Exemple #1
0
        // Counts the number of independent sets in a graph, such that:
        // - The vertices in P are legal choices for our IS, initially set to all vertices in the graph
        // - None of the vertices in X are used, initially empty
        // The performDFS boolean is used to check if we should perform a check for connectedness on this level of the recursion
        private static long Compute(Graph graph, BitSet P, BitSet X, bool performDFS)
        {
            // Base case, when P and X are both empty we cannot expand the IS
            if (P.IsEmpty && X.IsEmpty)
                return 1;

            // Base case, if a vertex w in X has no neighbor in P, then it means that this IS will never get maximal
            // since we could always include w. Thus, the IS will not be valid and we return 0.
            foreach (int w in X)
                if ((graph.OpenNeighborhood(w) * P).IsEmpty)
                    return 0;

            long count = 0;

            // If a DFS is needed we check if the graph induced by (P + X) is still connected.
            // If the graph is disconnected, in components c1,...,cn then we can simply count the IS of all these components
            // after which we simply multiply these numbers.
            if (performDFS)
            {
                if (!DepthFirstSearch.Connected(graph, P + X))
                {
                    count = 1;

                    foreach (BitSet component in DepthFirstSearch.ConnectedComponents(graph, P + X))
                        count *= Compute(graph, component * P, component * X, false);

                    return count;
                }
            }

            // Select a pivot in P to branch on
            // In this case we pick the vertex with the largest degree
            int maxDegree = -1; ;
            int pivot = -1;
            foreach (int u in P)
            {
                int deg = graph.Degree(u);
                if (deg > maxDegree)
                {
                    maxDegree = deg;
                    pivot = u;
                }
            }

            // There should always be a pivot after the selection procedure
            if (pivot == -1)
                throw new Exception("Pivot has not been selected");

            // We branch on the pivot, one branch we include the pivot in the IS.
            // This might possibly disconnect the subgraph G(P + X), thus we set the performDFS boolean to true.
            count = Compute(graph, P - graph.ClosedNeighborhood(pivot), X - graph.OpenNeighborhood(pivot), true);

            // One branch we exclude the pivot of the IS. This will not cause the graph to get possibly disconnected
            count += Compute(graph, P - pivot, X + pivot, false);

            return count;
        }
Exemple #2
0
        // Counts the number of independent sets in a graph, such that:
        // - All vertices in R are included in the independent set, initially empty
        // - Some of the vertices in P are included in the independent set, initially all vertices of the graph
        // - None of the vertices in X are included in the independent set, initially empty
        private static long Compute(Graph graph, BitSet R, BitSet P, BitSet X)
        {
            // Base case, when P and X are both empty we cannot expand the IS
            if (P.IsEmpty && X.IsEmpty)
                return 1;

            long count = 0;
            int pivot = -1;
            int min = int.MaxValue;

            // Procedure to find a pivot
            // The idea is that in any maximal IS, either vertex u or a neighbor of u is included (else we could expand by adding u to the IS)
            // We find the u with the smallest neighborhood, so that we will keep the number of branches low
            foreach (int u in (P + X))
            {
                int size = (P * graph.OpenNeighborhood(u)).Count;
                if (size < min)
                {
                    min = size;
                    pivot = u;
                }
            }

            // There should always be a pivot after the selection procedure, else P and X should both have been empty
            if (pivot == -1)
                throw new Exception("Pivot has not been selected");

            // Foreach vertex v in the set containing the legal choices of the the closed neighborhood of the pivot,
            // we include each choice in the IS and compute how many maximal IS will include v by going into recursion
            foreach (int v in (P * graph.ClosedNeighborhood(pivot)))
            {
                count += Compute(graph, R + v, P - graph.ClosedNeighborhood(v), X - graph.OpenNeighborhood(v));
                P.Remove(v);
                X.Add(v);
            }

            return count;
        }
Exemple #3
0
        // Counts the number of independent sets in a graph, such that:
        // - All vertices in R are included in the independent set, initially empty
        // - Some of the vertices in P are included in the independent set, initially all vertices of the graph
        // - None of the vertices in X are included in the independent set, initially empty
        private static int Compute(Graph graph, BitSet R, BitSet P, BitSet X)
        {
            // Base case, when P and X are both empty we cannot expand the IS
            if (P.IsEmpty && X.IsEmpty)
                return 1;

            int count = 0;
            BitSet copy = P.Copy();

            // Foreach vertex v in P we include it in the IS and compute how many maximal IS will include v by going into recursion.
            foreach (int v in copy)
            {
                count += Compute(graph, R + v, P - graph.ClosedNeighborhood(v), X - graph.OpenNeighborhood(v));
                P.Remove(v);
                X.Add(v);
            }

            return count;
        }