#Heavysine

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')
  X1 <- depgen(600, n, 'normnoise(rotate(heavysine.cv(n)), runif(1, 0, 1))',
               randrotate = FALSE)
  X2 <- depgen(200, n, 'varnormnoise(rotate(heavysine.cv(n)), \'0.25 * x + 0.25\')',
               randrotate = FALSE)
  X3 <- depgen(200, n, 'varnormnoise(rotate(heavysine.cv(n)), \'0.5 - abs(0.25 * x)\')',
               randrotate = FALSE)
  X <- rbind(X1, X2, X3)
  Xind <- sampleapply(X, n, 1)
  write.fst(Xind %>% as.data.frame(), sprintf('VAL/dep16n%sSCORE.fst', n))
  Ximage <- sampleapply(X, n, 0, grid = 25)
  write.fst(Ximage %>% as.data.frame(), sprintf('VAL/dep16n%sIMAGE.fst', n))
}