1v.random(1) Grass User's Manual v.random(1)
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6 v.random - Generates random 2D/3D vector points.
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9 vector, sampling, statistics, random, point pattern, stratified random
10 sampling, level1
11
13 v.random
14 v.random --help
15 v.random [-zab] output=name npoints=integer [restrict=name]
16 [layer=string] [cats=range] [where=sql_query] [zmin=float]
17 [zmax=float] [seed=integer] [column=name] [column_type=string]
18 [--overwrite] [--help] [--verbose] [--quiet] [--ui]
19 Flags:
21 -z
22 Create 3D output
23 -a
25 Generate n points for each individual area (requires restrict
26 parameter)
27 -b
29 Do not build topology
30 Advantageous when handling a large number of points
31 --overwrite
33 Allow output files to overwrite existing files
34 --help
36 Print usage summary
37 --verbose
39 Verbose module output
40 --quiet
42 Quiet module output
43 --ui
45 Force launching GUI dialog
46 Parameters:
48 output=name [required]
49 Name for output vector map
50 npoints=integer [required]
52 Number of points to be created
53 restrict=name
55 Name of input vector map
56 Restrict points to areas in input vector
57 layer=string
59 Layer number or name (’-1’ for all layers)
60 A single vector map can be connected to multiple database tables.
61 This number determines which table to use. When used with direct
62 OGR access this is the layer name.
63 Default: -1
64 cats=range
66 Category values
67 Example: 1,3,7-9,13
68 where=sql_query
70 WHERE conditions of SQL statement without ’where’ keyword
71 Example: income < 1000 and population >= 10000
72 zmin=float
74 Minimum z height (needs -z flag or column name)
75 Default: 0.0
76 zmax=float
78 Maximum z height (needs -z flag or column name)
79 Default: 0.0
80 seed=integer
82 The seed to initialize the random generator. If not set the process
83 ID is used
84 column=name
86 Name of column for z values
87 Writes z values to column
88 column_type=string
90 Type of column for z values
91 Options: integer, double precision
92 Default: double precision
93
95 v.random randomly generates vector points within the current region
96 using the selected random number generator.
97 v.random can generate also 3D vector points or write random value to
99 the attribute table. Point height range or attribute value range is
100 controlled by specifying zmin and zmax options. Both z values are
101 included in range (zmin <= z <= zmax). Generated random attribute value
102 type can be controlled by column_type. Use integer column type for
103 integers and double precision for floating point numbers. Integer val‐
104 ues are calculated by rounding random floating point number.
105 To produce repeatable results a random seed can be set using the option
107 seed.
108 Restriction to vector areas
110 If an restrict vector map with areas is specified, the location of ran‐
111 dom points is restricted to the selected areas. By default, the
112 requested number of points are distributed across all areas.
113 If the -a flag is given, the requested number of points is generated
115 for each individual area. For example, if 20 points should be generated
116 and the input map has 100 individual areas, 2000 points will be gener‐
117 ated in total.
118 Attributes attached to restrict vector map are also transferred if the
120 layer parameter is defined > 0, see example below.
121
123 Importantly, attributes will only be transferred if layer > 0 (e.g.,
124 layer=1).
125
127 All examples are based on the North Carolina sample dataset.
128 Generating random points in 2D
130 Generate 20 random points with binary attributes (only 0 or 1):
131 v.random output=binary_random npoints=20 zmin=0 zmax=1 column=’binary’
132 v.db.select binary_random
133 cat|binary
134 1|0.63495
135 2|0.233421
136 3|0.489302
137 4|0.748264
138 5|0.505556
139 6|0.32975
140 [...]
141 v.univar -d binary_random
142 Calculating geometric distances between 20 primitives...
143 [...]
144 minimum: 148.515
145 maximum: 16572.8
146 [...]
147 Generating random points in 2D with binary attributes
149 Generate 20 random points with binary attributes (only 0 or 1):
150 v.random output=binary_random npoints=20 zmin=0 zmax=1 column=’binary’ column_type=integer
151 v.db.select binary_random
152 cat|binary
153 1|0
154 2|0
155 3|0
156 4|0
157 5|1
158 6|0
159 [...]
160 Generating random points in 3D
162 Generate 20 random 3D points using a specific random seed:
163 v.random seed=52 output=height_random npoints=40 zmin=110 zmax=170 -z
164 v.univar -d height_random
165 Calculating geometric distances between 40 primitives...
166 [...]
167 minimum: 334.889
168 maximum: 18351.9
169 range: 18017
170 sum: 5.38425e+06
171 mean: 7266.2
172 mean of absolute values: 7266.2
173 population standard deviation: 3563.95
174 [...]
175 skewness: 0.34703
176 Random points with different X, Y, and Z coordinates
178 Generating random points in selected areas
180 Generate 3 random points only in selected areas ("RALEIGH" related ZIP
181 code areas):
182 v.random restrict=zipcodes_wake output=zipcodes_local_random_n3 npoints=3 where="ZIPNAME = ’RALEIGH’" -a
183 # visualization
184 d.mon wx0
185 d.vect zipcodes_wake
186 d.vect zipcodes_wake fcolor=yellow where="ZIPNAME = ’RALEIGH’"
187 d.vect zipcodes_local_random_n3 color=red icon=basic/circle
188 Fixed number of random points generated in selected areas
189 Generating random adjacent areas
191 To generate random adjacent areas, first the centroids are generated as
192 points, then a triangulation is run (North Carolina sample dataset:
193 g.region vector=nc_state
194 v.random output=randpoints6k npoints=6000
195 v.voronoi input=randpoints6k output=randareas6k
196 v.info -t randareas6k
197 v.category randareas6k option=print
198 # plot vector areas
199 d.mon wx0
200 d.vect randareas6k -c
201 Random adjacent areas from random points (here: used as centroids)
203 To eventually obtain isolated areas, selected areas can be extracted
205 with v.extract.
206 These vector areas can also be rasterized:
208 # rasterize areas
209 # note: rastermaps must result in at least 6k pixel in this example
210 g.region vector=nc_state res=500 -p -a
211 v.to.rast randareas6k out=randareas6k use=cat
212 r.colors randareas6k color=random
213 d.rast randareas6k
214 Random sampling from raster map
216 Generate 20 random samples from a raster map:
217 g.region -p raster=elevation
218 v.random output=random_samples npoints=20
219 v.db.addtable map=random_samples columns=’cat INTEGER, sample DOUBLE PRECISION’
220 v.what.rast map=random_samples raster=elevation column=sample
221 v.db.select random_samples
222 cat|sample
223 1|103.9935
224 2|129.1266
225 3|96.01388
226 [...]
227 Random sampling from vector map
229 Generate 20 random points and sample attribute data from geology (vec‐
230 tor) map:
231 g.region -p vector=geology
232 v.random output=random_samples npoints=20
233 v.db.addtable map=random_samples columns=’cat integer, geology varchar(100)’
234 v.what.vect map=random_samples column=geology query_map=geology query_layer=1 query_column=GEO_NAME
235 v.db.select random_samples
236 cat|geology
237 1|PzZm
238 2|
239 3|Zatm
240 [...]
241 Stratified random sampling: Random sampling from vector map by attribute
243 Generate 20 random points restricted to forested areas:
244 g.region -p raster=landclass96
245 r.to.vect -v input=landclass96 output=landclass96 type=area
246 v.random restrict=landclass96 output=random_samples npoints=20 where="label = ’forest’" layer=1
247 v.db.select map=random_samples
248 cat|landclass96_cat|landclass96_label
249 1|5|forest
250 2|5|forest
251 3|5|forest
252 ...
253 Random points only sampled in forested areas (stratified random sam‐
255 pling)
256 Stratified random sampling: Random sampling from vector map with spatial
258 constraints
259 Generating n points for each individual area: in this example two ran‐
260 dom points in each water body:
261 g.region -p raster=landclass96
262 r.to.vect -v input=landclass96 output=landclass96 type=area
263 v.random restrict=landclass96 output=random_samples npoints=2 where="label = ’water’" layer=1 -a
264 Two random points sampled in each individual water body (stratified
266 random sampling)
267
269 g.region, r.random, v.db.addtable, v.perturb, v.sample, v.univar,
270 v.what.rast, v.what.vect
271 SQL support in GRASS GIS
273
275 James Darrell McCauley <darrell@mccauley-usa.com>,
276 when he was at: Agricultural Engineering Purdue University
277
279 Available at: v.random source code (history)
280 Main index | Vector index | Topics index | Keywords index | Graphical
282 index | Full index
283 © 2003-2019 GRASS Development Team, GRASS GIS 7.8.2 Reference Manual
285GRASS 7.8.2 v.random(1)