add parallelisation to lqas_simulate; fix #73

DESCRIPTION

@@ -44,3 +44,6 @@ URL: https://nutriverse.io/sleacr/,https://github.com/nutriverse/sleacr
 BugReports: https://github.com/nutriverse/sleacr/issues
 Config/testthat/edition: 3
 VignetteBuilder: knitr
+Imports: 
+    parallel,
+    parallelly

NAMESPACE

@@ -21,5 +21,7 @@ importFrom(graphics,legend)
 importFrom(graphics,lines)
 importFrom(graphics,plot)
 importFrom(graphics,points)
+importFrom(parallel,mclapply)
+importFrom(parallelly,availableCores)
 importFrom(stats,lowess)
 importFrom(stats,phyper)

R/04-test_classifier.R

@@ -62,6 +62,8 @@ lqas_simulate_population <- function(proportion, pop) {
 #'   Default is 50 runs.
 #' @param replicates Number of replicate LQAS simulations to perform.
 #'   Default is set to 20 replicates.
+#' @param cores The number of computer cores to use/number of child processes
+#'   will be run simultaneously.
 #'
 #' @returns A data.frame with variable `cases` for total number of 
 #'   covered/cases, `outcome` for LQAS outcome, and `proportion` for the
@@ -163,19 +165,21 @@ lqas_simulate_runs <- function(pop,
                                pLower = 0,
                                pUpper = 1,
                                fine = 0.01,
-                               runs = 50) {
+                               runs = 50,
+                               cores = parallelly::availableCores(omit = 1)) {
   proportion <- rep.int(
     seq(from = pLower, to = pUpper, by = fine), times = runs
   ) |>
     sort()
 
-  result <- lapply(
+  result <- parallel::mclapply(
     X = proportion,
     FUN = lqas_simulate_run,
     pop = pop,
     n = n,
     dLower = dLower,
-    dUpper = dUpper
+    dUpper = dUpper,
+    mc.cores = cores
   ) |>
     (\(x) do.call(rbind, x))()
 
@@ -197,20 +201,22 @@ lqas_simulate_test <- function(pop,
                                pUpper = 1,
                                fine = 0.01,
                                runs = 50,
-                               replicates = 20) {
+                               replicates = 20,
+                               cores = parallelly::availableCores(omit = 1)) {
   proportion <- rep.int(
     seq(from = pLower, to = pUpper, by = fine), times = runs
   ) |>
     sort() |>
     rep(times = replicates)
 
-  x <- lapply(
+  x <- parallel::mclapply(
     X = proportion,
     FUN = lqas_simulate_run,
     pop = pop,
     n = n,
     dLower = dLower,
-    dUpper = dUpper
+    dUpper = dUpper,
+    mc.cores = cores
   ) |>
     (\(x) do.call(rbind, x))()
 
@@ -232,7 +238,8 @@ lqas_simulate_test <- function(pop,
 #'
 #' @param x Simulated results data produced by [lqas_simulate_test()]
 #'
-#' @returns A list of LQAS misclassification probabilities results
+#' @returns A list object of class `lqasClass` for LQAS misclassification 
+#'   probabilities results
 #'
 #' @examples
 #' sim <- lqas_simulate_test(
@@ -311,7 +318,6 @@ lqas_get_class_prob <- function(x) {
 #' @export
 #'
 
-
 print.lqasClass <- function(x, ...) {
   cat("                    Low : ", round(x$probs[1], 4), "\n",
       "               Moderate : ", round(x$probs[2], 4), "\n",

R/sleacr.R

@@ -1,20 +1,33 @@
-################################################################################
-#
+
+#' 
+#' Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage 
+#' (SLEAC) Tools
+#' 
+#' In the recent past, measurement of coverage has been mainly through two-stage 
+#' cluster sampled surveys either as part of a nutrition assessment or through a 
+#' specific coverage survey known as Centric Systematic Area Sampling (CSAS). 
+#' However, such methods are resource intensive and often only used for final 
+#' programme evaluation meaning results arrive too late for programme 
+#' adaptation. SLEAC, which stands for Simplified Lot Quality Assurance Sampling 
+#' Evaluation of Access and Coverage, is a low resource method designed 
+#' specifically to address this limitation and is used regularly for monitoring, 
+#' planning and importantly, timely improvement to programme quality, both for 
+#' agency and Ministry of Health (MoH) led programmes. This package provides 
+#' functions for use in conducting a SLEAC assessment.
+#'
 #' @references
 #' Myatt, Mark et al. 2012. Semi-Quantitative Evaluation of Access and
 #' Coverage (SQUEAC)/Simplified Lot Quality Assurance Sampling Evaluation of
 #' Access and Coverage (SLEAC) Technical Reference. Washington, DC: FHI 360/FANTA.
 #'
 #' @keywords internal
-#'
 #' @docType package
 #' @name sleacr
 #' @importFrom graphics abline legend lines plot points
 #' @importFrom stats lowess phyper
+#' @importFrom parallel mclapply
+#' @importFrom parallelly availableCores
 #'
-#'
-#
-################################################################################
 "_PACKAGE"
 
 

inst/WORDLIST

@@ -1,104 +1,108 @@
 Badjia
 Bagbe
 Bagbo
-Baimba
-Bainyawa
 Bambawo
+Bandajuma
+Bangema
 Baoma
-Benduma
-Bevehun
 Bongor
+Bowohun
 Bumpe
-Bumuvulahun
 CMAM
 CMD
 CSAS
 CodeFactor
 Codecov
-Damia
-Dar
 Deilenga
-Dukpuibu
 FANTA
 FHI
+Failor
+Feiba
 Foya
+Fuinda
+Gandorhun
+Gbanahun
+Gbangaima
+Gbanja
 Gbo
-Gbongboma
-Gboyeiya
-Geihun
-Gondama
-Hotawuloma
-Jagbewema
+Gorapon
+Huawuma
 Jaiama
-Jaluahun
-Jimmi
-Jojohun
-Jolu
-Kaimbe
+Jongo
+Juhun
+Kaduawo
 Kakua
+Kangama
+Kapima
+Kargoi
+Kassay
 Kemoh
-Kenjama
-Kesua
-Kimaya
+Kendebu
 Komboya
-Koni
-Kpetegonumei
+Komende
+Konima
+Korwama
+Kpah
+Kpallay
+Kpamajama
+Kpandobu
+Kpangbalia
 Kpetema
-Kpewama
+Kugbahun
 LQAS
+Lalewahun
 Lenga
+Levuma
 Lifecycle
 Lugbu
 Lunia
-Maboima
-Magbao
-Manowa
-Masahun
+Mambawa
+Mangaru
+Manguama
+Manyama
+Maryu
+Masao
+Mawojeh
 MoH
-Moawoma
-Mofindo
-Mogbondo
-Mokpendeh
-Mongere
-Mongeri
-Morku
+Monjemei
 Ngao
-Ngolamajie
-Ngoyiahun
 Nguabu
 Niawa
-Njekohun
+Njagbla
+Njala
+Nyallay
 Nyandehun
 ORCID
-Pelewahun
+Pataloo
 SLEAC
 SQUEAC
-Samabobu
+Sahn
 Samamie
-Sannah
-Sei
 Seilenga
 Seiwa
 Selenga
 Sembehun
-Sendeh
-Serabu
-Sewa
+Sewama
 Taninahun
 Tikonko
 Tissawa
-Tokpombu
-Tolobu
 Tongowa
 Valunia
-Wlihun
-Yarlenga
-Yeinken
-es
-kotumahun
+Wonde
+Yalenga
+YawaJu
+Yengema
+frac
+im
+lceil
+lfloor
 nutriverse
 offs
-salam
+quadrat
+quadrats
+rceil
+rfloor
 sleac
 subdistricts
 tibble
+undernutrition