NAME

       v.perturb  - Random location perturbations of vector points.

KEYWORDS

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

SYNOPSIS

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

   Flags:
       -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=name [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=name [required]
           Name for output vector map

       distribution=string
           Distribution of perturbation
           Options: uniform, normal
           Default: uniform

       parameters=float[,float,...] [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
           Default: 0

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

SEE ALSO

        v.random, v.univar

AUTHOR

       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)

       Accessed: unknown

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       © 2003-2022 GRASS Development Team, GRASS GIS 7.8.7 Reference Manual