.TH v.random 1grass "" "GRASS 7.8.5" "GRASS GIS User's Manual"
.SH NAME
\fI\fBv.random\fR\fR  \- Generates random 2D/3D vector points.
.SH KEYWORDS
vector, sampling, statistics, random, point pattern, stratified random sampling, level1
.SH SYNOPSIS
\fBv.random\fR
.br
\fBv.random \-\-help\fR
.br
\fBv.random\fR [\-\fBzab\fR] \fBoutput\fR=\fIname\fR \fBnpoints\fR=\fIinteger\fR  [\fBrestrict\fR=\fIname\fR]   [\fBlayer\fR=\fIstring\fR]   [\fBcats\fR=\fIrange\fR]   [\fBwhere\fR=\fIsql_query\fR]   [\fBzmin\fR=\fIfloat\fR]   [\fBzmax\fR=\fIfloat\fR]   [\fBseed\fR=\fIinteger\fR]   [\fBcolumn\fR=\fIname\fR]   [\fBcolumn_type\fR=\fIstring\fR]   [\-\-\fBoverwrite\fR]  [\-\-\fBhelp\fR]  [\-\-\fBverbose\fR]  [\-\-\fBquiet\fR]  [\-\-\fBui\fR]
.SS Flags:
.IP "\fB\-z\fR" 4m
.br
Create 3D output
.IP "\fB\-a\fR" 4m
.br
Generate n points for each individual area (requires restrict parameter)
.IP "\fB\-b\fR" 4m
.br
Do not build topology
.br
Advantageous when handling a large number of points
.IP "\fB\-\-overwrite\fR" 4m
.br
Allow output files to overwrite existing files
.IP "\fB\-\-help\fR" 4m
.br
Print usage summary
.IP "\fB\-\-verbose\fR" 4m
.br
Verbose module output
.IP "\fB\-\-quiet\fR" 4m
.br
Quiet module output
.IP "\fB\-\-ui\fR" 4m
.br
Force launching GUI dialog
.SS Parameters:
.IP "\fBoutput\fR=\fIname\fR \fB[required]\fR" 4m
.br
Name for output vector map
.IP "\fBnpoints\fR=\fIinteger\fR \fB[required]\fR" 4m
.br
Number of points to be created
.IP "\fBrestrict\fR=\fIname\fR" 4m
.br
Name of input vector map
.br
Restrict points to areas in input vector
.IP "\fBlayer\fR=\fIstring\fR" 4m
.br
Layer number or name (\(cq\-1\(cq for all layers)
.br
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.
.br
Default: \fI\-1\fR
.IP "\fBcats\fR=\fIrange\fR" 4m
.br
Category values
.br
Example: 1,3,7\-9,13
.IP "\fBwhere\fR=\fIsql_query\fR" 4m
.br
WHERE conditions of SQL statement without \(cqwhere\(cq keyword
.br
Example: income < 1000 and population >= 10000
.IP "\fBzmin\fR=\fIfloat\fR" 4m
.br
Minimum z height (needs \-z flag or column name)
.br
Default: \fI0.0\fR
.IP "\fBzmax\fR=\fIfloat\fR" 4m
.br
Maximum z height (needs \-z flag or column name)
.br
Default: \fI0.0\fR
.IP "\fBseed\fR=\fIinteger\fR" 4m
.br
The seed to initialize the random generator. If not set the process ID is used
.IP "\fBcolumn\fR=\fIname\fR" 4m
.br
Name of column for z values
.br
Writes z values to column
.IP "\fBcolumn_type\fR=\fIstring\fR" 4m
.br
Type of column for z values
.br
Options: \fIinteger, double precision\fR
.br
Default: \fIdouble precision\fR
.SH DESCRIPTION
\fIv.random\fR randomly generates vector points within the
current region using the selected random number generator.
.PP
\fIv.random\fR 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 \fBzmin\fR and \fBzmax\fR options.
Both z values are included in range (\fIzmin <= z <=
zmax\fR). Generated random attribute value type can be controlled
by \fBcolumn_type\fR. Use \fIinteger\fR column type for integers and
\fIdouble precision\fR for floating point numbers. Integer values are
calculated by rounding random floating point number.
.PP
To produce repeatable results a random seed can be set using the
option \fBseed\fR.
.SS Restriction to vector areas
.PP
If an \fBrestrict\fR 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.
.PP
If the \fB\-a\fR 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.
.PP
Attributes attached to \fBrestrict\fR vector map are also transferred
if the \fBlayer\fR parameter is defined > 0,
see \fIexample\fR
below.
.SH NOTES
Importantly, attributes will only be transferred if \fBlayer\fR > 0
(e.g., layer=1).
.SH EXAMPLES
All examples are based on the North Carolina sample dataset.
.SS Generating random points in 2D
Generate 20 random points with binary attributes (only 0 or 1):
.br
.nf
\fC
v.random output=binary_random npoints=20 zmin=0 zmax=1 column=\(cqbinary\(cq
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
[...]
\fR
.fi
.SS Generating random points in 2D with binary attributes
Generate 20 random points with binary attributes (only 0 or 1):
.br
.nf
\fC
v.random output=binary_random npoints=20 zmin=0 zmax=1 column=\(cqbinary\(cq column_type=integer
v.db.select binary_random
cat|binary
1|0
2|0
3|0
4|0
5|1
6|0
[...]
\fR
.fi
.SS Generating random points in 3D
Generate 20 random 3D points using a specific random seed:
.br
.nf
\fC
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
\fR
.fi
.PP
.br
Random points with different X, Y, and Z coordinates
.SS Generating random points in selected areas
Generate 3 random points only in selected areas (\(dqRALEIGH\(dq related ZIP
code areas):
.br
.nf
\fC
v.random restrict=zipcodes_wake output=zipcodes_local_random_n3 npoints=3 where=\(dqZIPNAME = \(cqRALEIGH\(cq\(dq \-a
# visualization
d.mon wx0
d.vect zipcodes_wake
d.vect zipcodes_wake fcolor=yellow where=\(dqZIPNAME = \(cqRALEIGH\(cq\(dq
d.vect zipcodes_local_random_n3 color=red icon=basic/circle
\fR
.fi
.br
\fIFixed number of random points generated in selected areas\fR
.SS 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:
.br
.nf
\fC
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
\fR
.fi
.PP
.br
Random adjacent areas from random points (here: used as centroids)
.PP
To eventually obtain isolated areas, selected areas can be extracted with
\fIv.extract\fR.
.PP
These vector areas can also be rasterized:
.br
.nf
\fC
# 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
\fR
.fi
.SS Random sampling from raster map
Generate 20 random samples from a raster map:
.br
.nf
\fC
g.region \-p raster=elevation
v.random output=random_samples npoints=20
v.db.addtable map=random_samples columns=\(cqcat INTEGER, sample DOUBLE PRECISION\(cq
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
[...]
\fR
.fi
.SS Random sampling from vector map
Generate 20 random points and sample attribute data from geology (vector) map:
.br
.nf
\fC
g.region \-p vector=geology
v.random output=random_samples npoints=20
v.db.addtable map=random_samples columns=\(cqcat integer, geology varchar(100)\(cq
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
[...]
\fR
.fi
.SS Stratified random sampling: Random sampling from vector map by attribute
Generate 20 random points restricted to forested areas:
.br
.nf
\fC
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=\(dqlabel = \(cqforest\(cq\(dq layer=1
v.db.select map=random_samples
cat|landclass96_cat|landclass96_label
1|5|forest
2|5|forest
3|5|forest
\&...
\fR
.fi
.PP
.br
Random points only sampled in forested areas (stratified random sampling)
.SS 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:
.br
.nf
\fC
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=\(dqlabel = \(cqwater\(cq\(dq layer=1 \-a
\fR
.fi
.PP
.br
Two random points sampled in each individual water body (stratified
random sampling)
.SH SEE ALSO
\fI
g.region,
r.random,
v.db.addtable,
v.perturb,
v.sample,
v.univar,
v.what.rast,
v.what.vect
\fR
.PP
SQL support in GRASS GIS
.SH AUTHOR
James Darrell McCauley
<darrell@mccauley\-usa.com>,
.br
when he was at:
Agricultural
Engineering
Purdue University
.SH SOURCE CODE
.PP
Available at: v.random source code (history)
.PP
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Full index
.PP
© 2003\-2020
GRASS Development Team,
GRASS GIS 7.8.5 Reference Manual