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v.net.centrality(1grass) GRASS GIS User's Manual v.net.centrality(1grass)

NAME

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:


Use geodesic calculation for longitude-latitude locations

Add points on nodes

Allow output files to overwrite existing files

Print usage summary

Verbose module output

Quiet module output

Force launching GUI dialog

Parameters:


Name of input vector map
Or data source for direct OGR access

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
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

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 population >= 10000

Arc forward/both direction(s) cost column (number)

Arc backward direction cost column (number)

Node cost column (number)

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

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

SOURCE CODE

Available at: v.net.centrality source code (history)

Accessed: Sat Jun 4 12:07:08 2022

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GRASS 8.2.0