This tutorial is probably also available as a Jupyter notebook in the demo folder in the polymake source and on github.

Different versions of this tutorial: latest release, release 3.4, release 3.3, release 3.2, nightly master

Matching Polytopes

In this tutorial we will use polymake to construct and analyse matching polytopes.

First we construct a graph, the complete graph on four nodes:

> $K4=new props::Graph(4);
> for (my $i=0; $i<4; ++$i) {
>   for (my $j=$i+1; $j<4; ++$j) {
>     $K4->edge($i,$j);
>   }
> }

(See also the Tutorial on Graphs for more on the construction of graphs.)

Next we like to have the node-edge-incidence matrix of our graph. Since the latest release of polymake does not yet support this, we have to write the function ourselves:

> sub node_edge_incidences {
>     my $g=shift;
>    my $A=new Matrix<Int>($g->nodes, $g->edges);
>     my $k=0;
>    for (my $i=0; $i<$g->nodes-1; ++$i) {
>        foreach (@{$g->adjacent_nodes($i)}) {
>            if ($_>$i) {
>                $A->[$i]->[$k]=1;
>                $A->[$_]->[$k]=1;
>                ++$k;
>            }
>        }
>    }
>    return $A;
> }

Now we can construct the node-edge-incidence matrix of our graph K4:

> $A=node_edge_incidences($K4);
> print $A;
1 1 1 0 0 0
1 0 0 1 1 0
0 1 0 1 0 1
0 0 1 0 1 1

With this we can now construct the constraint matrix consisting of an upper part for the nonnegativity constraints xe<html>≥</html>0 …

> $I=new Matrix<Int>([[1,0,0,0,0,0],[0,1,0,0,0,0],[0,0,1,0,0,0],[0,0,0,1,0,0],[0,0,0,0,1,0],[0,0,0,0,0,1]]);
> $Block1=new Matrix<Int>(new Vector<Int>([0,0,0,0,0,0]) | $I);

… and a lower part for the constraints Σ</html>e xe<html>≤</html>1 for each vertex v∈</html>V, where the sum is over all edges e containing v:

> $Block2=new Matrix<Int>(new Vector<Int>([1,1,1,1]) | -$A);

Now we can put both parts together and define the polytope:

> $Ineqs=new Matrix<Rational>($Block1 / $Block2);
> $P=new Polytope<Rational>(INEQUALITIES=>$Ineqs);

The matching polytope of K4 is the integer hull of P:

> $P_I=new Polytope<Rational>(POINTS=>$P->LATTICE_POINTS);

We can analyse some elementary properties of P_I

> print $P_I->POINTS;
1 0 0 0 0 0 0
1 0 0 0 0 0 1
1 0 0 0 0 1 0
1 0 0 0 1 0 0
1 0 0 1 0 0 0
1 0 0 1 1 0 0
1 0 1 0 0 0 0
1 0 1 0 0 1 0
1 1 0 0 0 0 0
1 1 0 0 0 0 1
> print $P_I->FACETS;
0 0 0 0 0 0 1
0 1 0 0 0 0 0
1 0 0 0 -1 -1 -1
1 -1 0 0 -1 -1 0
1 0 -1 0 -1 0 -1
1 -1 -1 0 -1 0 0
1 0 0 -1 0 -1 -1
1 -1 0 -1 0 -1 0
1 0 -1 -1 0 0 -1
1 -1 -1 -1 0 0 0
0 0 0 0 0 1 0
0 0 1 0 0 0 0
0 0 0 0 1 0 0
0 0 0 1 0 0 0
> print $P_I->N_FACETS;
14

… and compare them with the according properties of the defining polytope P:

> print $P->VERTICES;
1 0 0 0 1 0 0
1 0 1 0 0 0 0
1 1/2 1/2 0 1/2 0 0
1 0 0 0 0 0 0
1 1 0 0 0 0 0
1 1/2 0 1/2 0 1/2 0
1 0 1/2 1/2 0 0 1/2
1 0 0 0 1/2 1/2 1/2
1 0 0 0 0 1 0
1 0 0 1 0 0 0
1 0 0 0 0 0 1
1 1 0 0 0 0 1
1 0 1 0 0 1 0
1 0 0 1 1 0 0
> print $P->VOLUME;
1/72
> print $P_I->VOLUME;
1/90

Next we analyse the combinatorics of P_I: The Gale diagram of ''facet0''

> print $P_I->AMBIENT_DIM, " ", $P_I->DIM;
6 6
> print $P_I->F_VECTOR;
10 39 78 86 51 14
> print $P_I->FACET_SIZES;
8 8 6 6 6 6 6 6 6 6 8 8 8 8
> $facet0=facet($P_I,0);
> print $facet0->AMBIENT_DIM, " ", $facet0->DIM;
6 5
> print rows_labeled($facet0->VERTICES_IN_FACETS);
0:0 1 2 3 4 5 6
1:1 2 4 6 7
2:2 4 5 6 7
3:1 3 4 6 7
4:3 4 5 6 7
5:0 2 3 4 5 7
6:0 1 2 3 4 7
7:0 1 3 5 6 7
8:0 1 2 5 6 7
> $facet0->GALE;

The Gale diagram of facet0 is depicted on the right.

  • user_guide/tutorials/matching_polytopes.txt
  • Last modified: 2019/02/04 22:55
  • (external edit)