#Points

library(depstats)
library(tidyverse)
library(foreach)
library(fst)

sizes <- c(30, 50, 100, 200, 300, 400)

for (n in sizes) {
  set.seed(n)
  cat('\n', n, '\n')
  pts1 <- matrix(c( 1, 0,
                   -1, 0,
                    0, 1), ncol = 2, byrow = TRUE)
  pts2 <- matrix(c( 1,  0,
                   -1,  0,
                    0,  0,
                    0,  1,
                    0, -1), ncol = 2, byrow = TRUE)
  pts3 <- matrix(c( 1,  1,
                   -1,  1,
                    0,  0,
                    1, -1,
                   -1, -1), ncol = 2, byrow = TRUE)
  pts <- list(pts1, pts2, pts3)
  X <- depgen(1000, n, 'normnoise(pt.cld(n, pts[sample(c(1, 2, 3), 1)][[1]]), runif(1, 0.05, 0.5), TRUE)',
              randrotate = TRUE)
  Xind <- sampleapply(X, n, 1)
  write.fst(Xind %>% as.data.frame(), sprintf('VAL/dep5n%sSCORE.fst', n))
  Ximage <- sampleapply(X, n, 0, grid = 25)
  write.fst(Ximage %>% as.data.frame(), sprintf('VAL/dep5n%sIMAGE.fst', n))
}