r.surf.gauss - Generates a raster map using gaussian random number generator.

Author

       Jo Wood, ASSIST’s home

Description

r.surf.gauss produces a raster map of  Gaussian  deviates  whose  mean  and  standard  deviation  can  be
       expressed  by  the  user.  It  uses  a  Gaussian  random  number generator. It is essentially the same as
       r.surf.random, but uses a Gaussian random number generator instead.

Example

       g.region -p n=228500 s=215000 w=630000 e=645000 res=10
       r.surf.gauss out=gauss mean=0 sigma=10
       # check result
       r.univar gauss
       Figure:RandomGaussiansurfaceexample(mean:0;sigma:10)

       With the histogram tool the cell values versus count can be shown.

       Figure:HistogramofrandomGaussiansurfaceexample(mean:0;sigma:10)

Keywords

       raster, surface, random

Name

r.surf.gauss  - Generates a raster map using gaussian random number generator.
       Mean and standard deviation of gaussian deviates can be expressed by the user.

Source Code

       Available at: r.surf.gauss source code (history)

       Accessed: Friday Apr 04 01:19:39 2025

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       © 2003-2025 GRASS Development Team, GRASS GIS 8.4.1 Reference Manual

GRASS 8.4.1                                                                                 r.surf.gauss(1grass)

Synopsis

r.surf.gaussr.surf.gauss--helpr.surf.gaussoutput=name    [mean=float]    [sigma=float]    [seed=integer]    [--overwrite]   [--help]
       [--verbose]  [--quiet]  [--ui]

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

       mean=float
           Distribution mean
           Default: 0.0sigma=float
           Standard deviation
           Default: 1.0seed=integer
           Seed for random number generator
           The same seed can be used to obtain same results or random seed can be generated by other means.