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Generate candidate sampling points inside each region

Source: R/points.R
sda_points.Rd

For every polygon feature in my_shp it produces candidate points and aggregation weights, in the list format consumed by precompute_corr.

Usage

sda_points(
  my_shp,
  delta,
  method = 1L,
  weighted = FALSE,
  pop_shp = NULL,
  rho = 0.55,
  giveup = 1000L
)

Arguments

my_shp

an sf object of POLYGON/MULTIPOLYGON features.

delta

point spacing (grid step / SSI inhibition distance).

method

1 = SSI (default), 2 = uniform random, 3 = regular grid.

weighted

logical; if TRUE, weights are population density read from pop_shp, otherwise equal weights.

pop_shp

a terra::SpatRaster of population density (required when weighted = TRUE).

rho

packing density used to choose the number of points.

giveup

SSI rejection limit.

Value

a list of length nrow(my_shp); each element has xy and weight. Carries "weighted" and "my_shp" attributes.

See also

precompute_corr, which consumes this output.

Examples

# \donttest{
data(sdalgcp_data)
pts <- sda_points(sdalgcp_data, delta = 1.2, method = 3)   # regular grid points
length(pts)          # one entry per region
#> [1] 64
str(pts[[1]])        # $xy candidate coordinates and $weight
#> List of 2
#>  $ xy    : num [1:9, 1:2] 0 1.2 2.4 0 1.2 2.4 0 1.2 2.4 0 ...
#>   ..- attr(*, "dimnames")=List of 2
#>   .. ..$ : chr [1:9] "1" "2" "3" "4" ...
#>   .. ..$ : chr [1:2] "x" "y"
#>  $ weight: num [1:9] 0.111 0.111 0.111 0.111 0.111 ...
# }