REL: v0.1.1 and prev output bug fix

Fix
#34 (comment)
and roxygen comments.

CHANGELOG.md

@@ -6,7 +6,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to
 [Semantic Versioning](https://semver.org/spec/v2.0.0.html).  
 
-## Unreleased (To be deployed)  
+## [0.1.1] - 2024-04-16  
 
 ### Added  
 - Roxygen comments to R util files.  

R/utils_dt_display.R

@@ -77,41 +77,44 @@ bayes_cols <- c(
 #' Display Prevalence and CI/CrI Per Value
 #'
 #' The development of intervention plans are often determined based on the
-#' prevalence per a given value (e.g. 1/1000). This function applies this
-#' transformation.
+#' prevalence per a given value (e.g. multiplying by 2000 gives you the
+#' prevalence per 2000 units). This function applies this transformation across
+#' columns, as well as rounding (see note on rounding above).
 #'
 #' @param df dataframe PoolTestR output
 #' @param ptr_mode character String indicating PoolTestR mode used. Get from
 #' `which_pooltestr`.
-#' @param val integer Value to divide prevalence and intervals by.
-#'
+#' @param per_prev boolean Should values be displayed `per_val`?
+#' @param per_val integer Value to multiply prevalence and intervals by.
+#' @param digits integer Number of digits to round by.
+
 #' @return dataframe
-#' @name prev_per_val
-dt_display <- function(df, ptr_mode, divide_prev, divide_val, digits) {
+#' @name dt_display
+dt_display <- function(df, ptr_mode, per_prev, per_val, digits) {
   # poolprev_bayes requires both transformations
-  if (!divide_prev) {
-    # Don't divide
+  if (!per_prev) {
+    # Don't multiply
     val <- 1
   } else {
-    val <- divide_val
+    val <- per_val
   }
   if (ptr_mode %in% c("poolprev", "poolprev_strat", "poolprev_bayes")) {
     df <- df %>%
-      divide_cols(mle_cols, val) %>%
+      multiply_cols(mle_cols, val) %>%
       round_pool_cols(digits = digits, cols = mle_cols)
   }
   if (ptr_mode %in% c("poolprev_bayes", "hierpoolprev", "hierpoolprev_strat")) {
     df <- df %>%
-      divide_cols(bayes_cols, val) %>%
+      multiply_cols(bayes_cols, val) %>%
       round_pool_cols(digits = digits, cols = bayes_cols)
   }
   return(df)
 }
 
-#' @rdname divide_cols
-divide_cols <- function(df, cols, val) {
+#' @rdname dt_display
+multiply_cols <- function(df, cols, val) {
   dplyr::mutate(
     df,
-    dplyr::across(cols, ~ as.numeric(.) / val)
+    dplyr::across(cols, ~ as.numeric(.) * val)
   )
 }

rsconnect/shinyapps.io/fredjaya/pooltools.dcf

@@ -5,6 +5,6 @@ account: fredjaya
 server: shinyapps.io
 hostUrl: https://api.shinyapps.io/v1
 appId: 10880234
-bundleId: 8466707
+bundleId: 8499472
 url: https://fredjaya.shinyapps.io/pooltools/
 version: 1

server.R

@@ -176,16 +176,16 @@ server <- function(input, output, session) {
         # Prevalence and CI/CrI rounding
         numericInput("optsRoundAnalyse", "Number of decimal places to display", value = 4),
 
-        # Should prevalence and CI/CrI be divided by a value?
+        # Should prevalence and CI/CrI be multiplied by a value?
         checkboxInputTT(
-          "optsDividePrev",
+          "optsPerPrev",
           "Display prevalence per value",
-          tooltip = "Selecting this option will divide prevalence and interval estimates by a given value",
+          tooltip = "Selecting this option will multiply prevalence and interval estimates by a given value",
           value = F
         ),
         conditionalPanel(
-          condition = "input.optsDividePrev == true",
-          numericInput("optsDividePrevVal", label = "Value", value = 2000, min = 1, step = 1)
+          condition = "input.optsPerPrev == true",
+          numericInput("optsPerPrevVal", label = "Value", value = 2000, min = 1, step = 1)
         )
       ),
       tags$br()
@@ -223,8 +223,8 @@ server <- function(input, output, session) {
     data <- dt_display(
       df = data,
       ptr_mode = ptr_mode,
-      divide_prev = input$optsDividePrev,
-      divide_val = as.integer(input$optsDividePrevVal),
+      per_prev = input$optsPerPrev,
+      per_val = as.integer(input$optsPerPrevVal),
       digits = as.integer(input$optsRoundAnalyse)
     )