The Normaliz backend for polyhedral computations¶
Note
This backend requires PyNormaliz.
To install PyNormaliz, type sage -i pynormaliz
in the terminal.
AUTHORS:
Matthias Köppe (2016-12): initial version
Jean-Philippe Labbé (2019-04): Expose normaliz features and added functionalities
- class sage.geometry.polyhedron.backend_normaliz.Polyhedron_QQ_normaliz(parent, Vrep, Hrep, normaliz_cone=None, normaliz_data=None, normaliz_field=None, **kwds)¶
Bases:
sage.geometry.polyhedron.backend_normaliz.Polyhedron_normaliz
,sage.geometry.polyhedron.base_QQ.Polyhedron_QQ
Polyhedra over \(\QQ\) with normaliz.
INPUT:
Vrep
– a list[vertices, rays, lines]
orNone
Hrep
– a list[ieqs, eqns]
orNone
EXAMPLES:
sage: p = Polyhedron(vertices=[(0,0),(1,0),(0,1)], # optional - pynormaliz ....: rays=[(1,1)], lines=[], ....: backend='normaliz', base_ring=QQ) sage: TestSuite(p).run() # optional - pynormaliz
- ehrhart_series(variable='t')¶
Return the Ehrhart series of a compact rational polyhedron.
The Ehrhart series is the generating function where the coefficient of \(t^k\) is number of integer lattice points inside the \(k\)-th dilation of the polytope.
INPUT:
variable
– string (default:'t'
)
OUTPUT:
A rational function.
EXAMPLES:
sage: S = Polyhedron(vertices=[[0,1],[1,0]], backend='normaliz') # optional - pynormaliz sage: ES = S.ehrhart_series() # optional - pynormaliz sage: ES.numerator() # optional - pynormaliz 1 sage: ES.denominator().factor() # optional - pynormaliz (t - 1)^2 sage: C = Polyhedron(vertices = [[0,0,0],[0,0,1],[0,1,0],[0,1,1],[1,0,0],[1,0,1],[1,1,0],[1,1,1]],backend='normaliz') # optional - pynormaliz sage: ES = C.ehrhart_series() # optional - pynormaliz sage: ES.numerator() # optional - pynormaliz t^2 + 4*t + 1 sage: ES.denominator().factor() # optional - pynormaliz (t - 1)^4
The following example is from the Normaliz manual contained in the file
rational.in
:sage: rat_poly = Polyhedron(vertices=[[1/2,1/2],[-1/3,-1/3],[1/4,-1/2]],backend='normaliz') # optional - pynormaliz sage: ES = rat_poly.ehrhart_series() # optional - pynormaliz sage: ES.numerator() # optional - pynormaliz 2*t^6 + 3*t^5 + 4*t^4 + 3*t^3 + t^2 + t + 1 sage: ES.denominator().factor() # optional - pynormaliz (-1) * (t + 1)^2 * (t - 1)^3 * (t^2 + 1) * (t^2 + t + 1)
The polyhedron should be compact:
sage: C = Polyhedron(backend='normaliz',rays=[[1,2],[2,1]]) # optional - pynormaliz sage: C.ehrhart_series() # optional - pynormaliz Traceback (most recent call last): ... NotImplementedError: Ehrhart series can only be computed for compact polyhedron
See also
hilbert_series()
- hilbert_series(grading, variable='t')¶
Return the Hilbert series of the polyhedron with respect to
grading
.INPUT:
grading
– vector. The grading to use to form the Hilbert seriesvariable
– string (default:'t'
)
OUTPUT:
A rational function.
EXAMPLES:
sage: C = Polyhedron(backend='normaliz',rays=[[0,0,1],[0,1,1],[1,0,1],[1,1,1]]) # optional - pynormaliz sage: HS = C.hilbert_series([1,1,1]) # optional - pynormaliz sage: HS.numerator() # optional - pynormaliz t^2 + 1 sage: HS.denominator().factor() # optional - pynormaliz (-1) * (t + 1) * (t - 1)^3 * (t^2 + t + 1)
By changing the grading, you can get the Ehrhart series of the square lifted at height 1:
sage: C.hilbert_series([0,0,1]) # optional - pynormaliz (t + 1)/(-t^3 + 3*t^2 - 3*t + 1)
Here is an example
2cone.in
from the Normaliz manual:sage: C = Polyhedron(backend='normaliz',rays=[[1,3],[2,1]]) # optional - pynormaliz sage: HS = C.hilbert_series([1,1]) # optional - pynormaliz sage: HS.numerator() # optional - pynormaliz t^5 + t^4 + t^3 + t^2 + 1 sage: HS.denominator().factor() # optional - pynormaliz (t + 1) * (t - 1)^2 * (t^2 + 1) * (t^2 + t + 1) sage: HS = C.hilbert_series([1,2]) # optional - pynormaliz sage: HS.numerator() # optional - pynormaliz t^8 + t^6 + t^5 + t^3 + 1 sage: HS.denominator().factor() # optional - pynormaliz (t + 1) * (t - 1)^2 * (t^2 + 1) * (t^6 + t^5 + t^4 + t^3 + t^2 + t + 1)
Here is the magic square example form the Normaliz manual:
sage: eq = [[0,1,1,1,-1,-1,-1, 0, 0, 0], ....: [0,1,1,1, 0, 0, 0,-1,-1,-1], ....: [0,0,1,1,-1, 0, 0,-1, 0, 0], ....: [0,1,0,1, 0,-1, 0, 0,-1, 0], ....: [0,1,1,0, 0, 0,-1, 0, 0,-1], ....: [0,0,1,1, 0,-1, 0, 0, 0,-1], ....: [0,1,1,0, 0,-1, 0,-1, 0, 0]] sage: magic_square = Polyhedron(eqns=eq,backend='normaliz') & Polyhedron(rays=identity_matrix(9).rows()) # optional - pynormaliz sage: grading = [1,1,1,0,0,0,0,0,0] sage: magic_square.hilbert_series(grading) # optional - pynormaliz (t^6 + 2*t^3 + 1)/(-t^9 + 3*t^6 - 3*t^3 + 1)
See also
ehrhart_series()
- integral_points(threshold=10000)¶
Return the integral points in the polyhedron.
Uses either the naive algorithm (iterate over a rectangular bounding box) or triangulation + Smith form.
INPUT:
threshold
– integer (default: 10000); use the naïve algorithm as long as the bounding box is smaller than this
OUTPUT:
The list of integral points in the polyhedron. If the polyhedron is not compact, a
ValueError
is raised.EXAMPLES:
sage: Polyhedron(vertices=[(-1,-1), (1,0), (1,1), (0,1)], # optional - pynormaliz ....: backend='normaliz').integral_points() ((-1, -1), (0, 0), (0, 1), (1, 0), (1, 1)) sage: simplex = Polyhedron([(1,2,3), (2,3,7), (-2,-3,-11)], # optional - pynormaliz ....: backend='normaliz') sage: simplex.integral_points() # optional - pynormaliz ((-2, -3, -11), (0, 0, -2), (1, 2, 3), (2, 3, 7))
The polyhedron need not be full-dimensional:
sage: simplex = Polyhedron([(1,2,3,5), (2,3,7,5), (-2,-3,-11,5)], # optional - pynormaliz ....: backend='normaliz') sage: simplex.integral_points() # optional - pynormaliz ((-2, -3, -11, 5), (0, 0, -2, 5), (1, 2, 3, 5), (2, 3, 7, 5)) sage: point = Polyhedron([(2,3,7)], # optional - pynormaliz ....: backend='normaliz') sage: point.integral_points() # optional - pynormaliz ((2, 3, 7),) sage: empty = Polyhedron(backend='normaliz') # optional - pynormaliz sage: empty.integral_points() # optional - pynormaliz ()
Here is a simplex where the naive algorithm of running over all points in a rectangular bounding box no longer works fast enough:
sage: v = [(1,0,7,-1), (-2,-2,4,-3), (-1,-1,-1,4), (2,9,0,-5), (-2,-1,5,1)] sage: simplex = Polyhedron(v, backend='normaliz'); simplex # optional - pynormaliz A 4-dimensional polyhedron in ZZ^4 defined as the convex hull of 5 vertices sage: len(simplex.integral_points()) # optional - pynormaliz 49
A rather thin polytope for which the bounding box method would be a very bad idea (note this is a rational (non-lattice) polytope, so the other backends use the bounding box method):
sage: P = Polyhedron(vertices=((0, 0), (178933,37121))) + 1/1000*polytopes.hypercube(2) sage: P = Polyhedron(vertices=P.vertices_list(), # optional - pynormaliz ....: backend='normaliz') sage: len(P.integral_points()) # optional - pynormaliz 434
Finally, the 3-d reflexive polytope number 4078:
sage: v = [(1,0,0), (0,1,0), (0,0,1), (0,0,-1), (0,-2,1), ....: (-1,2,-1), (-1,2,-2), (-1,1,-2), (-1,-1,2), (-1,-3,2)] sage: P = Polyhedron(v, backend='normaliz') # optional - pynormaliz sage: pts1 = P.integral_points() # optional - pynormaliz sage: all(P.contains(p) for p in pts1) # optional - pynormaliz True sage: pts2 = LatticePolytope(v).points() # PALP sage: for p in pts1: p.set_immutable() # optional - pynormaliz sage: set(pts1) == set(pts2) # optional - pynormaliz True sage: timeit('Polyhedron(v, backend='normaliz').integral_points()') # not tested - random 625 loops, best of 3: 1.41 ms per loop sage: timeit('LatticePolytope(v).points()') # not tested - random 25 loops, best of 3: 17.2 ms per loop
- integral_points_generators()¶
Return the integral points generators of the polyhedron.
Every integral point in the polyhedron can be written as a (unique) non-negative linear combination of integral points contained in the three defining parts of the polyhedron: the integral points (the compact part), the recession cone, and the lineality space.
OUTPUT:
A tuple consisting of the integral points, the Hilbert basis of the recession cone, and an integral basis for the lineality space.
EXAMPLES:
Normaliz gives a nonnegative integer basis of the lineality space:
sage: P = Polyhedron(backend='normaliz',lines=[[2,2]]) # optional - pynormaliz sage: P.integral_points_generators() # optional - pynormaliz (((0, 0),), (), ((1, 1),))
A recession cone generated by two rays:
sage: C = Polyhedron(backend='normaliz',rays=[[1,2],[2,1]]) # optional - pynormaliz sage: C.integral_points_generators() # optional - pynormaliz (((0, 0),), ((1, 1), (1, 2), (2, 1)), ())
Empty polyhedron:
sage: P = Polyhedron(backend='normaliz') # optional - pynormaliz sage: P.integral_points_generators() # optional - pynormaliz ((), (), ())
- class sage.geometry.polyhedron.backend_normaliz.Polyhedron_ZZ_normaliz(parent, Vrep, Hrep, normaliz_cone=None, normaliz_data=None, normaliz_field=None, **kwds)¶
Bases:
sage.geometry.polyhedron.backend_normaliz.Polyhedron_QQ_normaliz
,sage.geometry.polyhedron.base_ZZ.Polyhedron_ZZ
Polyhedra over \(\ZZ\) with normaliz.
INPUT:
Vrep
– a list[vertices, rays, lines]
orNone
Hrep
– a list[ieqs, eqns]
orNone
EXAMPLES:
sage: p = Polyhedron(vertices=[(0,0),(1,0),(0,1)], # optional - pynormaliz ....: rays=[(1,1)], lines=[], ....: backend='normaliz', base_ring=ZZ) sage: TestSuite(p).run() # optional - pynormaliz
- class sage.geometry.polyhedron.backend_normaliz.Polyhedron_normaliz(parent, Vrep, Hrep, normaliz_cone=None, normaliz_data=None, normaliz_field=None, **kwds)¶
Bases:
sage.geometry.polyhedron.base.Polyhedron_base
Polyhedra with normaliz
INPUT:
parent
–Polyhedra
the parentVrep
– a list[vertices, rays, lines]
orNone
; the V-representation of the polyhedron; ifNone
, the polyhedron is determined by the H-representationHrep
– a list[ieqs, eqns]
orNone
; the H-representation of the polyhedron; ifNone
, the polyhedron is determined by the V-representationnormaliz_cone
– a PyNormaliz wrapper of a normaliz cone
Only one of
Vrep
,Hrep
, ornormaliz_cone
can be different fromNone
.EXAMPLES:
sage: p = Polyhedron(vertices=[(0,0),(1,0),(0,1)], rays=[(1,1)], # optional - pynormaliz ....: lines=[], backend='normaliz') sage: TestSuite(p).run() # optional - pynormaliz
Two ways to get the full space:
sage: Polyhedron(eqns=[[0, 0, 0]], backend='normaliz') # optional - pynormaliz A 2-dimensional polyhedron in QQ^2 defined as the convex hull of 1 vertex and 2 lines sage: Polyhedron(ieqs=[[0, 0, 0]], backend='normaliz') # optional - pynormaliz A 2-dimensional polyhedron in QQ^2 defined as the convex hull of 1 vertex and 2 lines
A lower-dimensional affine cone; we test that there are no mysterious inequalities coming in from the homogenization:
sage: P = Polyhedron(vertices=[(1, 1)], rays=[(0, 1)], # optional - pynormaliz ....: backend='normaliz') sage: P.n_inequalities() # optional - pynormaliz 1 sage: P.equations() # optional - pynormaliz (An equation (1, 0) x - 1 == 0,)
The empty polyhedron:
sage: P=Polyhedron(ieqs=[[-2, 1, 1], [-3, -1, -1], [-4, 1, -2]], # optional - pynormaliz ....: backend='normaliz') sage: P # optional - pynormaliz The empty polyhedron in QQ^2 sage: P.Vrepresentation() # optional - pynormaliz () sage: P.Hrepresentation() # optional - pynormaliz (An equation -1 == 0,)
- integral_hull()¶
Return the integral hull in the polyhedron.
This is a new polyhedron that is the convex hull of all integral points.
EXAMPLES:
Unbounded example from Normaliz manual, “a dull polyhedron”:
sage: P = Polyhedron(ieqs=[[1, 0, 2], [3, 0, -2], [3, 2, -2]], # optional - pynormaliz ....: backend='normaliz') sage: PI = P.integral_hull() # optional - pynormaliz sage: P.plot(color='yellow') + PI.plot(color='green') # optional - pynormaliz Graphics object consisting of 10 graphics primitives sage: PI.Vrepresentation() # optional - pynormaliz (A vertex at (-1, 0), A vertex at (0, 1), A ray in the direction (1, 0))
Nonpointed case:
sage: P = Polyhedron(vertices=[[1/2, 1/3]], rays=[[1, 1]], # optional - pynormaliz ....: lines=[[-1, 1]], backend='normaliz') sage: PI = P.integral_hull() # optional - pynormaliz sage: PI.Vrepresentation() # optional - pynormaliz (A vertex at (1, 0), A ray in the direction (1, 0), A line in the direction (1, -1))
Empty polyhedron:
sage: P = Polyhedron(backend='normaliz') # optional - pynormaliz sage: PI = P.integral_hull() # optional - pynormaliz sage: PI.Vrepresentation() # optional - pynormaliz ()