GRASS GIS manual: v.random

Note: A new GRASS GIS stable version has been released: GRASS GIS 7.6, available here.
Updated manual page: here

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
-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 inhab >= 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
- Restriction to vector areas
EXAMPLES
SEE ALSO
AUTHOR

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 attribute table. Point height range or attribute value range is controlled by specifying zmin and zmax values. Both z values are included in range (zmin <= z <= zmax). Generated random attribute value type can be controlled by column data 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 input 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.

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 polygons

Generate 3 random points only in selected polygons ("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

Fixd number of random points generated in selected polygons

Generating random adjacent polygons

To generate random adjacent polygons, 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 polygons
d.mon wx0
d.vect randareas6k -c

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

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

These vector polygons can also be rasterized:

# rasterize polygons
# 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

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)

AUTHOR

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

Last changed: $Date: 2017-05-13 02:16:01 -0700 (Sat, 13 May 2017) $

SOURCE CODE

Available at: v.random source code (history)