R/randomMask.R

In muschellij2/atropos: Core Software Infrastructure for 'ANTsR'

#' Get a random mask
#'
#' Get a mask with a specific number of voxels randomly
#' distributed on the input image/mask
#'
#' @param img an antsImage, either continuous or mask-like. This will
#' define the space where to sample voxels from. If this image is
#' continous (i.e., a T1), voxels will be sampled from all nonzero
#' voxels.
#' @param nsamples the number of random voxels to select from
#' @param perLabel logical, if true the input image must be multi-label
#' and the the output will have nsamples from each label (i.e., 200
#' samples from each label)
#' @param seed random seed
#'
#' @return binary antsImage with random voxels set to 1
#'
#' @author Pustina D
#'
#' @examples
#'
#' img<-antsImageRead( getANTsRData("r16"))
#' randmask<-randomMask(img,200)
#'
#' @export
randomMask = function(img, nsamples, perLabel=FALSE, seed ) {
  # set empty output image
  randmask = as.antsImage( array(0, dim = dim(img)), reference = img)

  # img can be continuous, search mask is all non zeros
  if (perLabel == FALSE) {
    img[ as.array(img) != 0 ] = 1
  }
  if ( ! missing( seed ) ) set.seed( seed )
  # get label vector except 0
  ulabs <- sort( unique( c( as.numeric( img ) ) ) )
  ulabs <- ulabs[ ulabs > 0 ]

  for (ulab in ulabs) {
    ulabvec <- as.array(img) == as.numeric( ulab )  # logical of this label
    n <- sum( ulabvec ) # total available voxels for label
    k <- min( c( nsamples, n ) ) # reduce nsample if not enough voxels
    ulabvec[ -(sample(which(ulabvec), k)) ] = FALSE # k random voxels from ulabvec
    randmask[ulabvec] = 1
  }
  return(randmask)
}