R/poLCA.compress.R

In poLCAParallel: Polytomous Variable Latent Class Analysis Parallel

#' @noRd
poLCA.compress <- function(y) {
  ym.sorted <- y[do.call(order, data.frame(y)), ]
  vars <- ncol(ym.sorted)
  datamat <- ym.sorted[1, ]
  freq <- 1
  curpos <- 1
  for (i in 2:nrow(ym.sorted)) {
    if (sum(ym.sorted[i, ] == ym.sorted[i - 1, ]) == vars) {
      freq[curpos] <- freq[curpos] + 1
    } else {
      datamat <- rbind(datamat, ym.sorted[i, ])
      freq <- c(freq, 1)
      curpos <- curpos + 1
    }
  }
  rownames(datamat) <- c(1:length(freq))
  ret <- list(datamat = datamat, freq = freq)
  return(ret)
}