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 [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:¶

-g

 

Use geodesic calculation for longitude-latitude locations

-a

 

Add points on nodes

--overwrite

 

Allow output files to overwrite existing files

--verbose

 

Verbose module output

--quiet

 

Quiet module output

Parameters:¶

input=name

 

Name of input vector map

layer=integer

 

Layer number

 

A single vector map can be connected to multiple database tables. This number determines which table to use.

 

Default: 1

output=name

 

Name for output vector map

cats=range

 

Category values

 

Example: 1,3,7-9,13

where=sql_query

 

WHERE conditions of SQL statement without 'where' keyword

 

Example: income = 10000

afcolumn=name

 

Name of arc forward/both direction(s) cost column

abcolumn=name

 

Name of arc backward direction cost column

degree=name

 

Name of degree centrality column

closeness=name

 

Name of closeness centrality column

betweenness=name

 

Name of betweenness centrality column

eigenvector=name

 

Name of eigenvector centrality column

iterations=integer

 

Maximum number of iterations to compute eigenvector centrality

 

Default: 1000

error=float

 

Cummulative 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 cummulative 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 Last changed: $Date: 2013-05-23 22:01:55 +0200 (Thu, 23 May 2013) $ Full index © 2003-2014 GRASS Development Team