not cnt:
continue
I = list(I)
id = identity_matrix(ZZ, len(I))
def vectorise(first, k, vec):
w = id[I.index(k)] if k in I else vector(ZZ, len(I))
return vector(ZZ, [first] + list(vec) + list(w))
polytopes = []
for (i, j) in self.pairs:
vertices = [vectorise(0, k, datum.ideals[i].initials[m].exponents()[0]) for m, k in enumerate(datum._ideal2poly[i])] +\
[vectorise(1, k, datum.ideals[j].initials[m].exponents()[0]) for m, k in enumerate(datum._ideal2poly[j])]
polytopes.append(Polyhedron(vertices=vertices, ambient_dim=1 + datum.ambient_dim + len(I)))
extended_RS = extra_RS * datum.RS * RationalSet(StrictlyPositiveOrthant(len(I)))
foo, ring = symbolic_to_ratfun(cnt * (q - 1)**(1 + len(I)) / q**(1 + datum.ambient_dim), [var('t'), var('q')])
corr_cnt = CyclotomicRationalFunction.from_laurent_polynomial(foo, ring)
for z in padically_evaluate_monomial_integral(extended_RS, polytopes, self.integrand):
yield corr_cnt * z
def padically_evaluate_regular(self, datum):
if not datum.is_regular():
raise ValueError('need a regular datum')
q = var('q')
count_cap = {}
N = Set(range(len(datum.polynomials)))
for I in Subsets(N):
F = [datum.initials[i].num for i in I]
V = SubvarietyOfTorus(F, torus_dim=datum.ambient_dim)
count_cap[I] = V.count()
for I in Subsets(N):
cnt = sum((-1)**len(J) * count_cap[I+J] for J in Subsets(N-I))
if not cnt:
continue
I = list(I)
polytopes = []
id = identity_matrix(ZZ, len(I))
def vectorise(k, vec):
w = id[I.index(k)] if k in I else vector(ZZ,len(I))
return vector(ZZ, list(vec) + list(w))
assert len(datum._ideal2poly[0]) == len(datum.ideals[0].gens)
polytopes = [Polyhedron(vertices=[ vectorise(k, datum.ideals[0].initials[m].exponents()[0]) for m,k in enumerate(datum._ideal2poly[0]) ], ambient_dim=datum.ambient_dim+len(I))]
extended_RS = datum.RS * RationalSet(StrictlyPositiveOrthant(len(I)))
foo, ring = symbolic_to_ratfun(cnt * (q - 1)**len(I) / q**datum.ambient_dim, [var('t'), var('q')])
corr_cnt = CyclotomicRationalFunction.from_laurent_polynomial(foo, ring)
assert all(extended_RS.ambient_dim == P.ambient_dim() for P in polytopes)
for z in padically_evaluate_monomial_integral(extended_RS, polytopes, [ (1,), (0,) ]):
yield corr_cnt * z
def root(self):
d = self.ring.ngens()
self.d = d
polyhedra = []
for i in range(d):
eqns = [
(i+1) * [0] + [1] + (d-i-1) * [0]
]
ieqs = [
[-1] + j * [0] + [1] + (d-j-1) * [0]
for j in range(i)
]
ieqs += [
(j+1) * [0] + [1] + (d-j-1) * [0]
for j in range(i+1,d)
]
polyhedra.append(Polyhedron(eqns=eqns, ieqs=ieqs))
self.RS = RationalSet(polyhedra, ambient_dim=d)
# NOTE:
# A bug in Sage prevents rank computations over (fields of fractions of)
# polynomial rings in zero variables over fields.
if d > 0:
F = FractionField(self.ring)
else:
F = FractionField(self.ring.base_ring())
two_u = matrix(F, self.R).rank() # self.R.rank()
if two_u % 2:
raise RuntimeError('this is odd')
self.u = two_u // 2
self.v = matrix(F, self.S).rank() # self.S.rank()
if not d:
return
F = [
LaurentIdeal(
gens = [LaurentPolynomial(_sqrt(f)) for f in principal_minors(self.R, 2*j)],
RS = self.RS,
normalise = True)
for j in range(0, self.u+1)
]
G = [LaurentIdeal(gens=[LaurentPolynomial(g) for g in self.S.minors(j)],
RS=self.RS,
normalise=True)
for j in range(self.v + 1)]
oo = self.u + self.v + 2
# On pairs:
# The first component is used as is, the second is multiplied by the extra
# variable. Note that index 0 corresponds to {1} and index oo to {0}.
# We skip the |F_1|/|F_0 cap xF_1| factor which is generically trivial.
self.pairs = (
[(oo, 0)] +
[(i, oo) for i in range(2, self.u)] + [(i + 1, i) for i in range(1, self.u)] +
[(i, oo) for i in range(self.u + 2, self.u + self.v + 1)] +
[(i + 1, i) for i in range(self.u + 1, self.u + self.v + 1)])
# Note: q^b t^a really corresponds to a*s - b, in contrast to subobjects, where
# the (-1)-shift coming from Jacobians is included.
# This also means we don't have to manually add (-1)s for extra variables.
self.integrand = (
(self.u,) + (self.u - 2) * (1,) + (self.u - 1) * (-1,) + (2 * self.v - 1) * (0,),
(self.d + 1 - self.v,) + (2 * self.u - 3) * (0,) + (self.v - 1) * (-1,) + self.v * (1,))
self.datum = IgusaDatum(F + G + [LaurentIdeal(gens=[], RS=self.RS, ring=FractionField(self.ring))])
self.datum = self.datum.simplify()
return self.datum
def __init__(self, eqns, ieqs):
self.eqns = eqns
self.ieqs = ieqs
self.ambient_dimension = len((self.eqns + self.ieqs)[0]) - 1
self.sage_polyhedron = SagePolyhedron(eqns=self.eqns, ieqs=self.ieqs)
def topologically_evaluate_regular(self, datum):
T = datum.toric_datum
if not T.is_regular():
raise ValueError('Can only processed regular toric data')
# All our polyhedra all really half-open cones (with a - 1 >=0
# being an imitation of a >= 0).
C = conify_polyhedron(T.polyhedron)
M = Set(range(T.length()))
logger.debug('Dimension of polyhedron: %d' % T.polyhedron.dim())
# STEP 1:
# Compute the Euler characteristcs of the subvarieties of
# Torus^sth defined by some subsets of T.initials.
# Afterwards, we'll combine those into Denef-style Euler characteristics
# via inclusion-exclusion.
logger.debug('STEP 1')
alpha = {}
tdim = {}
for I in Subsets(M):
logger.debug('Processing I = %s' % I)
F = [T.initials[i] for i in I]
V = SubvarietyOfTorus(F, torus_dim=T.ambient_dim)
U, W = V.split_off_torus()
# Keep track of the dimension of the torus factor for F == 0.
tdim[I] = W.torus_dim
if tdim[I] > C.dim():
# In this case, we will never need alpha[I].
logger.debug('Totally irrelevant intersection.')
# alpha[I] = ZZ(0)
else:
# To ensure that the computation of Euler characteristics succeeds in case
# of global non-degeneracy, we test this first.
# The 'euler_characteristic' method may change generating sets,
# possibly introducing degeneracies.
alpha[I] = U.khovanskii_characteristic() if U.is_nondegenerate(
) else U.euler_characteristic()
logger.debug(
'Essential Euler characteristic alpha[%s] = %d; dimension of torus factor = %d'
% (I, alpha[I], tdim[I]))
logger.debug(
'Done computing essential Euler characteristics of intersections: %s'
% alpha)
# STEP 2:
# Compute the topological zeta functions of the extended cones.
# That is, add extra variables, add variable constraints (here: just >= 0),
# and add newly monomialised conditions.
def cat(u, v):
return vector(list(u) + list(v))
logger.debug('STEP 2')
for I in Subsets(M):
logger.debug('Current set: I = %s' % I)
# P = C_0 x R_(>0)^I in the paper
P = DirectProductOfPolyhedra(T.polyhedron,
StrictlyPositiveOrthant(len(I)))
it = iter(identity_matrix(ZZ, len(I)).rows())
ieqs = []
for i in M:
# Turn lhs[i] | monomial of initials[i] * y[i] if in I,
# lhs[i] | monomial of initials[i] otherwise
# into honest cone conditions.
ieqs.append(
cat(
vector(ZZ, (0, )),
cat(
vector(ZZ, T.initials[i].exponents()[0]) -
vector(ZZ, T.lhs[i].exponents()[0]),
next(it) if i in I else zero_vector(ZZ, len(I)))))
if not ieqs:
# For some reason, not providing any constraints yields the empty
# polyhedron in Sage; it should be all of RR^whatever, IMO.
ieqs = [vector(ZZ, (T.ambient_dim + len(I) + 1) * [0])]
Q = Polyhedron(ieqs=ieqs,
base_ring=QQ,
ambient_dim=T.ambient_dim + len(I))
sigma = conify_polyhedron(P.intersection(Q))
logger.debug('Dimension of Hensel cone: %d' % sigma.dim())
# Obtain the desired Euler characteristic via inclusion-exclusion,
# restricted to those terms contributing to the constant term mod q-1.
chi = sum((-1)**len(J) * alpha[I + J] for J in Subsets(M - I)
if tdim[I + J] + len(I) == sigma.dim())
if not chi:
continue
# NOTE: dim(P) = dim(sigma): choose any point omega in P
# then a large point lambda in Pos^I will give (omega,lambda) in sigma.
# Moreover, small perturbations of (omega,lambda) don't change that
# so (omega,lambda) is an interior point of sigma inside P.
surfs = (topologise_cone(
sigma,
matrix([
cat(T.integrand[0], zero_vector(ZZ, len(I))),
cat(T.integrand[1], vector(ZZ,
len(I) * [-1]))
]).transpose()))
for S in surfs:
yield SURF(scalar=chi * S.scalar, rays=S.rays)
def PositiveOrthant(d):
if d == 0:
return Polyhedron(ambient_dim=0, eqns=[], ieqs=[(0, )], base_ring=QQ)
else:
return Polyhedron(ieqs=block_matrix(
[[matrix(QQ, d, 1), identity_matrix(QQ, d)]]))
class Polyhedron:
def __init__(self, eqns, ieqs):
self.eqns = eqns
self.ieqs = ieqs
self.ambient_dimension = len((self.eqns + self.ieqs)[0]) - 1
self.sage_polyhedron = SagePolyhedron(eqns=self.eqns, ieqs=self.ieqs)
@classmethod
def from_triangulation(cls, T, max_weight, zeroed=None, zeros=None):
if zeros is not None:
zeroed = [(zeros >> i) & 1 for i in range(2 * T.zeta)][::-1]
# Build the polytope.
eqns, ieqs = [], []
# Edge equations.
for i in range(T.zeta):
eqn = [0] * 2 * T.zeta
if T.is_flippable(i):
A, B = T.corner_lookup[i], T.corner_lookup[~i]
x, y = A.labels[1], A.labels[2]
z, w = B.labels[1], B.labels[2]
eqn[x], eqn[y], eqn[z], eqn[w] = +1, +1, -1, -1
else:
A = T.corner_lookup[i]
x = A.labels[1] if A[1] == ~A[0] else A.labels[2]
z = A.labels[0]
eqn[x], eqn[z] = +1, -1
eqns.append([0] + eqn) # V_x + X_y == V_z + V_w.
# Zeroed (in)equalities
for i in range(2 * T.zeta):
if not zeroed[i]:
ieq = [0] * 2 * T.zeta
ieq[i] = +1
ieqs.append([-1] + ieq) # V_i >= 1.
else: # Zeroed equation.
eqn = [0] * 2 * T.zeta
eqn[i] = +1
eqns.append([0] + eqn) # V_i == 0.
# Max weight inequality.
ieqs.append([max_weight] + [-1] * 2 * T.zeta) # sum V_i <= max_weight.
return cls(eqns=eqns, ieqs=ieqs)
def __str__(self):
return 'EQN:[\n{}\n]\nIEQS:[\n{}\n]'.format(
',\n'.join(str(eqn) for eqn in self.eqns),
',\n'.join(str(ieq) for ieq in self.ieqs))
def split(self, inequality):
return Polyhedron(self.eqns, self.ieqs + [inequality])
def restrict(self, equality):
return Polyhedron(self.eqns + [equality], self.ieqs)
def __contains__(self, coordinate):
assert len(coordinate) == self.ambient_dimension
homogenised = [1] + list(coordinate)
def dot(X, Y):
return sum(x * y for x, y in zip(X, Y))
# print([dot(homogenised, ieq) >= 0 for ieq in self.ieqs])
return all(dot(homogenised, eqn) == 0 for eqn in self.eqns) and all(
dot(homogenised, ieq) >= 0 for ieq in self.ieqs)
def get_index(self, coordinate, **kwds):
assert coordinate in self
D = self.ambient_dimension
P = self
index = 0
for i in range(D):
neg_axis = [0] * i + [-1] + [0] * (D - i - 1)
P_lt_comp = P.split([coordinate[i] - 1] + neg_axis)
index += P_lt_comp.integral_points_count(**kwds)
P = P.restrict([coordinate[i]] + neg_axis)
return index
def get_integral_point(self, index, **kwds):
if self.sage_polyhedron is not None:
return self.sage_polyhedron.get_integral_point(**kwds)
D = self.ambient_dimension
axes = [[0] * i + [1] + [0] * (D - i - 1) for i in range(D)]
coordinate = []
P = self
P_count = P.integral_points_count(
**kwds
) # Record the number of integral points in P_{lower <= x_i < upper}.
bounding_box = zip(*self.bounding_box())
for axis, bounds in zip(
axes, bounding_box
): # Now compute x_i, the ith component of coordinate.
neg_axis = [-x for x in axis]
lower, upper = int(
bounds[0]), int(bounds[1]) + 1 # So lower <= x_i < upper.
while lower < upper - 1:
# print(coordinate, lower, upper, P_count)
guess = (lower + upper) // 2 # > lower.
# Build new polyhedron by intersecting P with the halfspace {x_i < guess}.
P_lt_guess = P.split([-lower] + axis).split([guess - 1] +
neg_axis)
P_lt_guess_count = P_lt_guess.integral_points_count(**kwds)
if P_lt_guess_count > index: # Move upper down to guess.
upper = guess
index -= 0
P_count = P_lt_guess_count
else: # P_lt_guess_count <= index: # Move lower up to guess.
lower = guess
index -= P_lt_guess_count
P_count -= P_lt_guess_count
if P_count == 1:
Q = P.split([-lower] + axis).split([upper - 1] + neg_axis)
vertices = Q.vertices()
if len(vertices) == 1: # Polytope is 0-dimensional.
return [int(x)
for x in vertices[0]] # Remove any Fractions.
coordinate.append(
lower) # Record the new component that we have found.
P = P.restrict([lower] + neg_axis)
# assert self.get_index(coordinate) == orig_index
return coordinate
def integral_points_count(self, **kwds):
if self.sage_polyhedron is not None:
return self.sage_polyhedron.integral_points_count(**kwds)
latte_input = '{} {}\n{}\nlinearity {} {}'.format(
len(self.eqns) + len(self.ieqs),
self.ambient_dimension + 1,
'\n'.join(' '.join(str(x) for x in X)
for X in self.eqns + self.ieqs),
len(self.eqns),
' '.join(str(i + 1) for i in range(len(self.eqns))),
)
args = [os.path.abspath(os.path.join('bin', 'count'))]
for key, value in kwds.items():
if value is None or value is False:
continue
key = key.replace('_', '-')
if value is True:
args.append('--{}'.format(key))
else:
args.append('--{}={}'.format(key, value))
# args += ['/dev/stdin']
# The cwd argument is needed because latte
# always produces diagnostic output files.
with TemporaryDirectory() as tmpdir:
# with TemporaryDirectory() as tmpdir:
with open(os.path.join(tmpdir, 'test.pol'), 'w') as x:
x.write(latte_input)
args += [os.path.join(tmpdir, 'test.pol')]
# X = subprocess.run(args, capture_output=True)
# ans, err = X.stdout, X.stderr
# ret_code = X.returncode
latte_proc = Popen(args,
stdin=PIPE,
stdout=PIPE,
stderr=PIPE,
cwd=str(tmpdir))
ans, err = latte_proc.communicate()
ret_code = latte_proc.poll()
if ans: # Sometimes (when LattE's preproc does the work), no output appears on stdout.
ans = ans.splitlines()[-1].decode()
else:
# opening a file is slow (30e-6s), so we read the file
# numOfLatticePoints only in case of a IndexError above
with open(os.path.join(tmpdir, 'numOfLatticePoints'),
'r') as f:
ans = f.read()
try:
return int(ans)
except ValueError:
return 0
@memoize
def vertices(self):
if self.sage_polyhedron is not None:
return self.sage_polyhedron.vertices()
cddlib_input = 'H-representation\nlinearity {} {}\nbegin\n{} {} rational\n{}\nend'.format(
len(self.eqns),
' '.join(str(i + 1) for i in range(len(self.eqns))),
len(self.eqns) + len(self.ieqs),
self.ambient_dimension + 1,
'\n'.join(' '.join(str(x) for x in X)
for X in self.eqns + self.ieqs),
)
args = [os.path.abspath(os.path.join('bin', 'cddexec_gmp')), '--rep']
cddlib_proc = Popen(args, stdin=PIPE, stdout=PIPE, stderr=PIPE)
ans, err = cddlib_proc.communicate(input=cddlib_input.encode())
ret_code = cddlib_proc.poll()
def parse(x):
n, _, d = x.partition('/')
return Fraction(int(n), int(d) if d else 1)
return [[parse(item) for item in line.split()[1:]]
for line in ans.decode().splitlines()[4:-1]]
@memoize
def bounding_box(self):
return list(
zip(*[(min(coords), max(coords))
for coords in zip(*self.vertices())]))
def random_point(self):
while True:
p = [
randrange(int(lower),
int(upper) + 1)
for lower, upper in zip(*self.bounding_box())
]
if p in self:
return p
def dual_cone(self):
return reduce(lambda C, D: C.intersection(D),
(Cone(C.rays()).dual()
for C in self.cones)) if self.cones else Cone(
Polyhedron(ieqs=[(self.ambient_dim + 1) * (0, )]))
