Provided by: grass-doc_6.4.3-3_all

**NAME**

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

**KEYWORDS**

vector, network, centrality measures

**SYNOPSIS**

v.net.centralityv.net.centralityhelpv.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]Flags:-gUse geodesic calculation for longitude-latitude locations-aAdd points on nodes--overwriteAllow output files to overwrite existing files--verboseVerbose module output--quietQuiet module outputParameters:input=nameName of input vector maplayer=integerLayer number A single vector map can be connected to multiple database tables. This number determines which table to use. Default:1output=nameName for output vector mapcats=rangeCategory values Example: 1,3,7-9,13where=sql_queryWHERE conditions of SQL statement without 'where' keyword Example: income = 10000afcolumn=nameName of arc forward/both direction(s) cost columnabcolumn=nameName of arc backward direction cost columndegree=nameName of degree centrality columncloseness=nameName of closeness centrality columnbetweenness=nameName of betweenness centrality columneigenvector=nameName of eigenvector centrality columniterations=integerMaximum number of iterations to compute eigenvector centrality Default:1000error=floatCummulative error tolerance for eigenvector centrality Default:0.1

**DESCRIPTION**

v.net.centralitycomputes 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-aflag is set then points are added on nodes without points. Also, the points for which the output is computed can be specified bycats,layerandwhereparameters. However, if any of these parameters is present then-aflag 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 byNchoose2=N*(N-1)/2where 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 cummulativesquarederror between the successive iterations is less thanerror.

**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, MentorLastchanged:$Date:2013-05-2313:01:55-0700(Thu,23May2013)$Full index © 2003-2013 GRASS Development Team