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 longitude-latitude 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: 1,3,7-9,13
- 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*(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.
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: 2016-03-28 23:23:39 +0200 (Mon, 28 Mar 2016) $
Available at: v.net.centrality source code (history)
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