v.perturb - Random location perturbations of vector points.

NAME KEYWORDS SYNOPSIS Flags: Parameters: DESCRIPTION NOTES EXAMPLES Random, uniformly distributed selection Normal distributed selection Normal distributed selection with a minimum value SEE ALSO AUTHORS SOURCE CODE

NAME

v.perturb − Random location perturbations of vector points.

KEYWORDS

vector, geometry, statistics, random, point pattern, level1

v.perturb
v.perturb −−help
v.perturb [−sb] input=name [layer=string] output=name [distribution=string] parameters=float[,float,...] [minimum=float] [seed=integer] [−−overwrite] [−−help] [−−verbose] [−−quiet] [−−ui]

Flags:

−s

Generate random seed (result is non−deterministic)

−b

Do not build topology
Advantageous when handling a large number of points

−−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=nameÂ [required]

Name of input vector map
Or data source for direct OGR access

layer=string

Layer number or name (’−1’ for all layers)
A single vector map can be connected to multiple database tables. This number determines which table to use. When used with direct OGR access this is the layer name.
Default: −1

output=nameÂ [required]

Name for output vector map

distribution=string

Distribution of perturbation
Options: uniform, normal
Default: uniform

parameters=float[,float,...]Â [required]

Parameter(s) of distribution
If the distribution is uniform, only one parameter, the maximum, is needed. For a normal distribution, two parameters, the mean and standard deviation, are required.

minimum=float

Minimum deviation in map units
Default: 0.0

seed=integer

Seed for random number generation

DESCRIPTION

v.perturb reads a vector map of points and writes the same points but perturbs the eastings and northings by adding either a uniform or normal delta value. Perturbation means that a variating spatial deviation is added to the coordinates.

NOTES

The uniform distribution is always centered about zero. The associated parameter is constrained to be positive and specifies the maximum of the distribution; the minimum is the negation of that parameter. Do perturb into a ring around the center, the minimum parameter can be used.

Usually, the mean (first parameter) of the normal distribution is zero (i.e., the distribution is centered at zero). The standard deviation (second parameter) is naturally constrained to be positive.

Output vector points are not guaranteed to be contained within the current geographic region.

EXAMPLES

Random, uniformly distributed selection

To create a random, uniformly distributed selection of possible new points with a radius of 100,000 map units, use the following command:

v.perturb input=comm_colleges output=uniform_perturb parameters=100000

Your map should look similar to this figure:
Figure: Map showing the actual community college points and uniformly random chosen points.

Normal distributed selection

For a normal distribution with a mean of 5000 and standard deviation of 2000, use the following command:

v.perturb input=comm_colleges output=normal_perturb distribution=normal parameters=5000,2000

Figure: Map showing the actual community college points and normally random chosen and colored points. Notice that each point is closer to the original point.

Normal distributed selection with a minimum value

In order to include a minimum value of 500, use the following command:

v.perturb input=comm_colleges output=min_perturb distribution=normal parameters=100000,1000 minimum=500

AUTHORS

James Darrell McCauley
when he was at: Agricultural Engineering Purdue University

Random number generators originally written in FORTRAN by Wes Peterson and translated to C using f2c.

SOURCE CODE

Available at: v.perturb source code (history)

Latest change: Thursday Jan 26 14:10:26 2023 in commit: cdd84c130cea04b204479e2efdc75c742efc4843

Updated 2026-06-01 - jenkler.se | uex.se