GRASS logo

Note: A new GRASS GIS stable version has been released: GRASS GIS 7. Go directly to the new manual page here

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


vector, network, centrality measures

SYNOPSIS help [-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
Cumulative error tolerance for eigenvector centrality
Default: 0.1

DESCRIPTION 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 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. input=roads output=roads_cent closeness=closeness \
      betweenness=betweenness -a

SEE ALSO, v.generalize


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

Last changed: $Date: 2013-05-23 13:01:55 -0700 (Thu, 23 May 2013) $

Main index - vector index - Full index

© 2003-2016 GRASS Development Team