Remarks
A biconnected component is a subgraph which is connected and non-separable, i.e. after removing one single node the component is still connected.
Nodes will be clustered such that the nodes within each cluster are biconnected. Nodes that belong to multiple biconnected components (articulation nodes) will be assigned to exactly one of these clusters.
Other Clustering Algorithms
yFiles for HTML supports a number of other clustering algorithms:
- KMeansClustering – partitions the graph into clusters based on the distance between nodes and the cluster midpoints.
- HierarchicalClustering – partitions the graph into clusters by merging smaller clusters based on their distance.
- EdgeBetweennessClustering – partitions the graph into clusters based on edge-betweenness centrality.
- LouvainModularityClustering – partitions the graph into clusters by applying the Louvain modularity method.
- LabelPropagationClustering – partitions the graph into clusters by applying a label propagation algorithm.
Complexity
Examples
// prepare the biconnected components clustering algorithm
const algorithm = new BiconnectedComponentClustering()
// run the algorithm
const result = algorithm.run(graph)
// highlight the nodes of the clusters with different styles
for (const node of graph.nodes) {
const componentId = result.nodeClusterIds.get(node)!
graph.setStyle(node, clusterStyles.get(componentId)!)
}See Also
Developer's Guide
API
- biconnectedComponentClustering
Members
Constructors
Properties
Gets or sets the collection of edges which define a subset of the graph for the algorithms to work on.
If nothing is set, all edges of the graph will be processed.
If only the excludes are set, all edges in the graph except those provided in the excludes are processed.
Note that edges which start or end at nodes which are not in the subgraphNodes are automatically not considered by the algorithm.
ItemCollection<T> instances may be shared among algorithm instances and will be (re-)evaluated upon (re-)execution of the algorithm.
Examples
// prepare the biconnected components clustering algorithm
const algorithm = new BiconnectedComponentClustering({
// Ignore edges without target arrow heads
subgraphEdges: {
excludes: (edge: IEdge): boolean =>
edge.style instanceof PolylineEdgeStyle &&
edge.style.targetArrow instanceof Arrow &&
edge.style.targetArrow.type === ArrowType.NONE,
},
})
// run the algorithm
const result = algorithm.run(graph)
// highlight the nodes of the clusters with different styles
for (const node of graph.nodes) {
const componentId = result.nodeClusterIds.get(node)!
graph.setStyle(node, clusterStyles.get(componentId)!)
}Gets or sets the collection of nodes which define a subset of the graph for the algorithms to work on.
If nothing is set, all nodes of the graph will be processed.
If only the excludes are set, all nodes in the graph except those provided in the excludes are processed.
ItemCollection<T> instances may be shared among algorithm instances and will be (re-)evaluated upon (re-)execution of the algorithm.
Examples
// prepare the biconnected components clustering algorithm
const algorithm = new BiconnectedComponentClustering({
subgraphNodes: {
// only consider elliptical nodes in the graph
includes: (node: INode): boolean =>
node.style instanceof ShapeNodeStyle &&
node.style.shape === ShapeNodeShape.ELLIPSE,
// but ignore the first node, regardless of its shape
excludes: graph.nodes.first()!,
},
})
// run the algorithm
const result = algorithm.run(graph)
// highlight the nodes of the clusters with different styles
for (const node of graph.nodes) {
const componentId = result.nodeClusterIds.get(node)!
graph.setStyle(node, clusterStyles.get(componentId)!)
}Methods
Partitions the graph into clusters based on its biconnected components.
Parameters
- graph: IGraph
- The input graph to run the algorithm on.
Return Value
- BiconnectedComponentClusteringResult
- A BiconnectedComponentClusteringResult of clusters in the graph.
Throws
- Exception ({ name: 'InvalidOperationError' })
- If the algorithm can't create a valid result due to an invalid graph structure or wrongly configured properties.
Complexity
O(|E| + |V|)