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v.perturb - Random location perturbations of vector points.
vector, geometry, statistics, random, point pattern, level1
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
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.
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.
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
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.
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