  Any symmetric affinity function $w: V\times V \to \mathbb{R}_+$ defined on a
discrete set $V$ induces Euclidean space structure on $V$. In particular, an
undirected graph specified by an affinity (or adjacency) matrix can be
considered as a metric topological space. We have calculated the visual
representations of the probabilistic locus for a chain, a polyhedron, and a
finite 2-dimensional lattice.
