R/buildKNND.R

In SCORPION: Single Cell Oriented Reconstruction of PANDA Individual Optimized Networks

#' @importFrom methods is
buildKNND <- function(D, k = 5, return_neighbors_order = T, mode = "all") {
  ## print("Start knn_graph_from_dist")
  if (!is(D, "matrix") | !is(D, "dist")) {
    stop("D (X) mast be a matrix or dist!")
  }

  if (!is(D, "dist")) {
    D <- as.dist(D)
  }



  N <- (1 + sqrt(1 + 8 * length(D))) / 2 # number of cells

  if (k >= N) {
    stop("Not enought neighbors in data set!")
  }
  if (k < 1) {
    stop("Invalid number of nearest neighbors, k must be >= 1!")
  }

  row <- function(i, N) {
    return(c(
      if (i > 1) D[(i - 1) + c(0:(i - 2)) * (N - 1 - c(1:(i - 1)) / 2)],
      NA,
      if (i < N) D[((i - 1) * (N - 1) - ((i - 1) * (i - 2) / 2) + 1):(((i - 1) * (N - 1) - ((i - 1) * (i - 2) / 2) + 1) + N - i - 1)]
    ))
  }

  neighbors <- t(sapply(1:N, function(i) {
    order(row(i, N))[1:k]
  }))

  adj.knn <- split(neighbors, rep(1:nrow(neighbors), times = ncol(neighbors)))


  graph.knn <- igraph::graph_from_adj_list(adj.knn, duplicate = F, mode = mode)
  graph.knn <- igraph::simplify(graph.knn, remove.multiple = T)
  igraph::E(graph.knn)$weight <- 1

  if (return_neighbors_order) {
    res <- list(
      graph.knn = graph.knn,
      order = neighbors
    )
  } else {
    res <- list(graph.knn = graph.knn)
  }

  return(res)
}