mirror of
https://github.com/msberends/AMR.git
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99 lines
4.6 KiB
R
99 lines
4.6 KiB
R
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# ==================================================================== #
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# TITLE #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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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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# CITE AS #
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# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
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# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
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# Data. Journal of Statistical Software, 104(3), 1-31. #
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# doi:10.18637/jss.v104.i03 #
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# #
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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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#' Add Manual Antimicrobials to This Package
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#'
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#' With [add_custom_antimicrobials()] you can add your own manual antimicrobial codes to the `AMR` package.
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#' @param x a [data.frame] resembling the [antibiotics] data set, at least containing columns "ab" and "name"
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#' @details Due to how \R works, the [add_custom_antimicrobials()] function has to be run in every \R session - added antimicrobials are not stored between sessions and are thus lost when \R is exited. It is possible to save the antimicrobial additions to your `.Rprofile` file to circumvent this, for example:
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#'
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#' ```r
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#' library(AMR)
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#' add_custom_antimicrobials(
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#' data.frame(ab = "TEST",
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#' name = "Test Antibiotic",
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#' group = "Test Group")
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#' )
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#' ```
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#'
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#' Use [clear_custom_antimicrobials()] to clear the previously added antimicrobials.
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#' @rdname add_custom_antimicrobials
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#' @export
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#' @examples
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#' \donttest{
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#'
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#' # returns NA and throws a warning:
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#' as.ab("test")
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#'
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#' # now a manual entry - it will be considered by as.ab() and
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#' # all ab_*() functions
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#' add_custom_antimicrobials(
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#' data.frame(ab = "TEST",
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#' name = "Test Antibiotic",
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#' group = "Test Group")
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#' )
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#'
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#' "test" is now a new antibiotic:
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#' as.ab("test")
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#' ab_name("test")
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#' ab_group("test")
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#' }
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add_custom_antimicrobials <- function(x) {
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meet_criteria(x, allow_class = "data.frame")
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stop_ifnot(all(c("ab", "name") %in% colnames(x)),
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"`x` must contain columns \"ab\" and \"name\".")
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stop_if(any(x$ab %in% AB_lookup$ab),
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"Antimicrobial code(s) ", vector_and(x$ab[x$ab %in% AB_lookup$ab]), " already exist in the internal `antibiotics` data set.")
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x <- x[, colnames(AB_lookup)[colnames(AB_lookup) %in% colnames(x)], drop = FALSE]
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x$generalised_name <- generalise_antibiotic_name(x$name)
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x$generalised_all <- as.list(x$generalised_name)
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bind_rows <- import_fn("bind_rows", "dplyr", error_on_fail = FALSE)
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if (!is.null(bind_rows)) {
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new_df <- bind_rows(AB_lookup, x)
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} else {
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new_df <- rbind(AB_lookup, x, stringsAsFactors = FALSE)
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}
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assignInNamespace(x = "AB_lookup",
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value = new_df,
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ns = asNamespace("AMR"))
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message_("Added ", nr2char(nrow(x)), " record", ifelse(nrow(x) > 1, "s", ""), " to internal `antibiotics` data set.")
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}
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#' @rdname add_custom_antimicrobials
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#' @export
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clear_custom_antimicrobials <- function() {
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assignInNamespace(x = "AB_lookup",
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value = create_AB_lookup(),
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ns = asNamespace("AMR"))
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message_("Manual antimicrobials cleared.")
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}
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