table of contents
| v.net.centrality(1grass) | GRASS GIS User's Manual | v.net.centrality(1grass) |
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:¶
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
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 cumulative 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
SOURCE CODE¶
Available at: v.net.centrality source code (history)
Accessed: Thursday Aug 01 05:16:51 2024
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