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335 lines
11 KiB
R
Executable File
335 lines
11 KiB
R
Executable File
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Data Analysis for R #
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# #
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# SOURCE #
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# https://github.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2018-2021 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
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# collaboration with non-profit organisations Certe Medical #
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# Diagnostics & Advice, and University Medical Center Groningen. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
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# Visit our website for the full manual and a complete tutorial about #
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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#' Transform Input to Minimum Inhibitory Concentrations (MIC)
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#'
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#' This transforms a vector to a new class [`mic`], which is an ordered [factor] with valid minimum inhibitory concentrations (MIC) as levels. Invalid MIC values will be translated as `NA` with a warning.
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#' @inheritSection lifecycle Stable Lifecycle
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#' @rdname as.mic
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#' @param x vector
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#' @param na.rm a logical indicating whether missing values should be removed
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#' @details To interpret MIC values as RSI values, use [as.rsi()] on MIC values. It supports guidelines from EUCAST and CLSI.
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#' @return Ordered [factor] with additional class [`mic`]
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#' @aliases mic
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#' @export
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#' @seealso [as.rsi()]
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#' @inheritSection AMR Read more on Our Website!
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#' @examples
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#' mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
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#' is.mic(mic_data)
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#'
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#' # this can also coerce combined MIC/RSI values:
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#' as.mic("<=0.002; S") # will return <=0.002
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#'
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#' # interpret MIC values
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#' as.rsi(x = as.mic(2),
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#' mo = as.mo("S. pneumoniae"),
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#' ab = "AMX",
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#' guideline = "EUCAST")
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#' as.rsi(x = as.mic(4),
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#' mo = as.mo("S. pneumoniae"),
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#' ab = "AMX",
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#' guideline = "EUCAST")
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#'
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#' plot(mic_data)
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#' barplot(mic_data)
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as.mic <- function(x, na.rm = FALSE) {
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meet_criteria(x, allow_class = c("mic", "character", "numeric", "integer"), allow_NA = TRUE)
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meet_criteria(na.rm, allow_class = "logical", has_length = 1)
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if (is.mic(x)) {
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x
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} else {
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x <- unlist(x)
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if (na.rm == TRUE) {
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x <- x[!is.na(x)]
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}
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x.bak <- x
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# comma to period
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x <- gsub(",", ".", x, fixed = TRUE)
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# transform Unicode for >= and <=
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x <- gsub("\u2264", "<=", x, fixed = TRUE)
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x <- gsub("\u2265", ">=", x, fixed = TRUE)
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# remove space between operator and number ("<= 0.002" -> "<=0.002")
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x <- gsub("(<|=|>) +", "\\1", x)
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# transform => to >= and =< to <=
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x <- gsub("=<", "<=", x, fixed = TRUE)
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x <- gsub("=>", ">=", x, fixed = TRUE)
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# dots without a leading zero must start with 0
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x <- gsub("([^0-9]|^)[.]", "\\10.", x)
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# values like "<=0.2560.512" should be 0.512
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x <- gsub(".*[.].*[.]", "0.", x)
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# remove ending .0
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x <- gsub("[.]+0$", "", x)
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# remove all after last digit
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x <- gsub("[^0-9]+$", "", x)
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# keep only one zero before dot
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x <- gsub("0+[.]", "0.", x)
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# starting 00 is probably 0.0 if there's no dot yet
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x[!x %like% "[.]"] <- gsub("^00", "0.0", x[!x %like% "[.]"])
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# remove last zeroes
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x <- gsub("([.].?)0+$", "\\1", x)
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x <- gsub("(.*[.])0+$", "\\10", x)
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# remove ending .0 again
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x[x %like% "[.]"] <- gsub("0+$", "", x[x %like% "[.]"])
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# never end with dot
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x <- gsub("[.]$", "", x)
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# force to be character
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x <- as.character(x)
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# trim it
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x <- trimws(x)
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## previously unempty values now empty - should return a warning later on
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x[x.bak != "" & x == ""] <- "invalid"
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# these are allowed MIC values and will become factor levels
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ops <- c("<", "<=", "", ">=", ">")
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lvls <- c(c(t(vapply(FUN.VALUE = character(9), ops, function(x) paste0(x, "0.00", 1:9)))),
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unique(c(t(vapply(FUN.VALUE = character(104), ops, function(x) paste0(x, sort(as.double(paste0("0.0",
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sort(c(1:99, 125, 128, 256, 512, 625)))))))))),
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unique(c(t(vapply(FUN.VALUE = character(103), ops, function(x) paste0(x, sort(as.double(paste0("0.",
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c(1:99, 125, 128, 256, 512))))))))),
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c(t(vapply(FUN.VALUE = character(10), ops, function(x) paste0(x, sort(c(1:9, 1.5)))))),
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c(t(vapply(FUN.VALUE = character(45), ops, function(x) paste0(x, c(10:98)[9:98 %% 2 == TRUE])))),
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c(t(vapply(FUN.VALUE = character(15), ops, function(x) paste0(x, sort(c(2 ^ c(7:10), 80 * c(2:12))))))))
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na_before <- x[is.na(x) | x == ""] %pm>% length()
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x[!x %in% lvls] <- NA
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na_after <- x[is.na(x) | x == ""] %pm>% length()
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if (na_before != na_after) {
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list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ""] %pm>%
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unique() %pm>%
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sort() %pm>%
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vector_and(quotes = TRUE)
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warning_(na_after - na_before, " results truncated (",
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round(((na_after - na_before) / length(x)) * 100),
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"%) that were invalid MICs: ",
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list_missing, call = FALSE)
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}
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set_clean_class(factor(x, levels = lvls, ordered = TRUE),
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new_class = c("mic", "ordered", "factor"))
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}
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}
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all_valid_mics <- function(x) {
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if (!inherits(x, c("mic", "character", "factor", "numeric", "integer"))) {
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return(FALSE)
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}
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x_mic <- tryCatch(suppressWarnings(as.mic(x[!is.na(x)])),
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error = function(e) NA)
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!any(is.na(x_mic)) && !all(is.na(x))
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}
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#' @rdname as.mic
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#' @export
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is.mic <- function(x) {
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inherits(x, "mic")
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}
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#' @method as.double mic
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#' @export
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#' @noRd
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as.double.mic <- function(x, ...) {
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as.double(gsub("[<=>]+", "", as.character(x)))
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}
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#' @method as.integer mic
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#' @export
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#' @noRd
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as.integer.mic <- function(x, ...) {
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as.integer(gsub("[<=>]+", "", as.character(x)))
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}
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#' @method as.numeric mic
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#' @export
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#' @noRd
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as.numeric.mic <- function(x, ...) {
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as.numeric(gsub("[<=>]+", "", as.character(x)))
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}
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#' @method droplevels mic
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#' @export
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#' @noRd
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droplevels.mic <- function(x, exclude = if (any(is.na(levels(x)))) NULL else NA, ...) {
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x <- droplevels.factor(x, exclude = exclude, ...)
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class(x) <- c("mic", "ordered", "factor")
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x
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}
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# will be exported using s3_register() in R/zzz.R
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pillar_shaft.mic <- function(x, ...) {
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crude_numbers <- as.double(x)
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operators <- gsub("[^<=>]+", "", as.character(x))
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pasted <- trimws(paste0(operators, trimws(format(crude_numbers))))
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out <- pasted
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out[is.na(x)] <- font_na(NA)
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out <- gsub("(<|=|>)", font_silver("\\1"), out)
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create_pillar_column(out, align = "right", width = max(nchar(pasted)))
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}
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# will be exported using s3_register() in R/zzz.R
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type_sum.mic <- function(x, ...) {
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"mic"
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}
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#' @method print mic
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#' @export
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#' @noRd
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print.mic <- function(x, ...) {
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cat("Class <mic>\n")
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print(as.character(x), quote = FALSE)
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}
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#' @method summary mic
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#' @export
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#' @noRd
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summary.mic <- function(object, ...) {
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x <- object
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n_total <- length(x)
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x <- x[!is.na(x)]
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n <- length(x)
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value <- c("Class" = "mic",
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"<NA>" = n_total - n,
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"Min." = as.character(sort(x)[1]),
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"Max." = as.character(sort(x)[n]))
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class(value) <- c("summaryDefault", "table")
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value
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}
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#' @method plot mic
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#' @export
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#' @importFrom graphics barplot axis
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#' @rdname plot
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plot.mic <- function(x,
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main = paste("MIC values of", deparse(substitute(x))),
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ylab = "Frequency",
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xlab = "MIC value",
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axes = FALSE,
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...) {
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meet_criteria(main, allow_class = "character", has_length = 1)
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meet_criteria(ylab, allow_class = "character", has_length = 1)
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meet_criteria(xlab, allow_class = "character", has_length = 1)
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meet_criteria(axes, allow_class = "logical", has_length = 1)
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barplot(table(as.double(x)),
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ylab = ylab,
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xlab = xlab,
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axes = axes,
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main = main,
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...)
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axis(2, seq(0, max(table(as.double(x)))))
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}
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#' @method barplot mic
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#' @export
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#' @importFrom graphics barplot axis
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#' @rdname plot
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barplot.mic <- function(height,
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main = paste("MIC values of", deparse(substitute(height))),
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ylab = "Frequency",
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xlab = "MIC value",
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axes = FALSE,
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...) {
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meet_criteria(main, allow_class = "character", has_length = 1)
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meet_criteria(ylab, allow_class = "character", has_length = 1)
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meet_criteria(xlab, allow_class = "character", has_length = 1)
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meet_criteria(axes, allow_class = "logical", has_length = 1)
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barplot(table(as.double(height)),
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ylab = ylab,
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xlab = xlab,
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axes = axes,
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main = main,
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...)
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axis(2, seq(0, max(table(as.double(height)))))
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}
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#' @method [ mic
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#' @export
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#' @noRd
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"[.mic" <- function(x, ...) {
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y <- NextMethod()
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attributes(y) <- attributes(x)
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y
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}
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#' @method [[ mic
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#' @export
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#' @noRd
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"[[.mic" <- function(x, ...) {
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y <- NextMethod()
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attributes(y) <- attributes(x)
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y
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}
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#' @method [<- mic
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#' @export
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#' @noRd
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"[<-.mic" <- function(i, j, ..., value) {
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value <- as.mic(value)
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y <- NextMethod()
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attributes(y) <- attributes(i)
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y
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}
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#' @method [[<- mic
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#' @export
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#' @noRd
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"[[<-.mic" <- function(i, j, ..., value) {
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value <- as.mic(value)
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y <- NextMethod()
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attributes(y) <- attributes(i)
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y
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}
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#' @method c mic
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#' @export
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#' @noRd
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c.mic <- function(x, ...) {
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y <- unlist(lapply(list(...), as.character))
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x <- as.character(x)
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as.mic(c(x, y))
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}
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#' @method unique mic
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#' @export
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#' @noRd
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unique.mic <- function(x, incomparables = FALSE, ...) {
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y <- NextMethod()
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attributes(y) <- attributes(x)
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y
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}
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# will be exported using s3_register() in R/zzz.R
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get_skimmers.mic <- function(column) {
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skimr::sfl(
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skim_type = "mic",
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min = ~as.character(sort(stats::na.omit(.))[1]),
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max = ~as.character(sort(stats::na.omit(.))[length(stats::na.omit(.))]),
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median = ~as.character(stats::na.omit(.)[as.double(stats::na.omit(.)) == median(as.double(stats::na.omit(.)))])[1],
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n_unique = ~pm_n_distinct(., na.rm = TRUE),
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hist_log2 = ~skimr::inline_hist(log2(as.double(stats::na.omit(.))))
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)
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}
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