v.net.centrality  Computes degree, centrality, betweeness,
closeness and eigenvector centrality measures in the network.
vector, network, centrality measures
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]
 g

Use geodesic calculation for longitudelatitude locations
 a

Add points on nodes
 overwrite

Allow output files to overwrite existing files
 help

Print usage summary
 verbose

Verbose module output
 quiet

Quiet module output
 ui

Force launching GUI dialog
 input=name [required]

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

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=string

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
 output=name [required]

Name for output vector map
 cats=range

Category values
Example: 1,3,79,13
 where=sql_query

WHERE conditions of SQL statement without ’where’ keyword
Example: income < 1000 and population >= 10000
 arc_column=name

Arc forward/both direction(s) cost column (number)
 arc_backward_column=name

Arc backward direction cost column (number)
 node_column=string

Node cost column (number)
 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
v.net.centrality computes degree, closeness, betweenness and eigenvector
centrality measures.
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*(N1)/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.
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
v.net, v.generalize
Daniel Bundala, Google Summer of Code 2009, Student
Wolf Bergenheim, Mentor
Last changed: $Date: 20160328 23:23:39 +0200 (Mon, 28 Mar 2016) $
Available at: v.net.centrality source code (history)
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