R/get_clusters.R

Defines functions get_clusters

Documented in get_clusters

#' Assign cluster IDs to epicontacts data
#'
#' This function identifies transitive clusters (i.e. connected components) as well
#' as the number of members in each cluster, and adds this information to the
#' linelist data.
#'
#' @export
#'
#' @author Nistara Randhawa (\email{[email protected]@ucdavis.edu})
#'
#' @param x An \code{\link{epicontacts}} object.
#'
#' @param output A character string indicating the type of output: either an
#'   \code{\link{epicontacts}} object (default) or a \link{data.frame} containing
#' cluster memberships to which members of \code{\link{epicontacts}} linelist belong
#'   to.
#'
#' @param member_col Name of column to which cluster membership is assigned to in the
#' linelist. Default name is 'cluster_member'.
#'
#' @param size_col  Name of column to which cluster sizes are assigned to in the
#' linelist. Default name is 'cluster_size'.
#'
#' @param override Logical value indicating whether cluster member and size columns
#' should be overwritten if they already exist in the linelist. Default is 'FALSE'.
#'
#' @return An \code{\link{epicontacts}} object whose 'linelist' dataframe
#' contains new columns corresponding to cluster membership and size, or a
#' \link{data.frame} containing member ids, cluster memberships as factors,
#' and associated cluster sizes. All ids that were originally in the 'contacts'
#' dataframe but not in the linelist will also be added to the linelist.
#'
#' @importFrom stats setNames
#'
#'
#' @examples
#' if (require(outbreaks)) {
#' ## build data
#' x <- make_epicontacts(ebola_sim$linelist, ebola_sim$contacts,
#'                        id = "case_id",
#'                        to = "case_id",
#'                        from = "infector",
#'                        directed = TRUE)
#'
#'
#' ## add cluster membership and sizes to epicontacts 'linelist'
#' y <- get_clusters(x, output = "epicontacts")
#' y
#'
#' ## return a data.frame with linelist member ids and cluster memberships as
#' ## factors
#' z <- get_clusters(x, output = "data.frame")
#' head(z)
#'
#' }

get_clusters <- function(x, output = c("epicontacts", "data.frame"),
                         member_col = "cluster_member",
                         size_col = "cluster_size",
                         override = FALSE) {

  ## check if cluster columns pre-exist in linelist
  cluster_cols <- c(member_col, size_col)
  cluster_var <- c("member_col", "size_col")
  cond <- cluster_cols %in% names(x$linelist)
  if ((sum(cond) > 0) & !override) {
    if (sum(cond) == 1) {
      msg <- sprintf("'%s' is already in the linelist. Set 'override = TRUE' to write over it, else assign a different %s name.", cluster_cols[cond], cluster_var[cond])
      stop(msg)
    }
    if (sum(cond) == 2) {
      msg <- sprintf("'%s' and '%s' are already in the linelist. Set 'override = TRUE' to write over them, else assign different cluster column names.", cluster_cols[1], cluster_cols[2])
      stop(msg)
    }
  }


  output <- match.arg(output)
  net <- as.igraph.epicontacts(x)
  cs <- igraph::clusters(net)
  cs_size <- setNames(data.frame(cluster_member = seq_along(cs$csize),
                                 cluster_size = cs$csize),
                      cluster_cols)

  # Drop pre-existing cluster columns
  if (sum(cond) > 0) {
    x$linelist <- x$linelist[ , !(names(x$linelist) %in% cluster_cols)]
  }

  net_nodes <- setNames(data.frame(id =igraph::V(net)$id,
                          cluster_member = cs$membership,
                          stringsAsFactors = FALSE),
                        c("id", member_col))

  net_nodes <- dplyr::left_join(net_nodes, cs_size, by = member_col)
  if(output == "epicontacts") {
    x$linelist <- dplyr::full_join(x$linelist, net_nodes, by = "id")
    x$linelist[ member_col ] <- as.factor(x$linelist[[ member_col ]])
    return(x)
  } else {
    net_nodes[ member_col ] <- as.factor(net_nodes[[ member_col ]])
    return(net_nodes)
  }
}

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epicontacts documentation built on May 2, 2019, 11:29 a.m.