v.net.centrality - Computes degree, centrality, betweeness, closeness and eigenvector centrality measures in the network.
vector, network, centrality measures
v.net.centrality [-ga] input=name [layer=integer] output=name [cats=range] [where=sql_query] [afcolumn=name] [abcolumn=name] [degree=name] [closeness=name] [betweenness=name] [eigenvector=name] [iterations=integer] [error=float] [--overwrite] [--verbose] [--quiet]
- Use geodesic calculation for longitude-latitude locations
- Add points on nodes
- Allow output files to overwrite existing files
- Verbose module output
- Quiet module output
- Name of input vector map
- Layer number
- A single vector map can be connected to multiple database tables. This number determines which table to use.
- Default: 1
- 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 inhab >= 10000
- Name of arc forward/both direction(s) cost column
- Name of arc backward direction cost column
- 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
- Cummulative 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 ingored and no new points are added.
Betwenness 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 cummulative 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=close betweenness=betw -a
Daniel Bundala, Google Summer of Code 2009, Student
Wolf Bergenheim, Mentor
Last changed: $Date: 2011-11-08 01:42:51 -0800 (Tue, 08 Nov 2011) $
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