Remarks
Weight centrality measures the weight associated with incoming, outgoing, or all edges of a node.
When no weights are associated with edges, weight centrality becomes the same as DegreeCentrality.
Other Centrality Measures
yFiles for HTML supports a number of other centrality measures:
- GraphCentrality, ClosenessCentrality – emphasize nodes that have short paths to other nodes
- DegreeCentrality – emphasizes nodes with many edges
- BetweennessCentrality – emphasizes nodes and edges that are part of many short paths
- EigenvectorCentrality – computes the influence a node has on a network. The centrality value is higher if more nodes are connected to that node
- PageRank – computes page rank values for all nodes based on their attached edges
Complexity
- O(|V| + |E|) when edge weights are provided
- O(|V|) without edge weights
Examples
const result = new WeightCentrality({
considerIncomingEdges: false,
considerOutgoingEdges: true,
// Use the geometric edge length as weight
weights: (edge) =>
edge.style.renderer
.getPathGeometry(edge, edge.style)
.getPath()!
.getLength(),
}).run(graph)
// add node labels for centrality values
// and adjust node size according to centrality
result.normalizedNodeCentrality.forEach(({ key, value }) => {
const node = key
const centrality = value
graph.addLabel(key, String(value))
graph.setNodeLayout(
node,
new Rect(node.layout.center, new Size(centrality, centrality)),
)
})See Also
Developer's Guide
API
- weightCentrality
Members
Constructors
Properties
If both considerIncomingEdges and considerOutgoingEdges are false, all nodes will have the centrality 0.
Default is false.
Property Value
true if the incoming edges should be considered, false otherwise.If both considerIncomingEdges and considerOutgoingEdges are false, all nodes will have the centrality 0.
Default is true.
Property Value
true if the incoming edges should be considered, false otherwise.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
// configure the algorithm
const algorithm = new WeightCentrality({
// Use the geometric edge length as weight
weights: (edge) =>
edge.style.renderer
.getPathGeometry(edge, edge.style)
.getPath()!
.getLength(),
// 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)
// add node labels for centrality values
// and adjust node size according to centrality
result.normalizedNodeCentrality.forEach(({ key, value }) => {
const node = key
const centrality = value
graph.addLabel(key, String(value))
graph.setNodeLayout(
node,
new Rect(node.layout.center, new Size(centrality, centrality)),
)
})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
// configure the algorithm
const algorithm = new WeightCentrality({
// Use the geometric edge length as weight
weights: (edge) =>
edge.style.renderer
.getPathGeometry(edge, edge.style)
.getPath()!
.getLength(),
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)
// add node labels for centrality values
// and adjust node size according to centrality
result.normalizedNodeCentrality.forEach(({ key, value }) => {
const node = key
const centrality = value
graph.addLabel(key, String(value))
graph.setNodeLayout(
node,
new Rect(node.layout.center, new Size(centrality, centrality)),
)
})Gets or sets a mapping for edge weights.
Weight centrality sums the weights of adjacent edges on each node. Edge weights thus influence the centrality measure. If no weights are provided, all edges have the same uniform weight of 1 which reduces the measure to the number of adjacent edges. This is then the same as DegreeCentrality.
Edge weights for weight centrality must be positive.
Methods
Computes the weight centrality for the nodes of a graph.
Parameters
- graph: IGraph
- The input graph to run the algorithm on.
Return Value
- WeightCentralityResult
- A WeightCentralityResult from which the calculated centrality values can be obtained.
Throws
- Exception ({ name: 'InvalidOperationError' })
- If the algorithm can't create a valid result due to an invalid graph structure or wrongly configured properties.