Computes the weight centrality for the nodes of a graph.
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
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))
)
})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))
)
})Type Details
- yfiles module
- view-layout-bridge
- yfiles-umd modules
- view-layout-bridge
- Legacy UMD name
- yfiles.analysis.WeightCentrality
See Also
Constructors
Creates a new WeightCentrality instance.
Parameters
A map of options to pass to the method.
- weights - ItemMapping<IEdge,number>
A mapping for edge weights. This option sets the weights property on the created object.
- considerIncomingEdges - boolean
A value indicating whether incoming edges contribute to the centrality values of their target nodes. This option sets the considerIncomingEdges property on the created object.
- considerOutgoingEdges - boolean
A value indicating whether outgoing edges contribute to the centrality values of their source nodes. This option sets the considerOutgoingEdges property on the created object.
- subgraphNodes - ItemCollection<INode>
The collection of nodes which define a subset of the graph for the algorithms to work on. This option sets the subgraphNodes property on the created object.
- subgraphEdges - ItemCollection<IEdge>
The collection of edges which define a subset of the graph for the algorithms to work on. This option sets the subgraphEdges property on the created object.
Properties
Gets or sets a value indicating whether incoming edges contribute to the centrality values of their target nodes.
Remarks
If both considerIncomingEdges and considerOutgoingEdges are false all nodes will have the centrality 0.
Default is false.
Gets or sets a value indicating whether outgoing edges contribute to the centrality values of their source nodes.
Remarks
If both considerIncomingEdges and considerOutgoingEdges are false all nodes will have the centrality 0.
Default is true.
Gets or sets the collection of edges which define a subset of the graph for the algorithms to work on.
Remarks
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) =>
edge.style instanceof PolylineEdgeStyle &&
edge.style.targetArrow === IArrow.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))
)
})// 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 === IArrow.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.
Remarks
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) =>
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))
)
})// 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.
Remarks
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.
Complexity
O(|V|)
Parameters
A map of options to pass to the method.
- graph - IGraph
- The input graph to run the algorithm on.
Returns
- ↪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.