Base class for polyhedra over \(\ZZ\)¶
- class sage.geometry.polyhedron.base_ZZ.Polyhedron_ZZ(parent, Vrep, Hrep, Vrep_minimal=None, Hrep_minimal=None, pref_rep=None, mutable=False, **kwds)¶
Bases:
sage.geometry.polyhedron.base_QQ.Polyhedron_QQ
Base class for Polyhedra over \(\ZZ\)
- ehrhart_polynomial(engine=None, variable='t', verbose=False, dual=None, irrational_primal=None, irrational_all_primal=None, maxdet=None, no_decomposition=None, compute_vertex_cones=None, smith_form=None, dualization=None, triangulation=None, triangulation_max_height=None, **kwds)¶
Return the Ehrhart polynomial of this polyhedron.
Let \(P\) be a lattice polytope in \(\RR^d\) and define \(L(P,t) = \# (tP \cap \ZZ^d)\). Then E. Ehrhart proved in 1962 that \(L\) coincides with a rational polynomial of degree \(d\) for integer \(t\). \(L\) is called the Ehrhart polynomial of \(P\). For more information see the Wikipedia article Ehrhart_polynomial.
The Ehrhart polynomial may be computed using either LattE Integrale or Normaliz by setting
engine
to ‘latte’ or ‘normaliz’ respectively.INPUT:
engine
– string; The backend to use. Allowed values are:None
(default); When no input is given the Ehrhart polynomial is computed using LattE Integrale (optional)'latte'
; use LattE integrale program (optional)'normaliz'
; use Normaliz program (optional). The backend ofself
must be set to ‘normaliz’.
variable
– string (default: ‘t’); The variable in which the Ehrhart polynomial should be expressed.When the
engine
is ‘latte’ or None, the additional input values are:verbose
- boolean (default:False
); ifTrue
, print the whole output of the LattE command.
The following options are passed to the LattE command, for details consult the LattE documentation:
dual
- boolean; triangulate and signed-decompose in the dual spaceirrational_primal
- boolean; triangulate in the dual space, signed-decompose in the primal space using irrationalization.irrational_all_primal
- boolean; Triangulate and signed-decompose in the primal space using irrationalization.maxdet
– integer; decompose down to an index (determinant) ofmaxdet
instead of index 1 (unimodular cones).no_decomposition
– boolean; do not signed-decompose simplicial cones.compute_vertex_cones
– string; either ‘cdd’ or ‘lrs’ or ‘4ti2’smith_form
– string; either ‘ilio’ or ‘lidia’dualization
– string; either ‘cdd’ or ‘4ti2’triangulation
- string; ‘cddlib’, ‘4ti2’ or ‘topcom’triangulation_max_height
- integer; use a uniform distribution of height from 1 to this number
OUTPUT:
The Ehrhart polynomial as a univariate polynomial in
variable
over a rational field.See also
latte
the interface to LattE Integrale PyNormalizEXAMPLES:
To start, we find the Ehrhart polynomial of a three-dimensional
simplex
, first usingengine='latte'
. Leaving the engine unspecified sets theengine
to ‘latte’ by default:sage: simplex = Polyhedron(vertices=[(0,0,0),(3,3,3),(-3,2,1),(1,-1,-2)]) sage: poly = simplex.ehrhart_polynomial(engine = 'latte') # optional - latte_int sage: poly # optional - latte_int 7/2*t^3 + 2*t^2 - 1/2*t + 1 sage: poly(1) # optional - latte_int 6 sage: len(simplex.integral_points()) # optional - latte_int 6 sage: poly(2) # optional - latte_int 36 sage: len((2*simplex).integral_points()) # optional - latte_int 36
Now we find the same Ehrhart polynomial, this time using
engine='normaliz'
. To use the Normaliz engine, thesimplex
must be defined withbackend='normaliz'
:sage: simplex = Polyhedron(vertices=[(0,0,0),(3,3,3),(-3,2,1),(1,-1,-2)], backend='normaliz') # optional - pynormaliz sage: poly = simplex.ehrhart_polynomial(engine='normaliz') # optional - pynormaliz sage: poly # optional - pynormaliz 7/2*t^3 + 2*t^2 - 1/2*t + 1
If the
engine='normaliz'
, the backend should be'normaliz'
, otherwise it returns an error:sage: simplex = Polyhedron(vertices=[(0,0,0),(3,3,3),(-3,2,1),(1,-1,-2)]) sage: simplex.ehrhart_polynomial(engine='normaliz') # optional - pynormaliz Traceback (most recent call last): ... TypeError: The polyhedron's backend should be 'normaliz'
Now we find the Ehrhart polynomials of the unit hypercubes of dimensions three through six. They are computed first with
engine='latte'
and then withengine='normaliz'
. The degree of the Ehrhart polynomial matches the dimension of the hypercube, and the coefficient of the leading monomial equals the volume of the unit hypercube:sage: from itertools import product sage: def hypercube(d): ....: return Polyhedron(vertices=list(product([0,1],repeat=d))) sage: hypercube(3).ehrhart_polynomial() # optional - latte_int t^3 + 3*t^2 + 3*t + 1 sage: hypercube(4).ehrhart_polynomial() # optional - latte_int t^4 + 4*t^3 + 6*t^2 + 4*t + 1 sage: hypercube(5).ehrhart_polynomial() # optional - latte_int t^5 + 5*t^4 + 10*t^3 + 10*t^2 + 5*t + 1 sage: hypercube(6).ehrhart_polynomial() # optional - latte_int t^6 + 6*t^5 + 15*t^4 + 20*t^3 + 15*t^2 + 6*t + 1 sage: def hypercube(d): ....: return Polyhedron(vertices=list(product([0,1],repeat=d)),backend='normaliz') # optional - pynormaliz sage: hypercube(3).ehrhart_polynomial(engine='normaliz') # optional - pynormaliz t^3 + 3*t^2 + 3*t + 1 sage: hypercube(4).ehrhart_polynomial(engine='normaliz') # optional - pynormaliz t^4 + 4*t^3 + 6*t^2 + 4*t + 1 sage: hypercube(5).ehrhart_polynomial(engine='normaliz') # optional - pynormaliz t^5 + 5*t^4 + 10*t^3 + 10*t^2 + 5*t + 1 sage: hypercube(6).ehrhart_polynomial(engine='normaliz') # optional - pynormaliz t^6 + 6*t^5 + 15*t^4 + 20*t^3 + 15*t^2 + 6*t + 1
An empty polyhedron:
sage: p = Polyhedron(ambient_dim=3, vertices=[]) sage: p.ehrhart_polynomial() 0 sage: parent(_) Univariate Polynomial Ring in t over Rational Field
The polyhedron should be compact:
sage: C = Polyhedron(rays=[[1,2],[2,1]]) sage: C.ehrhart_polynomial() Traceback (most recent call last): ... ValueError: Ehrhart polynomial only defined for compact polyhedra
- fibration_generator(dim)¶
Generate the lattice polytope fibrations.
For the purposes of this function, a lattice polytope fiber is a sub-lattice polytope. Projecting the plane spanned by the subpolytope to a point yields another lattice polytope, the base of the fibration.
INPUT:
dim
– integer. The dimension of the lattice polytope fiber.
OUTPUT:
A generator yielding the distinct lattice polytope fibers of given dimension.
EXAMPLES:
sage: P = Polyhedron(toric_varieties.P4_11169().fan().rays(), base_ring=ZZ) sage: list( P.fibration_generator(2) ) [A 2-dimensional polyhedron in ZZ^4 defined as the convex hull of 3 vertices]
- find_translation(translated_polyhedron)¶
Return the translation vector to
translated_polyhedron
.INPUT:
translated_polyhedron
– a polyhedron.
OUTPUT:
A \(\ZZ\)-vector that translates
self
totranslated_polyhedron
. AValueError
is raised iftranslated_polyhedron
is not a translation ofself
, this can be used to check that two polyhedra are not translates of each other.EXAMPLES:
sage: X = polytopes.cube() sage: X.find_translation(X + vector([2,3,5])) (2, 3, 5) sage: X.find_translation(2*X) Traceback (most recent call last): ... ValueError: polyhedron is not a translation of self
- has_IP_property()¶
Test whether the polyhedron has the IP property.
The IP (interior point) property means that
self
is compact (a polytope).self
contains the origin as an interior point.
This implies that
self
is full-dimensional.The dual polyhedron is again a polytope (that is, a compact polyhedron), though not necessarily a lattice polytope.
EXAMPLES:
sage: Polyhedron([(1,1),(1,0),(0,1)], base_ring=ZZ).has_IP_property() False sage: Polyhedron([(0,0),(1,0),(0,1)], base_ring=ZZ).has_IP_property() False sage: Polyhedron([(-1,-1),(1,0),(0,1)], base_ring=ZZ).has_IP_property() True
REFERENCES:
- is_lattice_polytope()¶
Return whether the polyhedron is a lattice polytope.
OUTPUT:
True
if the polyhedron is compact and has only integral vertices,False
otherwise.EXAMPLES:
sage: polytopes.cross_polytope(3).is_lattice_polytope() True sage: polytopes.regular_polygon(5).is_lattice_polytope() False
- is_reflexive()¶
A lattice polytope is reflexive if it contains the origin in its interior and its polar with respect to the origin is a lattice polytope.
Equivalently, it is reflexive if it is of the form \(\{x \in \mathbb{R}^d: Ax \leq 1\}\) for some integer matrix \(A\) and \(d\) the ambient dimension.
EXAMPLES:
sage: p = Polyhedron(vertices=[(1,0,0),(0,1,0),(0,0,1),(-1,-1,-1)], base_ring=ZZ) sage: p.is_reflexive() True sage: polytopes.hypercube(4).is_reflexive() True sage: p = Polyhedron(vertices=[(1,0), (0,2), (-1,0), (0,-1)], base_ring=ZZ) sage: p.is_reflexive() False sage: p = Polyhedron(vertices=[(1,0), (0,2), (-1,0)], base_ring=ZZ) sage: p.is_reflexive() False
An error is raised, if the polyhedron is not compact:
sage: p = Polyhedron(rays=[(1,)], base_ring=ZZ) sage: p.is_reflexive() Traceback (most recent call last): ... ValueError: the polyhedron is not compact
- minkowski_decompositions()¶
Return all Minkowski sums that add up to the polyhedron.
OUTPUT:
A tuple consisting of pairs \((X,Y)\) of \(\ZZ\)-polyhedra that add up to
self
. All pairs up to exchange of the summands are returned, that is, \((Y,X)\) is not included if \((X,Y)\) already is.EXAMPLES:
sage: square = Polyhedron(vertices=[(0,0),(1,0),(0,1),(1,1)]) sage: square.minkowski_decompositions() ((A 0-dimensional polyhedron in ZZ^2 defined as the convex hull of 1 vertex, A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 4 vertices), (A 1-dimensional polyhedron in ZZ^2 defined as the convex hull of 2 vertices, A 1-dimensional polyhedron in ZZ^2 defined as the convex hull of 2 vertices))
Example from http://cgi.di.uoa.gr/~amantzaf/geo/
sage: Q = Polyhedron(vertices=[(4,0), (6,0), (0,3), (4,3)]) sage: R = Polyhedron(vertices=[(0,0), (5,0), (8,4), (3,2)]) sage: (Q+R).minkowski_decompositions() ((A 0-dimensional polyhedron in ZZ^2 defined as the convex hull of 1 vertex, A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 7 vertices), (A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 4 vertices, A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 4 vertices), (A 1-dimensional polyhedron in ZZ^2 defined as the convex hull of 2 vertices, A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 7 vertices), (A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 5 vertices, A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 4 vertices), (A 1-dimensional polyhedron in ZZ^2 defined as the convex hull of 2 vertices, A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 7 vertices), (A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 5 vertices, A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 3 vertices), (A 1-dimensional polyhedron in ZZ^2 defined as the convex hull of 2 vertices, A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 7 vertices), (A 1-dimensional polyhedron in ZZ^2 defined as the convex hull of 2 vertices, A 2-dimensional polyhedron in ZZ^2 defined as the convex hull of 6 vertices)) sage: [ len(square.dilation(i).minkowski_decompositions()) ....: for i in range(6) ] [1, 2, 5, 8, 13, 18] sage: [ ceil((i^2+2*i-1)/2)+1 for i in range(10) ] [1, 2, 5, 8, 13, 18, 25, 32, 41, 50]
- polar()¶
Return the polar (dual) polytope.
The polytope must have the IP-property (see
has_IP_property()
), that is, the origin must be an interior point. In particular, it must be full-dimensional.OUTPUT:
The polytope whose vertices are the coefficient vectors of the inequalities of
self
with inhomogeneous term normalized to unity.EXAMPLES:
sage: p = Polyhedron(vertices=[(1,0,0),(0,1,0),(0,0,1),(-1,-1,-1)], base_ring=ZZ) sage: p.polar() A 3-dimensional polyhedron in ZZ^3 defined as the convex hull of 4 vertices sage: type(_) <class 'sage.geometry.polyhedron.parent.Polyhedra_ZZ_ppl_with_category.element_class'> sage: p.polar().base_ring() Integer Ring