Cones

Introduction

Let $\mathbb{F}$ be an ordered field; the default is that $\mathbb{F}=\mathbb{Q}$ is the field of rational numbers and other fields are not yet supported everywhere in the implementation.

A set $C \subseteq \mathbb{F}^n$ is called a (polyhedral) cone if it can be written as the set of nonnegative linear combinations of finitely many vectors in $\mathbb{F}^n$. Equivalently, cones can be written as the intersection of finitely many homogeneous linear inequalities.

Any cone is a special case of a polyhedron. Conversely, intersecting a cone with a suitable affine hyperplane yields a polyhedron whose faces are in bijection with the faces of the cone. Going back and forth between polyhedra and their homogenizations, the cones, is a frequent operation. This is one reason for keeping cones as a distinct type.

Construction

positive_hullMethod
positive_hull([::Type{T} = fmpq,] R::AbstractCollection[RayVector] [, L::AbstractCollection[RayVector]]; non_redundant::Bool = false) where T<:scalar_types

A polyhedral cone, not necessarily pointed, defined by the positive hull of the rays R, with lineality given by L.

R is given row-wise as representative vectors, with lineality generated by the rows of L, i.e. the cone consists of all positive linear combinations of the rows of R plus all linear combinations of the rows of L.

This is an interior description, analogous to the $V$-representation of a polytope.

Redundant rays are allowed.

Examples

To construct the positive orthant as a Cone, you can write:

julia> R = [1 0; 0 1];

julia> PO = positive_hull(R)
A polyhedral cone in ambient dimension 2

To obtain the upper half-space of the plane:

julia> R = [0 1];

julia> L = [1 0];

julia> HS = positive_hull(R, L)
A polyhedral cone in ambient dimension 2
source
secondary_coneMethod
secondary_cone(SOP::SubdivisionOfPoints)

Return the secondary cone of a subdivision of points, the closure of all the weight vectors inducing the given subdivision of points.

Examples

For a non-regular subdivision, the secondary cone can still contain non-trivial weights, but it will not be full-dimensional.

julia> moaepts = [4 0 0; 0 4 0; 0 0 4; 2 1 1; 1 2 1; 1 1 2];

julia> moaeimnonreg0 = IncidenceMatrix([[4,5,6],[1,4,2],[2,4,5],[2,3,5],[3,5,6],[1,3,6],[1,4,6]]);

julia> MOAE = SubdivisionOfPoints(moaepts, moaeimnonreg0)
A subdivision of points in ambient dimension 3

julia> C = secondary_cone(MOAE)
A polyhedral cone in ambient dimension 6

julia> dim(C)
4
source

Auxiliary functions

```@docs ambientdim(C::Cone) contains(C::Cone, v::AbstractVector) fvector(C::Cone) hilbertbasis(C::Cone{fmpq}) codim(C::Cone) dim(C::Cone) polarize(C::Cone{T}) where T<:scalartypes intersect(C0::Cone{T}, C1::Cone{T}) where T<:scalartypes ispointed(C::Cone) isfulldimensional(C::Cone) linealitydim(C::Cone) linealityspace(C::Cone{T}) where T<:scalartypes nfacets(C::Cone) nrays(C::Cone) rays(C::Cone{T}) where T<:scalartypes raysmodulolineality(C::Cone{T}) where T<:scalartypes