Esempio n. 1
0
        /// <summary>
        /// Clusters and lays out the provided graph
        /// </summary>
        /// <param name="graphMapData">The graph to update</param>
        /// <param name="connectedGraph">The graph that needs to be clustered and layed out</param>
        private static void LayoutByClusters(GraphMapData graphMapData, GraphComponents connectedGraph)
        {
            System.Diagnostics.Debug.WriteLine("");
            foreach (Delegate d in ContextMenuManager.Instance.GetContextMenuOpeningInvocationList())
            {
                System.Diagnostics.Debug.WriteLine((d.Target as GraphComponents).Scope);
            }

            // Create a Cluster instance for the graph
            //Cluster clusterer = new Cluster(connectedGraph);

            // Specify the predicate to be used by the Cluster class.  In this case
            // we are determining clusters based on edges createdf during similarity
            // clustering.
            //clusterer.EdgePredicate = delegate(IEdge edge)
            //{
            //	bool isSimilarityDataEdge = edge is SimilarityDataEdge;
            //	return isSimilarityDataEdge;
            //};

            // Create the clusters and return a new graph.  Each node on the
            // graph will be represented as a PartitionNode
            //GraphComponents clusteredGraphComponents = clusterer.GetClusteredGraph();

            //bool isAttributeLayout = true;
            // If there is no different between the initial graph that was provided and
            // out clustered graph, we didn't really find clusters (most likely because
            // similarity clustering was not performed).
            //int clusteredNodesCount = clusteredGraphComponents.GetNodeViewModels().Count();
            //int connectedNodesCount = connectedGraph.GetNodeViewModels().Count();
            //if (clusteredNodesCount == connectedNodesCount)
            //{
                // TODO handle this better than just re-running

                // Rerun clustering without a predicate.  This means that clusters will
                // be based on regular edges.
            Cluster clusterer = new Cluster(connectedGraph);
            GraphComponents clusteredGraphComponents = clusterer.GetClusteredGraph();

            bool isAttributeLayout = false;
            //}

            System.Diagnostics.Debug.WriteLine("");
            foreach (Delegate d in ContextMenuManager.Instance.GetContextMenuOpeningInvocationList())
            {
                System.Diagnostics.Debug.WriteLine((d.Target as GraphComponents).Scope);
            }

            // Get all the nodes that are in the clustered graph. Remember that these are partition nodes.
            IEnumerable<INodeShape> clusteredComponents = clusteredGraphComponents.GetNodeViewModels();
            foreach (PartitionNode clusteredComponent in clusteredComponents)
            {
                // Create an appropriate layout to use for this cluster
                AsynchronousLayoutBase clusterLayout = GetClusterLayout(isAttributeLayout);
                using (GraphComponents clusteredGraph = clusteredComponent.GetGraph())
                {
                    GraphMapData clusteredGraphMapData = GetGraph(graphMapData, clusteredGraph);

                    // Run the layout.  This is laying out the individual cluster itself
                    clusterLayout.CalculateLayout(clusteredGraphMapData);
                }

                System.Diagnostics.Debug.WriteLine("");
                foreach (Delegate d in ContextMenuManager.Instance.GetContextMenuOpeningInvocationList())
                {
                    System.Diagnostics.Debug.WriteLine((d.Target as GraphComponents).Scope);
                }
            }

            System.Diagnostics.Debug.WriteLine("");
            foreach (Delegate d in ContextMenuManager.Instance.GetContextMenuOpeningInvocationList())
            {
                System.Diagnostics.Debug.WriteLine((d.Target as GraphComponents).Scope);
            }

            // Now we need to layout the entired clustered graph so it looks more organized
            GraphMapData clusteredGraphComponentsGraphMapData = GetClusteredGraph(graphMapData, clusteredGraphComponents);
            IDictionary<string, Point> originalPositions = GetOriginalPositions(clusteredGraphComponentsGraphMapData);
            FRLayout frLayout = new FRLayout();
            frLayout.CalculateLayout(clusteredGraphComponentsGraphMapData);
            ApplyOffsetToSubGraphs(graphMapData, clusteredGraphComponents, originalPositions, clusteredGraphComponentsGraphMapData);

            clusteredGraphComponents.Dispose();

            System.Diagnostics.Debug.WriteLine("");
            foreach (Delegate d in ContextMenuManager.Instance.GetContextMenuOpeningInvocationList())
            {
                System.Diagnostics.Debug.WriteLine((d.Target as GraphComponents).Scope);
            }
        }
Esempio n. 2
0
        /// <summary>
        /// Adds a highlight to the graph to indicate which data is clustered together
        /// </summary>
        /// <returns>A collection of polygron of clustered highlights on the graph</returns>
        public ICollection<Polygon> HighlightClusters()
        {
            RemoveHighlights();

            _cluster = new Cluster(GraphManager.Instance.GetGraphComponents(_scope));
            _cluster.EdgePredicate = delegate(Model.IEdge e) { return e is Model.SimilarityDataEdge; };

            GraphComponents clusteredGraph = _cluster.GetClusteredGraph();
            foreach (PartitionNode pn in clusteredGraph.GetNodeViewModels())
            {
                if (pn.Nodes.Count > 1)
                {
                    Polygon highlightPolygon = CreateHighlightPolygon(pn);
                    _clusterPolygons[highlightPolygon] = pn;
                }
            }
            clusteredGraph.Dispose();

            _highlightPolygons = _clusterPolygons.Keys;

            return _highlightPolygons;
        }