rename `limit_mic_range()` to `rescale_mic()`

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 2.1.1.9032
-Date: 2024-05-20
+Version: 2.1.1.9033
+Date: 2024-05-24
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)
   data analysis and to work with microbial and antimicrobial properties by

NAMESPACE

@@ -235,7 +235,6 @@ export(kurtosis)
 export(labels_sir_count)
 export(left_join_microorganisms)
 export(like)
-export(limit_mic_range)
 export(lincosamides)
 export(lipoglycopeptides)
 export(macrolides)
@@ -302,6 +301,7 @@ export(quinolones)
 export(random_disk)
 export(random_mic)
 export(random_sir)
+export(rescale_mic)
 export(reset_AMR_locale)
 export(resistance)
 export(resistance_predict)

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 2.1.1.9032
+# AMR 2.1.1.9033
 
 *(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support!)*
 
@@ -17,14 +17,14 @@ This package now supports not only tools for AMR data analysis in clinical setti
   * `ab_url()` now supports retrieving the WHOCC url of their ATCvet pages
 * `as.sir()` now returns additional factor levels "N" for non-interpretable and "SDD" for susceptible dose-dependent. Users can now set their own criteria (using regular expressions) as to what should be considered S, I, R, SDD, and N.
 * The function group `scale_*_mic()`, namely: `scale_x_mic()`, `scale_y_mic()`, `scale_colour_mic()` and `scale_fill_mic()`. They are advanced ggplot2 extensions to allow easy plotting of MIC values. They allow for manual range definition and plotting missing intermediate log2 levels.
-* Function `limit_mic_range()`, which allows to limit MIC values to a manually set range. This is the powerhouse behind the `scale_*_mic()` functions, but it can be used by users directly to e.g. compare equality in MIC distributions by rescaling them to the same range first.
-* Function `mo_group_members()` to retrieve the member microorganisms. For example, `mo_group_members("Strep group C")` returns a vector of all microorganisms that are in that group.
+* Function `rescale_mic()`, which allows to rescale MIC values to a manually set range. This is the powerhouse behind the `scale_*_mic()` functions, but it can be used by users directly to e.g. compare equality in MIC distributions by rescaling them to the same range first.
+* Function `mo_group_members()` to retrieve the member microorganisms of a microorganism group. For example, `mo_group_members("Strep group C")` returns a vector of all microorganisms that are in that group.
 
 ## Changed
 * For SIR interpretation, it is now possible to use column names for argument `ab` and `mo`: `as.sir(..., ab = "column1", mo = "column2")`. This greatly improves the flexibility for users.
 * For MICs:
   * Added as valid levels: 4096, 6 powers of 0.0625, and 5 powers of 192 (192, 384, 576, 768, 960)
-  * Added new argument `keep_operators` to `as.mic()`. This can be `"all"` (default), `"none"`, or `"edges"`. This argument is also available in the new `limit_mic_range()` and `scale_*_mic()` functions.
+  * Added new argument `keep_operators` to `as.mic()`. This can be `"all"` (default), `"none"`, or `"edges"`. This argument is also available in the new `rescale_mic()` and `scale_*_mic()` functions.
   * Comparisons of MIC values are now more strict. For example, `>32` is higher than (and never equal to) `32`. Thus, `as.mic(">32") == as.mic(32)` now returns `FALSE`, and `as.mic(">32") > as.mic(32)` now returns `TRUE`.
 * Updated `italicise_taxonomy()` to support HTML output
 * `mo_info()` now contains an extra element `group_members`, with the contents of the new `mo_group_members()` function

R/mic.R

@@ -96,7 +96,7 @@ VALID_MIC_LEVELS <- c(t(vapply(FUN.VALUE = character(length(VALID_MIC_LEVELS)),
 #'
 #' Use [droplevels()] to drop unused levels. At default, it will return a plain factor. Use `droplevels(..., as.mic = TRUE)` to maintain the `mic` class.
 #' 
-#' With [limit_mic_range()], existing MIC ranges can be limited to a defined range of MIC values. This can be useful to better compare MIC distributions.
+#' With [rescale_mic()], existing MIC ranges can be limited to a defined range of MIC values. This can be useful to better compare MIC distributions.
 #'
 #' For `ggplot2`, use one of the [`scale_*_mic()`][scale_x_mic()] functions to plot MIC values. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values.
 #' @return Ordered [factor] with additional class [`mic`], that in mathematical operations acts as a [numeric] vector. Bear in mind that the outcome of any mathematical operation on MICs will return a [numeric] value.
@@ -116,8 +116,8 @@ VALID_MIC_LEVELS <- c(t(vapply(FUN.VALUE = character(length(VALID_MIC_LEVELS)),
 #' quantile(mic_data)
 #' all(mic_data < 512)
 #' 
-#' # limit MICs using limit_mic_range()
-#' limit_mic_range(mic_data, mic_range = c(4, 16))
+#' # limit MICs using rescale_mic()
+#' rescale_mic(mic_data, mic_range = c(4, 16))
 #'
 #' # interpret MIC values
 #' as.sir(
@@ -270,7 +270,7 @@ NA_mic_ <- set_clean_class(factor(NA, levels = VALID_MIC_LEVELS, ordered = TRUE)
 #' @rdname as.mic
 #' @param mic_range a manual range to limit the MIC values, e.g., `mic_range = c(0.001, 32)`. Use `NA` to set no limit on one side, e.g., `mic_range = c(NA, 32)`.
 #' @export
-limit_mic_range <- function(x, mic_range, keep_operators = "edges", as.mic = TRUE) {
+rescale_mic <- function(x, mic_range, keep_operators = "edges", as.mic = TRUE) {
   meet_criteria(mic_range, allow_class = c("numeric", "integer", "logical"), has_length = 2, allow_NA = TRUE, allow_NULL = TRUE)
   stop_ifnot(all(mic_range %in% c(VALID_MIC_LEVELS, NA)),
              "Values in `mic_range` must be valid MIC values. Unvalid: ", vector_and(mic_range[mic_range %in% c(VALID_MIC_LEVELS, NA)]))

R/plot.R

@@ -117,7 +117,7 @@ scale_x_mic <- function(keep_operators = "edges", mic_range = NULL, drop = FALSE
   meet_criteria(drop, allow_class = "logical", has_length = 1)
   scale <- ggplot2::scale_x_discrete(drop = drop, ...)
   scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
-    limit_mic_range(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
+    rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
   }
   scale
 }
@@ -130,7 +130,7 @@ scale_y_mic <- function(keep_operators = "edges", mic_range = NULL, drop = FALSE
   meet_criteria(drop, allow_class = "logical", has_length = 1)
   scale <- ggplot2::scale_y_discrete(drop = drop, ...)
   scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
-    limit_mic_range(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
+    rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
   }
   scale
 }
@@ -143,7 +143,7 @@ scale_colour_mic <- function(keep_operators = "edges", mic_range = NULL, drop =
   meet_criteria(drop, allow_class = "logical", has_length = 1)
   scale <- ggplot2::scale_colour_discrete(drop = drop, ...)
   scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
-    limit_mic_range(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
+    rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
   }
   scale
 }
@@ -156,7 +156,7 @@ scale_fill_mic <- function(keep_operators = "edges", mic_range = NULL, drop = FA
   meet_criteria(drop, allow_class = "logical", has_length = 1)
   scale <- ggplot2::scale_fill_discrete(drop = drop, ...)
   scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
-    limit_mic_range(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
+    rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
   }
   scale
 }

R/sir.R

@@ -323,7 +323,7 @@ is_sir_eligible <- function(x, threshold = 0.05) {
 
 #' @rdname as.sir
 #' @export
-#' @param S,I,R,N,SDD a case-indepdendent [regular expression][base::regex] to translate input to this result. This regular expression will be run *after* all non-letters are removed from the input.
+#' @param S,I,R,N,SDD a case-independent [regular expression][base::regex] to translate input to this result. This regular expression will be run *after* all non-letters are removed from the input.
 # extra param: warn (logical, to never throw a warning)
 as.sir.default <- function(x, S = "^(S|U)+$", I = "^(I|H)+$", R = "^(R)+$", N = "^(N|V)+$", SDD = "^(SDD|D)+$", ...) {
   if (inherits(x, "sir")) {

man/as.mic.Rd

@@ -6,7 +6,7 @@
 \alias{mic}
 \alias{is.mic}
 \alias{NA_mic_}
-\alias{limit_mic_range}
+\alias{rescale_mic}
 \alias{droplevels.mic}
 \title{Transform Input to Minimum Inhibitory Concentrations (MIC)}
 \usage{
@@ -16,7 +16,7 @@ is.mic(x)
 
 NA_mic_
 
-limit_mic_range(x, mic_range, keep_operators = "edges", as.mic = TRUE)
+rescale_mic(x, mic_range, keep_operators = "edges", as.mic = TRUE)
 
 \method{droplevels}{mic}(x, as.mic = FALSE, ...)
 }
@@ -82,7 +82,7 @@ Using \code{\link[=as.double]{as.double()}} or \code{\link[=as.numeric]{as.numer
 
 Use \code{\link[=droplevels]{droplevels()}} to drop unused levels. At default, it will return a plain factor. Use \code{droplevels(..., as.mic = TRUE)} to maintain the \code{mic} class.
 
-With \code{\link[=limit_mic_range]{limit_mic_range()}}, existing MIC ranges can be limited to a defined range of MIC values. This can be useful to better compare MIC distributions.
+With \code{\link[=rescale_mic]{rescale_mic()}}, existing MIC ranges can be limited to a defined range of MIC values. This can be useful to better compare MIC distributions.
 
 For \code{ggplot2}, use one of the \code{\link[=scale_x_mic]{scale_*_mic()}} functions to plot MIC values. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values.
 
@@ -101,8 +101,8 @@ fivenum(mic_data)
 quantile(mic_data)
 all(mic_data < 512)
 
-# limit MICs using limit_mic_range()
-limit_mic_range(mic_data, mic_range = c(4, 16))
+# limit MICs using rescale_mic()
+rescale_mic(mic_data, mic_range = c(4, 16))
 
 # interpret MIC values
 as.sir(

man/as.sir.Rd

@@ -96,7 +96,7 @@ sir_interpretation_history(clean = FALSE)
 
 \item{threshold}{maximum fraction of invalid antimicrobial interpretations of \code{x}, see \emph{Examples}}
 
-\item{S, I, R, N, SDD}{a case-indepdendent \link[base:regex]{regular expression} to translate input to this result. This regular expression will be run \emph{after} all non-letters are removed from the input.}
+\item{S, I, R, N, SDD}{a case-independent \link[base:regex]{regular expression} to translate input to this result. This regular expression will be run \emph{after} all non-letters are removed from the input.}
 
 \item{mo}{a vector (or column name) with \link{character}s that can be coerced to valid microorganism codes with \code{\link[=as.mo]{as.mo()}}, can be left empty to determine it automatically}