edar: Package for eyetracking data analysis

#' #' Define a sockets version of mclapply
#' #'
#' #' An implementation of \code{\link[parallel]{mclapply}} using \code{parallel::parLapply}
#' #'
#' #' Windows does not support forking. This makes it impossible to use mclapply on Windows to
#' #' farm out work to additional cores.
#' #'
#' #' More words
#' #'
#' #'
#' #' @param ... What you pass to mclapply
#' #' @return mclapply like list
#' #' @import parallel
#' #' @export
#' mclapply_socket <- function(
#'   X, FUN, ..., mc.preschedule = TRUE, mc.set.seed = TRUE,
#'   mc.silent = FALSE, mc.cores = NULL,
#'   mc.cleanup = TRUE, mc.allow.recursive = TRUE
#' ) {
#'   ## Create a cluster
#'   if (is.null(mc.cores)) {
#'     mc.cores <- min(length(X), detectCores())
#'   }
#'   cl <- parallel::makeCluster( mc.cores )
#'   
#'   tryCatch( {
#'     ## Find out the names of the loaded packages
#'     loaded.package.names <- c(
#'       ## Base packages
#'       sessionInfo()$basePkgs,
#'       ## Additional packages
#'       names( sessionInfo()$otherPkgs ))
#'     
#'     ### Ship it to the clusters
#'     parallel::clusterExport(cl,
#'                             'loaded.package.names',
#'                             envir=environment())
#'     
#'     ## Load the libraries on all the clusters
#'     ## N.B. length(cl) returns the number of clusters
#'     parallel::parLapply( cl, 1:length(cl), function(xx){
#'       lapply(loaded.package.names, function(yy) {
#'         require(yy , character.only=TRUE)})
#'     })
#'     
#'     
#'     clusterExport_function(cl, FUN)
#'     
#'     ## Run the lapply in parallel, with a special case for the ... arguments
#'     if( length( list(...) ) == 0 ) {
#'       return(parallel::parLapply( cl = cl, X=X, fun=FUN) )
#'     } else {
#'       return(parallel::parLapply( cl = cl, X=X, fun=FUN, ...) )
#'     }
#'   }, finally = {
#'     ## Stop the cluster
#'     parallel::stopCluster(cl)
#'   })
#' }
#' 
#' 
#' #' Overwrite the serial version of mclapply on Windows only
#' #'
#' #' @param empty it takes nothing
#' #' @return mclapply like list
#' #' @export
#' mclapply <- switch( Sys.info()[['sysname']],
#'                     Windows = {mclapply_socket},
#'                     Linux   = {mclapply},
#'                     Darwin  = {mclapply})
#' #
#' # ## end mclapply.hack.R
#' 
#' 
#' 
#' clusterExport_function <- function(cl, FUN ) {
#'   
#'   ## We want the enclosing environment, not the calling environment
#'   ## (I had tried parent.frame, which was not what we needed)
#'   ##
#'   ## Written by Hadley Wickham, off the top of his head, when I asked him
#'   ##   for help at one of his Advanced R workshops.
#'   env <- environment(FUN)
#'   while(!identical(env, globalenv())) {
#'     env <- parent.env(env)
#'     parallel::clusterExport(cl, ls(all.names=TRUE, envir = env), envir = env)
#'   }
#'   parallel::clusterExport(cl, ls(all.names=TRUE, envir = env), envir = env)
#'   ## // End Hadley Wickham
#' }
#'