remove XY points to find which points provide the most coverage without moving cluster location (2D LIDAR)

make_areas_distinct_fast.R

require(raster)
require(sf)
require(dplyr)
require(data.table)

shiftReduceRaster = function (x, y) {
  r <- raster::shift(r, x*xres(r), y*yres(r))
  # get cell numbers
  cells <- cellFromXY(r, pts)
  # pick one point per cell
  sel <- aggregate(pts, list(cells), function(i)i[1])
  assign("pts", sel[,c("X", "Y",'id')], envir = .GlobalEnv)
}

sort_abs = function(x, na.last = TRUE, decreasing = FALSE) {
    x[order(abs(x), na.last = na.last, decreasing = decreasing)] 
}

shiftIntervals = sort_abs(seq(from = -1, to = 1, by = 0.05)) # start with 0,0

pts <- fread(file = '~/test.csv',na.strings = '')[,c("X", "Y",'id')]
r <- raster(ncol=36000, nrow=18000, vals=1) # takes 8GB of RAM

for (x in shiftIntervals) {
  for (y in shiftIntervals) {
    shiftReduceRaster(x, y)
  }
  gc()
}

rm(r)
gc()
fwrite(pts, file = '~/output.csv')