// Copyright ©2015 The gonum Authors. All rights reserved. // Use of this source code is governed by a BSD-style // license that can be found in the LICENSE file. package topo import ( "github.com/gonum/graph" "github.com/gonum/graph/internal" ) // VertexOrdering returns the vertex ordering and the k-cores of // the undirected graph g. func VertexOrdering(g graph.Undirected) (order []graph.Node, cores [][]graph.Node) { nodes := g.Nodes() // The algorithm used here is essentially as described at // http://en.wikipedia.org/w/index.php?title=Degeneracy_%28graph_theory%29&oldid=640308710 // Initialize an output list L. var l []graph.Node // Compute a number d_v for each vertex v in G, // the number of neighbors of v that are not already in L. // Initially, these numbers are just the degrees of the vertices. dv := make(map[int]int, len(nodes)) var ( maxDegree int neighbours = make(map[int][]graph.Node) ) for _, n := range nodes { adj := g.From(n) neighbours[n.ID()] = adj dv[n.ID()] = len(adj) if len(adj) > maxDegree { maxDegree = len(adj) } } // Initialize an array D such that D[i] contains a list of the // vertices v that are not already in L for which d_v = i. d := make([][]graph.Node, maxDegree+1) for _, n := range nodes { deg := dv[n.ID()] d[deg] = append(d[deg], n) } // Initialize k to 0. k := 0 // Repeat n times: s := []int{0} for _ = range nodes { // TODO(kortschak): Remove blank assignment when go1.3.3 is no longer supported. // Scan the array cells D[0], D[1], ... until // finding an i for which D[i] is nonempty. var ( i int di []graph.Node ) for i, di = range d { if len(di) != 0 { break } } // Set k to max(k,i). if i > k { k = i s = append(s, make([]int, k-len(s)+1)...) } // Select a vertex v from D[i]. Add v to the // beginning of L and remove it from D[i]. var v graph.Node v, d[i] = di[len(di)-1], di[:len(di)-1] l = append(l, v) s[k]++ delete(dv, v.ID()) // For each neighbor w of v not already in L, // subtract one from d_w and move w to the // cell of D corresponding to the new value of d_w. for _, w := range neighbours[v.ID()] { dw, ok := dv[w.ID()] if !ok { continue } for i, n := range d[dw] { if n.ID() == w.ID() { d[dw][i], d[dw] = d[dw][len(d[dw])-1], d[dw][:len(d[dw])-1] dw-- d[dw] = append(d[dw], w) break } } dv[w.ID()] = dw } } for i, j := 0, len(l)-1; i < j; i, j = i+1, j-1 { l[i], l[j] = l[j], l[i] } cores = make([][]graph.Node, len(s)) offset := len(l) for i, n := range s { cores[i] = l[offset-n : offset] offset -= n } return l, cores } // BronKerbosch returns the set of maximal cliques of the undirected graph g. func BronKerbosch(g graph.Undirected) [][]graph.Node { nodes := g.Nodes() // The algorithm used here is essentially BronKerbosch3 as described at // http://en.wikipedia.org/w/index.php?title=Bron%E2%80%93Kerbosch_algorithm&oldid=656805858 p := make(internal.Set, len(nodes)) for _, n := range nodes { p.Add(n) } x := make(internal.Set) var bk bronKerbosch order, _ := VertexOrdering(g) for _, v := range order { neighbours := g.From(v) nv := make(internal.Set, len(neighbours)) for _, n := range neighbours { nv.Add(n) } bk.maximalCliquePivot(g, []graph.Node{v}, make(internal.Set).Intersect(p, nv), make(internal.Set).Intersect(x, nv)) p.Remove(v) x.Add(v) } return bk } type bronKerbosch [][]graph.Node func (bk *bronKerbosch) maximalCliquePivot(g graph.Undirected, r []graph.Node, p, x internal.Set) { if len(p) == 0 && len(x) == 0 { *bk = append(*bk, r) return } neighbours := bk.choosePivotFrom(g, p, x) nu := make(internal.Set, len(neighbours)) for _, n := range neighbours { nu.Add(n) } for _, v := range p { if nu.Has(v) { continue } neighbours := g.From(v) nv := make(internal.Set, len(neighbours)) for _, n := range neighbours { nv.Add(n) } var found bool for _, n := range r { if n.ID() == v.ID() { found = true break } } var sr []graph.Node if !found { sr = append(r[:len(r):len(r)], v) } bk.maximalCliquePivot(g, sr, make(internal.Set).Intersect(p, nv), make(internal.Set).Intersect(x, nv)) p.Remove(v) x.Add(v) } } func (*bronKerbosch) choosePivotFrom(g graph.Undirected, p, x internal.Set) (neighbors []graph.Node) { // TODO(kortschak): Investigate the impact of pivot choice that maximises // |p ⋂ neighbours(u)| as a function of input size. Until then, leave as // compile time option. if !tomitaTanakaTakahashi { for _, n := range p { return g.From(n) } for _, n := range x { return g.From(n) } panic("bronKerbosch: empty set") } var ( max = -1 pivot graph.Node ) maxNeighbors := func(s internal.Set) { outer: for _, u := range s { nb := g.From(u) c := len(nb) if c <= max { continue } for n := range nb { if _, ok := p[n]; ok { continue } c-- if c <= max { continue outer } } max = c pivot = u neighbors = nb } } maxNeighbors(p) maxNeighbors(x) if pivot == nil { panic("bronKerbosch: empty set") } return neighbors }