r.random.weight - GRASS GIS manual

Note: This document is for an older version of GRASS GIS that has been discontinued. You should upgrade, and read the current manual page.

NAME

r.random.weight - Generates a binary raster layer with a random selection of raster cells depending on the weight of each cell in the input weight layer.

KEYWORDS

raster, sampling, random

SYNOPSIS

r.random.weight

r.random.weight --help

r.random.weight [-sn] weights=raster output=raster [start=float] [end=float] [subsample=string] [seed=integer] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

-s: Generate random seed (result is non-deterministic)
-n: set non-selected values to 0 (default to NULL)
--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:

weights=raster [required]: layer with weight
output=raster [required]: output layer
start=float: minimum weight
end=float: maximum weight
subsample=string: subsample
seed=integer: set seed for random number generation

DESCRIPTION
Examples
See also
AUTHOR

DESCRIPTION

r.rand.weight generates a binary raster layer with a random selection of raster cells which are assigned 1. The other cells are assigned NULL (or optionally 0). The change for a raster cell to get assigned a 1 (to get selected) depends on the weight (value) of that cell in the input weight layer.

By default the script is run setting a random seed every time. To ensure that your results are reproducible you can set the seed value under the 'Sample options' tab. See the 'Random number generator initialization' in the r.mapcalc helpfile for more details.

You can play with the probability for a cell to be selected by changing the minimum and/or maximum weights. The script will give a warning if the user defined minimum > minimum raster value or if the user defined maximum is smaller then the maximum raster value. The script will still run as the user may have set this values intentionally.

You can also set the total number of sample points to be selected using the under the 'Sample options' tab. This can be done using an absolute number or as percentage (see the help file of the r.random function for more details).