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**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.centrality--helpv.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:-gUse geodesic calculation for longitude-latitude locations-aAdd points on nodes--overwriteAllow output files to overwrite existing files--helpPrint usage summary--verboseVerbose module output--quietQuiet module output--uiForce launching GUI dialogParameters:input=name[required]Name of input vector map Or data source for direct OGR accessarc_layer=stringArc 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:1node_layer=stringNode 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:2output=name[required]Name for output vector mapcats=rangeCategory values Example: 1,3,7-9,13where=sql_queryWHERE conditions of SQL statement without ’where’ keyword Example: income < 1000 and population >= 10000arc_column=nameArc forward/both direction(s) cost column (number)arc_backward_column=nameArc backward direction cost column (number)node_column=stringNode cost column (number)degree=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=floatCumulative 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 cumulativesquarederror 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:$Date:2016-03-2823:23:39+0200(Mon,28Mar2016)$

**SOURCE** **CODE**

Available at: v.net.centrality source code (history) Main index | Vector index | Topics index | Keywords index | Graphical index | Full index © 2003-2019 GRASS Development Team, GRASS GIS 7.6.1 Reference Manual