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:

-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 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: Monday Apr 01 03:08:45 2024

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