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v.net.centrality.1grass - Man Page

Computes degree, centrality, betweeness, closeness and eigenvector centrality measures in the network.


vector, network, centrality measures


v.net.centrality --help
v.net.centrality [-ga] input=name  [arc_layer=string]   [node_layer=string]  output=name  [cats=range]   [where=sql_query]   [arc_column=name]   [arc_backward_column=name]   [node_column=string]   [degree=name]   [closeness=name]   [betweenness=name]   [eigenvector=name]   [iterations=integer]   [error=float]   [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]



Use geodesic calculation for longitude-latitude locations


Add points on nodes


Allow output files to overwrite existing files


Print usage summary


Verbose module output


Quiet module output


Force launching GUI dialog


input=name [required]

Name of input vector map
Or data source for direct OGR access


Arc layer
Vector features can have category values in different layers. This number determines which layer to use. When used with direct OGR access this is the layer name.
Default: 1


Node layer
Vector features can have category values in different layers. This number determines which layer to use. When used with direct OGR access this is the layer name.
Default: 2

output=name [required]

Name for output vector map


Category values
Example: 1,3,7-9,13


WHERE conditions of SQL statement without ’where’ keyword
Example: income < 1000 and population >= 10000


Arc forward/both direction(s) cost column (number)


Arc backward direction cost column (number)


Node cost column (number)


Name of degree centrality column


Name of closeness centrality column


Name of betweenness centrality column


Name of eigenvector centrality column


Maximum number of iterations to compute eigenvector centrality
Default: 1000


Cumulative error tolerance for eigenvector centrality
Default: 0.1


v.net.centrality computes degree, closeness, betweenness and eigenvector centrality measures.


The module computes various centrality measures for each node and stores them in the given columns of an attribute table, which is created and linked to the output map. For the description of these, please check the following wikipedia article. If the column name is not given for a measure then that measure is not computed. If -a flag is set then points are added on nodes without points. Also, the points for which the output is computed can be specified by cats, layer and where parameters. However, if any of these parameters is present then -a flag is ignored and no new points are added.
Betweenness measure is not normalised. In order to get the normalised values (between 0 and 1), each number needs to be divided by N choose 2=N*(N-1)/2 where N is the number of nodes in the connected component. Computation of eigenvector measure terminates if the given number of iterations is reached or the cumulative squared error between the successive iterations is less than error.


Compute closeness and betweenness centrality measures for each node and produce a map containing not only points already present in the input map but a map with point on every node.

v.net.centrality input=roads output=roads_cent closeness=closeness \
      betweenness=betweenness -a

See Also

v.net, v.generalize


Daniel Bundala, Google Summer of Code 2009, Student
Wolf Bergenheim, Mentor

Source Code

Available at: v.net.centrality source code (history)

Accessed: Tuesday May 14 13:41:20 2024

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