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- /****************************************************************************
- *
- * MODULE: r.random.cells
- * AUTHOR(S): Charles Ehlschlaeger; National Center for Geographic
- * Information and Analysis, University of California, Santa
- * Barbara (original contributor)
- * Markus Neteler <neteler itc.it>
- * Roberto Flor <flor itc.it>,
- * Brad Douglas <rez touchofmadness.com>,
- * Glynn Clements <glynn gclements.plus.com>Markus Neteler <neteler itc.it> (original contributor)
- * Bernhard Reiter <bernhard intevation.de>
- * PURPOSE: generates a random sets of cells that are at least
- * some distance apart
- * COPYRIGHT: (C) 2000-2004 by the GRASS Development Team
- *
- * This program is free software under the GNU General Public
- * License (>=v2). Read the file COPYING that comes with GRASS
- * for details.
- *
- *****************************************************************************/
- r.random.cells generates a random sets of cells that are at least
- some distance apart. The cells are numbered from 1 to the numbers of
- cells generated. Random cells will not be generated in areas masked off.
- OPTIONS
- -q
- This flag prevents the program from sending a verbose description to standard
- output of what the program is doing.
- -output
- Output map: Random cells. Each random cell has a unique non-zero cell
- value ranging from 1 to the number of cells generated. The heuristic for
- this algorithm is to randomly pick cells until there are no cells outside
- of the chosen cell's buffer of radius \fIdistance\fR.
- -distance
- Input value(s) [default 0.0]: distance determines the minimum distance
- the centers of the random cells will be apart.
- -seed
- Input value [default: random]: Specifies the random seed that
- r.random.cells will use to generate the cells. If the random seed
- is not given, then it will get a seed from the process ID number.
- NOTES
- The original purpose for this program was to generate independent random
- samples of cells in a study area. The distancevalue is the amount
- of spatial autocorrelation for the map being studied.
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