mirror of https://github.com/msberends/AMR.git
(v1.7.1.9005) ab class selectors for R-3.0 and R-3.1
This commit is contained in:
parent
c44d9392ca
commit
d04e83f494
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@ -107,9 +107,9 @@ jobs:
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sudo apt install -y libssl-dev pandoc pandoc-citeproc libxml2-dev libicu-dev libcurl4-openssl-dev libpng-dev
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- name: Query dependencies
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# this will change once a week, so it will cache dependency updates
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# this will change every day (i.e. at scheduled night run of GitHub Action), so it will cache dependency updates
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run: |
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writeLines(paste(format(Sys.Date(), "week %V %Y"), sprintf("R-%i.%i", getRversion()$major, getRversion()$minor)), ".github/week-R-version")
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writeLines(paste0(format(Sys.Date(), "%Y%m%d"), sprintf("-R-%i.%i", getRversion()$major, getRversion()$minor)), ".github/daily-R-bundle")
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shell: Rscript {0}
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- name: Restore cached R packages
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@ -117,7 +117,7 @@ jobs:
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uses: actions/cache@v2
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with:
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path: ${{ env.R_LIBS_USER }}
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key: ${{ matrix.config.os }}-${{ hashFiles('.github/week-R-version') }}-v4
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key: ${{ matrix.config.os }}-${{ hashFiles('.github/daily-R-bundle') }}-v4
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- name: Unpack AMR and install R dependencies
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if: always()
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@ -1,6 +1,6 @@
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Package: AMR
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Version: 1.7.1.9004
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Date: 2021-06-15
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Version: 1.7.1.9005
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Date: 2021-06-22
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Title: Antimicrobial Resistance Data Analysis
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Authors@R: c(
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person(role = c("aut", "cre"),
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13
NEWS.md
13
NEWS.md
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@ -1,12 +1,17 @@
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# `AMR` 1.7.1.9004
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## <small>Last updated: 15 June 2021</small>
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# `AMR` 1.7.1.9005
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## <small>Last updated: 22 June 2021</small>
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### Changed
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* Added more antibiotic class selectors: `aminopenicillins()`, `lincosamides()`, `lipoglycopeptides()`, `polymyxins()`, `quinolones()`, `streptogramins()` and `ureidopenicillins()`
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* Antibiotic class selectors (see `ab_class()`)
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* They now finally also work in R-3.0 and R-3.1, supporting every version of R since 2013
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* Added more selectors: `aminopenicillins()`, `lincosamides()`, `lipoglycopeptides()`, `polymyxins()`, `quinolones()`, `streptogramins()` and `ureidopenicillins()`
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* Fix for using selectors multiple times in one call (e.g., using them in `dplyr::filter()` and immediately after in `dplyr::select()`)
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* Added `ggplot2::autoplot()` generic for classes `<mic>`, `<disk>`, `<rsi>` and `<resistance_predict>`
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* Fix to prevent introducing `NA`s for old MO codes when running `as.mo()` on them
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* Added more informative error messages when any of the `proportion_*()` and `count_*()` functions fail
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* Fix for using antibiotic selectors multiple times in one call (e.g., using in `dplyr::filter()` and immediately after in `dplyr::select()`)
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* When printing a tibble with any old MO code, a warning will be thrown that old codes should be updated using `as.mo()`
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* Improved automatic column selector when `col_*` arguments are left blank, e.g. in `first_isolate()`
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* The right input types for `random_mic()`, `random_disk()` and `random_rsi()` are now enforced
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# `AMR` 1.7.1
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@ -170,65 +170,73 @@ search_type_in_df <- function(x, type, info = TRUE) {
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# remove attributes from other packages
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x <- as.data.frame(x, stringsAsFactors = FALSE)
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colnames(x) <- trimws(colnames(x))
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colnames_formatted <- tolower(generalise_antibiotic_name(colnames(x)))
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# -- mo
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if (type == "mo") {
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if (any(vapply(FUN.VALUE = logical(1), x, is.mo))) {
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found <- sort(colnames(x)[vapply(FUN.VALUE = logical(1), x, is.mo)])[1]
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} else if ("mo" %in% colnames(x) &
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suppressWarnings(
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all(x$mo %in% c(NA, microorganisms$mo)))) {
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# take first <mo> column
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found <- colnames(x)[vapply(FUN.VALUE = logical(1), x, is.mo)]
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} else if ("mo" %in% colnames_formatted &
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suppressWarnings(all(x$mo %in% c(NA, microorganisms$mo)))) {
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found <- "mo"
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} else if (any(colnames(x) %like% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$")) {
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found <- sort(colnames(x)[colnames(x) %like% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$"])[1]
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} else if (any(colnames(x) %like% "^(microorganism|organism|bacteria|ba[ck]terie)")) {
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found <- sort(colnames(x)[colnames(x) %like% "^(microorganism|organism|bacteria|ba[ck]terie)"])[1]
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} else if (any(colnames(x) %like% "species")) {
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found <- sort(colnames(x)[colnames(x) %like% "species"])[1]
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} else if (any(colnames_formatted %like_case% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$")) {
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found <- sort(colnames(x)[colnames_formatted %like_case% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$"])
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} else if (any(colnames_formatted %like_case% "^(microorganism|organism|bacteria|ba[ck]terie)")) {
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found <- sort(colnames(x)[colnames_formatted %like_case% "^(microorganism|organism|bacteria|ba[ck]terie)"])
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} else if (any(colnames_formatted %like_case% "species")) {
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found <- sort(colnames(x)[colnames_formatted %like_case% "species"])
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}
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}
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# -- key antibiotics
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if (type %in% c("keyantibiotics", "keyantimicrobials")) {
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if (any(colnames(x) %like% "^key.*(ab|antibiotics|antimicrobials)")) {
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found <- sort(colnames(x)[colnames(x) %like% "^key.*(ab|antibiotics|antimicrobials)"])[1]
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if (any(colnames_formatted %like_case% "^key.*(ab|antibiotics|antimicrobials)")) {
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found <- sort(colnames(x)[colnames_formatted %like_case% "^key.*(ab|antibiotics|antimicrobials)"])
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}
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}
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# -- date
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if (type == "date") {
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if (any(colnames(x) %like% "^(specimen date|specimen_date|spec_date)")) {
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if (any(colnames_formatted %like_case% "^(specimen date|specimen_date|spec_date)")) {
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# WHONET support
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found <- sort(colnames(x)[colnames(x) %like% "^(specimen date|specimen_date|spec_date)"])[1]
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found <- sort(colnames(x)[colnames_formatted %like_case% "^(specimen date|specimen_date|spec_date)"])
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if (!any(class(pm_pull(x, found)) %in% c("Date", "POSIXct"))) {
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stop(font_red(paste0("Found column '", font_bold(found), "' to be used as input for `col_", type,
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"`, but this column contains no valid dates. Transform its values to valid dates first.")),
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call. = FALSE)
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}
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} else if (any(vapply(FUN.VALUE = logical(1), x, function(x) inherits(x, c("Date", "POSIXct"))))) {
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found <- sort(colnames(x)[vapply(FUN.VALUE = logical(1), x, function(x) inherits(x, c("Date", "POSIXct")))])[1]
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# take first <Date> column
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found <- colnames(x)[vapply(FUN.VALUE = logical(1), x, function(x) inherits(x, c("Date", "POSIXct")))]
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}
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}
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# -- patient id
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if (type == "patient_id") {
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if (any(colnames(x) %like% "^(identification |patient|patid)")) {
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found <- sort(colnames(x)[colnames(x) %like% "^(identification |patient|patid)"])[1]
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crit1 <- colnames_formatted %like_case% "^(patient|patid)"
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if (any(crit1)) {
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found <- colnames(x)[crit1]
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} else {
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crit2 <- colnames_formatted %like_case% "(identification |patient|pat.*id)"
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if (any(crit2)) {
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found <- colnames(x)[crit2]
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}
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}
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}
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# -- specimen
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if (type == "specimen") {
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if (any(colnames(x) %like% "(specimen type|spec_type)")) {
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found <- sort(colnames(x)[colnames(x) %like% "(specimen type|spec_type)"])[1]
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} else if (any(colnames(x) %like% "^(specimen)")) {
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found <- sort(colnames(x)[colnames(x) %like% "^(specimen)"])[1]
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if (any(colnames_formatted %like_case% "(specimen type|spec_type)")) {
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found <- sort(colnames(x)[colnames_formatted %like_case% "(specimen type|spec_type)"])
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} else if (any(colnames_formatted %like_case% "^(specimen)")) {
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found <- sort(colnames(x)[colnames_formatted %like_case% "^(specimen)"])
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}
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}
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# -- UTI (urinary tract infection)
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if (type == "uti") {
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if (any(colnames(x) == "uti")) {
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found <- colnames(x)[colnames(x) == "uti"][1]
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} else if (any(colnames(x) %like% "(urine|urinary)")) {
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found <- sort(colnames(x)[colnames(x) %like% "(urine|urinary)"])[1]
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if (any(colnames_formatted == "uti")) {
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found <- colnames(x)[colnames_formatted == "uti"]
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} else if (any(colnames_formatted %like_case% "(urine|urinary)")) {
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found <- sort(colnames(x)[colnames_formatted %like_case% "(urine|urinary)"])
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}
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if (!is.null(found)) {
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# this column should contain logicals
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@ -241,10 +249,12 @@ search_type_in_df <- function(x, type, info = TRUE) {
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}
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}
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found <- found[1]
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if (!is.null(found) & info == TRUE) {
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if (message_not_thrown_before(fn = paste0("search_", type))) {
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msg <- paste0("Using column '", font_bold(found), "' as input for `col_", type, "`.")
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if (type %in% c("keyantibiotics", "specimen")) {
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if (type %in% c("keyantibiotics", "keyantimicrobials", "specimen")) {
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msg <- paste(msg, "Use", font_bold(paste0("col_", type), "= FALSE"), "to prevent this.")
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}
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message_(msg)
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@ -696,7 +706,7 @@ meet_criteria <- function(object,
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ifelse(!is.null(has_length) && length(has_length) == 1 && has_length == 1,
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"be a finite number",
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"all be finite numbers"),
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" (i.e., not be infinite)",
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" (i.e. not be infinite)",
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call = call_depth)
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}
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if (!is.null(contains_column_class)) {
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@ -713,13 +723,7 @@ meet_criteria <- function(object,
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return(invisible())
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}
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get_current_data <- function(arg_name, call, reuse_from_1st_call = TRUE) {
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# check if retrieved before, then get it from package environment to improve speed
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if (reuse_from_1st_call == TRUE &&
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identical(unique_call_id(entire_session = FALSE), pkg_env$get_current_data.call)) {
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return(pkg_env$get_current_data.out)
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}
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get_current_data <- function(arg_name, call) {
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# try dplyr::cur_data_all() first to support dplyr groups
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# only useful for e.g. dplyr::filter(), dplyr::mutate() and dplyr::summarise()
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# not useful (throws error) with e.g. dplyr::select() - but that will be caught later in this function
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@ -727,73 +731,32 @@ get_current_data <- function(arg_name, call, reuse_from_1st_call = TRUE) {
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if (!is.null(cur_data_all)) {
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out <- tryCatch(cur_data_all(), error = function(e) NULL)
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if (is.data.frame(out)) {
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out <- structure(out, type = "dplyr_cur_data_all")
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pkg_env$get_current_data.call <- unique_call_id(entire_session = FALSE)
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pkg_env$get_current_data.out <- out
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return(out)
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}
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}
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if (getRversion() < "3.2") {
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# R-3.0 and R-3.1 do not have an `x` element in the call stack, rendering this function useless
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# R-3.2 was released in April 2015
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if (is.na(arg_name)) {
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# such as for carbapenems() etc.
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warning_("this function requires R version 3.2 or later - you have ", R.version.string, call = call)
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return(data.frame())
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} else {
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# mimic a default R error, e.g. for example_isolates[which(mo_name() %like% "^ent"), ]
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stop_("argument `", arg_name, "` is missing with no default", call = call)
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return(structure(out, type = "dplyr_cur_data_all"))
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}
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}
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# try a (base R) method, by going over the complete system call stack with sys.frames()
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not_set <- TRUE
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source <- "base_R"
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frms <- lapply(sys.frames(), function(el) {
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if (not_set == TRUE && ".Generic" %in% names(el)) {
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if (tryCatch(".data" %in% names(el) && is.data.frame(el$`.data`), error = function(e) FALSE)) {
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# - - - -
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# dplyr
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# - - - -
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# an element `.data` will be in the system call stack when using dplyr::select()
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# [but not when using dplyr::filter(), dplyr::mutate() or dplyr::summarise()]
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not_set <<- FALSE
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source <<- "dplyr_selector"
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el$`.data`
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} else if (tryCatch(any(c("x", "xx") %in% names(el)), error = function(e) FALSE)) {
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# - - - -
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# base R
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# - - - -
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# an element `x` will be in this environment for only cols, e.g. `example_isolates[, carbapenems()]`
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# an element `xx` will be in this environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]`
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if (tryCatch(is.data.frame(el$xx), error = function(e) FALSE)) {
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not_set <<- FALSE
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el$xx
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} else if (tryCatch(is.data.frame(el$x))) {
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not_set <<- FALSE
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el$x
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} else {
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NULL
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}
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} else {
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NULL
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# try a manual (base R) method, by going over all underlying environments with sys.frames()
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for (el in sys.frames()) {
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if (!is.null(el$`.Generic`)) {
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# don't check `".Generic" %in% names(el)`, because in R < 3.2, `names(el)` is always NULL
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if (!is.null(el$`.data`) && is.data.frame(el$`.data`)) {
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# an element `.data` will be in the environment when using `dplyr::select()`
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# (but not when using `dplyr::filter()`, `dplyr::mutate()` or `dplyr::summarise()`)
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return(structure(el$`.data`, type = "dplyr_selector"))
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} else if (!is.null(el$xx) && is.data.frame(el$xx)) {
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# an element `xx` will be in the environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]`
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return(structure(el$xx, type = "base_R"))
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} else if (!is.null(el$x) && is.data.frame(el$x)) {
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# an element `x` will be in the environment for only cols, e.g. `example_isolates[, carbapenems()]`
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return(structure(el$x, type = "base_R"))
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}
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} else {
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NULL
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}
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})
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# lookup the matched frame and return its value: a data.frame
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vars_df <- tryCatch(frms[[which(!vapply(FUN.VALUE = logical(1), frms, is.null))]], error = function(e) NULL)
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if (is.data.frame(vars_df)) {
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out <- structure(vars_df, type = source)
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pkg_env$get_current_data.call <- unique_call_id(entire_session = FALSE)
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pkg_env$get_current_data.out <- out
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return(out)
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}
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# nothing worked, so:
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# no data.frame found, so an error must be returned:
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if (is.na(arg_name)) {
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if (isTRUE(is.numeric(call))) {
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fn <- as.character(sys.call(call + 1)[1])
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@ -982,8 +945,8 @@ font_grey_bg <- function(..., collapse = " ") {
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# similar to HTML #444444
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try_colour(..., before = "\033[48;5;238m", after = "\033[49m", collapse = collapse)
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} else {
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# similar to HTML #eeeeee
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try_colour(..., before = "\033[48;5;254m", after = "\033[49m", collapse = collapse)
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# similar to HTML #f0f0f0
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try_colour(..., before = "\033[48;5;255m", after = "\033[49m", collapse = collapse)
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}
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}
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font_green_bg <- function(..., collapse = " ") {
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@ -25,13 +25,12 @@
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#' Antibiotic Class Selectors
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#'
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#' These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. \strong{\Sexpr{ifelse(getRversion() < "3.2", paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
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#' These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
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#' @inheritSection lifecycle Stable Lifecycle
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#' @param ab_class an antimicrobial class, such as `"carbapenems"`. The columns `group`, `atc_group1` and `atc_group2` of the [antibiotics] data set will be searched (case-insensitive) for this value.
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#' @param only_rsi_columns a [logical] to indicate whether only columns of class `<rsi>` must be selected (defaults to `FALSE`), see [as.rsi()]
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#' @details \strong{\Sexpr{ifelse(getRversion() < "3.2", paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
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#'
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#' These functions can be used in data set calls for selecting columns and filtering rows, see *Examples*. They support base R, but work more convenient in dplyr functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()].
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#' @details
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#' These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the [Tidyverse selection helpers](https://tidyselect.r-lib.org/reference/language.html), but also work in base \R and not only in `dplyr` verbs. Nonetheless, they are very convenient to use with `dplyr` functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()], see *Examples*.
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#'
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#' All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) in the [antibiotics] data set. This means that a selector such as [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. Use the [ab_class()] function to filter/select on a manually defined antibiotic class.
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#'
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@ -267,18 +266,9 @@ ab_selector <- function(function_name,
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|||
meet_criteria(function_name, allow_class = "character", has_length = 1, allow_NULL = TRUE, .call_depth = 1)
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1, .call_depth = 1)
|
||||
meet_criteria(ab_class, allow_class = "character", has_length = 1, allow_NULL = TRUE, .call_depth = 1)
|
||||
|
||||
if (getRversion() < "3.2") {
|
||||
# get_current_data() does not work on R 3.0 and R 3.1.
|
||||
# R 3.2 was released in April 2015.
|
||||
warning_("antibiotic class selectors such as ", function_name,
|
||||
"() require R version 3.2 or later - you have ", R.version.string,
|
||||
call = FALSE)
|
||||
return(NULL)
|
||||
}
|
||||
|
||||
|
||||
# get_current_data() has to run each time, for cases where e.g., filter() and select() are used in same call
|
||||
vars_df <- get_current_data(arg_name = NA, call = -3, reuse_from_1st_call = FALSE)
|
||||
vars_df <- get_current_data(arg_name = NA, call = -3)
|
||||
# to improve speed, get_column_abx() will only run once when e.g. in a select or group call
|
||||
ab_in_data <- get_column_abx(vars_df, info = FALSE, only_rsi_columns = only_rsi_columns, sort = FALSE)
|
||||
|
||||
|
|
@ -315,12 +305,15 @@ ab_selector <- function(function_name,
|
|||
} else {
|
||||
agents_formatted <- paste0("'", font_bold(agents, collapse = NULL), "'")
|
||||
agents_names <- ab_name(names(agents), tolower = TRUE, language = NULL)
|
||||
need_name <- tolower(gsub("[^a-zA-Z]", "", agents)) != tolower(gsub("[^a-zA-Z]", "", agents_names))
|
||||
agents_formatted[need_name] <- paste0(agents_formatted[need_name],
|
||||
" (", agents_names[need_name], ")")
|
||||
message_("For `", function_name, "(", ifelse(function_name == "ab_class", paste0("\"", ab_class, "\""), ""), ")` using ",
|
||||
need_name <- generalise_antibiotic_name(agents) != generalise_antibiotic_name(agents_names)
|
||||
agents_formatted[need_name] <- paste0(agents_formatted[need_name], " (", agents_names[need_name], ")")
|
||||
message_("For `", function_name, "(",
|
||||
ifelse(function_name == "ab_class",
|
||||
paste0("\"", ab_class, "\""),
|
||||
""),
|
||||
")` using ",
|
||||
ifelse(length(agents) == 1, "column: ", "columns: "),
|
||||
vector_and(agents_formatted, quotes = FALSE))
|
||||
vector_and(agents_formatted, quotes = FALSE, sort = FALSE))
|
||||
}
|
||||
remember_thrown_message(function_name)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -62,7 +62,7 @@ filter_first_weighted_isolate <- function(x = NULL,
|
|||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
|
||||
meet_criteria(col_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
|
|
@ -104,7 +104,7 @@ key_antibiotics <- function(x = NULL,
|
|||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
|
||||
key_antimicrobials(x = x,
|
||||
|
|
@ -170,7 +170,7 @@ filter_ab_class <- function(x,
|
|||
if (missing(x) || is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- get_current_data(arg_name = "x", call = -2 - .call_depth, reuse_from_1st_call = FALSE)
|
||||
x <- get_current_data(arg_name = "x", call = -2 - .call_depth)
|
||||
.x_name <- "your_data"
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame", .call_depth = .call_depth)
|
||||
|
|
|
|||
|
|
@ -131,11 +131,8 @@
|
|||
#' # `example_isolates` is a data set available in the AMR package.
|
||||
#' # See ?example_isolates.
|
||||
#'
|
||||
#' example_isolates[first_isolate(example_isolates), ]
|
||||
#' \donttest{
|
||||
#' # faster way, only works in R 3.2 and later:
|
||||
#' example_isolates[first_isolate(), ]
|
||||
#'
|
||||
#' \donttest{
|
||||
#' # get all first Gram-negatives
|
||||
#' example_isolates[which(first_isolate() & mo_is_gram_negative()), ]
|
||||
#'
|
||||
|
|
@ -207,7 +204,7 @@ first_isolate <- function(x = NULL,
|
|||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
|
||||
meet_criteria(col_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
|
|
@ -618,7 +615,7 @@ filter_first_isolate <- function(x = NULL,
|
|||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
|
||||
meet_criteria(col_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
|
||||
|
|
|
|||
|
|
@ -36,7 +36,7 @@
|
|||
#' @param ... ignored, only in place to allow future extensions
|
||||
#' @details **Note:** As opposed to the `join()` functions of `dplyr`, [character] vectors are supported and at default existing columns will get a suffix `"2"` and the newly joined columns will not get a suffix.
|
||||
#'
|
||||
#' If the `dplyr` package is installed, their join functions will be used. Otherwise, the much slower [merge()] and [interaction()] functions from base R will be used.
|
||||
#' If the `dplyr` package is installed, their join functions will be used. Otherwise, the much slower [merge()] and [interaction()] functions from base \R will be used.
|
||||
#' @inheritSection AMR Read more on Our Website!
|
||||
#' @return a [data.frame]
|
||||
#' @export
|
||||
|
|
|
|||
|
|
@ -130,7 +130,7 @@ key_antimicrobials <- function(x = NULL,
|
|||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
|
||||
meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE, is_in = colnames(x))
|
||||
|
|
@ -232,7 +232,7 @@ all_antimicrobials <- function(x = NULL,
|
|||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
|
||||
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
|
||||
|
|
|
|||
2
R/mdro.R
2
R/mdro.R
|
|
@ -170,7 +170,7 @@ mdro <- function(x = NULL,
|
|||
if (is_null_or_grouped_tbl(x)) {
|
||||
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
|
||||
# is also fix for using a grouped df as input (a dot as first argument)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2, reuse_from_1st_call = FALSE), error = function(e) x)
|
||||
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
|
||||
}
|
||||
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
|
||||
meet_criteria(guideline, allow_class = c("list", "character"), allow_NULL = TRUE)
|
||||
|
|
|
|||
4
R/mo.R
4
R/mo.R
|
|
@ -1664,9 +1664,7 @@ pillar_shaft.mo <- function(x, ...) {
|
|||
out[is.na(x)] <- font_na(" NA")
|
||||
out[x == "UNKNOWN"] <- font_na(" UNKNOWN")
|
||||
|
||||
df <- tryCatch(get_current_data(arg_name = "x",
|
||||
call = 0,
|
||||
reuse_from_1st_call = FALSE),
|
||||
df <- tryCatch(get_current_data(arg_name = "x", call = 0),
|
||||
error = function(e) NULL)
|
||||
if (!is.null(df)) {
|
||||
mo_cols <- vapply(FUN.VALUE = logical(1), df, is.mo)
|
||||
|
|
|
|||
|
|
@ -747,16 +747,14 @@ mo_validate <- function(x, property, language, ...) {
|
|||
find_mo_col <- function(fn) {
|
||||
# this function tries to find an mo column in the data the function was called in,
|
||||
# which is useful when functions are used within dplyr verbs
|
||||
df <- get_current_data(arg_name = "x",
|
||||
call = -3,
|
||||
reuse_from_1st_call = FALSE) # will return an error if not found
|
||||
df <- get_current_data(arg_name = "x", call = -3) # will return an error if not found
|
||||
mo <- NULL
|
||||
try({
|
||||
mo <- suppressMessages(search_type_in_df(df, "mo"))
|
||||
}, silent = TRUE)
|
||||
if (!is.null(df) && !is.null(mo) && is.data.frame(df)) {
|
||||
if (message_not_thrown_before(fn = fn)) {
|
||||
message_("Using column '", font_bold(mo), "' as input for ", fn, "()")
|
||||
message_("Using column '", font_bold(mo), "' as input for `", fn, "()`")
|
||||
remember_thrown_message(fn = fn)
|
||||
}
|
||||
return(df[, mo, drop = TRUE])
|
||||
|
|
|
|||
2
R/plot.R
2
R/plot.R
|
|
@ -25,7 +25,7 @@
|
|||
|
||||
#' Plotting for Classes `rsi`, `mic` and `disk`
|
||||
#'
|
||||
#' Functions to plot classes `rsi`, `mic` and `disk`, with support for base R and `ggplot2`.
|
||||
#' Functions to plot classes `rsi`, `mic` and `disk`, with support for base \R and `ggplot2`.
|
||||
#' @inheritSection lifecycle Stable Lifecycle
|
||||
#' @inheritSection AMR Read more on Our Website!
|
||||
#' @param x,data MIC values created with [as.mic()] or disk diffusion values created with [as.disk()]
|
||||
|
|
|
|||
10
R/random.R
10
R/random.R
|
|
@ -32,7 +32,7 @@
|
|||
#' @param ab any [character] that can be coerced to a valid antimicrobial agent code with [as.ab()]
|
||||
#' @param prob_RSI a vector of length 3: the probabilities for R (1st value), S (2nd value) and I (3rd value)
|
||||
#' @param ... ignored, only in place to allow future extensions
|
||||
#' @details The base R function [sample()] is used for generating values.
|
||||
#' @details The base \R function [sample()] is used for generating values.
|
||||
#'
|
||||
#' Generated values are based on the latest EUCAST guideline implemented in the [rsi_translation] data set. To create specific generated values per bug or drug, set the `mo` and/or `ab` argument.
|
||||
#' @return class `<mic>` for [random_mic()] (see [as.mic()]) and class `<disk>` for [random_disk()] (see [as.disk()])
|
||||
|
|
@ -56,18 +56,26 @@
|
|||
#' random_disk(100, "Streptococcus pneumoniae", "ampicillin") # range 12-27
|
||||
#' }
|
||||
random_mic <- function(size, mo = NULL, ab = NULL, ...) {
|
||||
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(mo, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
random_exec("MIC", size = size, mo = mo, ab = ab)
|
||||
}
|
||||
|
||||
#' @rdname random
|
||||
#' @export
|
||||
random_disk <- function(size, mo = NULL, ab = NULL, ...) {
|
||||
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(mo, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
meet_criteria(ab, allow_class = "character", has_length = 1, allow_NULL = TRUE)
|
||||
random_exec("DISK", size = size, mo = mo, ab = ab)
|
||||
}
|
||||
|
||||
#' @rdname random
|
||||
#' @export
|
||||
random_rsi <- function(size, prob_RSI = c(0.33, 0.33, 0.33), ...) {
|
||||
meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
|
||||
meet_criteria(prob_RSI, allow_class = c("numeric", "integer"), has_length = 3)
|
||||
sample(as.rsi(c("R", "S", "I")), size = size, replace = TRUE, prob = prob_RSI)
|
||||
}
|
||||
|
||||
|
|
|
|||
6
R/rsi.R
6
R/rsi.R
|
|
@ -349,7 +349,7 @@ as.rsi.mic <- function(x,
|
|||
|
||||
# for dplyr's across()
|
||||
cur_column_dplyr <- import_fn("cur_column", "dplyr", error_on_fail = FALSE)
|
||||
if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0, reuse_from_1st_call = FALSE)), error = function(e) FALSE)) {
|
||||
if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0)), error = function(e) FALSE)) {
|
||||
# try to get current column, which will only be available when in across()
|
||||
ab <- tryCatch(cur_column_dplyr(),
|
||||
error = function(e) ab)
|
||||
|
|
@ -438,7 +438,7 @@ as.rsi.disk <- function(x,
|
|||
|
||||
# for dplyr's across()
|
||||
cur_column_dplyr <- import_fn("cur_column", "dplyr", error_on_fail = FALSE)
|
||||
if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0, reuse_from_1st_call = FALSE)), error = function(e) FALSE)) {
|
||||
if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0)), error = function(e) FALSE)) {
|
||||
# try to get current column, which will only be available when in across()
|
||||
ab <- tryCatch(cur_column_dplyr(),
|
||||
error = function(e) ab)
|
||||
|
|
@ -448,7 +448,7 @@ as.rsi.disk <- function(x,
|
|||
mo_var_found <- ""
|
||||
if (is.null(mo)) {
|
||||
tryCatch({
|
||||
df <- get_current_data(arg_name = "mo", call = -3, reuse_from_1st_call = FALSE) # will return an error if not found
|
||||
df <- get_current_data(arg_name = "mo", call = -3) # will return an error if not found
|
||||
mo <- NULL
|
||||
try({
|
||||
mo <- suppressMessages(search_type_in_df(df, "mo"))
|
||||
|
|
|
|||
Binary file not shown.
|
|
@ -24,8 +24,8 @@
|
|||
# ==================================================================== #
|
||||
|
||||
# some old R instances have trouble installing tinytest, so we ship it too
|
||||
install.packages("data-raw/tinytest_1.2.4.10.tar.gz")
|
||||
install.packages("data-raw/AMR_latest.tar.gz", dependencies = FALSE)
|
||||
install.packages("data-raw/tinytest_1.2.4.10.tar.gz", repos = "https://cran.rstudio.com/", type = "source")
|
||||
install.packages("data-raw/AMR_latest.tar.gz", repos = "https://cran.rstudio.com/", type = "source", dependencies = FALSE)
|
||||
|
||||
pkg_suggests <- gsub("[^a-zA-Z0-9]+", "", unlist(strsplit(packageDescription("AMR", fields = "Suggests"), ", ?")))
|
||||
cat("Packages listed in Suggests:", paste(pkg_suggests, collapse = ", "), "\n")
|
||||
|
|
|
|||
|
|
@ -81,7 +81,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="https://msberends.github.io/AMR//index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9004</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
|
|||
|
|
@ -81,7 +81,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9004</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
|
|||
|
|
@ -39,7 +39,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9004</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
@ -192,7 +192,7 @@
|
|||
<div class="page-header toc-ignore">
|
||||
<h1 data-toc-skip>Data sets for download / own use</h1>
|
||||
|
||||
<h4 class="date">15 June 2021</h4>
|
||||
<h4 class="date">22 June 2021</h4>
|
||||
|
||||
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/master/vignettes/datasets.Rmd"><code>vignettes/datasets.Rmd</code></a></small>
|
||||
<div class="hidden name"><code>datasets.Rmd</code></div>
|
||||
|
|
|
|||
|
|
@ -81,7 +81,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9004</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
|
|||
|
|
@ -81,7 +81,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9004</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
|
|||
|
|
@ -42,7 +42,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9004</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
@ -217,16 +217,12 @@
|
|||
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
|
||||
|
||||
<span class="va">example_isolates</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>bacteria <span class="op">=</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
|
||||
<span class="co">#> ℹ Using column 'mo' as input for `mo_is_gram_negative()`</span>
|
||||
<span class="co">#> ℹ Using column 'mo' as input for `mo_is_intrinsic_resistant()`</span>
|
||||
<span class="co">#> ℹ Determining intrinsic resistance based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic</span>
|
||||
<span class="co">#> Resistance and Unusual Phenotypes' v3.2 (2020)</span>
|
||||
<span class="co">#> ℹ For `aminoglycosides()` using columns: 'AMK' (amikacin), 'GEN' (gentamicin), 'KAN'</span>
|
||||
<span class="co">#> (kanamycin) and 'TOB' (tobramycin)</span>
|
||||
<span class="co">#> ℹ For `carbapenems()` using columns: 'IPM' (imipenem) and 'MEM' (meropenem)</span></code></pre></div>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>bacteria <span class="op">=</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span>,
|
||||
<span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span> <span class="op">%>%</span>
|
||||
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">bacteria</span>,
|
||||
<span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>,
|
||||
<span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></code></pre></div>
|
||||
<p>With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (<code><a href="reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><a href="reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>) and a column selection on two antibiotic groups (<code><a href="reference/antibiotic_class_selectors.html">aminoglycosides()</a></code> and <code><a href="reference/antibiotic_class_selectors.html">carbapenems()</a></code>), the reference data about <a href="./reference/microorganisms.html">all microorganisms</a> and <a href="./reference/antibiotics.html">all antibiotics</a> in the <code>AMR</code> package make sure you get what you meant:</p>
|
||||
<table class="table">
|
||||
<thead><tr class="header">
|
||||
|
|
@ -386,7 +382,7 @@
|
|||
<div id="latest-development-version" class="section level4">
|
||||
<h4 class="hasAnchor">
|
||||
<a href="#latest-development-version" class="anchor"></a>Latest development version</h4>
|
||||
<p><img src="https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master" alt="R-code-check"><img src="https://www.codefactor.io/repository/github/msberends/amr" alt="CodeFactor"><img src="https://codecov.io/gh/msberends/AMR?branch=master" alt="Codecov"></p>
|
||||
<p>[R-code-check][<a href="https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master" class="uri">https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master</a>](<a href="https://github.com/msberends/AMR/actions" class="uri">https://github.com/msberends/AMR/actions</a>) [CodeFactor][<a href="https://www.codefactor.io/repository/github/msberends/amr/badge" class="uri">https://www.codefactor.io/repository/github/msberends/amr/badge</a>](<a href="https://www.codefactor.io/repository/github/msberends/amr" class="uri">https://www.codefactor.io/repository/github/msberends/amr</a>) [Codecov][<a href="https://codecov.io/gh/msberends/AMR/branch/master/graph/badge.svg" class="uri">https://codecov.io/gh/msberends/AMR/branch/master/graph/badge.svg</a>](<a href="https://codecov.io/gh/msberends/AMR?branch=master" class="uri">https://codecov.io/gh/msberends/AMR?branch=master</a>)</p>
|
||||
<p>The latest and unpublished development version can be installed from GitHub in two ways:</p>
|
||||
<ol>
|
||||
<li>
|
||||
|
|
|
|||
|
|
@ -81,7 +81,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9004</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
@ -236,24 +236,34 @@
|
|||
<small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
|
||||
</div>
|
||||
|
||||
<div id="amr-1719004" class="section level1">
|
||||
<h1 class="page-header" data-toc-text="1.7.1.9004">
|
||||
<a href="#amr-1719004" class="anchor"></a><small> Unreleased </small><code>AMR</code> 1.7.1.9004</h1>
|
||||
<div id="last-updated-15-june-2021" class="section level2">
|
||||
<div id="amr-1719005" class="section level1">
|
||||
<h1 class="page-header" data-toc-text="1.7.1.9005">
|
||||
<a href="#amr-1719005" class="anchor"></a><small> Unreleased </small><code>AMR</code> 1.7.1.9005</h1>
|
||||
<div id="last-updated-22-june-2021" class="section level2">
|
||||
<h2 class="hasAnchor">
|
||||
<a href="#last-updated-15-june-2021" class="anchor"></a><small>Last updated: 15 June 2021</small>
|
||||
<a href="#last-updated-22-june-2021" class="anchor"></a><small>Last updated: 22 June 2021</small>
|
||||
</h2>
|
||||
<div id="changed" class="section level3">
|
||||
<h3 class="hasAnchor">
|
||||
<a href="#changed" class="anchor"></a>Changed</h3>
|
||||
<ul>
|
||||
<li>Added more antibiotic class selectors: <code><a href="../reference/antibiotic_class_selectors.html">aminopenicillins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">lincosamides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">lipoglycopeptides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">polymyxins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">quinolones()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">streptogramins()</a></code> and <code><a href="../reference/antibiotic_class_selectors.html">ureidopenicillins()</a></code>
|
||||
<li>Antibiotic class selectors (see <code><a href="../reference/antibiotic_class_selectors.html">ab_class()</a></code>)
|
||||
<ul>
|
||||
<li>They now finally also work in R-3.0 and R-3.1, supporting every version of R since 2013</li>
|
||||
<li>Added more selectors: <code><a href="../reference/antibiotic_class_selectors.html">aminopenicillins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">lincosamides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">lipoglycopeptides()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">polymyxins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">quinolones()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">streptogramins()</a></code> and <code><a href="../reference/antibiotic_class_selectors.html">ureidopenicillins()</a></code>
|
||||
</li>
|
||||
<li>Fix for using selectors multiple times in one call (e.g., using them in <code><a href="https://dplyr.tidyverse.org/reference/filter.html">dplyr::filter()</a></code> and immediately after in <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code>)</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li>Added <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html">ggplot2::autoplot()</a></code> generic for classes <code><mic></code>, <code><disk></code>, <code><rsi></code> and <code><resistance_predict></code>
|
||||
</li>
|
||||
<li>Fix to prevent introducing <code>NA</code>s for old MO codes when running <code><a href="../reference/as.mo.html">as.mo()</a></code> on them</li>
|
||||
<li>Added more informative error messages when any of the <code>proportion_*()</code> and <code>count_*()</code> functions fail</li>
|
||||
<li>Fix for using antibiotic selectors multiple times in one call (e.g., using in <code><a href="https://dplyr.tidyverse.org/reference/filter.html">dplyr::filter()</a></code> and immediately after in <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code>)</li>
|
||||
<li>When printing a tibble with any old MO code, a warning will be thrown that old codes should be updated using <code><a href="../reference/as.mo.html">as.mo()</a></code>
|
||||
</li>
|
||||
<li>Improved automatic column selector when <code>col_*</code> arguments are left blank, e.g. in <code><a href="../reference/first_isolate.html">first_isolate()</a></code>
|
||||
</li>
|
||||
<li>The right input types for <code><a href="../reference/random.html">random_mic()</a></code>, <code><a href="../reference/random.html">random_disk()</a></code> and <code><a href="../reference/random.html">random_rsi()</a></code> are now enforced</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
|
|
@ -307,7 +317,7 @@
|
|||
</ul>
|
||||
</li>
|
||||
<li>Function <code><a href="../reference/antibiotic_class_selectors.html">betalactams()</a></code> as additional antbiotic column selector and function <code><a href="../reference/AMR-deprecated.html">filter_betalactams()</a></code> as additional antbiotic column filter. The group of betalactams consists of all carbapenems, cephalosporins and penicillins.</li>
|
||||
<li>A <code>ggplot()</code> method for <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>
|
||||
<li>A <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> method for <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
|
|
@ -408,7 +418,7 @@
|
|||
<span class="co">#> Filtering on oxazolidinones: value in column `LNZ` (linezolid) is either "R", "S" or "I"</span></code></pre></div>
|
||||
</li>
|
||||
<li><p>Support for custom MDRO guidelines, using the new <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function, please see <code><a href="../reference/mdro.html">mdro()</a></code> for additional info</p></li>
|
||||
<li><p><code>ggplot()</code> generics for classes <code><mic></code> and <code><disk></code></p></li>
|
||||
<li><p><code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> generics for classes <code><mic></code> and <code><disk></code></p></li>
|
||||
<li>
|
||||
<p>Function <code><a href="../reference/mo_property.html">mo_is_yeast()</a></code>, which determines whether a microorganism is a member of the taxonomic class Saccharomycetes or the taxonomic order Saccharomycetales:</p>
|
||||
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
|
||||
|
|
@ -465,7 +475,7 @@
|
|||
<li>Plotting of MIC and disk diffusion values now support interpretation colouring if you supply the microorganism and antimicrobial agent</li>
|
||||
<li>All colours were updated to colour-blind friendly versions for values R, S and I for all plot methods (also applies to tibble printing)</li>
|
||||
<li>Interpretation of MIC and disk diffusion values to R/SI will now be translated if the system language is German, Dutch or Spanish (see <code>translate</code>)</li>
|
||||
<li>Plotting is now possible with base R using <code><a href="../reference/plot.html">plot()</a></code> and with ggplot2 using <code>ggplot()</code> on any vector of MIC and disk diffusion values</li>
|
||||
<li>Plotting is now possible with base R using <code><a href="../reference/plot.html">plot()</a></code> and with ggplot2 using <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> on any vector of MIC and disk diffusion values</li>
|
||||
</ul>
|
||||
</li>
|
||||
<li>Updated SNOMED codes to US Edition of SNOMED CT from 1 September 2020 and added the source to the help page of the <code>microorganisms</code> data set</li>
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ articles:
|
|||
datasets: datasets.html
|
||||
resistance_predict: resistance_predict.html
|
||||
welcome_to_AMR: welcome_to_AMR.html
|
||||
last_built: 2021-06-15T08:50Z
|
||||
last_built: 2021-06-22T10:02Z
|
||||
urls:
|
||||
reference: https://msberends.github.io/AMR//reference
|
||||
article: https://msberends.github.io/AMR//articles
|
||||
|
|
|
|||
|
|
@ -49,8 +49,7 @@
|
|||
<script src="../extra.js"></script>
|
||||
|
||||
<meta property="og:title" content="Antibiotic Class Selectors — antibiotic_class_selectors" />
|
||||
<meta property="og:description" content="These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
|
||||
" />
|
||||
<meta property="og:description" content="These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations." />
|
||||
<meta property="og:image" content="https://msberends.github.io/AMR/logo.png" />
|
||||
|
||||
|
||||
|
|
@ -83,7 +82,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9001</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
@ -240,8 +239,7 @@
|
|||
</div>
|
||||
|
||||
<div class="ref-description">
|
||||
<p>These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. <strong>
|
||||
</strong></p>
|
||||
<p>These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.</p>
|
||||
</div>
|
||||
|
||||
<pre class="usage"><span class='fu'>ab_class</span><span class='op'>(</span><span class='va'>ab_class</span>, only_rsi_columns <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>
|
||||
|
|
@ -305,9 +303,7 @@
|
|||
|
||||
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
|
||||
|
||||
<p><strong>
|
||||
</strong></p>
|
||||
<p>These functions can be used in data set calls for selecting columns and filtering rows, see <em>Examples</em>. They support base R, but work more convenient in dplyr functions such as <code><a href='https://dplyr.tidyverse.org/reference/select.html'>select()</a></code>, <code><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter()</a></code> and <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise()</a></code>.</p>
|
||||
<p>These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the <a href='https://tidyselect.r-lib.org/reference/language.html'>Tidyverse selection helpers</a>, but also work in base <span style="R">R</span> and not only in <code>dplyr</code> verbs. Nonetheless, they are very convenient to use with <code>dplyr</code> functions such as <code><a href='https://dplyr.tidyverse.org/reference/select.html'>select()</a></code>, <code><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter()</a></code> and <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise()</a></code>, see <em>Examples</em>.</p>
|
||||
<p>All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) in the <a href='antibiotics.html'>antibiotics</a> data set. This means that a selector such as <code>aminoglycosides()</code> will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. Use the <code>ab_class()</code> function to filter/select on a manually defined antibiotic class.</p>
|
||||
<h2 class="hasAnchor" id="full-list-of-supported-agents"><a class="anchor" href="#full-list-of-supported-agents"></a>Full list of supported agents</h2>
|
||||
|
||||
|
|
|
|||
|
|
@ -83,7 +83,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9002</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
|
|||
|
|
@ -83,7 +83,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
@ -457,11 +457,8 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
|
|||
<pre class="examples"><span class='co'># `example_isolates` is a data set available in the AMR package.</span>
|
||||
<span class='co'># See ?example_isolates.</span>
|
||||
|
||||
<span class='va'>example_isolates</span><span class='op'>[</span><span class='fu'>first_isolate</span><span class='op'>(</span><span class='va'>example_isolates</span><span class='op'>)</span>, <span class='op'>]</span>
|
||||
<span class='co'># \donttest{</span>
|
||||
<span class='co'># faster way, only works in R 3.2 and later:</span>
|
||||
<span class='va'>example_isolates</span><span class='op'>[</span><span class='fu'>first_isolate</span><span class='op'>(</span><span class='op'>)</span>, <span class='op'>]</span>
|
||||
|
||||
<span class='co'># \donttest{</span>
|
||||
<span class='co'># get all first Gram-negatives</span>
|
||||
<span class='va'>example_isolates</span><span class='op'>[</span><span class='fu'><a href='https://rdrr.io/r/base/which.html'>which</a></span><span class='op'>(</span><span class='fu'>first_isolate</span><span class='op'>(</span><span class='op'>)</span> <span class='op'>&</span> <span class='fu'><a href='mo_property.html'>mo_is_gram_negative</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>)</span>, <span class='op'>]</span>
|
||||
|
||||
|
|
|
|||
|
|
@ -81,7 +81,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9004</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
|
|||
|
|
@ -82,7 +82,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
@ -281,7 +281,7 @@
|
|||
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
|
||||
|
||||
<p><strong>Note:</strong> As opposed to the <code>join()</code> functions of <code>dplyr</code>, <a href='https://rdrr.io/r/base/character.html'>character</a> vectors are supported and at default existing columns will get a suffix <code>"2"</code> and the newly joined columns will not get a suffix.</p>
|
||||
<p>If the <code>dplyr</code> package is installed, their join functions will be used. Otherwise, the much slower <code><a href='https://rdrr.io/r/base/merge.html'>merge()</a></code> and <code><a href='https://rdrr.io/r/base/interaction.html'>interaction()</a></code> functions from base R will be used.</p>
|
||||
<p>If the <code>dplyr</code> package is installed, their join functions will be used. Otherwise, the much slower <code><a href='https://rdrr.io/r/base/merge.html'>merge()</a></code> and <code><a href='https://rdrr.io/r/base/interaction.html'>interaction()</a></code> functions from base <span style="R">R</span> will be used.</p>
|
||||
<h2 class="hasAnchor" id="stable-lifecycle"><a class="anchor" href="#stable-lifecycle"></a>Stable Lifecycle</h2>
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -82,7 +82,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9002</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
@ -239,7 +239,7 @@
|
|||
</div>
|
||||
|
||||
<div class="ref-description">
|
||||
<p>Functions to plot classes <code>rsi</code>, <code>mic</code> and <code>disk</code>, with support for base R and <code>ggplot2</code>.</p>
|
||||
<p>Functions to plot classes <code>rsi</code>, <code>mic</code> and <code>disk</code>, with support for base <span style="R">R</span> and <code>ggplot2</code>.</p>
|
||||
</div>
|
||||
|
||||
<pre class="usage"><span class='co'># S3 method for mic</span>
|
||||
|
|
|
|||
|
|
@ -82,7 +82,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
@ -278,7 +278,7 @@
|
|||
<p>class <code><mic></code> for <code>random_mic()</code> (see <code><a href='as.mic.html'>as.mic()</a></code>) and class <code><disk></code> for <code>random_disk()</code> (see <code><a href='as.disk.html'>as.disk()</a></code>)</p>
|
||||
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
|
||||
|
||||
<p>The base R function <code><a href='https://rdrr.io/r/base/sample.html'>sample()</a></code> is used for generating values.</p>
|
||||
<p>The base <span style="R">R</span> function <code><a href='https://rdrr.io/r/base/sample.html'>sample()</a></code> is used for generating values.</p>
|
||||
<p>Generated values are based on the latest EUCAST guideline implemented in the <a href='rsi_translation.html'>rsi_translation</a> data set. To create specific generated values per bug or drug, set the <code>mo</code> and/or <code>ab</code> argument.</p>
|
||||
<h2 class="hasAnchor" id="stable-lifecycle"><a class="anchor" href="#stable-lifecycle"></a>Stable Lifecycle</h2>
|
||||
|
||||
|
|
|
|||
|
|
@ -82,7 +82,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="../index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9002</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
|
|||
|
|
@ -81,7 +81,7 @@
|
|||
</button>
|
||||
<span class="navbar-brand">
|
||||
<a class="navbar-link" href="index.html">AMR (for R)</a>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9004</span>
|
||||
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.7.1.9005</span>
|
||||
</span>
|
||||
</div>
|
||||
|
||||
|
|
|
|||
22
index.md
22
index.md
|
|
@ -25,16 +25,12 @@ library(AMR)
|
|||
library(dplyr)
|
||||
|
||||
example_isolates %>%
|
||||
mutate(bacteria = mo_fullname(mo)) %>%
|
||||
filter(mo_is_gram_negative(), mo_is_intrinsic_resistant(ab = "cefotax")) %>%
|
||||
select(bacteria, aminoglycosides(), carbapenems())
|
||||
#> ℹ Using column 'mo' as input for `mo_is_gram_negative()`
|
||||
#> ℹ Using column 'mo' as input for `mo_is_intrinsic_resistant()`
|
||||
#> ℹ Determining intrinsic resistance based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic
|
||||
#> Resistance and Unusual Phenotypes' v3.2 (2020)
|
||||
#> ℹ For `aminoglycosides()` using columns: 'AMK' (amikacin), 'GEN' (gentamicin), 'KAN'
|
||||
#> (kanamycin) and 'TOB' (tobramycin)
|
||||
#> ℹ For `carbapenems()` using columns: 'IPM' (imipenem) and 'MEM' (meropenem)
|
||||
mutate(bacteria = mo_fullname()) %>%
|
||||
filter(mo_is_gram_negative(),
|
||||
mo_is_intrinsic_resistant(ab = "cefotax")) %>%
|
||||
select(bacteria,
|
||||
aminoglycosides(),
|
||||
carbapenems())
|
||||
```
|
||||
|
||||
With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (`mo_is_gram_negative()` and `mo_is_intrinsic_resistant()`) and a column selection on two antibiotic groups (`aminoglycosides()` and `carbapenems()`), the reference data about [all microorganisms](./reference/microorganisms.html) and [all antibiotics](./reference/antibiotics.html) in the `AMR` package make sure you get what you meant:
|
||||
|
|
@ -114,9 +110,9 @@ It will be downloaded and installed automatically. For RStudio, click on the men
|
|||
|
||||
#### Latest development version
|
||||
|
||||
|
||||
](https://www.codefactor.io/repository/github/msberends/amr)
|
||||
](https://codecov.io/gh/msberends/AMR?branch=master)
|
||||
![R-code-check][https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master](https://github.com/msberends/AMR/actions)
|
||||
![CodeFactor][https://www.codefactor.io/repository/github/msberends/amr/badge](https://www.codefactor.io/repository/github/msberends/amr)
|
||||
![Codecov][https://codecov.io/gh/msberends/AMR/branch/master/graph/badge.svg](https://codecov.io/gh/msberends/AMR?branch=master)
|
||||
|
||||
The latest and unpublished development version can be installed from GitHub in two ways:
|
||||
|
||||
|
|
|
|||
|
|
@ -23,52 +23,48 @@
|
|||
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
||||
# ==================================================================== #
|
||||
|
||||
if (getRversion() < "3.2") {
|
||||
expect_warning(example_isolates[, aminoglycosides(), drop = FALSE])
|
||||
}
|
||||
if (getRversion() >= "3.2") {
|
||||
# antibiotic class selectors require at least R-3.2
|
||||
expect_true(ncol(example_isolates[, ab_class("antimyco"), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, aminoglycosides(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, aminopenicillins(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, betalactams(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, carbapenems(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins_1st(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins_2nd(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins_3rd(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins_4th(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins_5th(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, fluoroquinolones(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, glycopeptides(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, lincosamides(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, lipoglycopeptides(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, macrolides(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, oxazolidinones(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, penicillins(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, polymyxins(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, streptogramins(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, quinolones(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, tetracyclines(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, ureidopenicillins(), drop = FALSE]) < ncol(example_isolates))
|
||||
|
||||
# Examples:
|
||||
|
||||
# select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
|
||||
expect_equal(ncol(example_isolates[, c("mo", aminoglycosides())]), 5, tolerance = 0.5)
|
||||
|
||||
# filter using any() or all()
|
||||
expect_equal(nrow(example_isolates[any(carbapenems() == "R"), ]), 55, tolerance = 0.5)
|
||||
expect_equal(nrow(subset(example_isolates, any(carbapenems() == "R"))), 55, tolerance = 0.5)
|
||||
|
||||
# filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
|
||||
expect_equal(nrow(example_isolates[any(carbapenems()), ]), 962, tolerance = 0.5)
|
||||
expect_equal(nrow(example_isolates[all(carbapenems()), ]), 756, tolerance = 0.5)
|
||||
|
||||
# filter with multiple antibiotic selectors using c()
|
||||
expect_equal(nrow(example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]), 26, tolerance = 0.5)
|
||||
|
||||
# filter + select in one go: get penicillins in carbapenems-resistant strains
|
||||
expect_equal(nrow(example_isolates[any(carbapenems() == "R"), penicillins()]), 55, tolerance = 0.5)
|
||||
expect_equal(ncol(example_isolates[any(carbapenems() == "R"), penicillins()]), 7, tolerance = 0.5)
|
||||
}
|
||||
# antibiotic class selectors
|
||||
expect_true(ncol(example_isolates[, ab_class("antimyco"), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, aminoglycosides(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, aminopenicillins(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, betalactams(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, carbapenems(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins_1st(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins_2nd(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins_3rd(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins_4th(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, cephalosporins_5th(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, fluoroquinolones(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, glycopeptides(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, lincosamides(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, lipoglycopeptides(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, macrolides(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, oxazolidinones(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, penicillins(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, polymyxins(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, streptogramins(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, quinolones(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, tetracyclines(), drop = FALSE]) < ncol(example_isolates))
|
||||
expect_true(ncol(example_isolates[, ureidopenicillins(), drop = FALSE]) < ncol(example_isolates))
|
||||
|
||||
# Examples:
|
||||
|
||||
# select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
|
||||
expect_equal(ncol(example_isolates[, c("mo", aminoglycosides())]), 5, tolerance = 0.5)
|
||||
|
||||
# filter using any() or all()
|
||||
expect_equal(nrow(example_isolates[any(carbapenems() == "R"), ]), 55, tolerance = 0.5)
|
||||
expect_equal(nrow(subset(example_isolates, any(carbapenems() == "R"))), 55, tolerance = 0.5)
|
||||
|
||||
# filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
|
||||
expect_equal(nrow(example_isolates[any(carbapenems()), ]), 962, tolerance = 0.5)
|
||||
expect_equal(nrow(example_isolates[all(carbapenems()), ]), 756, tolerance = 0.5)
|
||||
|
||||
# filter with multiple antibiotic selectors using c()
|
||||
expect_equal(nrow(example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]), 26, tolerance = 0.5)
|
||||
|
||||
# filter + select in one go: get penicillins in carbapenems-resistant strains
|
||||
expect_equal(nrow(example_isolates[any(carbapenems() == "R"), penicillins()]), 55, tolerance = 0.5)
|
||||
expect_equal(ncol(example_isolates[any(carbapenems() == "R"), penicillins()]), 7, tolerance = 0.5)
|
||||
|
||||
|
|
|
|||
|
|
@ -79,12 +79,10 @@ ureidopenicillins(only_rsi_columns = FALSE)
|
|||
\item{only_rsi_columns}{a \link{logical} to indicate whether only columns of class \verb{<rsi>} must be selected (defaults to \code{FALSE}), see \code{\link[=as.rsi]{as.rsi()}}}
|
||||
}
|
||||
\description{
|
||||
These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. \strong{\Sexpr{ifelse(getRversion() < "3.2", paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
|
||||
These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
|
||||
}
|
||||
\details{
|
||||
\strong{\Sexpr{ifelse(getRversion() < "3.2", paste0("NOTE: THESE FUNCTIONS DO NOT WORK ON YOUR CURRENT R VERSION. These functions require R version 3.2 or later - you have ", R.version.string, "."), "")}}
|
||||
|
||||
These functions can be used in data set calls for selecting columns and filtering rows, see \emph{Examples}. They support base R, but work more convenient in dplyr functions such as \code{\link[dplyr:select]{select()}}, \code{\link[dplyr:filter]{filter()}} and \code{\link[dplyr:summarise]{summarise()}}.
|
||||
These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the \href{https://tidyselect.r-lib.org/reference/language.html}{Tidyverse selection helpers}, but also work in base \R and not only in \code{dplyr} verbs. Nonetheless, they are very convenient to use with \code{dplyr} functions such as \code{\link[dplyr:select]{select()}}, \code{\link[dplyr:filter]{filter()}} and \code{\link[dplyr:summarise]{summarise()}}, see \emph{Examples}.
|
||||
|
||||
All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) in the \link{antibiotics} data set. This means that a selector such as \code{\link[=aminoglycosides]{aminoglycosides()}} will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. Use the \code{\link[=ab_class]{ab_class()}} function to filter/select on a manually defined antibiotic class.
|
||||
}
|
||||
|
|
|
|||
|
|
@ -181,11 +181,8 @@ On our website \url{https://msberends.github.io/AMR/} you can find \href{https:/
|
|||
# `example_isolates` is a data set available in the AMR package.
|
||||
# See ?example_isolates.
|
||||
|
||||
example_isolates[first_isolate(example_isolates), ]
|
||||
\donttest{
|
||||
# faster way, only works in R 3.2 and later:
|
||||
example_isolates[first_isolate(), ]
|
||||
|
||||
\donttest{
|
||||
# get all first Gram-negatives
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example_isolates[which(first_isolate() & mo_is_gram_negative()), ]
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|
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@ -41,7 +41,7 @@ Join the data set \link{microorganisms} easily to an existing data set or to a \
|
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\details{
|
||||
\strong{Note:} As opposed to the \code{join()} functions of \code{dplyr}, \link{character} vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix.
|
||||
|
||||
If the \code{dplyr} package is installed, their join functions will be used. Otherwise, the much slower \code{\link[=merge]{merge()}} and \code{\link[=interaction]{interaction()}} functions from base R will be used.
|
||||
If the \code{dplyr} package is installed, their join functions will be used. Otherwise, the much slower \code{\link[=merge]{merge()}} and \code{\link[=interaction]{interaction()}} functions from base \R will be used.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
|
|
|
|||
|
|
@ -158,7 +158,7 @@
|
|||
The \code{ggplot} functions return a \code{\link[ggplot2:ggplot]{ggplot}} model that is extendible with any \code{ggplot2} function.
|
||||
}
|
||||
\description{
|
||||
Functions to plot classes \code{rsi}, \code{mic} and \code{disk}, with support for base R and \code{ggplot2}.
|
||||
Functions to plot classes \code{rsi}, \code{mic} and \code{disk}, with support for base \R and \code{ggplot2}.
|
||||
}
|
||||
\details{
|
||||
The interpretation of "I" will be named "Increased exposure" for all EUCAST guidelines since 2019, and will be named "Intermediate" in all other cases.
|
||||
|
|
|
|||
|
|
@ -31,7 +31,7 @@ class \verb{<mic>} for \code{\link[=random_mic]{random_mic()}} (see \code{\link[
|
|||
These functions can be used for generating random MIC values and disk diffusion diameters, for AMR data analysis practice. By providing a microorganism and antimicrobial agent, the generated results will reflect reality as much as possible.
|
||||
}
|
||||
\details{
|
||||
The base R function \code{\link[=sample]{sample()}} is used for generating values.
|
||||
The base \R function \code{\link[=sample]{sample()}} is used for generating values.
|
||||
|
||||
Generated values are based on the latest EUCAST guideline implemented in the \link{rsi_translation} data set. To create specific generated values per bug or drug, set the \code{mo} and/or \code{ab} argument.
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue