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NAME

       v.random  - Generates random 2D/3D vector points.

KEYWORDS

       vector, sampling, statistics, random, point pattern, stratified random sampling, level1

SYNOPSIS

       v.random
       v.random --help
       v.random    [-zab]   output=name   npoints=integer    [restrict=name]     [layer=string]     [cats=range]
       [where=sql_query]   [zmin=float]   [zmax=float]   [seed=integer]    [column=name]    [column_type=string]
       [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]

   Flags:
       -z
           Create 3D output

       -a
           Generate n points for each individual area (requires restrict parameter)

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

       npoints=integer [required]
           Number of points to be created

       restrict=name
           Name of input vector map
           Restrict points to areas in input vector

       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

       cats=range
           Category values
           Example: 1,3,7-9,13

       where=sql_query
           WHERE conditions of SQL statement without ’where’ keyword
           Example: income < 1000 and population >= 10000

       zmin=float
           Minimum z height (needs -z flag or column name)
           Default: 0.0

       zmax=float
           Maximum z height (needs -z flag or column name)
           Default: 0.0

       seed=integer
           The seed to initialize the random generator. If not set the process ID is used

       column=name
           Name of column for z values
           Writes z values to column

       column_type=string
           Type of column for z values
           Options: integer, double precision
           Default: double precision

DESCRIPTION

       v.random randomly generates vector points within the current region  using  the  selected  random  number
       generator.

       v.random  can  generate  also 3D vector points or write random value to the attribute table. Point height
       range or attribute value range is controlled by specifying zmin and zmax  options.   Both  z  values  are
       included  in  range  (zmin  <=  z  <=  zmax).  Generated random attribute value type can be controlled by
       column_type. Use integer column type for integers  and  double  precision  for  floating  point  numbers.
       Integer values are calculated by rounding random floating point number.

       To produce repeatable results a random seed can be set using the option seed.

   Restriction to vector areas
       If  an  restrict  vector  map with areas is specified, the location of random points is restricted to the
       selected areas. By default, the requested number of points are distributed across all areas.

       If the -a flag is given, the requested number of points  is  generated  for  each  individual  area.  For
       example, if 20 points should be generated and the input map has 100 individual areas, 2000 points will be
       generated in total.

       Attributes attached to restrict vector map are also transferred if the layer parameter is  defined  >  0,
       see example below.

NOTES

       Importantly, attributes will only be transferred if layer > 0 (e.g., layer=1).

EXAMPLES

       All examples are based on the North Carolina sample dataset.

   Generating random points in 2D
       Generate 20 random points with binary attributes (only 0 or 1):
       v.random output=binary_random npoints=20 zmin=0 zmax=1 column=’binary’
       v.db.select binary_random
       cat|binary
       1|0.63495
       2|0.233421
       3|0.489302
       4|0.748264
       5|0.505556
       6|0.32975
       [...]
       v.univar -d binary_random
       Calculating geometric distances between 20 primitives...
       [...]
       minimum: 148.515
       maximum: 16572.8
       [...]

   Generating random points in 2D with binary attributes
       Generate 20 random points with binary attributes (only 0 or 1):
       v.random output=binary_random npoints=20 zmin=0 zmax=1 column=’binary’ column_type=integer
       v.db.select binary_random
       cat|binary
       1|0
       2|0
       3|0
       4|0
       5|1
       6|0
       [...]

   Generating random points in 3D
       Generate 20 random 3D points using a specific random seed:
       v.random seed=52 output=height_random npoints=40 zmin=110 zmax=170 -z
       v.univar -d height_random
       Calculating geometric distances between 40 primitives...
       [...]
       minimum: 334.889
       maximum: 18351.9
       range: 18017
       sum: 5.38425e+06
       mean: 7266.2
       mean of absolute values: 7266.2
       population standard deviation: 3563.95
       [...]
       skewness: 0.34703

       Random points with different X, Y, and Z coordinates

   Generating random points in selected areas
       Generate 3 random points only in selected areas ("RALEIGH" related ZIP code areas):
       v.random restrict=zipcodes_wake output=zipcodes_local_random_n3 npoints=3 where="ZIPNAME = ’RALEIGH’" -a
       # visualization
       d.mon wx0
       d.vect zipcodes_wake
       d.vect zipcodes_wake fcolor=yellow where="ZIPNAME = ’RALEIGH’"
       d.vect zipcodes_local_random_n3 color=red icon=basic/circle
       Fixed number of random points generated in selected areas

   Generating random adjacent areas
       To  generate  random adjacent areas, first the centroids are generated as points, then a triangulation is
       run (North Carolina sample dataset:
       g.region vector=nc_state
       v.random output=randpoints6k npoints=6000
       v.voronoi input=randpoints6k output=randareas6k
       v.info -t randareas6k
       v.category randareas6k option=print
       # plot vector areas
       d.mon wx0
       d.vect randareas6k -c

       Random adjacent areas from random points (here: used as centroids)

       To eventually obtain isolated areas, selected areas can be extracted with v.extract.

       These vector areas can also be rasterized:
       # rasterize areas
       # note: rastermaps must result in at least 6k pixel in this example
       g.region vector=nc_state res=500 -p -a
       v.to.rast randareas6k out=randareas6k use=cat
       r.colors randareas6k color=random
       d.rast randareas6k

   Random sampling from raster map
       Generate 20 random samples from a raster map:
       g.region -p raster=elevation
       v.random output=random_samples npoints=20
       v.db.addtable map=random_samples columns=’cat INTEGER, sample DOUBLE PRECISION’
       v.what.rast map=random_samples raster=elevation column=sample
       v.db.select random_samples
       cat|sample
       1|103.9935
       2|129.1266
       3|96.01388
       [...]

   Random sampling from vector map
       Generate 20 random points and sample attribute data from geology (vector) map:
       g.region -p vector=geology
       v.random output=random_samples npoints=20
       v.db.addtable map=random_samples columns=’cat integer, geology varchar(100)’
       v.what.vect map=random_samples column=geology query_map=geology query_layer=1 query_column=GEO_NAME
       v.db.select random_samples
       cat|geology
       1|PzZm
       2|
       3|Zatm
       [...]

   Stratified random sampling: Random sampling from vector map by attribute
       Generate 20 random points restricted to forested areas:
       g.region -p raster=landclass96
       r.to.vect -v input=landclass96 output=landclass96 type=area
       v.random restrict=landclass96 output=random_samples npoints=20 where="label = ’forest’" layer=1
       v.db.select map=random_samples
       cat|landclass96_cat|landclass96_label
       1|5|forest
       2|5|forest
       3|5|forest
       ...

       Random points only sampled in forested areas (stratified random sampling)

   Stratified random sampling: Random sampling from vector map with spatial constraints
       Generating n points for each individual area: in this example two random points in each water body:
       g.region -p raster=landclass96
       r.to.vect -v input=landclass96 output=landclass96 type=area
       v.random restrict=landclass96 output=random_samples npoints=2 where="label = ’water’" layer=1 -a

       Two random points sampled in each individual water body (stratified random sampling)

SEE ALSO

        g.region, r.random, v.db.addtable, v.perturb, v.sample, v.univar, v.what.rast, v.what.vect

       SQL support in GRASS GIS

AUTHOR

       James Darrell McCauley <darrell@mccauley-usa.com>,
       when he was at: Agricultural Engineering Purdue University

SOURCE CODE

       Available at: v.random source code (history)

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       © 2003-2019 GRASS Development Team, GRASS GIS 7.8.2 Reference Manual