v.net.centralitygrass - Online in the Cloud

PROGRAM:

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 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

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 inhab >= 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 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

Use v.net.centralitygrass online using onworks.net services