#Circ

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')
  c1 <- matrix(c(0, 0), ncol = 2, byrow = TRUE)
  c2 <- matrix(c( 1, 0,
                 -1, 0,
                  0, 1), ncol = 2, byrow = TRUE)
  c3 <- matrix(c( 1,  1,
                 -1,  1,
                  1, -1,
                 -1, -1), ncol = 2, byrow = TRUE)
  cs <- list(c1, c2, c3)
  X1 <- depgen(600, n, 'normnoise(circ.cv(n, cs[sample(c(1, 2, 3), 1)][[1]]), runif(1, 0, 1))',
               randrotate = TRUE)
  X2 <- depgen(200, n, 'varnormnoise(circ.cv(n, cs[sample(c(1, 2, 3), 1)][[1]]), \'0.5 * x\')',
               randrotate = TRUE)
  X3 <- depgen(200, n, 'varnormnoise(circ.cv(n, cs[sample(c(1, 2, 3), 1)][[1]]), \'0.5 - abs(0.5 * x)\')',
               randrotate = TRUE)
  X <- rbind(X1, X2, X3)
  Xind <- sampleapply(X, n, 1)
  write.fst(Xind %>% as.data.frame(), sprintf('VAL/dep7n%sSCORE.fst', n))
  Ximage <- sampleapply(X, n, 0, grid = 25)
  write.fst(Ximage %>% as.data.frame(), sprintf('VAL/dep7n%sIMAGE.fst', n))
}