v.net.centrality.1grass man page
v.net.centrality — Computes degree, centrality, betweeness, closeness and eigenvector centrality measures in the network.
Keywords
vector, network, centrality measures
Synopsis
v.net.centrality
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]
Flags
- -g
Use geodesic calculation for longitude-latitude locations
- -a
Add points on nodes
- --overwrite
Allow output files to overwrite existing files
- --help
Print usage summary
- --verbose
Verbose module output
- --quiet
Quiet module output
- --ui
Force launching GUI dialog
Parameters
- input=name [required]
Name of input vector map
Or data source for direct OGR access- arc_layer=string
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=string
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
- cats=range
Category values
Example: 1,3,7-9,13- where=sql_query
WHERE conditions of SQL statement without ’where’ keyword
Example: income < 1000 and population >= 10000- arc_column=name
Arc forward/both direction(s) cost column (number)
- arc_backward_column=name
Arc backward direction cost column (number)
- node_column=string
Node cost column (number)
- degree=name
Name of degree centrality column
- closeness=name
Name of closeness centrality column
- betweenness=name
Name of betweenness centrality column
- eigenvector=name
Name of eigenvector centrality column
- iterations=integer
Maximum number of iterations to compute eigenvector centrality
Default: 1000- error=float
Cumulative error tolerance for eigenvector centrality
Default: 0.1
Description
v.net.centrality computes degree, closeness, betweenness and eigenvector centrality measures.
Notes
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.
Examples
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
Authors
Daniel Bundala, Google Summer of Code 2009, Student
Wolf Bergenheim, Mentor
Last changed: $Date: 2016-03-28 23:23:39 +0200 (Mon, 28 Mar 2016) $
Source Code
Available at: v.net.centrality source code (history)
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