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:
- -g
- Use geodesic calculation for longitude-latitude projects
- -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
Parameters:
- 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
SOURCE CODE
Available at:
v.net.centrality source code
(history)
Latest change: Friday Oct 25 16:16:09 2024 in commit: 4ea983fff87951516b6e4578a0527e3b10f04643
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