# for the kNN() function
library(VIM)
load_mnist <- function() {
  load_image_file <- function(filename) {
   ret = list()
    f = file(filename,'rb')
    readBin(f,'integer',n=1,size=4,endian='big')
    ret$n = readBin(f,'integer',n=1,size=4,endian='big')
    nrow = readBin(f,'integer',n=1,size=4,endian='big')
    ncol = readBin(f,'integer',n=1,size=4,endian='big')
    x = readBin(f,'integer',n=ret$n*nrow*ncol,size=1,signed=F)
    ret$x = matrix(x, ncol=nrow*ncol, byrow=T)
    close(f)
    ret
  }
  load_label_file <- function(filename) {
    f = file(filename,'rb')
    readBin(f,'integer',n=1,size=4,endian='big')
    n = readBin(f,'integer',n=1,size=4,endian='big')
    y = readBin(f,'integer',n=n,size=1,signed=F)
    close(f)
    y
  }
  train <<- load_image_file("train-images.idx3-ubyte")
  test <<- load_image_file("t10k-images.idx3-ubyte")

  # no
  kNN(train)

  # no
  kNN(test)

  train$y <<- load_label_file("train-labels.idx1-ubyte")
  test$y <<- load_label_file("t10k-labels.idx1-ubyte")
}

show_digit <- function(arr784, col=gray(12:1/12)) {
  image(matrix(arr784, nrow=28)[,28:1], col=col)
}