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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.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 < 1000 and inhab >= 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*
- 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 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 13:01:55 -0700 (Thu, 23 May 2013) $*

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