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

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dr. M.S. (Matthijs) Berends 2024-05-24 15:07:41 +02:00
parent d214f74e25
commit c3ce1b551d
8 changed files with 22 additions and 22 deletions
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4
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR Package: AMR
Version: 2.1.1.9032 Version: 2.1.1.9033
Date: 2024-05-20 Date: 2024-05-24
Title: Antimicrobial Resistance Data Analysis Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR) Description: Functions to simplify and standardise antimicrobial resistance (AMR)
data analysis and to work with microbial and antimicrobial properties by data analysis and to work with microbial and antimicrobial properties by

2
NAMESPACE
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@ -235,7 +235,6 @@ export(kurtosis)
export(labels_sir_count) export(labels_sir_count)
export(left_join_microorganisms) export(left_join_microorganisms)
export(like) export(like)
export(limit_mic_range)
export(lincosamides) export(lincosamides)
export(lipoglycopeptides) export(lipoglycopeptides)
export(macrolides) export(macrolides)
@ -302,6 +301,7 @@ export(quinolones)
export(random_disk) export(random_disk)
export(random_mic) export(random_mic)
export(random_sir) export(random_sir)
export(rescale_mic)
export(reset_AMR_locale) export(reset_AMR_locale)
export(resistance) export(resistance)
export(resistance_predict) export(resistance_predict)

8
NEWS.md
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@ -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!)* *(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 * `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. * `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. * 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 `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. For example, `mo_group_members("Strep group C")` returns a vector of all microorganisms that are in that group. * 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 ## 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 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: * For MICs:
* Added as valid levels: 4096, 6 powers of 0.0625, and 5 powers of 192 (192, 384, 576, 768, 960) * 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`. * 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 * 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 * `mo_info()` now contains an extra element `group_members`, with the contents of the new `mo_group_members()` function

8
R/mic.R
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@ -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. #' 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. #' 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. #' @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) #' quantile(mic_data)
#' all(mic_data < 512) #' all(mic_data < 512)
#' #'
#' # limit MICs using limit_mic_range() #' # limit MICs using rescale_mic()
#' limit_mic_range(mic_data, mic_range = c(4, 16)) #' rescale_mic(mic_data, mic_range = c(4, 16))
#' #'
#' # interpret MIC values #' # interpret MIC values
#' as.sir( #' as.sir(
@ -270,7 +270,7 @@ NA_mic_ <- set_clean_class(factor(NA, levels = VALID_MIC_LEVELS, ordered = TRUE)
#' @rdname as.mic #' @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)`. #' @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 #' @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) 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)), 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)])) "Values in `mic_range` must be valid MIC values. Unvalid: ", vector_and(mic_range[mic_range %in% c(VALID_MIC_LEVELS, NA)]))

8
R/plot.R
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@ -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) meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_x_discrete(drop = drop, ...) scale <- ggplot2::scale_x_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) { scale$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 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) meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_y_discrete(drop = drop, ...) scale <- ggplot2::scale_y_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) { scale$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 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) meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_colour_discrete(drop = drop, ...) scale <- ggplot2::scale_colour_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) { scale$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 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) meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_fill_discrete(drop = drop, ...) scale <- ggplot2::scale_fill_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) { scale$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 scale
} }

2
R/sir.R
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@ -323,7 +323,7 @@ is_sir_eligible <- function(x, threshold = 0.05) {
#' @rdname as.sir #' @rdname as.sir
#' @export #' @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) # 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)+$", ...) { as.sir.default <- function(x, S = "^(S|U)+$", I = "^(I|H)+$", R = "^(R)+$", N = "^(N|V)+$", SDD = "^(SDD|D)+$", ...) {
if (inherits(x, "sir")) { if (inherits(x, "sir")) {

10
man/as.mic.Rd
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@ -6,7 +6,7 @@
\alias{mic} \alias{mic}
\alias{is.mic} \alias{is.mic}
\alias{NA_mic_} \alias{NA_mic_}
\alias{limit_mic_range} \alias{rescale_mic}
\alias{droplevels.mic} \alias{droplevels.mic}
\title{Transform Input to Minimum Inhibitory Concentrations (MIC)} \title{Transform Input to Minimum Inhibitory Concentrations (MIC)}
\usage{ \usage{
@ -16,7 +16,7 @@ is.mic(x)
NA_mic_ 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, ...) \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. 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. 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) quantile(mic_data)
all(mic_data < 512) all(mic_data < 512)
# limit MICs using limit_mic_range() # limit MICs using rescale_mic()
limit_mic_range(mic_data, mic_range = c(4, 16)) rescale_mic(mic_data, mic_range = c(4, 16))
# interpret MIC values # interpret MIC values
as.sir( as.sir(

2
man/as.sir.Rd
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@ -96,7 +96,7 @@ sir_interpretation_history(clean = FALSE)
\item{threshold}{maximum fraction of invalid antimicrobial interpretations of \code{x}, see \emph{Examples}} \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} \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}