poly_sampler.R

# a simplified version of the sampler used in https://github.com/obrl-soil/disaggregation 
# takes n random samples in each polygon of a spatialpolygonsdataframe
# note that n samples may not be acheived if the polygon shape is particularly convoluted

# indata = spatialpolygonsdataframe
# sample_rate = positive integer
# pid_field = character string - column name. if omitted, rownames used instead

poly_sampler <- function(indata = NULL, sample_rate = NULL, pid_field = NULL) {
  crs <- indata@proj4string 
  sample_points <- vector('list', length = length(indata@polygons))
  # sampling loop (one polygon at a time)
  for (i in 1:length(indata@polygons)) { 
    
    polyid  <- if (is.null(pid_field)) {
      rownames(indata@data[i, ]) 
    } else {
      indata@data[i, c(pid_field)] 
    }
    
    spoints <- spsample(indata[i, ], n = sample_rate, type = "random", iter = 10)
    data <- data.frame("POLY_NO" = polyid,
                       "SAMP_NO" = 1:length(spoints),
                       "SAMP_X"  = spoints@coords[, 1],
                       "SAMP_Y"  = spoints@coords[, 2],
                       stringsAsFactors = FALSE)
    spointsdf <- SpatialPointsDataFrame(spoints, data, proj4string = crs)
    sample_points[[i]] <- spointsdf
  }
  # combine the samples from each polygon into one SPDF and return
  all_samplepoints <- do.call('rbind', sample_points)
  return(all_samplepoints)
}