public List <MinCutEdge <T> > ComputeMinCut(WeightedDiGraph <T, W> graph,
                                                    T source, T sink)
        {
            var edmondsKarpMaxFlow = new EdmondKarpMaxFlow <T, W>(operators);

            var maxFlowResidualGraph = edmondsKarpMaxFlow
                                       .computeMaxFlowAndReturnResidualGraph(graph, source, sink);

            //according to Min Max theory
            //the Min Cut can be obtained by Finding edges
            //from Reachable Vertices from Source
            //to unreachable vertices in residual graph
            var reachableVertices = getReachable(maxFlowResidualGraph, source);

            var result = new List <MinCutEdge <T> >();

            foreach (var vertex in reachableVertices)
            {
                foreach (var edge in graph.Vertices[vertex].OutEdges)
                {
                    //if unreachable
                    if (!reachableVertices.Contains(edge.Key.Value))
                    {
                        result.Add(new MinCutEdge <T>(vertex, edge.Key.Value));
                    }
                }
            }

            return(result);
        }
Beispiel #2
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        public List <MinCutEdge <T> > ComputeMinCut(IDiGraph <T> graph,
                                                    T source, T sink)
        {
            if (this.@operator == null)
            {
                throw new ArgumentException("Provide an operator implementation for generic type W during initialization.");
            }

            if (!graph.IsWeightedGraph)
            {
                if ([email protected]() != typeof(int))
                {
                    throw new ArgumentException("Edges of unweighted graphs are assigned an imaginary weight of one (1)." +
                                                "Provide an appropriate IFlowOperators<int> operator implementation during initialization.");
                }
            }

            var edmondsKarpMaxFlow = new EdmondKarpMaxFlow <T, W>(@operator);

            var maxFlowResidualGraph = edmondsKarpMaxFlow
                                       .computeMaxFlowAndReturnResidualGraph(graph, source, sink);

            //according to Min Max theory
            //the Min Cut can be obtained by Finding edges
            //from Reachable Vertices from Source
            //to unreachable vertices in residual graph
            var reachableVertices = getReachable(maxFlowResidualGraph, source);

            var result = new List <MinCutEdge <T> >();

            foreach (var vertex in reachableVertices)
            {
                foreach (var edge in graph.GetVertex(vertex).OutEdges)
                {
                    //if unreachable
                    if (!reachableVertices.Contains(edge.TargetVertexKey))
                    {
                        result.Add(new MinCutEdge <T>(vertex, edge.TargetVertexKey));
                    }
                }
            }

            return(result);
        }
        /// <summary>
        /// Get Max Match from Given BiPartitioned Graph.
        /// </summary>
        private List <MatchEdge <T> > getMaxBiPartiteMatching(IGraph <T> graph,
                                                              Dictionary <int, List <T> > partitions)
        {
            //add unit edges from dymmy source to group 1 vertices
            var dummySource = @operator.GetRandomUniqueVertex();

            if (graph.ContainsVertex(dummySource))
            {
                throw new Exception("Dummy vertex provided is not unique to given graph.");
            }

            //add unit edges from group 2 vertices to sink
            var dummySink = @operator.GetRandomUniqueVertex();

            if (graph.ContainsVertex(dummySink))
            {
                throw new Exception("Dummy vertex provided is not unique to given graph.");
            }

            var workGraph = createFlowGraph(graph, dummySource, dummySink, partitions);

            //run ford fulkerson using edmon karp method
            var fordFulkerson = new EdmondKarpMaxFlow <T, int>(@operator);

            var flowPaths = fordFulkerson
                            .ComputeMaxFlowAndReturnFlowPath(workGraph, dummySource, dummySink);

            //now gather all group1 to group 2 edges in residual graph with positive flow
            var result = new List <MatchEdge <T> >();

            foreach (var path in flowPaths)
            {
                result.Add(new MatchEdge <T>(path[1], path[2]));
            }

            return(result);
        }