st_sample | R Documentation |
Sample points on or in (sets of) spatial features.
By default, returns a pre-specified number of points that is equal to
size
(if type = "random"
and exact = TRUE
) or an approximation of
size
otherwise. spatstat
methods are
interfaced and do not use the size
argument, see examples.
st_sample(x, size, ...)
## S3 method for class 'sf'
st_sample(x, size, ...)
## S3 method for class 'sfc'
st_sample(
x,
size,
...,
type = "random",
exact = TRUE,
warn_if_not_integer = TRUE,
by_polygon = FALSE,
progress = FALSE
)
## S3 method for class 'sfg'
st_sample(x, size, ...)
x |
object of class |
size |
sample size(s) requested; either total size, or a numeric vector with sample sizes for each feature geometry. When sampling polygons, the returned sampling size may differ from the requested size, as the bounding box is sampled, and sampled points intersecting the polygon are returned. |
... |
passed on to sample for |
type |
character; indicates the spatial sampling type; one of |
exact |
logical; should the length of output be exactly |
warn_if_not_integer |
logical; if |
by_polygon |
logical; for |
progress |
logical; if |
The function is vectorised: it samples size
points across all geometries in
the object if size
is a single number, or the specified number of points
in each feature if size
is a vector of integers equal in length to the geometry
of x
.
if x
has dimension 2 (polygons) and geographical coordinates (long/lat), uniform random sampling on the sphere is applied, see e.g. http://mathworld.wolfram.com/SpherePointPicking.html.
For regular
or hexagonal
sampling of polygons, the resulting size is only an approximation.
As parameter called offset
can be passed to control ("fix") regular or hexagonal sampling: for polygons a length 2 numeric vector (by default: a random point from st_bbox(x)
); for lines use a number like runif(1)
.
Fibonacci sampling see: Alvaro Gonzalez, 2010. Measurement of Areas on a Sphere Using Fibonacci and Latitude-Longitude Lattices. Mathematical Geosciences 42(1), p. 49-64
For regular sampling on the sphere, see also geosphere::regularCoordinates
.
Sampling methods from package spatstat
are interfaced (see examples), and need their own parameters to be set.
For instance, to use spatstat.random::rThomas()
, set type = "Thomas"
.
an sfc
object containing the sampled POINT
geometries
nc = st_read(system.file("shape/nc.shp", package="sf"))
p1 = st_sample(nc[1:3, ], 6)
p2 = st_sample(nc[1:3, ], 1:3)
plot(st_geometry(nc)[1:3])
plot(p1, add = TRUE)
plot(p2, add = TRUE, pch = 2)
x = st_sfc(st_polygon(list(rbind(c(0,0),c(90,0),c(90,90),c(0,90),c(0,0)))), crs = st_crs(4326))
plot(x, axes = TRUE, graticule = TRUE)
if (sf_extSoftVersion()["proj.4"] >= "4.9.0")
plot(p <- st_sample(x, 1000), add = TRUE)
if (require(lwgeom, quietly = TRUE)) { # for st_segmentize()
x2 = st_transform(st_segmentize(x, 1e4), st_crs("+proj=ortho +lat_0=30 +lon_0=45"))
g = st_transform(st_graticule(), st_crs("+proj=ortho +lat_0=30 +lon_0=45"))
plot(x2, graticule = g)
if (sf_extSoftVersion()["proj.4"] >= "4.9.0") {
p2 = st_transform(p, st_crs("+proj=ortho +lat_0=30 +lon_0=45"))
plot(p2, add = TRUE)
}
}
x = st_sfc(st_polygon(list(rbind(c(0,0),c(90,0),c(90,10),c(0,90),c(0,0))))) # NOT long/lat:
plot(x)
p_exact = st_sample(x, 1000, exact = TRUE)
p_not_exact = st_sample(x, 1000, exact = FALSE)
length(p_exact); length(p_not_exact)
plot(st_sample(x, 1000), add = TRUE)
x = st_sfc(st_polygon(list(rbind(c(-180,-90),c(180,-90),c(180,90),c(-180,90),c(-180,-90)))),
crs=st_crs(4326))
# FIXME:
#if (sf_extSoftVersion()["proj.4"] >= "4.9.0") {
# p = st_sample(x, 1000)
# st_sample(p, 3)
#}
# hexagonal:
sfc = st_sfc(st_polygon(list(rbind(c(0,0), c(1,0), c(1,1), c(0,0)))))
plot(sfc)
h = st_sample(sfc, 100, type = "hexagonal")
h1 = st_sample(sfc, 100, type = "hexagonal")
plot(h, add = TRUE)
plot(h1, col = 'red', add = TRUE)
c(length(h), length(h1)) # approximate!
pt = st_multipoint(matrix(1:20,,2))
ls = st_sfc(st_linestring(rbind(c(0,0),c(0,1))),
st_linestring(rbind(c(0,0),c(.1,0))),
st_linestring(rbind(c(0,1),c(.1,1))),
st_linestring(rbind(c(2,2),c(2,2.00001))))
st_sample(ls, 80)
plot(st_sample(ls, 80))
# spatstat example:
if (require(spatstat.random)) {
x <- sf::st_sfc(sf::st_polygon(list(rbind(c(0, 0), c(10, 0), c(10, 10), c(0, 0)))))
# for spatstat.random::rThomas(), set type = "Thomas":
pts <- st_sample(x, kappa = 1, mu = 10, scale = 0.1, type = "Thomas")
}
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