small fixes

New tibbles, cleanup

.Rbuildignore

@@ -23,14 +23,16 @@
 ^data-raw$
 ^\.lintr$
 ^tests/testthat/_snaps$
-^vignettes/AMR.Rmd$
-^vignettes/benchmarks.Rmd$
-^vignettes/datasets.Rmd$
-^vignettes/EUCAST.Rmd$
-^vignettes/MDR.Rmd$
-^vignettes/PCA.Rmd$
-^vignettes/resistance_predict.Rmd$
-^vignettes/SPSS.Rmd$
-^vignettes/WHONET.Rmd$
+^vignettes/AMR\.Rmd$
+^vignettes/AMR_intro\.png$
+^vignettes/benchmarks\.Rmd$
+^vignettes/benchmarks\.Rmd\.not$
+^vignettes/datasets\.Rmd$
+^vignettes/EUCAST\.Rmd$
+^vignettes/MDR\.Rmd$
+^vignettes/PCA\.Rmd$
+^vignettes/resistance_predict\.Rmd$
+^vignettes/SPSS\.Rmd$
+^vignettes/WHONET\.Rmd$
 ^logo.svg$
 ^CRAN-SUBMISSION$

.github/prehooks/pre-commit

@@ -0,0 +1,76 @@
+#!/bin/sh
+
+echo "Running pre-commit hook..."
+
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+if command -v Rscript > /dev/null; then
+  if [ "$(Rscript -e 'cat(all(c('"'pkgload'"', '"'devtools'"', '"'dplyr'"', '"'styler'"') %in% rownames(installed.packages())))')" = "TRUE" ]; then
+    Rscript -e "source('data-raw/_pre_commit_hook.R')"
+    currentpkg=`Rscript -e "cat(pkgload::pkg_name())"`
+    echo "-> Adding all files in folders 'data-raw', 'inst', 'man', and 'R' to this git commit"
+    git add data-raw/*
+    git add inst/*
+    git add man/*
+    git add R/*
+  else
+    echo "- R package 'pkgload', 'devtools', 'dplyr', or 'styler' not installed!"
+    currentpkg="your"
+  fi
+else
+  echo "- R is not available on your system!"
+  currentpkg="your"
+fi
+echo ""
+
+
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+echo ">> Updating semantic versioning and date..."
+
+# get tags from remote, and remove tags not on remote:
+git fetch origin --prune --prune-tags --quiet
+currenttagfull=`git describe --tags --abbrev=0`
+currenttag=`git describe --tags --abbrev=0 | sed 's/v//'`
+if [ "$currenttag" = "" ]; then
+  # there is no tag, so set tag to 0.0.1 and commit index to current count
+  echo ">>  - no git tags found, create one in this format: 'v(x).(y).(z)'!"
+  currenttag="0.0.1"
+  currentcommit=`git rev-list --count HEAD`
+else
+  # there is a tag, so base version number on that
+  currentcommit=`git rev-list --count ${currenttagfull}..HEAD`
+  if (( "$currentcommit" == 0 )); then
+    # tag is new, so this must become the version number
+    currentversion="$currenttag"
+  fi
+  echo ">>  - latest tag is '${currenttagfull}', with ${currentcommit} previous commits"
+fi
+if [ "$currentversion" = "" ]; then
+  # combine tag (e.g. 1.2.3) and commit number (like 5) increased by 9000 to indicate beta version
+  currentversion="$currenttag.$((currentcommit + 9001))" # results in e.g. 1.2.3.9005
+fi
+echo ">>  - ${currentpkg} pkg version set to ${currentversion}"
+
+# set version number and date to DESCRIPTION file
+sed -i -- "s/^Version: .*/Version: ${currentversion}/" DESCRIPTION
+sed -i -- "s/^Date: .*/Date: $(date '+%Y-%m-%d')/" DESCRIPTION
+echo ">>  - updated DESCRIPTION"
+# remove leftover on macOS
+rm -f DESCRIPTION--
+# add to commit
+git add DESCRIPTION
+
+# set version number to NEWS file
+if [ -e "NEWS.md" ]; then
+  if [ "$currentpkg" = "your" ]; then
+    currentpkg=""
+  fi
+  sed -i -- "1s/.*/# ${currentpkg} ${currentversion}/" NEWS.md
+  echo ">>  - updated NEWS.md"
+  # remove leftover on macOS
+  rm -f NEWS.md--
+  # add to commit
+  git add NEWS.md
+else
+  echo ">>  - no NEWS.md found!"
+fi
+echo ">>  "

.github/workflows/check-pr.yaml

@@ -0,0 +1,81 @@
+# ==================================================================== #
+# TITLE                                                                #
+# Antimicrobial Resistance (AMR) Data Analysis for R                   #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# LICENCE                                                              #
+# (c) 2018-2022 Berends MS, Luz CF et al.                              #
+# Developed at the University of Groningen, the Netherlands, in        #
+# collaboration with non-profit organisations Certe Medical            #
+# Diagnostics & Advice, and University Medical Center Groningen.       # 
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+on:
+  pull_request:
+    # run in each PR in this repo
+    branches: '**'
+
+name: R-code-check-PR
+
+jobs:
+  R-code-check-PR:
+    # do not run if we are the authors - the other checks will already run
+    if: ${{ github.event.comment.author_association != 'MEMBER' && github.event.comment.author_association != 'OWNER' }}
+    
+    runs-on: ${{ matrix.config.os }}
+
+    continue-on-error: ${{ matrix.config.allowfail }}
+
+    name: ${{ matrix.config.os }} (R-${{ matrix.config.r }})
+
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - {os: macOS-latest,   r: 'devel',   allowfail: true}
+          - {os: macOS-latest,   r: 'release', allowfail: false}
+          - {os: ubuntu-latest,  r: 'devel',   allowfail: true}
+          - {os: ubuntu-latest,  r: 'release', allowfail: false}
+          - {os: windows-latest, r: 'devel',   allowfail: true}
+          - {os: windows-latest, r: 'release', allowfail: false}
+
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      R_KEEP_PKG_SOURCE: yes
+    
+    steps:
+      - uses: actions/checkout@v3
+
+      - uses: r-lib/actions/setup-pandoc@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          r-version: ${{ matrix.config.r }}
+          # use RStudio Package Manager to quickly install packages
+          use-public-rspm: true      
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::rcmdcheck
+          needs: check
+
+      - uses: r-lib/actions/check-r-package@v2
+        env:
+          _R_CHECK_LENGTH_1_CONDITION_: verbose
+          _R_CHECK_LENGTH_1_LOGIC2_: verbose
+          # during 'R CMD check', R_LIBS_USER will be overwritten, so:
+          R_LIBS_USER_GH_ACTIONS: ${{ env.R_LIBS_USER }}
+          R_RUN_TINYTEST: true

.github/workflows/check.yaml

@@ -25,12 +25,8 @@
 
 on:
   push:
-    branches:
-      - development
-      - main
-  pull_request:
-    branches:
-      - main
+     # run after a git push on any branch in this repo
+    branches: '**'
   schedule:
     # run a schedule everyday at 1 AM.
     # this is to check that all dependencies are still available (see R/zzz.R)
@@ -52,42 +48,33 @@ jobs:
         config:
           # test all systems against all released versions of R >= 3.0, we support them all!
           - {os: macOS-latest,   r: 'devel',   allowfail: true}
+          - {os: macOS-latest,   r: '4.2',     allowfail: false}
           - {os: macOS-latest,   r: '4.1',     allowfail: false}
           - {os: macOS-latest,   r: '4.0',     allowfail: false}
           - {os: macOS-latest,   r: '3.6',     allowfail: false}
-          - {os: macOS-latest,   r: '3.5',     allowfail: false}
-          - {os: macOS-latest,   r: '3.4',     allowfail: false}
-          - {os: macOS-latest,   r: '3.3',     allowfail: false}
-          - {os: macOS-latest,   r: '3.2',     allowfail: false}
-          # - {os: macOS-latest,   r: '3.1',     allowfail: true}
-          # - {os: macOS-latest,   r: '3.0',     allowfail: true}
-          - {os: ubuntu-20.04,   r: 'devel',   allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '4.1',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '4.0',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.6',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.5',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.4',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.3',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.2',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.1',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
-          - {os: ubuntu-20.04,   r: '3.0',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
+          - {os: ubuntu-22.04,   r: 'devel',   allowfail: true,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
+          - {os: ubuntu-22.04,   r: '4.2',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
+          - {os: ubuntu-22.04,   r: '4.1',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
+          - {os: ubuntu-22.04,   r: '4.0',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
+          - {os: ubuntu-22.04,   r: '3.6',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
+          - {os: ubuntu-22.04,   r: '3.5',     allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
+          - {os: ubuntu-22.04,   r: '3.4',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
+          - {os: ubuntu-22.04,   r: '3.3',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
+          - {os: ubuntu-22.04,   r: '3.2',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
+          - {os: ubuntu-22.04,   r: '3.1',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
+          - {os: ubuntu-22.04,   r: '3.0',     allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
           - {os: windows-latest, r: 'devel',   allowfail: true}
+          - {os: windows-latest, r: '4.2',     allowfail: false}
           - {os: windows-latest, r: '4.1',     allowfail: false}
           - {os: windows-latest, r: '4.0',     allowfail: false}
           - {os: windows-latest, r: '3.6',     allowfail: false}
-          - {os: windows-latest, r: '3.5',     allowfail: false}
-          - {os: windows-latest, r: '3.4',     allowfail: false}
-          - {os: windows-latest, r: '3.3',     allowfail: false}
-          # - {os: windows-latest, r: '3.2',     allowfail: true}
-          # - {os: windows-latest, r: '3.1',     allowfail: true}
-          # - {os: windows-latest, r: '3.0',     allowfail: true}
     env:
       R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
       RSPM: ${{ matrix.config.rspm }}
       R_REPOSITORIES: "https://cran.rstudio.com"
     
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
 
       - uses: r-lib/actions/setup-r@v2
         with:
@@ -99,9 +86,9 @@ jobs:
         if: runner.os == 'Linux'
         # update the below with sysreqs::sysreqs("DESCRIPTION") and check the "DEB" entries (for Ubuntu).
         # we don't want to depend on the sysreqs pkg here, as it requires quite a recent R version
-        # as of May 2021: https://sysreqs.r-hub.io/pkg/AMR,R,cleaner,curl,dplyr,ggplot2,ggtext,knitr,microbenchmark,pillar,readxl,rmarkdown,rstudioapi,rvest,skimr,tidyr,tinytest,xml2,backports,crayon,rlang,vctrs,evaluate,highr,markdown,stringr,yaml,xfun,cli,ellipsis,fansi,lifecycle,utf8,glue,mime,magrittr,stringi,generics,R6,tibble,tidyselect,pkgconfig,purrr,digest,gtable,isoband,MASS,mgcv,scales,withr,nlme,Matrix,farver,labeling,munsell,RColorBrewer,viridisLite,lattice,colorspace,gridtext,Rcpp,RCurl,png,jpeg,bitops,cellranger,progress,rematch,hms,prettyunits,htmltools,jsonlite,tinytex,base64enc,httr,selectr,openssl,askpass,sys,repr,cpp11
+        # as of May 2021: https://sysreqs.r-hub.io/pkg/AMR,R,cleaner,curl,dplyr,ggplot2,knitr,microbenchmark,pillar,readxl,rmarkdown,rstudioapi,rvest,skimr,tidyr,tinytest,xml2,backports,crayon,rlang,vctrs,evaluate,highr,markdown,stringr,yaml,xfun,cli,ellipsis,fansi,lifecycle,utf8,glue,mime,magrittr,stringi,generics,R6,tibble,tidyselect,pkgconfig,purrr,digest,gtable,isoband,MASS,mgcv,scales,withr,nlme,Matrix,farver,labeling,munsell,RColorBrewer,viridisLite,lattice,colorspace,gridtext,Rcpp,RCurl,png,jpeg,bitops,cellranger,progress,rematch,hms,prettyunits,htmltools,jsonlite,tinytex,base64enc,httr,selectr,openssl,askpass,sys,repr,cpp11
         run: |
-          sudo apt install -y libssl-dev libxml2-dev libicu-dev libcurl4-openssl-dev libpng-dev
+          sudo apt install -y libssl-dev libxml2-dev libcurl4-openssl-dev
       
       - name: Restore cached R packages
         # this step will add the step 'Post Restore cached R packages' on a succesful run
@@ -110,10 +97,9 @@ jobs:
           path: ${{ env.R_LIBS_USER }}
           key: ${{ matrix.config.os }}-r-${{ matrix.config.r }}-v4
 
-      - name: Unpack AMR and install R dependencies
+      - name: Install R dependencies
         if: always()
         run: |
-          tar -xf data-raw/AMR_latest.tar.gz
           Rscript -e "source('data-raw/_install_deps.R')"
         shell: bash
         
@@ -126,33 +112,42 @@ jobs:
         shell: Rscript {0}
         
       - name: Remove vignettes on R without knitr support
-        if: matrix.config.r == '3.0' || matrix.config.r == '3.1' || matrix.config.r == '3.2'
-        # writing to DESCRIPTION2 and then moving to DESCRIPTION is required for R < 3.3 as writeLines() cannot overwrite
+        if: matrix.config.r == '3.0' || matrix.config.r == '3.1' || matrix.config.r == '3.2' || matrix.config.r == '3.3'
+        # writing to DESCRIPTION2 and then moving to DESCRIPTION is required for R <= 3.3 as writeLines() cannot overwrite
         run: |
-          rm -rf AMR/vignettes
-          Rscript -e "writeLines(readLines('AMR/DESCRIPTION')[!grepl('VignetteBuilder', readLines('AMR/DESCRIPTION'))], 'AMR/DESCRIPTION2')"
-          rm AMR/DESCRIPTION
-          mv AMR/DESCRIPTION2 AMR/DESCRIPTION
+          rm -rf vignettes
+          Rscript -e "writeLines(readLines('DESCRIPTION')[!grepl('VignetteBuilder', readLines('DESCRIPTION'))], 'DESCRIPTION2')"
+          rm DESCRIPTION
+          mv DESCRIPTION2 DESCRIPTION
         shell: bash
         
       - name: Run R CMD check
         if: always()
         env:
+          # see https://rstudio.github.io/r-manuals/r-ints/Tools.html for an overview
           _R_CHECK_CRAN_INCOMING_: false
-          _R_CHECK_FORCE_SUGGESTS_: false
           _R_CHECK_DEPENDS_ONLY_: true
           _R_CHECK_LENGTH_1_CONDITION_: verbose
           _R_CHECK_LENGTH_1_LOGIC2_: verbose
+          # no check for old R versions - these packages require higher R versions
+          _R_CHECK_RD_XREFS_: ${{ matrix.config.r != '3.0' && matrix.config.r != '3.1' && matrix.config.r != '3.2' && matrix.config.r != '3.3' && matrix.config.r != '3.4' }}
+          _R_CHECK_FORCE_SUGGESTS_: false
+          R_CHECK_CONSTANTS: 5
+          R_JIT_STRATEGY: 3
           # during 'R CMD check', R_LIBS_USER will be overwritten, so:
           R_LIBS_USER_GH_ACTIONS: ${{ env.R_LIBS_USER }}
+          # this is a required value to run the unit tests:
           R_RUN_TINYTEST: true
         run: |
-          R CMD check --no-manual --run-donttest --run-dontrun AMR
+          cd ..
+          R CMD build AMR
+          R CMD check --as-cran --no-manual --run-donttest --run-dontrun AMR_*.tar.gz
         shell: bash
 
       - name: Show unit tests output
         if: always()
         run: |
+          cd ../AMR.Rcheck
           find . -name 'tinytest.Rout*' -exec cat '{}' \; || true
         shell: bash
 
@@ -161,4 +156,4 @@ jobs:
         uses: actions/upload-artifact@v2
         with:
           name: artifacts-${{ matrix.config.os }}-r${{ matrix.config.r }}
-          path: AMR.Rcheck
+          path: ${{ github.workspace }}/AMR.Rcheck

.github/workflows/codecovr.yaml

@@ -25,65 +25,38 @@
 
 on:
   push:
-    branches:
-      - development
-      - main
+    branches: '**'
   pull_request:
-    branches:
-      - main
+    branches: '**'
 
 name: code-coverage
 
 jobs:
   code-coverage:
-    runs-on: macOS-latest
+    runs-on: ubuntu-latest
     env:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      CODECOV_TOKEN: ${{secrets.CODECOV_TOKEN}}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
+
+      - uses: r-lib/actions/setup-pandoc@v2
 
       - uses: r-lib/actions/setup-r@v2
         with:
           r-version: release
-      
-      - uses: r-lib/actions/setup-pandoc@v2
-        # with:
-        #   pandoc-version: '2.7.3' # The pandoc version to download (if necessary) and use.
+          # use RStudio Package Manager to quickly install packages
+          use-public-rspm: true
 
-      - name: Query dependencies
-        # this will change once a week, so it will cache dependency updates
-        run: |
-          writeLines(paste(format(Sys.Date(), "week %V %Y"), sprintf("R-%i.%i", getRversion()$major, getRversion()$minor)), ".github/week-R-version")
-        shell: Rscript {0}
-        
-      - name: Restore cached R packages
-        # this step will add the step 'Post Restore cached R packages' on a succesful run
-        uses: actions/cache@v2
+      - uses: r-lib/actions/setup-r-dependencies@v2
         with:
-          path: ${{ env.R_LIBS_USER }}
-          key: ${{ matrix.config.os }}-${{ hashFiles('.github/week-R-version') }}-v4
-
-      - name: Unpack AMR and install R dependencies
-        run: |
-          tar -xf data-raw/AMR_latest.tar.gz
-          Rscript -e "source('data-raw/_install_deps.R')"
-        shell: bash
-        
-      - name: Show session info
-        run: |
-          options(width = 100)
-          utils::sessionInfo()
-          as.data.frame(utils::installed.packages())[, "Version", drop = FALSE]
-        shell: Rscript {0}
+          extra-packages: any::covr
 
       - name: Test coverage
         env:
-          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+          R_LIBS_USER_GH_ACTIONS: ${{ env.R_LIBS_USER }}
           R_RUN_TINYTEST: true
         run: |
-          install.packages("covr", repos = "https://cran.rstudio.com/")
-          library(AMR)
-          library(tinytest)
           x <- covr::codecov(line_exclusions = list("R/atc_online.R", "R/mo_source.R", "R/translate.R", "R/resistance_predict.R", "R/aa_helper_functions.R", "R/aa_helper_pm_functions.R", "R/zzz.R"))
           print(x)
         shell: Rscript {0}

.github/workflows/lintr.yaml

@@ -25,45 +25,31 @@
 
 on:
   push:
-    branches:
-      - development
-      - main
+    branches: '**'
   pull_request:
-    branches:
-      - main
+    branches: '**'
 
 name: lintr
 
 jobs:
   lintr:
-    runs-on: macOS-latest
+    runs-on: ubuntu-latest
     env:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
+
+      - uses: r-lib/actions/setup-pandoc@v2
 
       - uses: r-lib/actions/setup-r@v2
-
-      - name: Query dependencies
-        run: |
-          install.packages('remotes')
-          saveRDS(remotes::dev_package_deps(dependencies = TRUE), ".github/depends.Rds", version = 2)
-          writeLines(sprintf("R-%i.%i", getRversion()$major, getRversion()$minor), ".github/R-version")
-        shell: Rscript {0}
-
-      - name: Cache R packages
-        uses: actions/cache@v2
         with:
-          path: ${{ env.R_LIBS_USER }}
-          key: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-${{ hashFiles('.github/depends.Rds') }}
-          restore-keys: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-
+          r-version: release
+          # use RStudio Package Manager to quickly install packages
+          use-public-rspm: true
 
-      - name: Install dependencies
-        run: |
-          install.packages(c("remotes"))
-          remotes::install_deps(dependencies = TRUE)
-          remotes::install_cran("lintr")
-        shell: Rscript {0}
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::lintr
 
       - name: Lint
         run: lintr::lint_package(linters = lintr::with_defaults(line_length_linter = NULL, trailing_whitespace_linter = NULL, object_name_linter = NULL, cyclocomp_linter = NULL, object_length_linter = lintr::object_length_linter(length = 50L)), exclusions = list("R/aa_helper_pm_functions.R"))

.github/workflows/website.yaml

@@ -0,0 +1,60 @@
+# ==================================================================== #
+# TITLE                                                                #
+# Antimicrobial Resistance (AMR) Data Analysis for R                   #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# LICENCE                                                              #
+# (c) 2018-2022 Berends MS, Luz CF et al.                              #
+# Developed at the University of Groningen, the Netherlands, in        #
+# collaboration with non-profit organisations Certe Medical            #
+# Diagnostics & Advice, and University Medical Center Groningen.       # 
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+# Create a website from the R documentation using pkgdown
+# Git commit and push to the 'gh-pages' branch
+
+on:
+  push:
+    # only on main
+    branches: 'main'
+
+name: Update website
+
+jobs:
+  update-website:
+    runs-on: ubuntu-latest
+    continue-on-error: true
+    steps:
+      # Set up R (current stable version) and developer tools
+      - uses: actions/checkout@v3
+      - uses: r-lib/actions/setup-pandoc@v2
+      - name: Set up R
+        uses: r-lib/actions/setup-r@v2
+        with:
+            r-version: "release"
+            # use RStudio Package Manager (RSPM) to quickly install packages
+            use-public-rspm: true
+      - name: Set up R dependencies
+        uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::pkgdown
+
+      # Send updates to repo using GH Actions bot
+      - name: Create website in separate branch
+        run: |
+          git config user.name "github-actions"
+          git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
+          Rscript -e 'pkgdown::deploy_to_branch(new_process = FALSE, clean = TRUE, install = TRUE, branch = "gh-pages")'

.gitignore

@@ -5,7 +5,6 @@ doc
 .Rhistory
 .RData
 .Ruserdata
-AMR.Rproj
 tests/testthat/Rplots.pdf
 inst/doc
 /src/*.o

AMR.Rproj

@@ -0,0 +1,25 @@
+Version: 1.0
+
+RestoreWorkspace: No
+SaveWorkspace: No
+AlwaysSaveHistory: Yes
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
+
+AutoAppendNewline: Yes
+LineEndingConversion: Posix
+
+BuildType: Package
+PackageUseDevtools: Yes
+PackageInstallArgs: --no-multiarch --with-keep.source
+PackageBuildArgs: --no-build-vignettes
+PackageCheckArgs: --no-build-vignettes --as-cran
+PackageRoxygenize: rd,collate,namespace
+
+UseNativePipeOperator: No

DESCRIPTION

@@ -1,82 +1,41 @@
 Package: AMR
-Version: 1.8.1
-Date: 2022-03-17
+Version: 1.8.1.9046
+Date: 2022-08-29
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)
     data analysis and to work with microbial and antimicrobial properties by
     using evidence-based methods and reliable reference data such as LPSN
     <doi:10.1099/ijsem.0.004332>.
 Authors@R: c(
-  person(given = c("Matthijs", "S."),
-         family = "Berends", 
-         email = "m.berends@certe.nl",
-         role = c("aut", "cre"),
-         comment = c(ORCID = "0000-0001-7620-1800")),
-  person(given = c("Christian", "F."),
-         family = "Luz", 
-         role = c("aut", "ctb"),
-         comment = c(ORCID = "0000-0001-5809-5995")),
-  person(given = "Dennis",
-         family = "Souverein", 
-         role = c("aut", "ctb"),
-         comment = c(ORCID = "0000-0003-0455-0336")),
-  person(given = c("Erwin", "E.", "A."),
-         family = "Hassing", 
-         role = c("aut", "ctb")),
-  person(given = c("Casper", "J."),
-         family = "Albers", 
-         role = "ths",
-         comment = c(ORCID = "0000-0002-9213-6743")),
-  person(given = c("Judith", "M."),
-         family = "Fonville", 
-         role = "ctb"),
-  person(given = c("Alex", "W."),
-         family = "Friedrich", 
-         role = "ths",
-         comment = c(ORCID = "0000-0003-4881-038X")),
-  person(given = "Corinna",
-         family = "Glasner", 
-         role = "ths",
-         comment = c(ORCID = "0000-0003-1241-1328")),
-  person(given = c("Eric", "H.", "L.", "C.", "M."),
-         family = "Hazenberg", 
-         role = "ctb"),
-  person(given = "Gwen",
-         family = "Knight", 
-         role = "ctb",
-         comment = c(ORCID = "0000-0002-7263-9896")),
-  person(given = "Annick",
-         family = "Lenglet", 
-         role = "ctb",
-         comment = c(ORCID = "0000-0003-2013-8405")),
-  person(given = c("Bart", "C."),
-         family = "Meijer", 
-         role = "ctb"),
-  person(given = "Sofia",
-         family = "Ny",
-         role = "ctb",
-         comment = c(ORCID = "0000-0002-2017-1363")),
-  person(given = c("Rogier", "P."),
-         family = "Schade", 
-         role = "ctb"),
-  person(given = c("Bhanu", "N.", "M."),
-         family = "Sinha", 
-         role = "ths",
-         comment = c(ORCID = "0000-0003-1634-0010")),
-  person(given = "Anthony", 
-         family = "Underwood", 
-         role = "ctb",
-         comment = c(ORCID = "0000-0002-8547-4277")))
+ person(family = "Berends",     c("Matthijs", "S."), role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7620-1800"), email = "m.berends@certe.nl"),
+ person(family = "Luz",         c("Christian", "F."), role = c("aut", "ctb"), comment = c(ORCID = "0000-0001-5809-5995")),
+ person(family = "Souverein",   c("Dennis"), role = c("aut", "ctb"), comment = c(ORCID = "0000-0003-0455-0336")),
+ person(family = "Hassing",     c("Erwin", "E.", "A."), role = c("aut", "ctb")),
+ person(family = "Albers",      c("Casper", "J."), role = "ths", comment = c(ORCID = "0000-0002-9213-6743")),
+ person(family = "Dutey-Magni", c("Peter"), role = "ctb", comment = c(ORCID = "0000-0002-8942-9836")),
+ person(family = "Fonville",    c("Judith", "M"), role = "ctb"),
+ person(family = "Friedrich",   c("Alex", "W."), role = "ths", comment = c(ORCID = "0000-0003-4881-038X")),
+ person(family = "Glasner",     c("Corinna"), role = "ths", comment = c(ORCID = "0000-0003-1241-1328")),
+ person(family = "Hazenberg",   c("Eric", "H.", "L.", "C.", "M."), role = "ctb"),
+ person(family = "Knight",      c("Gwen"), role = "ctb", comment = c(ORCID = "0000-0002-7263-9896")),
+ person(family = "Lenglet",     c("Annick"), role = "ctb", comment = c(ORCID = "0000-0003-2013-8405")),
+ person(family = "Meijer",      c("Bart", "C."), role = "ctb"),
+ person(family = "Mykhailenko", c("Dmytro"), role = "ctb"),
+ person(family = "Mymrikov",    c("Anton"), role = "ctb"),
+ person(family = "Ny",          c("Sofia"), role = "ctb", comment = c(ORCID = "0000-0002-2017-1363")),
+ person(family = "Schade",      c("Rogier", "P."), role = "ctb"),
+ person(family = "Sinha",       c("Bhanu", "N.", "M."), role = "ths", comment = c(ORCID = "0000-0003-1634-0010")),
+ person(family = "Underwood",   c("Anthony"), role = "ctb", comment = c(ORCID = "0000-0002-8547-4277")))
 Depends: R (>= 3.0.0)
 Enhances:
   cleaner,
   skimr,
   ggplot2,
+  tibble,
   tidyselect
 Suggests: 
   curl,
   dplyr,
-  ggtext,
   knitr,
   progress,
   readxl,
@@ -90,5 +49,5 @@ BugReports: https://github.com/msberends/AMR/issues
 License: GPL-2 | file LICENSE
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.1
 Roxygen: list(markdown = TRUE)

NAMESPACE

@@ -50,7 +50,6 @@ S3method(any,mic)
 S3method(as.data.frame,ab)
 S3method(as.data.frame,mo)
 S3method(as.double,mic)
-S3method(as.integer,mic)
 S3method(as.list,custom_eucast_rules)
 S3method(as.list,custom_mdro_guideline)
 S3method(as.matrix,mic)
@@ -310,6 +309,7 @@ export(quinolones)
 export(random_disk)
 export(random_mic)
 export(random_rsi)
+export(reset_AMR_locale)
 export(resistance)
 export(resistance_predict)
 export(right_join_microorganisms)
@@ -318,6 +318,7 @@ export(rsi_predict)
 export(scale_rsi_colours)
 export(scale_y_percent)
 export(semi_join_microorganisms)
+export(set_AMR_locale)
 export(set_ab_names)
 export(set_mo_source)
 export(skewness)
@@ -325,6 +326,7 @@ export(streptogramins)
 export(susceptibility)
 export(tetracyclines)
 export(theme_rsi)
+export(translate_AMR)
 export(trimethoprims)
 export(ureidopenicillins)
 importFrom(graphics,arrows)

NEWS.md

@@ -1,8 +1,37 @@
+# AMR 1.8.1.9046
+
+### New
+* EUCAST 2022 and CLSI 2022 guidelines have been added for `as.rsi()`. EUCAST 2022 is now the new default guideline for all MIC and disks diffusion interpretations.
+* Support for `data.frame`-enhancing R packages, more specifically: `data.table`, `tibble`, and `tsibble`. AMR package functions that have a data set as output (such as `rsi_df()` and `bug_drug_combinations()`), will now return the same data type as the input. Furthermore, all our data sets are now in `tibble` format.
+* Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info [in this article on our website](https://msberends.github.io/AMR/articles/datasets.html).
+* Support for the following languages: Chinese, Greek, Japanese, Polish, Turkish and Ukrainian. We are very grateful for the valuable input by our colleagues from other countries. The `AMR` package is now available in 16 languages.
+
+### Changed
+* Fix for using `as.rsi()` on certain EUCAST breakpoints for MIC values
+* Fix for using `as.rsi()` on `NA` values (e.g. `as.rsi(as.disk(NA), ...)`)
+* Removed `as.integer()` for MIC values, since MIC are not integer values and running `table()` on MIC values  consequently failed for not being able to retrieve the level position (as that's how normally `as.integer()` on `factor`s work)
+* `droplevels()` on MIC will now return a common `factor` at default and will lose the `<mic>` class. Use `droplevels(..., as.mic = TRUE)` to keep the `<mic>` class.
+* Small fix for using `ab_from_text()`
+* Fixes for reading in text files using `set_mo_source()`, which now also allows the source file to contain valid taxonomic names instead of only valid microorganism ID of this package
+* Using any `random_*()` function (such as `random_mic()`) is now possible by directly calling the package without loading it first: `AMR::random_mic(10)`
+* Added *Toxoplasma gondii* (`P_TXPL_GOND`) to the `microorganisms` data set, together with its genus, family, and order
+* Changed value in column `prevalence` of the `microorganisms` data set from 3 to 2 for these genera: *Acholeplasma*, *Alistipes*, *Alloprevotella*, *Bergeyella*, *Borrelia*, *Brachyspira*, *Butyricimonas*, *Cetobacterium*, *Chlamydia*, *Chlamydophila*, *Deinococcus*, *Dysgonomonas*, *Elizabethkingia*, *Empedobacter*, *Haloarcula*, *Halobacterium*, *Halococcus*, *Myroides*, *Odoribacter*, *Ornithobacterium*, *Parabacteroides*, *Pedobacter*, *Phocaeicola*, *Porphyromonas*, *Riemerella*, *Sphingobacterium*, *Streptobacillus*, *Tenacibaculum*, *Terrimonas*, *Victivallis*, *Wautersiella*, *Weeksella*
+* Fix for using the form `df[carbapenems() == "R", ]` using the latest `vctrs` package
+* Fix for using `info = FALSE` in `mdro()`
+* All data sets in this package are now exported as `tibble`, instead of base R `data.frame`s. Older R versions are still supported.
+* Automatic language determination will give a note once a session
+* For all interpretation guidelines using `as.rsi()` on amoxicillin, the rules for ampicillin will be used if amoxicillin rules are not available
+* Fix for using `ab_atc()` on non-existing ATC codes
+
+### Other
+* New website to make use of the new Bootstrap 5 and pkgdown v2.0. The website now contains results for all examples and will be automatically regenerated with every change to our repository, using GitHub Actions
+* Added Peter Dutey-Magni and Anton Mymrikov as contributors, to thank them for their valuable input
+* Set up Git Large File Storage (Git LFS) for the large SAS and SPSS file formats
+* All R and Rmd files in this project are now styled using the `styler` package
+
+
 # `AMR` 1.8.1
 
-
-All functions in this package are considered to be stable. Updates to the AMR interpretation rules (such as by EUCAST and CLSI), the microbial taxonomy, and the antibiotic dosages will all be updated every 6 to 12 months.
-
 ### Changed
 * Fix for using `as.rsi()` on values containing capped values (such as `>=`), sometimes leading to `NA`
 * Support for antibiotic interpretations of the MIPS laboratory system: `"U"` for S ('susceptible urine'), `"D"` for I ('susceptible dose-dependent')
@@ -187,7 +216,7 @@ All functions in this package are considered to be stable. Updates to the AMR in
 * Functions `oxazolidinones()` (an antibiotic selector function) and `filter_oxazolidinones()` (an antibiotic filter function) to select/filter on e.g. linezolid and tedizolid
   ```r
   library(dplyr)
-  x <- example_isolates %>% select(date, hospital_id, oxazolidinones())
+  x <- example_isolates %>% select(date, ward, oxazolidinones())
   #> Selecting oxazolidinones: column 'LNZ' (linezolid)
   
   x <- example_isolates %>% filter_oxazolidinones()
@@ -272,7 +301,7 @@ All functions in this package are considered to be stable. Updates to the AMR in
   ```r
   library(dplyr)
   example_isolates %>%
-    group_by(patient_id, hospital_id) %>%
+    group_by(patient_id, ward) %>%
     filter(is_new_episode(date, episode_days = 60))
   ```
 * Functions `mo_is_gram_negative()` and `mo_is_gram_positive()` as wrappers around `mo_gramstain()`. They always return `TRUE` or `FALSE` (except when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
@@ -886,7 +915,7 @@ This software is now out of beta and considered stable. Nonetheless, this packag
       boxplot()
     # grouped boxplots:
     septic_patients %>% 
-      group_by(hospital_id) %>% 
+      group_by(ward) %>% 
       freq(age) %>%
       boxplot()
     ```
@@ -1139,13 +1168,13 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
   * Support for grouping variables, test with:
     ```r
     septic_patients %>% 
-      group_by(hospital_id) %>% 
+      group_by(ward) %>% 
       freq(gender)
     ```
   * Support for (un)selecting columns:
     ```r
     septic_patients %>% 
-      freq(hospital_id) %>% 
+      freq(ward) %>% 
       select(-count, -cum_count) # only get item, percent, cum_percent
     ```
   * Check for `hms::is.hms`

R/aa_globals.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -24,34 +24,50 @@
 # ==================================================================== #
 
 # add new version numbers here, and add the rules themselves to "data-raw/eucast_rules.tsv" and rsi_translation
-# (sourcing "data-raw/_internals.R" will process the TSV file)
-EUCAST_VERSION_BREAKPOINTS <- list("11.0" = list(version_txt = "v11.0",
-                                                 year = 2021, 
-                                                 title = "'EUCAST Clinical Breakpoint Tables'",
-                                                 url = "https://www.eucast.org/clinical_breakpoints/"),
-                                   "10.0" = list(version_txt = "v10.0",
-                                                 year = 2020, 
-                                                 title = "'EUCAST Clinical Breakpoint Tables'",
-                                                 url = "https://www.eucast.org/ast_of_bacteria/previous_versions_of_documents/"))
-EUCAST_VERSION_EXPERT_RULES <- list("3.1" = list(version_txt = "v3.1",
-                                                 year = 2016, 
-                                                 title = "'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes'",
-                                                 url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"),
-                                    "3.2" = list(version_txt = "v3.2",
-                                                 year = 2020, 
-                                                 title = "'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes'",
-                                                 url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"),
-                                    "3.3" = list(version_txt = "v3.3",
-                                                 year = 2021, 
-                                                 title = "'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes'",
-                                                 url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"))
+# (sourcing "data-raw/_pre_commit_hook.R" will process the TSV file)
+EUCAST_VERSION_BREAKPOINTS <- list(
+  "11.0" = list(
+    version_txt = "v11.0",
+    year = 2021,
+    title = "'EUCAST Clinical Breakpoint Tables'",
+    url = "https://www.eucast.org/clinical_breakpoints/"
+  ),
+  "10.0" = list(
+    version_txt = "v10.0",
+    year = 2020,
+    title = "'EUCAST Clinical Breakpoint Tables'",
+    url = "https://www.eucast.org/ast_of_bacteria/previous_versions_of_documents/"
+  )
+)
+EUCAST_VERSION_EXPERT_RULES <- list(
+  "3.1" = list(
+    version_txt = "v3.1",
+    year = 2016,
+    title = "'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes'",
+    url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"
+  ),
+  "3.2" = list(
+    version_txt = "v3.2",
+    year = 2020,
+    title = "'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes'",
+    url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"
+  ),
+  "3.3" = list(
+    version_txt = "v3.3",
+    year = 2021,
+    title = "'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes'",
+    url = "https://www.eucast.org/expert_rules_and_expected_phenotypes/"
+  )
+)
 
-SNOMED_VERSION <- list(title = "Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS)",
-                       current_source = "US Edition of SNOMED CT from 1 September 2020",
-                       current_version = 12,
-                       current_oid = "2.16.840.1.114222.4.11.1009",
-                       value_set_name = "Microorganism",
-                       url = "https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009")
+SNOMED_VERSION <- list(
+  title = "Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS)",
+  current_source = "US Edition of SNOMED CT from 1 September 2020",
+  current_version = 12,
+  current_oid = "2.16.840.1.114222.4.11.1009",
+  value_set_name = "Microorganism",
+  url = "https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009"
+)
 
 CATALOGUE_OF_LIFE <- list(
   year = 2019,
@@ -61,73 +77,75 @@ CATALOGUE_OF_LIFE <- list(
   yearmonth_LPSN = "5 October 2021"
 )
 
-globalVariables(c(".rowid",
-                  "ab",
-                  "ab_txt",
-                  "affect_ab_name",
-                  "affect_mo_name",
-                  "angle",
-                  "antibiotic",
-                  "antibiotics",
-                  "atc_group1",
-                  "atc_group2",
-                  "base_ab",
-                  "code",
-                  "cols",
-                  "count",
-                  "data",
-                  "disk",
-                  "dosage",
-                  "dose",
-                  "dose_times",
-                  "fullname",
-                  "fullname_lower",
-                  "g_species",
-                  "genus",
-                  "gr",
-                  "group",
-                  "guideline",
-                  "hjust",
-                  "input",
-                  "intrinsic_resistant",
-                  "isolates",
-                  "lang",
-                  "language",
-                  "lookup",
-                  "method",
-                  "mic",
-                  "mic ",
-                  "microorganism",
-                  "microorganisms",
-                  "microorganisms.codes",
-                  "microorganisms.old",
-                  "mo",
-                  "name",
-                  "new",
-                  "observations",
-                  "old",
-                  "old_name",
-                  "pattern",
-                  "R",
-                  "rank_index",
-                  "reference.rule",
-                  "reference.rule_group",
-                  "reference.version",
-                  "rowid",
-                  "rsi",
-                  "rsi_translation",
-                  "rule_group",
-                  "rule_name",
-                  "se_max",
-                  "se_min",
-                  "species",
-                  "species_id",
-                  "total",
-                  "txt",
-                  "type",
-                  "value",
-                  "varname",
-                  "xvar",
-                  "y",
-                  "year",
-                  "yvar"))
+globalVariables(c(
+  ".rowid",
+  "ab",
+  "ab_txt",
+  "affect_ab_name",
+  "affect_mo_name",
+  "angle",
+  "antibiotic",
+  "antibiotics",
+  "atc_group1",
+  "atc_group2",
+  "base_ab",
+  "code",
+  "cols",
+  "count",
+  "data",
+  "disk",
+  "dosage",
+  "dose",
+  "dose_times",
+  "fullname",
+  "fullname_lower",
+  "g_species",
+  "genus",
+  "gr",
+  "group",
+  "guideline",
+  "hjust",
+  "input",
+  "intrinsic_resistant",
+  "isolates",
+  "lang",
+  "language",
+  "lookup",
+  "method",
+  "mic",
+  "mic ",
+  "microorganism",
+  "microorganisms",
+  "microorganisms.codes",
+  "microorganisms.old",
+  "mo",
+  "name",
+  "new",
+  "observations",
+  "old",
+  "old_name",
+  "pattern",
+  "R",
+  "rank_index",
+  "reference.rule",
+  "reference.rule_group",
+  "reference.version",
+  "rowid",
+  "rsi",
+  "rsi_translation",
+  "rule_group",
+  "rule_name",
+  "se_max",
+  "se_min",
+  "species",
+  "species_id",
+  "total",
+  "txt",
+  "type",
+  "value",
+  "varname",
+  "xvar",
+  "y",
+  "year",
+  "yvar"
+))

R/aa_helper_pm_functions.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -34,10 +34,10 @@
 #
 # All functions are prefixed with 'pm_' to make it obvious that they are dplyr substitutes.
 #
-# All code below was released under MIT license, that permits 'free of charge, to any person obtaining a 
+# All code below was released under MIT license, that permits 'free of charge, to any person obtaining a
 # copy of the software and associated documentation files (the "Software"), to deal in the Software
 # without restriction, including without limitation the rights to use, copy, modify, merge, publish,
-# distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software 
+# distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software
 # is furnished to do so', given that a copyright notice is given in the software.
 #
 # Copyright notice on 19 September 2020, the day this code was downloaded, as found on
@@ -206,7 +206,9 @@ pm_distinct <- function(.data, ...) {
 }
 
 pm_distinct.default <- function(.data, ..., .keep_all = FALSE) {
-  if (ncol(.data) == 0L) return(.data[1, ])
+  if (ncol(.data) == 0L) {
+    return(.data[1, ])
+  }
   cols <- pm_deparse_dots(...)
   col_names <- names(cols)
   col_len <- length(cols)
@@ -336,7 +338,9 @@ pm_print.grouped_data <- function(x, ..., digits = NULL, quote = FALSE, right =
 }
 
 pm_group_data <- function(.data) {
-  if (!pm_has_groups(.data)) return(data.frame(.rows = I(list(seq_len(nrow(.data))))))
+  if (!pm_has_groups(.data)) {
+    return(data.frame(.rows = I(list(seq_len(nrow(.data))))))
+  }
   pm_groups <- pm_get_groups(.data)
   pm_group_data_worker(.data, pm_groups)
 }
@@ -360,7 +364,9 @@ pm_group_rows <- function(.data) {
 }
 
 pm_group_indices <- function(.data) {
-  if (!pm_has_groups(.data)) return(rep(1L, nrow(.data)))
+  if (!pm_has_groups(.data)) {
+    return(rep(1L, nrow(.data)))
+  }
   pm_groups <- pm_get_groups(.data)
   res <- unique(.data[, pm_groups, drop = FALSE])
   res <- res[do.call(order, lapply(pm_groups, function(x) res[, x])), , drop = FALSE]
@@ -417,7 +423,9 @@ pm_group_keys <- function(.data) {
   pm_context$setup(.data)
   res <- pm_context$.data[, pm_context$get_colnames() %in% pm_groups, drop = FALSE]
   res <- res[!duplicated(res), , drop = FALSE]
-  if (nrow(res) == 0L) return(res)
+  if (nrow(res) == 0L) {
+    return(res)
+  }
   class(res) <- "data.frame"
   res <- res[do.call(order, lapply(pm_groups, function(x) res[, x])), , drop = FALSE]
   rownames(res) <- NULL
@@ -509,7 +517,9 @@ pm_join_message <- function(by) {
 pm_lag <- function(x, pm_n = 1L, default = NA) {
   if (inherits(x, "ts")) stop("`x` must be a vector, not a `ts` object, do you want `stats::pm_lag()`?")
   if (length(pm_n) != 1L || !is.numeric(pm_n) || pm_n < 0L) stop("`pm_n` must be a nonnegative integer scalar")
-  if (pm_n == 0L) return(x)
+  if (pm_n == 0L) {
+    return(x)
+  }
   tryCatch(
     storage.mode(default) <- typeof(x),
     warning = function(w) {
@@ -525,7 +535,9 @@ pm_lag <- function(x, pm_n = 1L, default = NA) {
 
 pm_lead <- function(x, pm_n = 1L, default = NA) {
   if (length(pm_n) != 1L || !is.numeric(pm_n) || pm_n < 0L) stop("pm_n must be a nonnegative integer scalar")
-  if (pm_n == 0L) return(x)
+  if (pm_n == 0L) {
+    return(x)
+  }
   tryCatch(
     storage.mode(default) <- typeof(x),
     warning = function(w) {
@@ -565,7 +577,9 @@ pm_mutate.grouped_data <- function(.data, ...) {
 }
 pm_n_distinct <- function(..., na.rm = FALSE) {
   res <- c(...)
-  if (is.list(res)) return(nrow(unique(as.data.frame(res, stringsAsFactors = FALSE))))
+  if (is.list(res)) {
+    return(nrow(unique(as.data.frame(res, stringsAsFactors = FALSE))))
+  }
   if (isTRUE(na.rm)) res <- res[!is.na(res)]
   length(unique(res))
 }
@@ -593,7 +607,7 @@ pm_pull <- function(.data, var = -1) {
   } else if (var_deparse %in% col_names) {
     var <- var_deparse
   }
-  .data[, var]
+  .data[, var, drop = TRUE]
 }
 pm_set_names <- function(object = nm, nm) {
   names(object) <- nm
@@ -669,15 +683,16 @@ pm_rename_with <- function(.data, .fn, .cols = pm_everything(), ...) {
   .data
 }
 pm_replace_with <- function(x, i, val, arg_name) {
-  if (is.null(val)) return(x)
+  if (is.null(val)) {
+    return(x)
+  }
   pm_check_length(val, x, arg_name)
   pm_check_type(val, x, arg_name)
   pm_check_class(val, x, arg_name)
   i[is.na(i)] <- FALSE
   if (length(val) == 1L) {
     x[i] <- val
-  }
-  else {
+  } else {
     x[i] <- val[i]
   }
   x
@@ -686,7 +701,9 @@ pm_replace_with <- function(x, i, val, arg_name) {
 pm_check_length <- function(x, y, arg_name) {
   length_x <- length(x)
   length_y <- length(y)
-  if (all(length_x %in% c(1L, length_y))) return()
+  if (all(length_x %in% c(1L, length_y))) {
+    return()
+  }
   if (length_y == 1) {
     stop(arg_name, " must be length 1, not ", paste(length_x, sep = ", "))
   } else {
@@ -697,15 +714,21 @@ pm_check_length <- function(x, y, arg_name) {
 pm_check_type <- function(x, y, arg_name) {
   x_type <- typeof(x)
   y_type <- typeof(y)
-  if (identical(x_type, y_type)) return()
+  if (identical(x_type, y_type)) {
+    return()
+  }
   stop(arg_name, " must be `", y_type, "`, not `", x_type, "`")
 }
 
 pm_check_class <- function(x, y, arg_name) {
-  if (!is.object(x)) return()
+  if (!is.object(x)) {
+    return()
+  }
   exp_classes <- class(y)
   out_classes <- class(x)
-  if (identical(out_classes, exp_classes)) return()
+  if (identical(out_classes, exp_classes)) {
+    return()
+  }
   stop(arg_name, " must have class `", exp_classes, "`, not class `", out_classes, "`")
 }
 pm_rownames_to_column <- function(.data, var = "rowname") {
@@ -827,8 +850,7 @@ pm_select_positions <- function(.data, ..., .group_pos = FALSE) {
 
 pm_eval_expr <- function(x) {
   type <- typeof(x)
-  switch(
-    type,
+  switch(type,
     "integer" = x,
     "double" = as.integer(x),
     "character" = pm_select_char(x),
@@ -864,8 +886,7 @@ pm_select_symbol <- function(expr) {
 
 pm_eval_call <- function(x) {
   type <- as.character(x[[1]])
-  switch(
-    type,
+  switch(type,
     `:` = pm_select_seq(x),
     `!` = pm_select_negate(x),
     `-` = pm_select_minus(x),
@@ -1029,7 +1050,7 @@ pm_is_wholenumber <- function(x) {
   x %% 1L == 0L
 }
 
-pm_seq2 <- function (from, to) {
+pm_seq2 <- function(from, to) {
   if (length(from) != 1) stop("`from` must be length one")
   if (length(to) != 1) stop("`to` must be length one")
   if (from > to) integer() else seq.int(from, to)
@@ -1041,19 +1062,25 @@ pm_is_function <- function(x, frame) {
     warning = function(w) FALSE,
     error = function(e) FALSE
   )
-  if (isTRUE(res)) return(res)
+  if (isTRUE(res)) {
+    return(res)
+  }
   res <- tryCatch(
     is.function(eval(x)),
     warning = function(w) FALSE,
     error = function(e) FALSE
   )
-  if (isTRUE(res)) return(res)
+  if (isTRUE(res)) {
+    return(res)
+  }
   res <- tryCatch(
     is.function(eval(as.symbol(deparse(substitute(x))))),
     warning = function(w) FALSE,
     error = function(e) FALSE
   )
-  if (isTRUE(res)) return(res)
+  if (isTRUE(res)) {
+    return(res)
+  }
   FALSE
 }
 

R/ab.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' Transform Input to an Antibiotic ID
 #'
 #' Use this function to determine the antibiotic code of one or more antibiotics. The data set [antibiotics] will be searched for abbreviations, official names and synonyms (brand names).
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x a [character] vector to determine to antibiotic ID
 #' @param flag_multiple_results a [logical] to indicate whether a note should be printed to the console that probably more than one antibiotic code or name can be retrieved from a single input value.
 #' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
@@ -34,16 +33,16 @@
 #' @rdname as.ab
 #' @inheritSection WHOCC WHOCC
 #' @details All entries in the [antibiotics] data set have three different identifiers: a human readable EARS-Net code (column `ab`, used by ECDC and WHONET), an ATC code (column `atc`, used by WHO), and a CID code (column `cid`, Compound ID, used by PubChem). The data set contains more than 5,000 official brand names from many different countries, as found in PubChem. Not that some drugs contain multiple ATC codes.
-#' 
+#'
 #' All these properties will be searched for the user input. The [as.ab()] can correct for different forms of misspelling:
-#' 
+#'
 #'  * Wrong spelling of drug names (such as "tobramicin" or "gentamycin"), which corrects for most audible similarities such as f/ph, x/ks, c/z/s, t/th, etc.
 #'  * Too few or too many vowels or consonants
 #'  * Switching two characters (such as "mreopenem", often the case in clinical data, when doctors typed too fast)
 #'  * Digitalised paper records, leaving artefacts like 0/o/O (zero and O's), B/8, n/r, etc.
 #'
 #' Use the [`ab_*`][ab_property()] functions to get properties based on the returned antibiotic ID, see *Examples*.
-#' 
+#'
 #' Note: the [as.ab()] and [`ab_*`][ab_property()] functions may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems.
 #' @section Source:
 #' World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/}
@@ -51,11 +50,10 @@
 #' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm}
 #' @aliases ab
 #' @return A [character] [vector] with additional class [`ab`]
-#' @seealso 
+#' @seealso
 #' * [antibiotics] for the [data.frame] that is being used to determine ATCs
 #' * [ab_from_text()] for a function to retrieve antimicrobial drugs from clinical text (from health care records)
 #' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
 #' @export
 #' @examples
 #' # these examples all return "ERY", the ID of erythromycin:
@@ -67,52 +65,52 @@
 #' as.ab("ERYT")
 #' as.ab("ERY")
 #' as.ab("eritromicine") # spelled wrong, yet works
-#' as.ab("Erythrocin")   # trade name
-#' as.ab("Romycin")      # trade name
-#' 
+#' as.ab("Erythrocin") # trade name
+#' as.ab("Romycin") # trade name
+#'
 #' # spelling from different languages and dyslexia are no problem
 #' ab_atc("ceftriaxon")
-#' ab_atc("cephtriaxone")     # small spelling error
-#' ab_atc("cephthriaxone")    # or a bit more severe
+#' ab_atc("cephtriaxone") # small spelling error
+#' ab_atc("cephthriaxone") # or a bit more severe
 #' ab_atc("seephthriaaksone") # and even this works
 #'
 #' # use ab_* functions to get a specific properties (see ?ab_property);
 #' # they use as.ab() internally:
-#' ab_name("J01FA01")    # "Erythromycin"
-#' ab_name("eryt")       # "Erythromycin"
+#' ab_name("J01FA01") # "Erythromycin"
+#' ab_name("eryt") # "Erythromycin"
 #' \donttest{
 #' if (require("dplyr")) {
-#' 
+#'
 #'   # you can quickly rename <rsi> columns using dplyr >= 1.0.0:
 #'   example_isolates %>%
 #'     rename_with(as.ab, where(is.rsi))
-#'    
 #' }
 #' }
 as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
   meet_criteria(x, allow_class = c("character", "numeric", "integer", "factor"), allow_NA = TRUE)
   meet_criteria(flag_multiple_results, allow_class = "logical", has_length = 1)
   meet_criteria(info, allow_class = "logical", has_length = 1)
-  
+
   check_dataset_integrity()
-  
+
   if (is.ab(x)) {
     return(x)
   }
   if (all(x %in% c(AB_lookup$ab, NA))) {
     # all valid AB codes, but not yet right class
     return(set_clean_class(x,
-                           new_class = c("ab", "character")))
+      new_class = c("ab", "character")
+    ))
   }
-  
+
   initial_search <- is.null(list(...)$initial_search)
   already_regex <- isTRUE(list(...)$already_regex)
   fast_mode <- isTRUE(list(...)$fast_mode)
-  
+
   x_bak <- x
   x <- toupper(x)
   x_nonNA <- x[!is.na(x)]
-  
+
   # remove diacritics
   x <- iconv(x, from = "UTF-8", to = "ASCII//TRANSLIT")
   x <- gsub('"', "", x, fixed = TRUE)
@@ -123,11 +121,12 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
   if (already_regex == FALSE) {
     x_bak_clean <- generalise_antibiotic_name(x_bak_clean)
   }
-  
+
   x <- unique(x_bak_clean) # this means that every x is in fact generalise_antibiotic_name(x)
   x_new <- rep(NA_character_, length(x))
   x_unknown <- character(0)
-  
+  x_unknown_ATCs <- character(0)
+
   note_if_more_than_one_found <- function(found, index, from_text) {
     if (initial_search == TRUE & isTRUE(length(from_text) > 1)) {
       abnames <- ab_name(from_text, tolower = TRUE, initial_search = FALSE)
@@ -135,13 +134,15 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
         abnames <- abnames[!abnames %in% c("clavulanic acid", "avibactam")]
       }
       if (length(abnames) > 1) {
-        message_("More than one result was found for item ", index, ": ",
-                 vector_and(abnames, quotes = FALSE))
+        message_(
+          "More than one result was found for item ", index, ": ",
+          vector_and(abnames, quotes = FALSE)
+        )
       }
     }
     found[1L]
   }
-  
+
   # Fill in names, AB codes, CID codes and ATC codes directly (`x` is already clean and uppercase)
   known_names <- x %in% AB_lookup$generalised_name
   x_new[known_names] <- AB_lookup$ab[match(x[known_names], AB_lookup$generalised_name)]
@@ -149,77 +150,96 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
   known_codes_atc <- vapply(FUN.VALUE = logical(1), x, function(x_) x_ %in% unlist(AB_lookup$atc), USE.NAMES = FALSE)
   known_codes_cid <- x %in% AB_lookup$cid
   x_new[known_codes_ab] <- AB_lookup$ab[match(x[known_codes_ab], AB_lookup$ab)]
-  x_new[known_codes_atc] <- AB_lookup$ab[vapply(FUN.VALUE = integer(1),
-                                                x[known_codes_atc],
-                                                function(x_) which(vapply(FUN.VALUE = logical(1),
-                                                                          AB_lookup$atc,
-                                                                          function(atc) x_ %in% atc))[1L],
-                                                USE.NAMES = FALSE)]
+  x_new[known_codes_atc] <- AB_lookup$ab[vapply(
+    FUN.VALUE = integer(1),
+    x[known_codes_atc],
+    function(x_) {
+      which(vapply(
+        FUN.VALUE = logical(1),
+        AB_lookup$atc,
+        function(atc) x_ %in% atc
+      ))[1L]
+    },
+    USE.NAMES = FALSE
+  )]
   x_new[known_codes_cid] <- AB_lookup$ab[match(x[known_codes_cid], AB_lookup$cid)]
   already_known <- known_names | known_codes_ab | known_codes_atc | known_codes_cid
-  
+
   if (initial_search == TRUE & sum(already_known) < length(x)) {
     progress <- progress_ticker(n = sum(!already_known), n_min = 25, print = info) # start if n >= 25
     on.exit(close(progress))
   }
-  
+
   for (i in which(!already_known)) {
-    
     if (initial_search == TRUE) {
       progress$tick()
     }
-    
+
     if (is.na(x[i]) | is.null(x[i])) {
       next
     }
     if (identical(x[i], "") |
-        # prevent "bacteria" from coercing to TMP, since Bacterial is a brand name of it:
-        identical(tolower(x[i]), "bacteria")) {
+      # prevent "bacteria" from coercing to TMP, since Bacterial is a brand name of it:
+      identical(tolower(x[i]), "bacteria")) {
       x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
       next
     }
-    
+    if (x[i] %like_case% "[A-Z][0-9][0-9][A-Z][A-Z][0-9][0-9]") {
+      # seems an ATC code, but the available ones are in `already_known`, so:
+      x_unknown <- c(x_unknown, x[i])
+      x_unknown_ATCs <- c(x_unknown_ATCs, x[i])
+      x_new[i] <- NA_character_
+      next
+    }
+
     if (fast_mode == FALSE && flag_multiple_results == TRUE && x[i] %like% "[ ]") {
       from_text <- tryCatch(suppressWarnings(ab_from_text(x[i], initial_search = FALSE, translate_ab = FALSE)[[1]]),
-                            error = function(e) character(0))
+        error = function(e) character(0)
+      )
     } else {
       from_text <- character(0)
     }
-    
+
     # old code for phenoxymethylpenicillin (Peni V)
     if (x[i] == "PNV") {
       x_new[i] <- "PHN"
       next
     }
-    
+
     # exact LOINC code
-    loinc_found <- unlist(lapply(AB_lookup$generalised_loinc,
-                                 function(s) x[i] %in% s))
+    loinc_found <- unlist(lapply(
+      AB_lookup$generalised_loinc,
+      function(s) x[i] %in% s
+    ))
     found <- antibiotics$ab[loinc_found == TRUE]
     if (length(found) > 0) {
       x_new[i] <- note_if_more_than_one_found(found, i, from_text)
       next
     }
-    
+
     # exact synonym
-    synonym_found <- unlist(lapply(AB_lookup$generalised_synonyms,
-                                   function(s) x[i] %in% s))
+    synonym_found <- unlist(lapply(
+      AB_lookup$generalised_synonyms,
+      function(s) x[i] %in% s
+    ))
     found <- antibiotics$ab[synonym_found == TRUE]
     if (length(found) > 0) {
       x_new[i] <- note_if_more_than_one_found(found, i, from_text)
       next
     }
-    
+
     # exact abbreviation
-    abbr_found <- unlist(lapply(AB_lookup$generalised_abbreviations,
-                                # require at least 2 characters for abbreviations
-                                function(s) x[i] %in% s & nchar(x[i]) >= 2))
+    abbr_found <- unlist(lapply(
+      AB_lookup$generalised_abbreviations,
+      # require at least 2 characters for abbreviations
+      function(s) x[i] %in% s & nchar(x[i]) >= 2
+    ))
     found <- antibiotics$ab[abbr_found == TRUE]
     if (length(found) > 0) {
       x_new[i] <- note_if_more_than_one_found(found, i, from_text)
       next
     }
-    
+
     # length of input is quite long, and Levenshtein distance is only max 2
     if (nchar(x[i]) >= 10) {
       levenshtein <- as.double(utils::adist(x[i], AB_lookup$generalised_name))
@@ -229,7 +249,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
         next
       }
     }
-    
+
     # allow characters that resemble others, but only continue when having more than 3 characters
     if (nchar(x[i]) <= 3) {
       x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
@@ -237,7 +257,6 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
     }
     x_spelling <- x[i]
     if (already_regex == FALSE) {
-      
       x_spelling <- gsub("[IY]+", "[IY]+", x_spelling, perl = TRUE)
       x_spelling <- gsub("(C|K|Q|QU|S|Z|X|KS)+", "(C|K|Q|QU|S|Z|X|KS)+", x_spelling, perl = TRUE)
       x_spelling <- gsub("(PH|F|V)+", "(PH|F|V)+", x_spelling, perl = TRUE)
@@ -260,23 +279,25 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
       x_spelling <- gsub("(O|0)", "(O|0)+", x_spelling, perl = TRUE)
       x_spelling <- gsub("++", "+", x_spelling, fixed = TRUE)
     }
-    
+
     # try if name starts with it
-    found <- antibiotics[which(AB_lookup$generalised_name %like% paste0("^", x_spelling)), ]$ab
+    found <- antibiotics[which(AB_lookup$generalised_name %like% paste0("^", x_spelling)), "ab", drop = TRUE]
     if (length(found) > 0) {
       x_new[i] <- note_if_more_than_one_found(found, i, from_text)
       next
     }
     # try if name ends with it
-    found <- antibiotics[which(AB_lookup$generalised_name %like% paste0(x_spelling, "$")), ]$ab
+    found <- antibiotics[which(AB_lookup$generalised_name %like% paste0(x_spelling, "$")), "ab", drop = TRUE]
     if (nchar(x[i]) >= 4 & length(found) > 0) {
       x_new[i] <- note_if_more_than_one_found(found, i, from_text)
       next
     }
-    
+
     # and try if any synonym starts with it
-    synonym_found <- unlist(lapply(AB_lookup$generalised_synonyms,
-                                   function(s) any(s %like% paste0("^", x_spelling))))
+    synonym_found <- unlist(lapply(
+      AB_lookup$generalised_synonyms,
+      function(s) any(s %like% paste0("^", x_spelling))
+    ))
     found <- antibiotics$ab[synonym_found == TRUE]
     if (length(found) > 0) {
       x_new[i] <- note_if_more_than_one_found(found, i, from_text)
@@ -287,7 +308,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
 
     if (initial_search == TRUE && fast_mode == FALSE) {
       # only run on first try
-      
+
       # try by removing all spaces
       if (x[i] %like% " ") {
         found <- suppressWarnings(as.ab(gsub(" +", "", x[i], perl = TRUE), initial_search = FALSE))
@@ -296,7 +317,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
           next
         }
       }
-      
+
       # try by removing all spaces and numbers
       if (x[i] %like% " " | x[i] %like% "[0-9]") {
         found <- suppressWarnings(as.ab(gsub("[ 0-9]", "", x[i], perl = TRUE), initial_search = FALSE))
@@ -305,45 +326,53 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
           next
         }
       }
-      
+
       # transform back from other languages and try again
-      x_translated <- paste(lapply(strsplit(x[i], "[^A-Z0-9]"),
-                                   function(y) {
-                                     for (i in seq_len(length(y))) {
-                                       for (lang in LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]) {
-                                         y[i] <- ifelse(tolower(y[i]) %in% tolower(TRANSLATIONS[, lang, drop = TRUE]),
-                                                        TRANSLATIONS[which(tolower(TRANSLATIONS[, lang, drop = TRUE]) == tolower(y[i]) &
-                                                                                  !isFALSE(TRANSLATIONS$fixed)), "pattern"],
-                                                        y[i])
-                                       }
-                                     }
-                                     generalise_antibiotic_name(y)
-                                   })[[1]],
-                            collapse = "/")
+      x_translated <- paste(lapply(
+        strsplit(x[i], "[^A-Z0-9]"),
+        function(y) {
+          for (i in seq_len(length(y))) {
+            for (lang in LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]) {
+              y[i] <- ifelse(tolower(y[i]) %in% tolower(TRANSLATIONS[, lang, drop = TRUE]),
+                TRANSLATIONS[which(tolower(TRANSLATIONS[, lang, drop = TRUE]) == tolower(y[i]) &
+                  !isFALSE(TRANSLATIONS$fixed)), "pattern"],
+                y[i]
+              )
+            }
+          }
+          generalise_antibiotic_name(y)
+        }
+      )[[1]],
+      collapse = "/"
+      )
       x_translated_guess <- suppressWarnings(as.ab(x_translated, initial_search = FALSE))
       if (!is.na(x_translated_guess)) {
         x_new[i] <- x_translated_guess
         next
       }
-      
+
       # now also try to coerce brandname combinations like "Amoxy/clavulanic acid"
-      x_translated <- paste(lapply(strsplit(x_translated, "[^A-Z0-9 ]"),
-                                   function(y) {
-                                     for (i in seq_len(length(y))) {
-                                       y_name <- suppressWarnings(ab_name(y[i], language = NULL, initial_search = FALSE))
-                                       y[i] <- ifelse(!is.na(y_name),
-                                                      y_name,
-                                                      y[i])
-                                     }
-                                     generalise_antibiotic_name(y)
-                                   })[[1]],
-                            collapse = "/")
+      x_translated <- paste(lapply(
+        strsplit(x_translated, "[^A-Z0-9 ]"),
+        function(y) {
+          for (i in seq_len(length(y))) {
+            y_name <- suppressWarnings(ab_name(y[i], language = NULL, initial_search = FALSE))
+            y[i] <- ifelse(!is.na(y_name),
+              y_name,
+              y[i]
+            )
+          }
+          generalise_antibiotic_name(y)
+        }
+      )[[1]],
+      collapse = "/"
+      )
       x_translated_guess <- suppressWarnings(as.ab(x_translated, initial_search = FALSE))
       if (!is.na(x_translated_guess)) {
         x_new[i] <- x_translated_guess
         next
       }
-      
+
       # try by removing all trailing capitals
       if (x[i] %like_case% "[a-z]+[A-Z]+$") {
         found <- suppressWarnings(as.ab(gsub("[A-Z]+$", "", x[i], perl = TRUE), initial_search = FALSE))
@@ -352,27 +381,28 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
           next
         }
       }
-      
+
       # keep only letters
       found <- suppressWarnings(as.ab(gsub("[^A-Z]", "", x[i], perl = TRUE), initial_search = FALSE))
       if (!is.na(found)) {
         x_new[i] <- note_if_more_than_one_found(found, i, from_text)
         next
       }
-      
+
       # try from a bigger text, like from a health care record, see ?ab_from_text
       # already calculated above if flag_multiple_results = TRUE
       if (flag_multiple_results == TRUE) {
         found <- from_text[1L]
       } else {
         found <- tryCatch(suppressWarnings(ab_from_text(x[i], initial_search = FALSE, translate_ab = FALSE)[[1]][1L]),
-                          error = function(e) NA_character_)
+          error = function(e) NA_character_
+        )
       }
       if (!is.na(found)) {
         x_new[i] <- note_if_more_than_one_found(found, i, from_text)
         next
       }
-      
+
       # first 5 except for cephalosporins, then first 7 (those cephalosporins all start quite the same!)
       found <- suppressWarnings(as.ab(substr(x[i], 1, 5), initial_search = FALSE))
       if (!is.na(found) && ab_group(found, initial_search = FALSE) %unlike% "cephalosporins") {
@@ -384,7 +414,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
         x_new[i] <- note_if_more_than_one_found(found, i, from_text)
         next
       }
-      
+
       # make all consonants facultative
       search_str <- gsub("([BCDFGHJKLMNPQRSTVWXZ])", "\\1*", x[i], perl = TRUE)
       found <- suppressWarnings(as.ab(search_str, initial_search = FALSE, already_regex = TRUE))
@@ -396,7 +426,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
         x_new[i] <- note_if_more_than_one_found(found, i, from_text)
         next
       }
-      
+
       # make all vowels facultative
       search_str <- gsub("([AEIOUY])", "\\1*", x[i], perl = TRUE)
       found <- suppressWarnings(as.ab(search_str, initial_search = FALSE, already_regex = TRUE))
@@ -408,7 +438,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
         x_new[i] <- note_if_more_than_one_found(found, i, from_text)
         next
       }
-      
+
       # allow misspelling of vowels
       x_spelling <- gsub("A+", "[AEIOU]+", x_spelling, fixed = TRUE)
       x_spelling <- gsub("E+", "[AEIOU]+", x_spelling, fixed = TRUE)
@@ -420,17 +450,18 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
         x_new[i] <- note_if_more_than_one_found(found, i, from_text)
         next
       }
-      
+
       # try with switched character, like "mreopenem"
       for (j in seq_len(nchar(x[i]))) {
         x_switched <- paste0(
           # beginning part:
           substr(x[i], 1, j - 1),
           # here is the switching of 2 characters:
-          substr(x[i], j + 1, j + 1), 
-          substr(x[i], j, j), 
+          substr(x[i], j + 1, j + 1),
+          substr(x[i], j, j),
           # ending part:
-          substr(x[i], j + 2, nchar(x[i])))
+          substr(x[i], j + 2, nchar(x[i]))
+        )
         found <- suppressWarnings(as.ab(x_switched, initial_search = FALSE))
         if (!is.na(found)) {
           break
@@ -440,37 +471,40 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
         x_new[i] <- found[1L]
         next
       }
-      
     } # end of initial_search = TRUE
-    
+
     # not found
     x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
   }
-  
+
   if (initial_search == TRUE & sum(already_known) < length(x)) {
     close(progress)
   }
-  
+
   # take failed ATC codes apart from rest
-  x_unknown_ATCs <- x_unknown[x_unknown %like% "[A-Z][0-9][0-9][A-Z][A-Z][0-9][0-9]"]
-  x_unknown <- x_unknown[!x_unknown %in% x_unknown_ATCs]
-  if (length(x_unknown_ATCs) > 0 & fast_mode == FALSE) {
-    warning_("in `as.ab()`: these ATC codes are not (yet) in the antibiotics data set: ",
-             vector_and(x_unknown_ATCs), ".")
+  if (length(x_unknown_ATCs) > 0 && fast_mode == FALSE) {
+    warning_(
+      "in `as.ab()`: these ATC codes are not (yet) in the antibiotics data set: ",
+      vector_and(x_unknown_ATCs), "."
+    )
   }
-  
-  if (length(x_unknown) > 0 & fast_mode == FALSE) {
-    warning_("in `as.ab()`: these values could not be coerced to a valid antimicrobial ID: ",
-             vector_and(x_unknown), ".")
+  x_unknown <- x_unknown[!x_unknown %in% x_unknown_ATCs]
+
+  if (length(x_unknown) > 0 && fast_mode == FALSE) {
+    warning_(
+      "in `as.ab()`: these values could not be coerced to a valid antimicrobial ID: ",
+      vector_and(x_unknown), "."
+    )
   }
 
   x_result <- x_new[match(x_bak_clean, x)]
   if (length(x_result) == 0) {
     x_result <- NA_character_
   }
-  
+
   set_clean_class(x_result,
-                  new_class = c("ab", "character"))
+    new_class = c("ab", "character")
+  )
 }
 
 #' @rdname as.ab

R/ab_from_text.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -24,9 +24,8 @@
 # ==================================================================== #
 
 #' Retrieve Antimicrobial Drug Names and Doses from Clinical Text
-#' 
+#'
 #' Use this function on e.g. clinical texts from health care records. It returns a [list] with all antimicrobial drugs, doses and forms of administration found in the texts.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param text text to analyse
 #' @param type type of property to search for, either `"drug"`, `"dose"` or `"administration"`, see *Examples*
 #' @param collapse a [character] to pass on to `paste(, collapse = ...)` to only return one [character] per element of `text`, see *Examples*
@@ -35,57 +34,62 @@
 #' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
 #' @param ... arguments passed on to [as.ab()]
 #' @details This function is also internally used by [as.ab()], although it then only searches for the first drug name and will throw a note if more drug names could have been returned. Note: the [as.ab()] function may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems.
-#' 
+#'
 #' ## Argument `type`
 #' At default, the function will search for antimicrobial drug names. All text elements will be searched for official names, ATC codes and brand names. As it uses [as.ab()] internally, it will correct for misspelling.
-#' 
+#'
 #' With `type = "dose"` (or similar, like "dosing", "doses"), all text elements will be searched for [numeric] values that are higher than 100 and do not resemble years. The output will be [numeric]. It supports any unit (g, mg, IE, etc.) and multiple values in one clinical text, see *Examples*.
-#' 
+#'
 #' With `type = "administration"` (or abbreviations, like "admin", "adm"), all text elements will be searched for a form of drug administration. It supports the following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal and vaginal. Abbreviations for oral (such as 'po', 'per os') will become "oral", all values for intravenous (such as 'iv', 'intraven') will become "iv". It supports multiple values in one clinical text, see *Examples*.
-#' 
+#'
 #' ## Argument `collapse`
 #' Without using `collapse`, this function will return a [list]. This can be convenient to use e.g. inside a `mutate()`):\cr
-#' `df %>% mutate(abx = ab_from_text(clinical_text))` 
-#' 
+#' `df %>% mutate(abx = ab_from_text(clinical_text))`
+#'
 #' The returned AB codes can be transformed to official names, groups, etc. with all [`ab_*`][ab_property()] functions such as [ab_name()] and [ab_group()], or by using the `translate_ab` argument.
-#' 
+#'
 #' With using `collapse`, this function will return a [character]:\cr
-#' `df %>% mutate(abx = ab_from_text(clinical_text, collapse = "|"))` 
+#' `df %>% mutate(abx = ab_from_text(clinical_text, collapse = "|"))`
 #' @export
 #' @return A [list], or a  [character] if `collapse` is not `NULL`
-#' @inheritSection AMR Read more on Our Website!
-#' @examples 
-#' # mind the bad spelling of amoxicillin in this line, 
+#' @examples
+#' # mind the bad spelling of amoxicillin in this line,
 #' # straight from a true health care record:
 #' ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds")
-#' 
+#'
 #' ab_from_text("500 mg amoxi po and 400mg cipro iv")
 #' ab_from_text("500 mg amoxi po and 400mg cipro iv", type = "dose")
 #' ab_from_text("500 mg amoxi po and 400mg cipro iv", type = "admin")
-#' 
+#'
 #' ab_from_text("500 mg amoxi po and 400mg cipro iv", collapse = ", ")
 #' \donttest{
 #' # if you want to know which antibiotic groups were administered, do e.g.:
 #' abx <- ab_from_text("500 mg amoxi po and 400mg cipro iv")
 #' ab_group(abx[[1]])
-#' 
+#'
 #' if (require("dplyr")) {
-#'   tibble(clinical_text = c("given 400mg cipro and 500 mg amox",
-#'                            "started on doxy iv today")) %>% 
-#'     mutate(abx_codes = ab_from_text(clinical_text),
-#'            abx_doses = ab_from_text(clinical_text, type = "doses"),
-#'            abx_admin = ab_from_text(clinical_text, type = "admin"),
-#'            abx_coll = ab_from_text(clinical_text, collapse = "|"),
-#'            abx_coll_names = ab_from_text(clinical_text,
-#'                                          collapse = "|",
-#'                                          translate_ab = "name"),
-#'            abx_coll_doses = ab_from_text(clinical_text,
-#'                                          type = "doses",
-#'                                          collapse = "|"),
-#'            abx_coll_admin = ab_from_text(clinical_text,
-#'                                          type = "admin",
-#'                                          collapse = "|"))
-#' 
+#'   tibble(clinical_text = c(
+#'     "given 400mg cipro and 500 mg amox",
+#'     "started on doxy iv today"
+#'   )) %>%
+#'     mutate(
+#'       abx_codes = ab_from_text(clinical_text),
+#'       abx_doses = ab_from_text(clinical_text, type = "doses"),
+#'       abx_admin = ab_from_text(clinical_text, type = "admin"),
+#'       abx_coll = ab_from_text(clinical_text, collapse = "|"),
+#'       abx_coll_names = ab_from_text(clinical_text,
+#'         collapse = "|",
+#'         translate_ab = "name"
+#'       ),
+#'       abx_coll_doses = ab_from_text(clinical_text,
+#'         type = "doses",
+#'         collapse = "|"
+#'       ),
+#'       abx_coll_admin = ab_from_text(clinical_text,
+#'         type = "admin",
+#'         collapse = "|"
+#'       )
+#'     )
 #' }
 #' }
 ab_from_text <- function(text,
@@ -98,7 +102,7 @@ ab_from_text <- function(text,
   if (missing(type)) {
     type <- type[1L]
   }
-  
+
   meet_criteria(text)
   meet_criteria(type, allow_class = "character", has_length = 1)
   meet_criteria(collapse, has_length = 1, allow_NULL = TRUE)
@@ -107,18 +111,17 @@ ab_from_text <- function(text,
   meet_criteria(info, allow_class = "logical", has_length = 1)
 
   type <- tolower(trimws(type))
-  
+
   text <- tolower(as.character(text))
   text_split_all <- strsplit(text, "[ ;.,:\\|]")
   progress <- progress_ticker(n = length(text_split_all), n_min = 5, print = info)
   on.exit(close(progress))
-  
+
   if (type %like% "(drug|ab|anti)") {
-    
     translate_ab <- get_translate_ab(translate_ab)
-    
-    if (isTRUE(thorough_search) | 
-        (isTRUE(is.null(thorough_search)) & max(vapply(FUN.VALUE = double(1), text_split_all, length), na.rm = TRUE) <= 3)) {
+
+    if (isTRUE(thorough_search) |
+      (isTRUE(is.null(thorough_search)) & max(vapply(FUN.VALUE = double(1), text_split_all, length), na.rm = TRUE) <= 3)) {
       text_split_all <- text_split_all[nchar(text_split_all) >= 4 & grepl("[a-z]+", text_split_all)]
       result <- lapply(text_split_all, function(text_split) {
         progress$tick()
@@ -126,7 +129,6 @@ ab_from_text <- function(text,
           out <- as.ab(text_split, ...)
         )
       })
-      
     } else {
       # no thorough search
       abbr <- unlist(antibiotics$abbreviations)
@@ -138,25 +140,30 @@ ab_from_text <- function(text,
       synonyms_part1 <- synonyms[seq_len(0.5 * length(synonyms))]
       synonyms_part2 <- synonyms[!synonyms %in% synonyms_part1]
       to_regex <- function(x) {
-        paste0("^(",
-               paste0(unique(gsub("[^a-z0-9]+", "", sort(tolower(x)))), collapse = "|"),
-               ").*")
+        paste0(
+          "^(",
+          paste0(unique(gsub("[^a-z0-9]+", "", sort(tolower(x)))), collapse = "|"),
+          ").*"
+        )
       }
       result <- lapply(text_split_all, function(text_split) {
         progress$tick()
         suppressWarnings(
-          out <- as.ab(unique(c(text_split[text_split %like_case% to_regex(abbr)],
-                                text_split[text_split %like_case% to_regex(names_atc)],
-                                text_split[text_split %like_case% to_regex(synonyms_part1)],
-                                text_split[text_split %like_case% to_regex(synonyms_part2)])
-          ),
-          ...)
+          out <- as.ab(
+            unique(c(
+              text_split[text_split %like_case% to_regex(abbr)],
+              text_split[text_split %like_case% to_regex(names_atc)],
+              text_split[text_split %like_case% to_regex(synonyms_part1)],
+              text_split[text_split %like_case% to_regex(synonyms_part2)]
+            )),
+            ...
+          )
         )
       })
     }
-    
+
     close(progress)
-    
+
     result <- lapply(result, function(out) {
       out <- out[!is.na(out)]
       if (length(out) == 0) {
@@ -167,27 +174,24 @@ ab_from_text <- function(text,
         }
         out
       }
-      
     })
-    
   } else if (type %like% "dos") {
     text_split_all <- strsplit(text, " ")
     result <- lapply(text_split_all, function(text_split) {
       text_split <- text_split[text_split %like% "^[0-9]{2,}(/[0-9]+)?[a-z]*$"]
       # only left part of "/", like 500 in  "500/125"
-      text_split <-  gsub("/.*", "", text_split)
+      text_split <- gsub("/.*", "", text_split)
       text_split <- gsub(",", ".", text_split, fixed = TRUE) # foreign system using comma as decimal sep
       text_split <- as.double(gsub("[^0-9.]", "", text_split))
       # minimal 100 units/mg and no years that unlikely doses
       text_split <- text_split[text_split >= 100 & !text_split %in% c(1951:1999, 2001:2049)]
-      
+
       if (length(text_split) > 0) {
         text_split
       } else {
         NA_real_
       }
     })
-    
   } else if (type %like% "adm") {
     result <- lapply(text_split_all, function(text_split) {
       text_split <- text_split[text_split %like% "(^iv$|intraven|^po$|per os|oral|implant|inhal|instill|nasal|paren|rectal|sublingual|buccal|trans.*dermal|vaginal)"]
@@ -199,11 +203,10 @@ ab_from_text <- function(text,
         NA_character_
       }
     })
-    
   } else {
     stop_("`type` must be either 'drug', 'dose' or 'administration'")
   }
-  
+
   # collapse text if needed
   if (!is.null(collapse)) {
     result <- vapply(FUN.VALUE = character(1), result, function(x) {
@@ -214,7 +217,6 @@ ab_from_text <- function(text,
       }
     })
   }
-  
+
   result
-  
 }

R/ab_property.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' Get Properties of an Antibiotic
 #'
 #' Use these functions to return a specific property of an antibiotic from the [antibiotics] data set. All input values will be evaluated internally with [as.ab()].
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()]
 #' @param tolower a [logical] to indicate whether the first [character] of every output should be transformed to a lower case [character]. This will lead to e.g. "polymyxin B" and not "polymyxin b".
 #' @param property one of the column names of one of the [antibiotics] data set: `vector_or(colnames(antibiotics), sort = FALSE)`.
@@ -38,14 +37,14 @@
 #' @param snake_case a [logical] to indicate whether the names should be in so-called [snake case](https://en.wikipedia.org/wiki/Snake_case): in lower case and all spaces/slashes replaced with an underscore (`_`)
 #' @param only_first a [logical] to indicate whether only the first ATC code must be returned, with giving preference to J0-codes (i.e., the antimicrobial drug group)
 #' @details All output [will be translated][translate] where possible.
-#' 
+#'
 #' The function [ab_url()] will return the direct URL to the official WHO website. A warning will be returned if the required ATC code is not available.
-#' 
+#'
 #' The function [set_ab_names()] is a special column renaming function for [data.frame]s. It renames columns names that resemble antimicrobial drugs. It always makes sure that the new column names are unique. If `property = "atc"` is set, preference is given to ATC codes from the J-group.
 #' @inheritSection as.ab Source
 #' @rdname ab_property
 #' @name ab_property
-#' @return 
+#' @return
 #' - An [integer] in case of [ab_cid()]
 #' - A named [list] in case of [ab_info()] and multiple [ab_atc()]/[ab_synonyms()]/[ab_tradenames()]
 #' - A [double] in case of [ab_ddd()]
@@ -54,46 +53,47 @@
 #' @export
 #' @seealso [antibiotics]
 #' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' # all properties:
-#' ab_name("AMX")       # "Amoxicillin"
-#' ab_atc("AMX")        # "J01CA04" (ATC code from the WHO)
-#' ab_cid("AMX")        # 33613 (Compound ID from PubChem)
-#' ab_synonyms("AMX")   # a list with brand names of amoxicillin
+#' ab_name("AMX") # "Amoxicillin"
+#' ab_atc("AMX") # "J01CA04" (ATC code from the WHO)
+#' ab_cid("AMX") # 33613 (Compound ID from PubChem)
+#' ab_synonyms("AMX") # a list with brand names of amoxicillin
 #' ab_tradenames("AMX") # same
-#' ab_group("AMX")      # "Beta-lactams/penicillins"
+#' ab_group("AMX") # "Beta-lactams/penicillins"
 #' ab_atc_group1("AMX") # "Beta-lactam antibacterials, penicillins"
 #' ab_atc_group2("AMX") # "Penicillins with extended spectrum"
-#' ab_url("AMX")        # link to the official WHO page
+#' ab_url("AMX") # link to the official WHO page
 #'
 #' # smart lowercase tranformation
-#' ab_name(x = c("AMC", "PLB"))  # "Amoxicillin/clavulanic acid" "Polymyxin B"
-#' ab_name(x = c("AMC", "PLB"),
-#'         tolower = TRUE)       # "amoxicillin/clavulanic acid" "polymyxin B"
+#' ab_name(x = c("AMC", "PLB")) # "Amoxicillin/clavulanic acid" "Polymyxin B"
+#' ab_name(
+#'   x = c("AMC", "PLB"),
+#'   tolower = TRUE
+#' ) # "amoxicillin/clavulanic acid" "polymyxin B"
 #'
 #' # defined daily doses (DDD)
-#' ab_ddd("AMX", "oral")       #  1.5
+#' ab_ddd("AMX", "oral") #  1.5
 #' ab_ddd_units("AMX", "oral") # "g"
-#' ab_ddd("AMX", "iv")         #  3
-#' ab_ddd_units("AMX", "iv")   # "g"
+#' ab_ddd("AMX", "iv") #  3
+#' ab_ddd_units("AMX", "iv") # "g"
 #'
-#' ab_info("AMX")       # all properties as a list
+#' ab_info("AMX") # all properties as a list
 #'
 #' # all ab_* functions use as.ab() internally, so you can go from 'any' to 'any':
-#' ab_atc("AMP")           # ATC code of AMP (ampicillin)
-#' ab_group("J01CA01")     # Drug group of ampicillins ATC code
-#' ab_loinc("ampicillin")  # LOINC codes of ampicillin
-#' ab_name("21066-6")      # "Ampicillin" (using LOINC)
-#' ab_name(6249)           # "Ampicillin" (using CID)
-#' ab_name("J01CA01")      # "Ampicillin" (using ATC)
-#' 
+#' ab_atc("AMP") # ATC code of AMP (ampicillin)
+#' ab_group("J01CA01") # Drug group of ampicillins ATC code
+#' ab_loinc("ampicillin") # LOINC codes of ampicillin
+#' ab_name("21066-6") # "Ampicillin" (using LOINC)
+#' ab_name(6249) # "Ampicillin" (using CID)
+#' ab_name("J01CA01") # "Ampicillin" (using ATC)
+#'
 #' # spelling from different languages and dyslexia are no problem
 #' ab_atc("ceftriaxon")
 #' ab_atc("cephtriaxone")
 #' ab_atc("cephthriaxone")
 #' ab_atc("seephthriaaksone")
-#' 
+#'
 #' # use set_ab_names() for renaming columns
 #' colnames(example_isolates)
 #' colnames(set_ab_names(example_isolates))
@@ -101,31 +101,34 @@
 #' \donttest{
 #' if (require("dplyr")) {
 #'   example_isolates %>%
-#'     set_ab_names()
-#'     
+#'     set_ab_names() %>%
+#'     head()
+#'
 #'   # this does the same:
 #'   example_isolates %>%
-#'     rename_with(set_ab_names)
-#'   
+#'     rename_with(set_ab_names) %>%
+#'     head()
+#'
 #'   # set_ab_names() works with any AB property:
 #'   example_isolates %>%
-#'     set_ab_names(property = "atc")
-#'     
-#'  example_isolates %>%
-#'    set_ab_names(where(is.rsi)) %>%
-#'    colnames()
-#'    
-#'  example_isolates %>%
-#'    set_ab_names(NIT:VAN) %>%
-#'    colnames()
+#'     set_ab_names(property = "atc") %>%
+#'     head()
+#'
+#'   example_isolates %>%
+#'     set_ab_names(where(is.rsi)) %>%
+#'     colnames()
+#'
+#'   example_isolates %>%
+#'     set_ab_names(NIT:VAN) %>%
+#'     colnames()
 #' }
 #' }
 ab_name <- function(x, language = get_AMR_locale(), tolower = FALSE, ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(tolower, allow_class = "logical", has_length = 1)
-  
-  x <- translate_AMR(ab_validate(x = x, property = "name", ...), language = language, only_affect_ab_names = TRUE)
+
+  x <- translate_into_language(ab_validate(x = x, property = "name", ...), language = language, only_affect_ab_names = TRUE)
   if (tolower == TRUE) {
     # use perl to only transform the first character
     # as we want "polymyxin B", not "polymyxin b"
@@ -166,7 +169,7 @@ ab_tradenames <- function(x, ...) {
 ab_group <- function(x, language = get_AMR_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  translate_AMR(ab_validate(x = x, property = "group", ...), language = language, only_affect_ab_names = TRUE)
+  translate_into_language(ab_validate(x = x, property = "group", ...), language = language, only_affect_ab_names = TRUE)
 }
 
 #' @rdname ab_property
@@ -175,27 +178,29 @@ ab_group <- function(x, language = get_AMR_locale(), ...) {
 ab_atc <- function(x, only_first = FALSE, ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(only_first, allow_class = "logical", has_length = 1)
-  
+
   atcs <- ab_validate(x = x, property = "atc", ...)
-  
+
   if (only_first == TRUE) {
-    atcs <- vapply(FUN.VALUE = character(1),
-                   # get only the first ATC code
-                   atcs,
-                   function(x) {
-                     # try to get the J-group
-                     if (any(x %like% "^J")) {
-                       x[x %like% "^J"][1L]
-                     } else {
-                       as.character(x[1L])
-                     }
-                   })
+    atcs <- vapply(
+      FUN.VALUE = character(1),
+      # get only the first ATC code
+      atcs,
+      function(x) {
+        # try to get the J-group
+        if (any(x %like% "^J")) {
+          x[x %like% "^J"][1L]
+        } else {
+          as.character(x[1L])
+        }
+      }
+    )
   } else if (length(atcs) == 1) {
     atcs <- unname(unlist(atcs))
   } else {
     names(atcs) <- x
   }
-  
+
   atcs
 }
 
@@ -204,7 +209,7 @@ ab_atc <- function(x, only_first = FALSE, ...) {
 ab_atc_group1 <- function(x, language = get_AMR_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  translate_AMR(ab_validate(x = x, property = "atc_group1", ...), language = language, only_affect_ab_names = TRUE)
+  translate_into_language(ab_validate(x = x, property = "atc_group1", ...), language = language, only_affect_ab_names = TRUE)
 }
 
 #' @rdname ab_property
@@ -212,7 +217,7 @@ ab_atc_group1 <- function(x, language = get_AMR_locale(), ...) {
 ab_atc_group2 <- function(x, language = get_AMR_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  translate_AMR(ab_validate(x = x, property = "atc_group2", ...), language = language, only_affect_ab_names = TRUE)
+  translate_into_language(ab_validate(x = x, property = "atc_group2", ...), language = language, only_affect_ab_names = TRUE)
 }
 
 #' @rdname ab_property
@@ -233,26 +238,30 @@ ab_loinc <- function(x, ...) {
 ab_ddd <- function(x, administration = "oral", ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(administration, is_in = c("oral", "iv"), has_length = 1)
-  
+
   x <- as.ab(x, ...)
   ddd_prop <- administration
   # old behaviour
   units <- list(...)$units
   if (!is.null(units) && isTRUE(units)) {
     if (message_not_thrown_before("ab_ddd", entire_session = TRUE)) {
-      warning_("in `ab_ddd()`: using `ab_ddd(..., units = TRUE)` is deprecated, use `ab_ddd_units()` to retrieve units instead.",
-               "This warning will be shown once per session.")
+      warning_(
+        "in `ab_ddd()`: using `ab_ddd(..., units = TRUE)` is deprecated, use `ab_ddd_units()` to retrieve units instead.",
+        "This warning will be shown once per session."
+      )
     }
     ddd_prop <- paste0(ddd_prop, "_units")
   } else {
     ddd_prop <- paste0(ddd_prop, "_ddd")
   }
   out <- ab_validate(x = x, property = ddd_prop)
-  
+
   if (any(ab_name(x, language = NULL) %like% "/" & is.na(out))) {
-    warning_("in `ab_ddd()`: DDDs of some combined products are available for different dose combinations and not (yet) part of the AMR package.",
-             "Please refer to the WHOCC website:\n",
-             "www.whocc.no/ddd/list_of_ddds_combined_products/")
+    warning_(
+      "in `ab_ddd()`: DDDs of some combined products are available for different dose combinations and not (yet) part of the AMR package.",
+      "Please refer to the WHOCC website:\n",
+      "www.whocc.no/ddd/list_of_ddds_combined_products/"
+    )
   }
   out
 }
@@ -262,14 +271,16 @@ ab_ddd <- function(x, administration = "oral", ...) {
 ab_ddd_units <- function(x, administration = "oral", ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(administration, is_in = c("oral", "iv"), has_length = 1)
-  
+
   x <- as.ab(x, ...)
   if (any(ab_name(x, language = NULL) %like% "/")) {
-    warning_("in `ab_ddd_units()`: DDDs of combined products are available for different dose combinations and not (yet) part of the AMR package.",
-             "Please refer to the WHOCC website:\n",
-             "www.whocc.no/ddd/list_of_ddds_combined_products/")
+    warning_(
+      "in `ab_ddd_units()`: DDDs of combined products are available for different dose combinations and not (yet) part of the AMR package.",
+      "Please refer to the WHOCC website:\n",
+      "www.whocc.no/ddd/list_of_ddds_combined_products/"
+    )
   }
-  
+
   ddd_prop <- paste0(administration, "_units")
   ab_validate(x = x, property = ddd_prop)
 }
@@ -279,21 +290,29 @@ ab_ddd_units <- function(x, administration = "oral", ...) {
 ab_info <- function(x, language = get_AMR_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- as.ab(x, ...)
-  list(ab = as.character(x),
-       cid = ab_cid(x),
-       name = ab_name(x, language = language),
-       group = ab_group(x, language = language),
-       atc = ab_atc(x),
-       atc_group1 = ab_atc_group1(x, language = language),
-       atc_group2 = ab_atc_group2(x, language = language),
-       tradenames = ab_tradenames(x),
-       loinc = ab_loinc(x),
-       ddd = list(oral = list(amount = ab_ddd(x, administration = "oral"),
-                              units = ab_ddd_units(x, administration = "oral")),
-                  iv = list(amount = ab_ddd(x, administration = "iv"),
-                            units = ab_ddd_units(x, administration = "iv"))))
+  list(
+    ab = as.character(x),
+    cid = ab_cid(x),
+    name = ab_name(x, language = language),
+    group = ab_group(x, language = language),
+    atc = ab_atc(x),
+    atc_group1 = ab_atc_group1(x, language = language),
+    atc_group2 = ab_atc_group2(x, language = language),
+    tradenames = ab_tradenames(x),
+    loinc = ab_loinc(x),
+    ddd = list(
+      oral = list(
+        amount = ab_ddd(x, administration = "oral"),
+        units = ab_ddd_units(x, administration = "oral")
+      ),
+      iv = list(
+        amount = ab_ddd(x, administration = "iv"),
+        units = ab_ddd_units(x, administration = "iv")
+      )
+    )
+  )
 }
 
 
@@ -302,18 +321,18 @@ ab_info <- function(x, language = get_AMR_locale(), ...) {
 ab_url <- function(x, open = FALSE, ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(open, allow_class = "logical", has_length = 1)
-  
+
   ab <- as.ab(x = x, ...)
   atcs <- ab_atc(ab, only_first = TRUE)
   u <- paste0("https://www.whocc.no/atc_ddd_index/?code=", atcs, "&showdescription=no")
   u[is.na(atcs)] <- NA_character_
   names(u) <- ab_name(ab)
-  
+
   NAs <- ab_name(ab, tolower = TRUE, language = NULL)[!is.na(ab) & is.na(atcs)]
   if (length(NAs) > 0) {
     warning_("in `ab_url()`: no ATC code available for ", vector_and(NAs, quotes = FALSE), ".")
   }
-  
+
   if (open == TRUE) {
     if (length(u) > 1 & !is.na(u[1L])) {
       warning_("in `ab_url()`: only the first URL will be opened, as `browseURL()` only suports one string.")
@@ -331,7 +350,7 @@ ab_property <- function(x, property = "name", language = get_AMR_locale(), ...)
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(property, is_in = colnames(antibiotics), has_length = 1)
   meet_criteria(language, is_in = c(LANGUAGES_SUPPORTED, ""), has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
-  translate_AMR(ab_validate(x = x, property = property, ...), language = language)
+  translate_into_language(ab_validate(x = x, property = property, ...), language = language)
 }
 
 #' @rdname ab_property
@@ -342,17 +361,17 @@ set_ab_names <- function(data, ..., property = "name", language = get_AMR_locale
   meet_criteria(property, is_in = colnames(antibiotics), has_length = 1, ignore.case = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(snake_case, allow_class = "logical", has_length = 1, allow_NULL = TRUE)
-  
+
   x_deparsed <- deparse(substitute(data))
   if (length(x_deparsed) > 1 || any(x_deparsed %unlike% "[a-z]+")) {
     x_deparsed <- "your_data"
   }
-  
+
   property <- tolower(property)
   if (is.null(snake_case)) {
     snake_case <- property == "name"
   }
-  
+
   if (is.data.frame(data)) {
     if (tryCatch(length(list(...)) > 0, error = function(e) TRUE)) {
       df <- pm_select(data, ...)
@@ -369,44 +388,50 @@ set_ab_names <- function(data, ..., property = "name", language = get_AMR_locale
     vars_ab <- as.ab(data, fast_mode = TRUE)
     vars <- data[!is.na(vars_ab)]
   }
-  x <- vapply(FUN.VALUE = character(1),
-              ab_property(vars, property = property, language = language),
-              function(x) {
-                if (property == "atc") {
-                  # try to get the J-group
-                  if (any(x %like% "^J")) {
-                    x[x %like% "^J"][1L]
-                  } else {
-                    as.character(x[1L])
-                  }
-                } else {
-                  as.character(x[1L])
-                }
-              },
-              USE.NAMES = FALSE)
+  x <- vapply(
+    FUN.VALUE = character(1),
+    ab_property(vars, property = property, language = language),
+    function(x) {
+      if (property == "atc") {
+        # try to get the J-group
+        if (any(x %like% "^J")) {
+          x[x %like% "^J"][1L]
+        } else {
+          as.character(x[1L])
+        }
+      } else {
+        as.character(x[1L])
+      }
+    },
+    USE.NAMES = FALSE
+  )
   if (any(x %in% c("", NA))) {
-    warning_("in `set_ab_names()`: no ", property, " found for column(s): ",
-             vector_and(vars[x %in% c("", NA)], sort = FALSE))
+    warning_(
+      "in `set_ab_names()`: no ", property, " found for column(s): ",
+      vector_and(vars[x %in% c("", NA)], sort = FALSE)
+    )
     x[x %in% c("", NA)] <- vars[x %in% c("", NA)]
   }
-  
+
   if (snake_case == TRUE) {
     x <- tolower(gsub("[^a-zA-Z0-9]+", "_", x))
   }
-  
+
   if (any(duplicated(x))) {
     # very hacky way of adding the index to each duplicate
     # so      "Amoxicillin", "Amoxicillin",   "Amoxicillin"
     # will be "Amoxicillin", "Amoxicillin_2", "Amoxicillin_3"
-    invisible(lapply(unique(x),
-                     function(u) {
-                       dups <- which(x == u)
-                       if (length(dups) > 1) {
-                         # there are duplicates
-                         dup_add_int <- dups[2:length(dups)]
-                         x[dup_add_int] <<- paste0(x[dup_add_int], "_", c(2:length(dups)))
-                       }
-                     }))
+    invisible(lapply(
+      unique(x),
+      function(u) {
+        dups <- which(x == u)
+        if (length(dups) > 1) {
+          # there are duplicates
+          dup_add_int <- dups[2:length(dups)]
+          x[dup_add_int] <<- paste0(x[dup_add_int], "_", c(2:length(dups)))
+        }
+      }
+    ))
   }
   if (is.data.frame(data)) {
     colnames(data)[colnames(data) %in% vars] <- x
@@ -418,25 +443,28 @@ set_ab_names <- function(data, ..., property = "name", language = get_AMR_locale
 }
 
 ab_validate <- function(x, property, ...) {
-  
   check_dataset_integrity()
-  
+
   if (tryCatch(all(x[!is.na(x)] %in% AB_lookup$ab), error = function(e) FALSE)) {
     # special case for ab_* functions where class is already <ab>
     x <- AB_lookup[match(x, AB_lookup$ab), property, drop = TRUE]
-    
   } else {
     # try to catch an error when inputting an invalid argument
     # so the 'call.' can be set to FALSE
-    tryCatch(x[1L] %in% antibiotics[1, property],
-             error = function(e) stop(e$message, call. = FALSE))
+    tryCatch(x[1L] %in% antibiotics[1, property, drop = TRUE],
+      error = function(e) stop(e$message, call. = FALSE)
+    )
 
-    if (!all(x %in% AB_lookup[, property])) {
+    if (!all(x %in% AB_lookup[, property, drop = TRUE])) {
       x <- as.ab(x, ...)
-      x <- AB_lookup[match(x, AB_lookup$ab), property, drop = TRUE]
+      if (all(is.na(x)) && is.list(AB_lookup[, property, drop = TRUE])) {
+        x <- rep(NA_character_, length(x))
+      } else {
+        x <- AB_lookup[match(x, AB_lookup$ab), property, drop = TRUE]
+      }
     }
   }
-  
+
   if (property == "ab") {
     return(set_clean_class(x, new_class = c("ab", "character")))
   } else if (property == "cid") {

R/ab_selectors.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -24,9 +24,8 @@
 # ==================================================================== #
 
 #' Antibiotic Selectors
-#' 
+#'
 #' These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group, without the need to define the columns or antibiotic abbreviations. In short, if you have a column name that resembles an antimicrobial agent, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "CZO" and "J01DB04" will all be picked up by [cephalosporins()].
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param ab_class an antimicrobial class or a part of it, such as `"carba"` and `"carbapenems"`. The columns `group`, `atc_group1` and `atc_group2` of the [antibiotics] data set will be searched (case-insensitive) for this value.
 #' @param filter an [expression] to be evaluated in the [antibiotics] data set, such as `name %like% "trim"`
 #' @param only_rsi_columns a [logical] to indicate whether only columns of class `<rsi>` must be selected (defaults to `FALSE`), see [as.rsi()]
@@ -34,130 +33,157 @@
 #' @param ... ignored, only in place to allow future extensions
 #' @details
 #' These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the [Tidyverse selection helpers][tidyselect::language] such as [`everything()`][tidyselect::everything()], 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*.
-#' 
-#' 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.) according to the [antibiotics] data set. This means that a selector such as [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc. 
-#' 
+#'
+#' 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.) according to the [antibiotics] data set. This means that a selector such as [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
+#'
 #' The [ab_class()] function can be used to filter/select on a manually defined antibiotic class. It searches for results in the [antibiotics] data set within the columns `group`, `atc_group1` and `atc_group2`.
 #' @section Full list of supported (antibiotic) classes:
-#' 
+#'
 #' `r paste0(" * ", na.omit(sapply(DEFINED_AB_GROUPS, function(ab) ifelse(tolower(gsub("^AB_", "", ab)) %in% ls(envir = asNamespace("AMR")), paste0("[", tolower(gsub("^AB_", "", ab)), "()] can select: \\cr ", vector_and(paste0(ab_name(eval(parse(text = ab), envir = asNamespace("AMR")), language = NULL, tolower = TRUE), " (", eval(parse(text = ab), envir = asNamespace("AMR")), ")"), quotes = FALSE, sort = TRUE)), character(0)), USE.NAMES = FALSE)), "\n", collapse = "")`
 #' @rdname antibiotic_class_selectors
 #' @name antibiotic_class_selectors
 #' @return (internally) a [character] vector of column names, with additional class `"ab_selector"`
 #' @export
 #' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
-#' @examples 
+
+#' @examples
 #' # `example_isolates` is a data set available in the AMR package.
 #' # See ?example_isolates.
-#' 
+#' example_isolates
+#'
 #' # base R ------------------------------------------------------------------
-#' 
+#'
 #' # select columns 'IPM' (imipenem) and 'MEM' (meropenem)
 #' example_isolates[, carbapenems()]
-#' 
+#'
 #' # select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
 #' example_isolates[, c("mo", aminoglycosides())]
-#' 
+#'
 #' # select only antibiotic columns with DDDs for oral treatment
 #' example_isolates[, administrable_per_os()]
-#' 
+#'
 #' # filter using any() or all()
 #' example_isolates[any(carbapenems() == "R"), ]
 #' subset(example_isolates, any(carbapenems() == "R"))
-#' 
+#'
 #' # filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
 #' example_isolates[any(carbapenems()), ]
 #' example_isolates[all(carbapenems()), ]
-#' 
+#'
 #' # filter with multiple antibiotic selectors using c()
 #' example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]
-#' 
+#'
 #' # filter + select in one go: get penicillins in carbapenems-resistant strains
 #' example_isolates[any(carbapenems() == "R"), penicillins()]
-#' 
+#'
 #' # You can combine selectors with '&' to be more specific. For example,
 #' # penicillins() would select benzylpenicillin ('peni G') and
 #' # administrable_per_os() would select erythromycin. Yet, when combined these
 #' # drugs are both omitted since benzylpenicillin is not administrable per os
 #' # and erythromycin is not a penicillin:
 #' example_isolates[, penicillins() & administrable_per_os()]
-#' 
+#'
 #' # ab_selector() applies a filter in the `antibiotics` data set and is thus very
 #' # flexible. For instance, to select antibiotic columns with an oral DDD of at
 #' # least 1 gram:
 #' example_isolates[, ab_selector(oral_ddd > 1 & oral_units == "g")]
-#' 
+#'
 #' # dplyr -------------------------------------------------------------------
 #' \donttest{
 #' if (require("dplyr")) {
-#' 
-#'   # get AMR for all aminoglycosides e.g., per hospital:
+#'
+#'   # get AMR for all aminoglycosides e.g., per ward:
 #'   example_isolates %>%
-#'     group_by(hospital_id) %>% 
+#'     group_by(ward) %>%
 #'     summarise(across(aminoglycosides(), resistance))
-#'     
+#' }
+#' if (require("dplyr")) {
+#'
 #'   # You can combine selectors with '&' to be more specific:
 #'   example_isolates %>%
 #'     select(penicillins() & administrable_per_os())
-#'   
+#' }
+#' if (require("dplyr")) {
+#'
 #'   # get AMR for only drugs that matter - no intrinsic resistance:
 #'   example_isolates %>%
-#'     filter(mo_genus() %in% c("Escherichia", "Klebsiella")) %>% 
-#'     group_by(hospital_id) %>% 
+#'     filter(mo_genus() %in% c("Escherichia", "Klebsiella")) %>%
+#'     group_by(ward) %>%
 #'     summarise(across(not_intrinsic_resistant(), resistance))
-#'     
+#' }
+#' if (require("dplyr")) {
+#'
 #'   # get susceptibility for antibiotics whose name contains "trim":
 #'   example_isolates %>%
-#'     filter(first_isolate()) %>% 
-#'     group_by(hospital_id) %>% 
+#'     filter(first_isolate()) %>%
+#'     group_by(ward) %>%
 #'     summarise(across(ab_selector(name %like% "trim"), susceptibility))
-#' 
+#' }
+#' if (require("dplyr")) {
+#'
 #'   # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
-#'   example_isolates %>% 
+#'   example_isolates %>%
 #'     select(carbapenems())
-#'     
+#' }
+#' if (require("dplyr")) {
+#'
 #'   # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
-#'   example_isolates %>% 
+#'   example_isolates %>%
 #'     select(mo, aminoglycosides())
-#'     
-#'  # any() and all() work in dplyr's filter() too:
-#'  example_isolates %>% 
-#'     filter(any(aminoglycosides() == "R"),
-#'            all(cephalosporins_2nd() == "R"))
-#'     
-#'  # also works with c():
-#'  example_isolates %>% 
+#' }
+#' if (require("dplyr")) {
+#'
+#'   # any() and all() work in dplyr's filter() too:
+#'   example_isolates %>%
+#'     filter(
+#'       any(aminoglycosides() == "R"),
+#'       all(cephalosporins_2nd() == "R")
+#'     )
+#' }
+#' if (require("dplyr")) {
+#'
+#'   # also works with c():
+#'   example_isolates %>%
 #'     filter(any(c(carbapenems(), aminoglycosides()) == "R"))
-#'     
-#'  # not setting any/all will automatically apply all():
-#'  example_isolates %>% 
+#' }
+#' if (require("dplyr")) {
+#'
+#'   # not setting any/all will automatically apply all():
+#'   example_isolates %>%
 #'     filter(aminoglycosides() == "R")
-#'  #> i Assuming a filter on all 4 aminoglycosides.
-#'     
+#' }
+#' if (require("dplyr")) {
+#'
 #'   # this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
-#'   example_isolates %>% 
+#'   example_isolates %>%
 #'     select(mo, ab_class("mycobact"))
-#'     
-#'   # get bug/drug combinations for only macrolides in Gram-positives:
-#'   example_isolates %>% 
-#'     filter(mo_is_gram_positive()) %>% 
-#'     select(mo, macrolides()) %>% 
+#' }
+#' if (require("dplyr")) {
+#'
+#'   # get bug/drug combinations for only glycopeptides in Gram-positives:
+#'   example_isolates %>%
+#'     filter(mo_is_gram_positive()) %>%
+#'     select(mo, glycopeptides()) %>%
 #'     bug_drug_combinations() %>%
 #'     format()
-#'     
-#'   data.frame(some_column = "some_value",
-#'              J01CA01 = "S") %>%   # ATC code of ampicillin
-#'     select(penicillins())         # only the 'J01CA01' column will be selected
-#'     
-#'     
-#'   # with dplyr 1.0.0 and higher (that adds 'across()'), this is all equal:
-#'   example_isolates[carbapenems() == "R", ]
-#'   example_isolates %>% filter(carbapenems() == "R")
-#'   example_isolates %>% filter(across(carbapenems(), ~.x == "R"))
+#' }
+#' if (require("dplyr")) {
+#'   data.frame(
+#'     some_column = "some_value",
+#'     J01CA01 = "S"
+#'   ) %>% # ATC code of ampicillin
+#'     select(penicillins()) # only the 'J01CA01' column will be selected
+#' }
+#' if (require("dplyr")) {
+#'
+#'   # with recent versions of dplyr this is all equal:
+#'   x <- example_isolates[carbapenems() == "R", ]
+#'   y <- example_isolates %>% filter(carbapenems() == "R")
+#'   z <- example_isolates %>% filter(if_all(carbapenems(), ~ .x == "R"))
+#'   identical(x, y) && identical(y, z)
 #' }
 #' }
-ab_class <- function(ab_class, 
+ab_class <- function(ab_class,
                      only_rsi_columns = FALSE,
                      only_treatable = TRUE,
                      ...) {
@@ -170,30 +196,36 @@ ab_class <- function(ab_class,
 #' @rdname antibiotic_class_selectors
 #' @details The [ab_selector()] function can be used to internally filter the [antibiotics] data set on any results, see *Examples*. It allows for filtering on a (part of) a certain name, and/or a group name or even a minimum of DDDs for oral treatment. This function yields the highest flexibility, but is also the least user-friendly, since it requires a hard-coded filter to set.
 #' @export
-ab_selector <- function(filter, 
+ab_selector <- function(filter,
                         only_rsi_columns = FALSE,
                         only_treatable = TRUE,
                         ...) {
   meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
   meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
-  
+
   # get_current_data() has to run each time, for cases where e.g., filter() and select() are used in same call
   # but it only takes a couple of milliseconds
   vars_df <- get_current_data(arg_name = NA, call = -2)
   # 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, fn = "ab_selector")
+  ab_in_data <- get_column_abx(vars_df,
+    info = FALSE, only_rsi_columns = only_rsi_columns,
+    sort = FALSE, fn = "ab_selector"
+  )
   call <- substitute(filter)
   agents <- tryCatch(AMR::antibiotics[which(eval(call, envir = AMR::antibiotics)), "ab", drop = TRUE],
-                     error = function(e) stop_(e$message, call = -5))
+    error = function(e) stop_(e$message, call = -5)
+  )
   agents <- ab_in_data[ab_in_data %in% agents]
-  message_agent_names(function_name = "ab_selector", 
-                      agents = agents,
-                      ab_group = NULL,
-                      examples = "",
-                      call = call)
+  message_agent_names(
+    function_name = "ab_selector",
+    agents = agents,
+    ab_group = NULL,
+    examples = "",
+    call = call
+  )
   structure(unname(agents),
-            class = c("ab_selector", "character"))
+    class = c("ab_selector", "character")
+  )
 }
 
 #' @rdname antibiotic_class_selectors
@@ -384,24 +416,34 @@ administrable_per_os <- function(only_rsi_columns = FALSE, ...) {
   # but it only takes a couple of milliseconds
   vars_df <- get_current_data(arg_name = NA, call = -2)
   # 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, fn = "administrable_per_os")
+  ab_in_data <- get_column_abx(vars_df,
+    info = FALSE, only_rsi_columns = only_rsi_columns,
+    sort = FALSE, fn = "administrable_per_os"
+  )
   agents_all <- antibiotics[which(!is.na(antibiotics$oral_ddd)), "ab", drop = TRUE]
   agents <- antibiotics[which(antibiotics$ab %in% ab_in_data & !is.na(antibiotics$oral_ddd)), "ab", drop = TRUE]
   agents <- ab_in_data[ab_in_data %in% agents]
-  message_agent_names(function_name = "administrable_per_os", 
-                      agents = agents,
-                      ab_group = "administrable_per_os",
-                      examples = paste0(" (such as ", 
-                                        vector_or(ab_name(sample(agents_all,
-                                                                 size = min(5, length(agents_all)),
-                                                                 replace = FALSE),
-                                                          tolower = TRUE,
-                                                          language = NULL),
-                                                  quotes = FALSE), 
-                                        ")"))
+  message_agent_names(
+    function_name = "administrable_per_os",
+    agents = agents,
+    ab_group = "administrable_per_os",
+    examples = paste0(
+      " (such as ",
+      vector_or(ab_name(sample(agents_all,
+        size = min(5, length(agents_all)),
+        replace = FALSE
+      ),
+      tolower = TRUE,
+      language = NULL
+      ),
+      quotes = FALSE
+      ),
+      ")"
+    )
+  )
   structure(unname(agents),
-            class = c("ab_selector", "character"))
+    class = c("ab_selector", "character")
+  )
 }
 
 #' @rdname antibiotic_class_selectors
@@ -412,17 +454,22 @@ administrable_iv <- function(only_rsi_columns = FALSE, ...) {
   # but it only takes a couple of milliseconds
   vars_df <- get_current_data(arg_name = NA, call = -2)
   # 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, fn = "administrable_iv")
+  ab_in_data <- get_column_abx(vars_df,
+    info = FALSE, only_rsi_columns = only_rsi_columns,
+    sort = FALSE, fn = "administrable_iv"
+  )
   agents_all <- antibiotics[which(!is.na(antibiotics$iv_ddd)), "ab", drop = TRUE]
   agents <- antibiotics[which(antibiotics$ab %in% ab_in_data & !is.na(antibiotics$iv_ddd)), "ab", drop = TRUE]
   agents <- ab_in_data[ab_in_data %in% agents]
-  message_agent_names(function_name = "administrable_iv", 
-                      agents = agents,
-                      ab_group = "administrable_iv",
-                      examples = "")
+  message_agent_names(
+    function_name = "administrable_iv",
+    agents = agents,
+    ab_group = "administrable_iv",
+    examples = ""
+  )
   structure(unname(agents),
-            class = c("ab_selector", "character"))
+    class = c("ab_selector", "character")
+  )
 }
 
 #' @rdname antibiotic_class_selectors
@@ -435,35 +482,47 @@ not_intrinsic_resistant <- function(only_rsi_columns = FALSE, col_mo = NULL, ver
   # but it only takes a couple of milliseconds
   vars_df <- get_current_data(arg_name = NA, call = -2)
   # 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, fn = "not_intrinsic_resistant")
+  ab_in_data <- get_column_abx(vars_df,
+    info = FALSE, only_rsi_columns = only_rsi_columns,
+    sort = FALSE, fn = "not_intrinsic_resistant"
+  )
   # intrinsic vars
-  vars_df_R <- tryCatch(sapply(eucast_rules(vars_df,
-                                            col_mo = col_mo,
-                                            version_expertrules = version_expertrules,
-                                            rules = "expert",
-                                            info = FALSE),
-                               function(col) tryCatch(!any(is.na(col)) && all(col == "R"),
-                                                      error = function(e) FALSE)),
-                        error = function(e) stop_("in not_intrinsic_resistant(): ", e$message, call = FALSE))
-  
+  vars_df_R <- tryCatch(sapply(
+    eucast_rules(vars_df,
+      col_mo = col_mo,
+      version_expertrules = version_expertrules,
+      rules = "expert",
+      info = FALSE
+    ),
+    function(col) {
+      tryCatch(!any(is.na(col)) && all(col == "R"),
+        error = function(e) FALSE
+      )
+    }
+  ),
+  error = function(e) stop_("in not_intrinsic_resistant(): ", e$message, call = FALSE)
+  )
+
   agents <- ab_in_data[ab_in_data %in% names(vars_df_R[which(vars_df_R)])]
   if (length(agents) > 0 &&
-      message_not_thrown_before("not_intrinsic_resistant", sort(agents))) {
+    message_not_thrown_before("not_intrinsic_resistant", sort(agents))) {
     agents_formatted <- paste0("'", font_bold(agents, collapse = NULL), "'")
     agents_names <- ab_name(names(agents), tolower = TRUE, language = NULL)
     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 `not_intrinsic_resistant()` removing ",
-             ifelse(length(agents) == 1, "column ", "columns "),
-             vector_and(agents_formatted, quotes = FALSE, sort = FALSE))
+    message_(
+      "For `not_intrinsic_resistant()` removing ",
+      ifelse(length(agents) == 1, "column ", "columns "),
+      vector_and(agents_formatted, quotes = FALSE, sort = FALSE)
+    )
   }
-  
+
   vars_df_R <- names(vars_df_R)[which(!vars_df_R)]
   # find columns that are abx, but also intrinsic R
   out <- unname(intersect(ab_in_data, vars_df_R))
   structure(out,
-            class = c("ab_selector", "character"))
+    class = c("ab_selector", "character")
+  )
 }
 
 ab_select_exec <- function(function_name,
@@ -474,61 +533,74 @@ ab_select_exec <- function(function_name,
   # but it only takes a couple of milliseconds
   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, fn = function_name)
+  ab_in_data <- get_column_abx(vars_df,
+    info = FALSE, only_rsi_columns = only_rsi_columns,
+    sort = FALSE, fn = function_name
+  )
   # untreatable drugs
   if (only_treatable == TRUE) {
     untreatable <- antibiotics[which(antibiotics$name %like% "-high|EDTA|polysorbate|macromethod|screening|/nacubactam"), "ab", drop = TRUE]
     if (any(untreatable %in% names(ab_in_data))) {
       if (message_not_thrown_before(function_name, "ab_class", "untreatable", entire_session = TRUE)) {
-        warning_("in `", function_name, "()`: some agents were ignored since they cannot be used for treating patients: ",
-                 vector_and(ab_name(names(ab_in_data)[names(ab_in_data) %in% untreatable],
-                                    language = NULL,
-                                    tolower = TRUE),
-                            quotes = FALSE,
-                            sort = TRUE), ". They can be included using `", function_name, "(only_treatable = FALSE)`. ",
-                 "This warning will be shown once per session.")
+        warning_(
+          "in `", function_name, "()`: some agents were ignored since they cannot be used for treating patients: ",
+          vector_and(ab_name(names(ab_in_data)[names(ab_in_data) %in% untreatable],
+            language = NULL,
+            tolower = TRUE
+          ),
+          quotes = FALSE,
+          sort = TRUE
+          ), ". They can be included using `", function_name, "(only_treatable = FALSE)`. ",
+          "This warning will be shown once per session."
+        )
       }
       ab_in_data <- ab_in_data[!names(ab_in_data) %in% untreatable]
     }
   }
-  
+
   if (length(ab_in_data) == 0) {
     message_("No antimicrobial agents found in the data.")
     return(NULL)
   }
-  
+
   if (is.null(ab_class_args)) {
-    # their upper case equivalent are vectors with class <ab>, created in data-raw/_internals.R
+    # their upper case equivalent are vectors with class <ab>, created in data-raw/_pre_commit_hook.R
     # carbapenems() gets its codes from AMR:::AB_CARBAPENEMS
-    abx <- get(paste0("AB_", toupper(function_name)), envir = asNamespace("AMR"))  
+    abx <- get(paste0("AB_", toupper(function_name)), envir = asNamespace("AMR"))
     ab_group <- function_name
     examples <- paste0(" (such as ", vector_or(ab_name(sample(abx, size = min(2, length(abx)), replace = FALSE),
-                                                       tolower = TRUE,
-                                                       language = NULL),
-                                               quotes = FALSE), ")")
+      tolower = TRUE,
+      language = NULL
+    ),
+    quotes = FALSE
+    ), ")")
   } else {
     # this for the 'manual' ab_class() function
-    abx <- subset(AB_lookup,
-                  group %like% ab_class_args |
-                    atc_group1 %like% ab_class_args |
-                    atc_group2 %like% ab_class_args)$ab
+    abx <- subset(
+      AB_lookup,
+      group %like% ab_class_args |
+        atc_group1 %like% ab_class_args |
+        atc_group2 %like% ab_class_args
+    )$ab
     ab_group <- find_ab_group(ab_class_args)
     function_name <- "ab_class"
     examples <- paste0(" (such as ", find_ab_names(ab_class_args, 2), ")")
   }
-  
+
   # get the columns with a group names in the chosen ab class
   agents <- ab_in_data[names(ab_in_data) %in% abx]
-  
-  message_agent_names(function_name = function_name, 
-                      agents = agents,
-                      ab_group = ab_group,
-                      examples = examples,
-                      ab_class_args = ab_class_args)
-  
+
+  message_agent_names(
+    function_name = function_name,
+    agents = agents,
+    ab_group = ab_group,
+    examples = examples,
+    ab_class_args = ab_class_args
+  )
+
   structure(unname(agents),
-            class = c("ab_selector", "character"))
+    class = c("ab_selector", "character")
+  )
 }
 
 #' @method c ab_selector
@@ -536,7 +608,8 @@ ab_select_exec <- function(function_name,
 #' @noRd
 c.ab_selector <- function(...) {
   structure(unlist(lapply(list(...), as.character)),
-            class = c("ab_selector", "character"))
+    class = c("ab_selector", "character")
+  )
 }
 
 all_any_ab_selector <- function(type, ..., na.rm = TRUE) {
@@ -548,18 +621,20 @@ all_any_ab_selector <- function(type, ..., na.rm = TRUE) {
   }
   cols_ab <- cols_ab[!cols_ab %in% result]
   df <- get_current_data(arg_name = NA, call = -3)
-  
+
   if (type == "all") {
     scope_fn <- all
   } else {
     scope_fn <- any
   }
-  
+
   x_transposed <- as.list(as.data.frame(t(df[, cols_ab, drop = FALSE]), stringsAsFactors = FALSE))
-  vapply(FUN.VALUE = logical(1),
-         X = x_transposed,
-         FUN = function(y) scope_fn(y %in% result, na.rm = na.rm),
-         USE.NAMES = FALSE)
+  vapply(
+    FUN.VALUE = logical(1),
+    X = x_transposed,
+    FUN = function(y) scope_fn(y %in% result, na.rm = na.rm),
+    USE.NAMES = FALSE
+  )
 }
 
 #' @method all ab_selector
@@ -619,12 +694,15 @@ any.ab_selector_any_all <- function(..., na.rm = FALSE) {
   } else {
     type <- "all"
     if (length(e1) > 1) {
-      message_("Assuming a filter on ", type, " ", length(e1), " ", gsub("[\\(\\)]", "", fn_name),
-               ". Wrap around `all()` or `any()` to prevent this note.")
+      message_(
+        "Assuming a filter on ", type, " ", length(e1), " ", gsub("[\\(\\)]", "", fn_name),
+        ". Wrap around `all()` or `any()` to prevent this note."
+      )
     }
   }
   structure(all_any_ab_selector(type = type, e1, e2),
-            class = c("ab_selector_any_all", "logical"))
+    class = c("ab_selector_any_all", "logical")
+  )
 }
 
 #' @method != ab_selector
@@ -641,15 +719,18 @@ any.ab_selector_any_all <- function(..., na.rm = FALSE) {
   } else {
     type <- "all"
     if (length(e1) > 1) {
-      message_("Assuming a filter on ", type, " ", length(e1), " ", gsub("[\\(\\)]", "", fn_name),
-               ". Wrap around `all()` or `any()` to prevent this note.")
+      message_(
+        "Assuming a filter on ", type, " ", length(e1), " ", gsub("[\\(\\)]", "", fn_name),
+        ". Wrap around `all()` or `any()` to prevent this note."
+      )
     }
   }
   # this is `!=`, so turn around the values
   rsi <- c("R", "S", "I")
   e2 <- rsi[rsi != e2]
   structure(all_any_ab_selector(type = type, e1, e2),
-            class = c("ab_selector_any_all", "logical"))
+    class = c("ab_selector_any_all", "logical")
+  )
 }
 
 #' @method & ab_selector
@@ -659,7 +740,8 @@ any.ab_selector_any_all <- function(..., na.rm = FALSE) {
   # this is only required for base R, since tidyselect has already implemented this
   # e.g., for: example_isolates[, penicillins() & administrable_per_os()]
   structure(intersect(unclass(e1), unclass(e2)),
-            class = c("ab_selector", "character"))
+    class = c("ab_selector", "character")
+  )
 }
 #' @method | ab_selector
 #' @export
@@ -668,7 +750,8 @@ any.ab_selector_any_all <- function(..., na.rm = FALSE) {
   # this is only required for base R, since tidyselect has already implemented this
   # e.g., for: example_isolates[, penicillins() | administrable_per_os()]
   structure(union(unclass(e1), unclass(e2)),
-            class = c("ab_selector", "character"))
+    class = c("ab_selector", "character")
+  )
 }
 
 is_any <- function(el1) {
@@ -685,38 +768,40 @@ is_all <- function(el1) {
 find_ab_group <- function(ab_class_args) {
   ab_class_args <- gsub("[^a-zA-Z0-9]", ".*", ab_class_args)
   AB_lookup %pm>%
-    subset(group %like% ab_class_args | 
-             atc_group1 %like% ab_class_args | 
-             atc_group2 %like% ab_class_args) %pm>%
+    subset(group %like% ab_class_args |
+      atc_group1 %like% ab_class_args |
+      atc_group2 %like% ab_class_args) %pm>%
     pm_pull(group) %pm>%
     unique() %pm>%
     tolower() %pm>%
-    sort() %pm>% 
+    sort() %pm>%
     paste(collapse = "/")
 }
 
 find_ab_names <- function(ab_group, n = 3) {
   ab_group <- gsub("[^a-zA-Z|0-9]", ".*", ab_group)
-  
+
   # try popular first, they have DDDs
   drugs <- antibiotics[which((!is.na(antibiotics$iv_ddd) | !is.na(antibiotics$oral_ddd)) &
-                               antibiotics$name %unlike% " " &
-                               antibiotics$group %like% ab_group &
-                               antibiotics$ab %unlike% "[0-9]$"), ]$name
+    antibiotics$name %unlike% " " &
+    antibiotics$group %like% ab_group &
+    antibiotics$ab %unlike% "[0-9]$"), ]$name
   if (length(drugs) < n) {
     # now try it all
     drugs <- antibiotics[which((antibiotics$group %like% ab_group |
-                                  antibiotics$atc_group1 %like% ab_group |
-                                  antibiotics$atc_group2 %like% ab_group) &
-                                 antibiotics$ab %unlike% "[0-9]$"), ]$name
+      antibiotics$atc_group1 %like% ab_group |
+      antibiotics$atc_group2 %like% ab_group) &
+      antibiotics$ab %unlike% "[0-9]$"), ]$name
   }
   if (length(drugs) == 0) {
     return("??")
   }
   vector_or(ab_name(sample(drugs, size = min(n, length(drugs)), replace = FALSE),
-                    tolower = TRUE,
-                    language = NULL),
-            quotes = FALSE)
+    tolower = TRUE,
+    language = NULL
+  ),
+  quotes = FALSE
+  )
 }
 
 message_agent_names <- function(function_name, agents, ab_group = NULL, examples = "", ab_class_args = NULL, call = NULL) {
@@ -736,15 +821,19 @@ message_agent_names <- function(function_name, agents, ab_group = NULL, examples
       agents_names <- ab_name(names(agents), tolower = TRUE, language = NULL)
       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_args, "\""),
-                      ifelse(!is.null(call),
-                             paste0(deparse(call), collapse = " "),
-                             "")),
-               ")` using ",
-               ifelse(length(agents) == 1, "column ", "columns "),
-               vector_and(agents_formatted, quotes = FALSE, sort = FALSE))
+      message_(
+        "For `", function_name, "(",
+        ifelse(function_name == "ab_class",
+          paste0("\"", ab_class_args, "\""),
+          ifelse(!is.null(call),
+            paste0(deparse(call), collapse = " "),
+            ""
+          )
+        ),
+        ")` using ",
+        ifelse(length(agents) == 1, "column ", "columns "),
+        vector_and(agents_formatted, quotes = FALSE, sort = FALSE)
+      )
     }
   }
 }

R/age.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -25,35 +25,38 @@
 
 #' Age in Years of Individuals
 #'
-#' Calculates age in years based on a reference date, which is the sytem date at default.
-#' @inheritSection lifecycle Stable Lifecycle
+#' Calculates age in years based on a reference date, which is the system date at default.
 #' @param x date(s), [character] (vectors) will be coerced with [as.POSIXlt()]
 #' @param reference reference date(s) (defaults to today), [character] (vectors) will be coerced with [as.POSIXlt()]
 #' @param exact a [logical] to indicate whether age calculation should be exact, i.e. with decimals. It divides the number of days of [year-to-date](https://en.wikipedia.org/wiki/Year-to-date) (YTD) of `x` by the number of days in the year of `reference` (either 365 or 366).
 #' @param na.rm a [logical] to indicate whether missing values should be removed
 #' @param ... arguments passed on to [as.POSIXlt()], such as `origin`
 #' @details Ages below 0 will be returned as `NA` with a warning. Ages above 120 will only give a warning.
-#' 
+#'
 #' This function vectorises over both `x` and `reference`, meaning that either can have a length of 1 while the other argument has a larger length.
 #' @return An [integer] (no decimals) if `exact = FALSE`, a [double] (with decimals) otherwise
 #' @seealso To split ages into groups, use the [age_groups()] function.
-#' @inheritSection AMR Read more on Our Website!
 #' @export
 #' @examples
-#' # 10 random birth dates
-#' df <- data.frame(birth_date = Sys.Date() - runif(10) * 25000)
+#' # 10 random pre-Y2K birth dates
+#' df <- data.frame(birth_date = as.Date("2000-01-01") - runif(10) * 25000)
+#'
 #' # add ages
 #' df$age <- age(df$birth_date)
+#'
 #' # add exact ages
 #' df$age_exact <- age(df$birth_date, exact = TRUE)
 #'
+#' # add age at millenium switch
+#' df$age_at_y2k <- age(df$birth_date, "2000-01-01")
+#'
 #' df
 age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
   meet_criteria(x, allow_class = c("character", "Date", "POSIXt"))
   meet_criteria(reference, allow_class = c("character", "Date", "POSIXt"))
   meet_criteria(exact, allow_class = "logical", has_length = 1)
   meet_criteria(na.rm, allow_class = "logical", has_length = 1)
-  
+
   if (length(x) != length(reference)) {
     if (length(x) == 1) {
       x <- rep(x, length(reference))
@@ -65,26 +68,32 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
   }
   x <- as.POSIXlt(x, ...)
   reference <- as.POSIXlt(reference, ...)
-  
+
   # from https://stackoverflow.com/a/25450756/4575331
   years_gap <- reference$year - x$year
   ages <- ifelse(reference$mon < x$mon | (reference$mon == x$mon & reference$mday < x$mday),
-                 as.integer(years_gap - 1),
-                 as.integer(years_gap))
-  
+    as.integer(years_gap - 1),
+    as.integer(years_gap)
+  )
+
   # add decimals
   if (exact == TRUE) {
     # get dates of `x` when `x` would have the year of `reference`
-    x_in_reference_year <- as.POSIXlt(paste0(format(as.Date(reference), "%Y"),
-                                             format(as.Date(x), "-%m-%d")),
-                                      format = "%Y-%m-%d")
+    x_in_reference_year <- as.POSIXlt(paste0(
+      format(as.Date(reference), "%Y"),
+      format(as.Date(x), "-%m-%d")
+    ),
+    format = "%Y-%m-%d"
+    )
     # get differences in days
-    n_days_x_rest <- as.double(difftime(as.Date(reference), 
-                                        as.Date(x_in_reference_year),
-                                        units = "days"))
+    n_days_x_rest <- as.double(difftime(as.Date(reference),
+      as.Date(x_in_reference_year),
+      units = "days"
+    ))
     # get numbers of days the years of `reference` has for a reliable denominator
     n_days_reference_year <- as.POSIXlt(paste0(format(as.Date(reference), "%Y"), "-12-31"),
-                                        format = "%Y-%m-%d")$yday + 1
+      format = "%Y-%m-%d"
+    )$yday + 1
     # add decimal parts of year
     mod <- n_days_x_rest / n_days_reference_year
     # negative mods are cases where `x_in_reference_year` > `reference` - so 'add' a year
@@ -92,7 +101,7 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
     # and finally add to ages
     ages <- ages + mod
   }
-  
+
   if (any(ages < 0, na.rm = TRUE)) {
     ages[!is.na(ages) & ages < 0] <- NA
     warning_("in `age()`: NAs introduced for ages below 0.")
@@ -100,11 +109,11 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
   if (any(ages > 120, na.rm = TRUE)) {
     warning_("in `age()`: some ages are above 120.")
   }
-  
+
   if (isTRUE(na.rm)) {
     ages <- ages[!is.na(ages)]
   }
-  
+
   if (exact == TRUE) {
     as.double(ages)
   } else {
@@ -115,12 +124,11 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
 #' Split Ages into Age Groups
 #'
 #' Split ages into age groups defined by the `split` argument. This allows for easier demographic (antimicrobial resistance) analysis.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x age, e.g. calculated with [age()]
 #' @param split_at values to split `x` at, defaults to age groups 0-11, 12-24, 25-54, 55-74 and 75+. See *Details*.
 #' @param na.rm a [logical] to indicate whether missing values should be removed
 #' @details To split ages, the input for the `split_at` argument can be:
-#' 
+#'
 #' * A [numeric] vector. A value of e.g. `c(10, 20)` will split `x` on 0-9, 10-19 and 20+. A value of only `50` will split `x` on 0-49 and 50+.
 #'   The default is to split on young children (0-11), youth (12-24), young adults (25-54), middle-aged adults (55-74) and elderly (75+).
 #' * A character:
@@ -131,7 +139,7 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
 #' @return Ordered [factor]
 #' @seealso To determine ages, based on one or more reference dates, use the [age()] function.
 #' @export
-#' @inheritSection AMR Read more on Our Website!
+
 #' @examples
 #' ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)
 #'
@@ -150,7 +158,7 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
 #' age_groups(ages, split_at = "fives")
 #'
 #' # split specifically for children
-#' age_groups(ages, c(1, 2, 4, 6, 13, 17))
+#' age_groups(ages, c(1, 2, 4, 6, 13, 18))
 #' age_groups(ages, "children")
 #'
 #' \donttest{
@@ -158,17 +166,22 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
 #' if (require("dplyr")) {
 #'   example_isolates %>%
 #'     filter_first_isolate() %>%
-#'     filter(mo == as.mo("E. coli")) %>%
+#'     filter(mo == as.mo("Escherichia coli")) %>%
 #'     group_by(age_group = age_groups(age)) %>%
 #'     select(age_group, CIP) %>%
-#'     ggplot_rsi(x = "age_group", minimum = 0)
+#'     ggplot_rsi(
+#'       x = "age_group",
+#'       minimum = 0,
+#'       x.title = "Age Group",
+#'       title = "Ciprofloxacin resistance per age group"
+#'     )
 #' }
 #' }
 age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
   meet_criteria(x, allow_class = c("numeric", "integer"), is_positive_or_zero = TRUE, is_finite = TRUE)
   meet_criteria(split_at, allow_class = c("numeric", "integer", "character"), is_positive_or_zero = TRUE, is_finite = TRUE)
-  meet_criteria(na.rm, allow_class = "logical", has_length = 1) 
-  
+  meet_criteria(na.rm, allow_class = "logical", has_length = 1)
+
   if (any(x < 0, na.rm = TRUE)) {
     x[x < 0] <- NA
     warning_("in `age_groups()`: NAs introduced for ages below 0.")
@@ -178,7 +191,7 @@ age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
     if (split_at %like% "^(child|kid|junior)") {
       split_at <- c(0, 1, 2, 4, 6, 13, 18)
     } else if (split_at %like% "^(elder|senior)") {
-      split_at <-  c(65, 75, 85)
+      split_at <- c(65, 75, 85)
     } else if (split_at %like% "^five") {
       split_at <- 1:20 * 5
     } else if (split_at %like% "^ten") {
@@ -192,7 +205,7 @@ age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
   }
   split_at <- split_at[!is.na(split_at)]
   stop_if(length(split_at) == 1, "invalid value for `split_at`") # only 0 is available
-  
+
   # turn input values to 'split_at' indices
   y <- x
   lbls <- split_at
@@ -201,15 +214,15 @@ age_groups <- function(x, split_at = c(12, 25, 55, 75), na.rm = FALSE) {
     # create labels
     lbls[i - 1] <- paste0(unique(c(split_at[i - 1], split_at[i] - 1)), collapse = "-")
   }
-  
+
   # last category
   lbls[length(lbls)] <- paste0(split_at[length(split_at)], "+")
-  
+
   agegroups <- factor(lbls[y], levels = lbls, ordered = TRUE)
-  
+
   if (isTRUE(na.rm)) {
     agegroups <- agegroups[!is.na(agegroups)]
   }
-  
+
   agegroups
 }

R/amr.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -28,9 +28,9 @@
 #' Welcome to the `AMR` package.
 #' @details
 #' `AMR` is a free, open-source and independent \R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
-#' 
+#'
 #' After installing this package, \R knows `r format_included_data_number(microorganisms)` distinct microbial species and all `r format_included_data_number(rbind(antibiotics[, "atc", drop = FALSE], antivirals[, "atc", drop = FALSE]))` antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.
-#' 
+#'
 #' This package is fully independent of any other \R package and works on Windows, macOS and Linux with all versions of \R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This \R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation.
 #'
 #' This package can be used for:
@@ -50,15 +50,13 @@
 #' - Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code
 #' - Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI
 #' - Principal component analysis for AMR
-#' 
-#' @section Reference Data Publicly Available:
-#' All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this `AMR` package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find [all download links on our website](https://msberends.github.io/AMR/articles/datasets.html), which is automatically updated with every code change.
-#' @section Read more on Our Website!:
-#' On our website <https://msberends.github.io/AMR/> you can find [a comprehensive tutorial](https://msberends.github.io/AMR/articles/AMR.html) about how to conduct AMR data analysis, the [complete documentation of all functions](https://msberends.github.io/AMR/reference/) and [an example analysis using WHONET data](https://msberends.github.io/AMR/articles/WHONET.html).
-#' @section Contact Us:
-#' For suggestions, comments or questions, please contact us at:
 #'
-#' Matthijs S. Berends \cr
+#' @section Reference Data Publicly Available:
+#' All data sets in this `AMR` package (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
+#' @section Contact Us:
+#' For suggestions, comments or questions, please contact us via:
+#'
+#' Dr. Matthijs S. Berends \cr
 #' m.s.berends \[at\] umcg \[dot\] nl \cr
 #' University of Groningen
 #' Department of Medical Microbiology and Infection Prevention \cr

R/atc_online.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' Get ATC Properties from WHOCC Website
 #'
 #' Gets data from the WHOCC website to determine properties of an Anatomical Therapeutic Chemical (ATC) (e.g. an antibiotic), such as the name, defined daily dose (DDD) or standard unit.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param atc_code a [character] (vector) with ATC code(s) of antibiotics, will be coerced with [as.ab()] and [ab_atc()] internally if not a valid ATC code
 #' @param property property of an ATC code. Valid values are `"ATC"`, `"Name"`, `"DDD"`, `"U"` (`"unit"`), `"Adm.R"`, `"Note"` and `groups`. For this last option, all hierarchical groups of an ATC code will be returned, see *Examples*.
 #' @param administration type of administration when using `property = "Adm.R"`, see *Details*
@@ -35,7 +34,7 @@
 #' @param ... arguments to pass on to `atc_property`
 #' @details
 #' Options for argument `administration`:
-#' 
+#'
 #' - `"Implant"` = Implant
 #' - `"Inhal"` = Inhalation
 #' - `"Instill"` = Instillation
@@ -48,28 +47,27 @@
 #' - `"V"` = vaginal
 #'
 #' Abbreviations of return values when using `property = "U"` (unit):
-#' 
+#'
 #' - `"g"` = gram
 #' - `"mg"` = milligram
-#' - `"mcg"`` = microgram
+#' - `"mcg"` = microgram
 #' - `"U"` = unit
 #' - `"TU"` = thousand units
 #' - `"MU"` = million units
 #' - `"mmol"` = millimole
 #' - `"ml"` = millilitre (e.g. eyedrops)
-#' 
+#'
 #' **N.B. This function requires an internet connection and only works if the following packages are installed: `curl`, `rvest`, `xml2`.**
 #' @export
 #' @rdname atc_online
-#' @inheritSection AMR Read more on Our Website!
 #' @source <https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/>
 #' @examples
 #' \donttest{
-#' if (requireNamespace("curl") && requireNamespace("rvest") && requireNamespace("xml2")) { 
+#' if (requireNamespace("curl") && requireNamespace("rvest") && requireNamespace("xml2")) {
 #'   # oral DDD (Defined Daily Dose) of amoxicillin
 #'   atc_online_property("J01CA04", "DDD", "O")
 #'   atc_online_ddd(ab_atc("amox"))
-#' 
+#'
 #'   # parenteral DDD (Defined Daily Dose) of amoxicillin
 #'   atc_online_property("J01CA04", "DDD", "P")
 #'
@@ -86,7 +84,7 @@ atc_online_property <- function(atc_code,
   meet_criteria(administration, allow_class = "character", has_length = 1)
   meet_criteria(url, allow_class = "character", has_length = 1, looks_like = "https?://")
   meet_criteria(url_vet, allow_class = "character", has_length = 1, looks_like = "https?://")
-  
+
   has_internet <- import_fn("has_internet", "curl")
   html_attr <- import_fn("html_attr", "rvest")
   html_children <- import_fn("html_children", "rvest")
@@ -95,20 +93,21 @@ atc_online_property <- function(atc_code,
   html_table <- import_fn("html_table", "rvest")
   html_text <- import_fn("html_text", "rvest")
   read_html <- import_fn("read_html", "xml2")
-  
+
   check_dataset_integrity()
-  
+
   if (!all(atc_code %in% unlist(antibiotics$atc))) {
     atc_code <- as.character(ab_atc(atc_code, only_first = TRUE))
   }
-  
+
   if (!has_internet()) {
     message_("There appears to be no internet connection, returning NA.",
-             add_fn = font_red,
-             as_note = FALSE)
+      add_fn = font_red,
+      as_note = FALSE
+    )
     return(rep(NA, length(atc_code)))
   }
-  
+
   property <- tolower(property)
   # also allow unit as property
   if (property == "unit") {
@@ -121,12 +120,11 @@ atc_online_property <- function(atc_code,
   } else {
     returnvalue <- rep(NA_character_, length(atc_code))
   }
-  
+
   progress <- progress_ticker(n = length(atc_code), 3)
   on.exit(close(progress))
-  
+
   for (i in seq_len(length(atc_code))) {
-    
     progress$tick()
 
     if (atc_code[i] %like% "^Q") {
@@ -136,19 +134,20 @@ atc_online_property <- function(atc_code,
       atc_url <- url
     }
     atc_url <- sub("%s", atc_code[i], atc_url, fixed = TRUE)
-    
+
     if (property == "groups") {
       out <- tryCatch(
         read_html(atc_url) %pm>%
           html_node("#content") %pm>%
           html_children() %pm>%
-          html_node("a"), 
-        error = function(e) NULL)
+          html_node("a"),
+        error = function(e) NULL
+      )
       if (is.null(out)) {
         message_("Connection to ", atc_url, " failed.")
         return(rep(NA, length(atc_code)))
       }
-      
+
       # get URLS of items
       hrefs <- out %pm>% html_attr("href")
       # get text of items
@@ -158,50 +157,50 @@ atc_online_property <- function(atc_code,
       # last one is antibiotics, skip it
       texts <- texts[seq_len(length(texts)) - 1]
       returnvalue <- c(list(texts), returnvalue)
-      
     } else {
       out <- tryCatch(
         read_html(atc_url) %pm>%
           html_nodes("table") %pm>%
           html_table(header = TRUE) %pm>%
-          as.data.frame(stringsAsFactors = FALSE), 
-        error = function(e) NULL)
+          as.data.frame(stringsAsFactors = FALSE),
+        error = function(e) NULL
+      )
       if (is.null(out)) {
         message_("Connection to ", atc_url, " failed.")
         return(rep(NA, length(atc_code)))
       }
-      
+
       # case insensitive column names
       colnames(out) <- gsub("^atc.*", "atc", tolower(colnames(out)))
-      
+
       if (length(out) == 0) {
         warning_("in `atc_online_property()`: ATC not found: ", atc_code[i], ". Please check ", atc_url, ".")
         returnvalue[i] <- NA
         next
       }
-      
+
       if (property %in% c("atc", "name")) {
         # ATC and name are only in first row
-        returnvalue[i] <- out[1, property]
+        returnvalue[i] <- out[1, property, drop = TRUE]
       } else {
-        if (!"adm.r" %in% colnames(out) | is.na(out[1, "adm.r"])) {
+        if (!"adm.r" %in% colnames(out) | is.na(out[1, "adm.r", drop = TRUE])) {
           returnvalue[i] <- NA
           next
         } else {
           for (j in seq_len(nrow(out))) {
             if (out[j, "adm.r"] == administration) {
-              returnvalue[i] <- out[j, property]
+              returnvalue[i] <- out[j, property, drop = TRUE]
             }
           }
         }
       }
     }
   }
-  
+
   if (property == "groups" & length(returnvalue) == 1) {
     returnvalue <- returnvalue[[1]]
   }
-  
+
   returnvalue
 }
 

R/availability.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,19 +26,17 @@
 #' Check Availability of Columns
 #'
 #' Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. [susceptibility()] and [resistance()].
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param tbl a [data.frame] or [list]
 #' @param width number of characters to present the visual availability, defaults to filling the width of the console
 #' @details The function returns a [data.frame] with columns `"resistant"` and `"visual_resistance"`. The values in that columns are calculated with [resistance()].
 #' @return [data.frame] with column names of `tbl` as row names
-#' @inheritSection AMR Read more on Our Website!
 #' @export
 #' @examples
 #' availability(example_isolates)
 #' \donttest{
 #' if (require("dplyr")) {
 #'   example_isolates %>%
-#'     filter(mo == as.mo("E. coli")) %>%
+#'     filter(mo == as.mo("Escherichia coli")) %>%
 #'     select_if(is.rsi) %>%
 #'     availability()
 #' }
@@ -46,50 +44,54 @@
 availability <- function(tbl, width = NULL) {
   meet_criteria(tbl, allow_class = "data.frame")
   meet_criteria(width, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
-  
+
+  tbl <- as.data.frame(tbl, stringsAsFactors = FALSE)
+
   x <- vapply(FUN.VALUE = double(1), tbl, function(x) {
-    1 - sum(is.na(x)) / length(x) 
+    1 - sum(is.na(x)) / length(x)
   })
   n <- vapply(FUN.VALUE = double(1), tbl, function(x) length(x[!is.na(x)]))
   R <- vapply(FUN.VALUE = double(1), tbl, function(x) ifelse(is.rsi(x), resistance(x, minimum = 0), NA_real_))
   R_print <- character(length(R))
   R_print[!is.na(R)] <- percentage(R[!is.na(R)])
   R_print[is.na(R)] <- ""
-  
+
   if (is.null(width)) {
     width <- options()$width -
       (max(nchar(colnames(tbl))) +
-         # count col
-         8 +
-         # available % column
-         10 +
-         # resistant % column
-         10 +
-         # extra margin
-         5)
+        # count col
+        8 +
+        # available % column
+        10 +
+        # resistant % column
+        10 +
+        # extra margin
+        5)
     width <- width / 2
   }
-  
+
   if (length(R[is.na(R)]) == ncol(tbl)) {
     width <- width * 2 + 10
   }
-  
+
   x_chars_R <- strrep("#", round(width * R, digits = 2))
   x_chars_SI <- strrep("-", width - nchar(x_chars_R))
   vis_resistance <- paste0("|", x_chars_R, x_chars_SI, "|")
   vis_resistance[is.na(R)] <- ""
-  
+
   x_chars <- strrep("#", round(x, digits = 2) / (1 / width))
   x_chars_empty <- strrep("-", width - nchar(x_chars))
-  
-  df <- data.frame(count = n,
-                   available = percentage(x),
-                   visual_availabilty = paste0("|", x_chars, x_chars_empty, "|"),
-                   resistant = R_print,
-                   visual_resistance = vis_resistance,
-                   stringsAsFactors = FALSE)
+
+  df <- data.frame(
+    count = n,
+    available = percentage(x),
+    visual_availabilty = paste0("|", x_chars, x_chars_empty, "|"),
+    resistant = R_print,
+    visual_resistance = vis_resistance,
+    stringsAsFactors = FALSE
+  )
   if (length(R[is.na(R)]) == ncol(tbl)) {
-    df[, 1:3]
+    df[, 1:3, drop = FALSE]
   } else {
     df
   }

R/bug_drug_combinations.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -24,41 +24,44 @@
 # ==================================================================== #
 
 #' Determine Bug-Drug Combinations
-#' 
+#'
 #' Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use [format()] on the result to prettify it to a publishable/printable format, see *Examples*.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @inheritParams eucast_rules
 #' @param combine_IR a [logical] to indicate whether values R and I should be summed
 #' @param add_ab_group a [logical] to indicate where the group of the antimicrobials must be included as a first column
 #' @param remove_intrinsic_resistant [logical] to indicate that rows and columns with 100% resistance for all tested antimicrobials must be removed from the table
-#' @param FUN the function to call on the `mo` column to transform the microorganism codes, defaults to [mo_shortname()] 
+#' @param FUN the function to call on the `mo` column to transform the microorganism codes, defaults to [mo_shortname()]
 #' @param translate_ab a [character] of length 1 containing column names of the [antibiotics] data set
 #' @param ... arguments passed on to `FUN`
 #' @inheritParams rsi_df
 #' @inheritParams base::formatC
-#' @details The function [format()] calculates the resistance per bug-drug combination. Use `combine_IR = FALSE` (default) to test R vs. S+I and `combine_IR = TRUE` to test R+I vs. S. 
+#' @details The function [format()] calculates the resistance per bug-drug combination. Use `combine_IR = FALSE` (default) to test R vs. S+I and `combine_IR = TRUE` to test R+I vs. S.
 #' @export
 #' @rdname bug_drug_combinations
 #' @return The function [bug_drug_combinations()] returns a [data.frame] with columns "mo", "ab", "S", "I", "R" and "total".
 #' @source \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, *Clinical and Laboratory Standards Institute (CLSI)*. <https://clsi.org/standards/products/microbiology/documents/m39/>.
-#' @inheritSection AMR Read more on Our Website!
-#' @examples 
+#' @examples
 #' \donttest{
 #' x <- bug_drug_combinations(example_isolates)
-#' x
+#' head(x)
 #' format(x, translate_ab = "name (atc)")
-#' 
+#'
 #' # Use FUN to change to transformation of microorganism codes
-#' bug_drug_combinations(example_isolates, 
-#'                       FUN = mo_gramstain)
-#'                            
 #' bug_drug_combinations(example_isolates,
-#'                       FUN = function(x) ifelse(x == as.mo("E. coli"),
-#'                                                "E. coli",
-#'                                                "Others"))
+#'   FUN = mo_gramstain
+#' )
+#'
+#' bug_drug_combinations(example_isolates,
+#'   FUN = function(x) {
+#'     ifelse(x == as.mo("Escherichia coli"),
+#'       "E. coli",
+#'       "Others"
+#'     )
+#'   }
+#' )
 #' }
-bug_drug_combinations <- function(x, 
-                                  col_mo = NULL, 
+bug_drug_combinations <- function(x,
+                                  col_mo = NULL,
                                   FUN = mo_shortname,
                                   ...) {
   meet_criteria(x, allow_class = "data.frame", contains_column_class = "rsi")
@@ -73,13 +76,13 @@ bug_drug_combinations <- function(x,
   } else {
     stop_ifnot(col_mo %in% colnames(x), "column '", col_mo, "' (`col_mo`) not found")
   }
-  
+
   x.bak <- x
   x <- as.data.frame(x, stringsAsFactors = FALSE)
   x[, col_mo] <- FUN(x[, col_mo, drop = TRUE], ...)
-  
+
   unique_mo <- sort(unique(x[, col_mo, drop = TRUE]))
-  
+
   # select only groups and antibiotics
   if (is_null_or_grouped_tbl(x.bak)) {
     data_has_groups <- TRUE
@@ -89,21 +92,23 @@ bug_drug_combinations <- function(x,
     data_has_groups <- FALSE
     x <- x[, c(col_mo, names(which(vapply(FUN.VALUE = logical(1), x, is.rsi)))), drop = FALSE]
   }
-  
+
   run_it <- function(x) {
-    out <- data.frame(mo = character(0),
-                      ab = character(0),
-                      S = integer(0),
-                      I = integer(0),
-                      R = integer(0),
-                      total = integer(0),
-                      stringsAsFactors = FALSE)
+    out <- data.frame(
+      mo = character(0),
+      ab = character(0),
+      S = integer(0),
+      I = integer(0),
+      R = integer(0),
+      total = integer(0),
+      stringsAsFactors = FALSE
+    )
     if (data_has_groups) {
       group_values <- unique(x[, which(colnames(x) %in% groups), drop = FALSE])
       rownames(group_values) <- NULL
       x <- x[, which(!colnames(x) %in% groups), drop = FALSE]
     }
-    
+
     for (i in seq_len(length(unique_mo))) {
       # filter on MO group and only select R/SI columns
       x_mo_filter <- x[which(x[, col_mo, drop = TRUE] == unique_mo[i]), names(which(vapply(FUN.VALUE = logical(1), x, is.rsi))), drop = FALSE]
@@ -113,18 +118,21 @@ bug_drug_combinations <- function(x,
         data.frame(S = m["S", ], I = m["I", ], R = m["R", ], stringsAsFactors = FALSE)
       })
       merged <- do.call(rbind, pivot)
-      out_group <- data.frame(mo = rep(unique_mo[i], NROW(merged)),
-                              ab = rownames(merged),
-                              S = merged$S,
-                              I = merged$I,
-                              R = merged$R,
-                              total = merged$S + merged$I + merged$R,
-                              stringsAsFactors = FALSE)
+      out_group <- data.frame(
+        mo = rep(unique_mo[i], NROW(merged)),
+        ab = rownames(merged),
+        S = merged$S,
+        I = merged$I,
+        R = merged$R,
+        total = merged$S + merged$I + merged$R,
+        stringsAsFactors = FALSE
+      )
       if (data_has_groups) {
         if (nrow(group_values) < nrow(out_group)) {
           # repeat group_values for the number of rows in out_group
           repeated <- rep(seq_len(nrow(group_values)),
-                          each = nrow(out_group) / nrow(group_values))
+            each = nrow(out_group) / nrow(group_values)
+          )
           group_values <- group_values[repeated, , drop = FALSE]
         }
         out_group <- cbind(group_values, out_group)
@@ -143,18 +151,15 @@ bug_drug_combinations <- function(x,
     }
     res
   }
-  
+
   if (data_has_groups) {
     out <- apply_group(x, "run_it", groups)
-    rownames(out) <- NULL
-    set_clean_class(out,
-                    new_class = c("grouped", "bug_drug_combinations", "data.frame"))
   } else {
     out <- run_it(x)
-    rownames(out) <- NULL
-    set_clean_class(out,
-                    new_class = c("bug_drug_combinations", "data.frame"))
   }
+  rownames(out) <- NULL
+  out <- as_original_data_class(out, class(x.bak))
+  structure(out, class = c("bug_drug_combinations", ifelse(data_has_groups, "grouped", character(0)), class(out)))
 }
 
 #' @method format bug_drug_combinations
@@ -181,25 +186,31 @@ format.bug_drug_combinations <- function(x,
   meet_criteria(remove_intrinsic_resistant, allow_class = "logical", has_length = 1)
   meet_criteria(decimal.mark, allow_class = "character", has_length = 1)
   meet_criteria(big.mark, allow_class = "character", has_length = 1)
-  
+
+  x.bak <- x
   if (inherits(x, "grouped")) {
     # bug_drug_combinations() has been run on groups, so de-group here
     warning_("in `format()`: formatting the output of `bug_drug_combinations()` does not support grouped variables, they were ignored")
+    x <- as.data.frame(x, stringsAsFactors = FALSE)
     idx <- split(seq_len(nrow(x)), paste0(x$mo, "%%", x$ab))
-    x <- data.frame(mo = gsub("(.*)%%(.*)", "\\1", names(idx)),
-                    ab = gsub("(.*)%%(.*)", "\\2", names(idx)),
-                    S = sapply(idx, function(i) sum(y$S[i], na.rm = TRUE)), 
-                    I = sapply(idx, function(i) sum(y$I[i], na.rm = TRUE)), 
-                    R = sapply(idx, function(i) sum(y$R[i], na.rm = TRUE)),
-                    total = sapply(idx, function(i) sum(y$S[i], na.rm = TRUE) + 
-                                     sum(y$I[i], na.rm = TRUE) +
-                                     sum(y$R[i], na.rm = TRUE)),
-                    stringsAsFactors = FALSE)
+    x <- data.frame(
+      mo = gsub("(.*)%%(.*)", "\\1", names(idx)),
+      ab = gsub("(.*)%%(.*)", "\\2", names(idx)),
+      S = sapply(idx, function(i) sum(x$S[i], na.rm = TRUE)),
+      I = sapply(idx, function(i) sum(x$I[i], na.rm = TRUE)),
+      R = sapply(idx, function(i) sum(x$R[i], na.rm = TRUE)),
+      total = sapply(idx, function(i) {
+        sum(x$S[i], na.rm = TRUE) +
+          sum(x$I[i], na.rm = TRUE) +
+          sum(x$R[i], na.rm = TRUE)
+      }),
+      stringsAsFactors = FALSE
+    )
   }
-  
+
   x <- as.data.frame(x, stringsAsFactors = FALSE)
   x <- subset(x, total >= minimum)
-  
+
   if (remove_intrinsic_resistant == TRUE) {
     x <- subset(x, R != total)
   }
@@ -208,7 +219,7 @@ format.bug_drug_combinations <- function(x,
   } else {
     x$isolates <- x$R + x$I
   }
-  
+
   give_ab_name <- function(ab, format, language) {
     format <- tolower(format)
     ab_txt <- rep(format, length(ab))
@@ -224,15 +235,16 @@ format.bug_drug_combinations <- function(x,
     }
     ab_txt
   }
-  
+
   remove_NAs <- function(.data) {
     cols <- colnames(.data)
     .data <- as.data.frame(lapply(.data, function(x) ifelse(is.na(x), "", x)),
-                           stringsAsFactors = FALSE)
+      stringsAsFactors = FALSE
+    )
     colnames(.data) <- cols
     .data
   }
-  
+
   create_var <- function(.data, ...) {
     dots <- list(...)
     for (i in seq_len(length(dots))) {
@@ -240,78 +252,90 @@ format.bug_drug_combinations <- function(x,
     }
     .data
   }
-  
+
   y <- x %pm>%
-    create_var(ab = as.ab(x$ab),
-               ab_txt = give_ab_name(ab = x$ab, format = translate_ab, language = language)) %pm>%
-    pm_group_by(ab, ab_txt, mo) %pm>% 
-    pm_summarise(isolates = sum(isolates, na.rm = TRUE),
-              total = sum(total, na.rm = TRUE)) %pm>% 
+    create_var(
+      ab = as.ab(x$ab),
+      ab_txt = give_ab_name(ab = x$ab, format = translate_ab, language = language)
+    ) %pm>%
+    pm_group_by(ab, ab_txt, mo) %pm>%
+    pm_summarise(
+      isolates = sum(isolates, na.rm = TRUE),
+      total = sum(total, na.rm = TRUE)
+    ) %pm>%
     pm_ungroup()
-  
-  y <- y %pm>% 
-    create_var(txt = paste0(percentage(y$isolates / y$total, decimal.mark = decimal.mark, big.mark = big.mark), 
-                            " (", trimws(format(y$isolates, big.mark = big.mark)), "/",
-                            trimws(format(y$total, big.mark = big.mark)), ")")) %pm>% 
+
+  y <- y %pm>%
+    create_var(txt = paste0(
+      percentage(y$isolates / y$total, decimal.mark = decimal.mark, big.mark = big.mark),
+      " (", trimws(format(y$isolates, big.mark = big.mark)), "/",
+      trimws(format(y$total, big.mark = big.mark)), ")"
+    )) %pm>%
     pm_select(ab, ab_txt, mo, txt) %pm>%
     pm_arrange(mo)
-  
+
   # replace tidyr::pivot_wider() from here
   for (i in unique(y$mo)) {
-    mo_group <- y[which(y$mo == i), c("ab", "txt")]
+    mo_group <- y[which(y$mo == i), c("ab", "txt"), drop = FALSE]
     colnames(mo_group) <- c("ab", i)
     rownames(mo_group) <- NULL
-    y <- y %pm>% 
+    y <- y %pm>%
       pm_left_join(mo_group, by = "ab")
   }
-  y <- y %pm>% 
-    pm_distinct(ab, .keep_all = TRUE) %pm>% 
-    pm_select(-mo, -txt) %pm>% 
+  y <- y %pm>%
+    pm_distinct(ab, .keep_all = TRUE) %pm>%
+    pm_select(-mo, -txt) %pm>%
     # replace tidyr::pivot_wider() until here
     remove_NAs()
 
   select_ab_vars <- function(.data) {
-    .data[, c("ab_group", "ab_txt", colnames(.data)[!colnames(.data) %in% c("ab_group", "ab_txt", "ab")])]
+    .data[, c("ab_group", "ab_txt", colnames(.data)[!colnames(.data) %in% c("ab_group", "ab_txt", "ab")]), drop = FALSE]
   }
-  
-  y <- y %pm>% 
-    create_var(ab_group = ab_group(y$ab, language = language)) %pm>% 
-    select_ab_vars() %pm>% 
+
+  y <- y %pm>%
+    create_var(ab_group = ab_group(y$ab, language = language)) %pm>%
+    select_ab_vars() %pm>%
     pm_arrange(ab_group, ab_txt)
-  y <- y %pm>% 
+  y <- y %pm>%
     create_var(ab_group = ifelse(y$ab_group != pm_lag(y$ab_group) | is.na(pm_lag(y$ab_group)), y$ab_group, ""))
-  
+
   if (add_ab_group == FALSE) {
-    y <- y %pm>% 
+    y <- y %pm>%
       pm_select(-ab_group) %pm>%
       pm_rename("Drug" = ab_txt)
-    colnames(y)[1] <- translate_AMR(colnames(y)[1], language, only_unknown = FALSE)
+    colnames(y)[1] <- translate_into_language(colnames(y)[1], language, only_unknown = FALSE)
   } else {
-    y <- y %pm>% 
-      pm_rename("Group" = ab_group,
-                "Drug" = ab_txt)
+    y <- y %pm>%
+      pm_rename(
+        "Group" = ab_group,
+        "Drug" = ab_txt
+      )
   }
-  
+
   if (!is.null(language)) {
-    colnames(y) <- translate_AMR(colnames(y), language, only_unknown = FALSE)
+    colnames(y) <- translate_into_language(colnames(y), language, only_unknown = FALSE)
   }
-  
+
   if (remove_intrinsic_resistant == TRUE) {
     y <- y[, !vapply(FUN.VALUE = logical(1), y, function(col) all(col %like% "100", na.rm = TRUE) & !any(is.na(col))), drop = FALSE]
   }
-  
+
   rownames(y) <- NULL
-  y
+  as_original_data_class(y, class(x.bak))
 }
 
 #' @method print bug_drug_combinations
 #' @export
 print.bug_drug_combinations <- function(x, ...) {
   x_class <- class(x)
-  print(set_clean_class(x, 
-                        new_class = x_class[!x_class %in% c("bug_drug_combinations", "grouped")]),
-        ...)
+  print(
+    set_clean_class(x,
+      new_class = x_class[!x_class %in% c("bug_drug_combinations", "grouped")]
+    ),
+    ...
+  )
   message_("Use 'format()' on this result to get a publishable/printable format.",
-           ifelse(inherits(x, "grouped"), " Note: The grouping variable(s) will be ignored.", ""),
-           as_note = FALSE)
+    ifelse(inherits(x, "grouped"), " Note: The grouping variable(s) will be ignored.", ""),
+    as_note = FALSE
+  )
 }

R/catalogue_of_life.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -49,9 +49,9 @@ format_included_data_number <- function(data) {
 #' [Click here][catalogue_of_life] for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with [catalogue_of_life_version()].
 #' @section Included Taxa:
 #' Included are:
-#' - All `r format_included_data_number(microorganisms[which(microorganisms$kingdom %in% c("Archeae", "Bacteria", "Chromista", "Protozoa")), ])` (sub)species from the kingdoms of Archaea, Bacteria, Chromista and Protozoa
-#' - All `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Fungi" & microorganisms$order %in% c("Eurotiales", "Microascales", "Mucorales", "Onygenales", "Pneumocystales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales")), ])` (sub)species from these orders of the kingdom of Fungi: Eurotiales, Microascales, Mucorales, Onygenales, Pneumocystales, Saccharomycetales, Schizosaccharomycetales and Tremellales, as well as `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Fungi" & !microorganisms$order %in% c("Eurotiales", "Microascales", "Mucorales", "Onygenales", "Pneumocystales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales")), ])` other fungal (sub)species. The kingdom of Fungi is a very large taxon with almost 300,000 different (sub)species, of which most are not microbial (but rather macroscopic, like mushrooms). Because of this, not all fungi fit the scope of this package and including everything would tremendously slow down our algorithms too. By only including the aforementioned taxonomic orders, the most relevant fungi are covered (such as all species of *Aspergillus*, *Candida*, *Cryptococcus*, *Histplasma*, *Pneumocystis*, *Saccharomyces* and *Trichophyton*).
-#' - All `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Animalia"), ])` (sub)species from `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Animalia"), "genus"])` other relevant genera from the kingdom of Animalia (such as *Strongyloides* and *Taenia*)
+#' - All `r format_included_data_number(microorganisms[which(microorganisms$kingdom %in% c("Archeae", "Bacteria", "Chromista", "Protozoa")), , drop = FALSE])` (sub)species from the kingdoms of Archaea, Bacteria, Chromista and Protozoa
+#' - All `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Fungi" & microorganisms$order %in% c("Eurotiales", "Microascales", "Mucorales", "Onygenales", "Pneumocystales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales")), , drop = FALSE])` (sub)species from these orders of the kingdom of Fungi: Eurotiales, Microascales, Mucorales, Onygenales, Pneumocystales, Saccharomycetales, Schizosaccharomycetales and Tremellales, as well as `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Fungi" & !microorganisms$order %in% c("Eurotiales", "Microascales", "Mucorales", "Onygenales", "Pneumocystales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales")), ])` other fungal (sub)species. The kingdom of Fungi is a very large taxon with almost 300,000 different (sub)species, of which most are not microbial (but rather macroscopic, like mushrooms). Because of this, not all fungi fit the scope of this package and including everything would tremendously slow down our algorithms too. By only including the aforementioned taxonomic orders, the most relevant fungi are covered (such as all species of *Aspergillus*, *Candida*, *Cryptococcus*, *Histplasma*, *Pneumocystis*, *Saccharomyces* and *Trichophyton*).
+#' - All `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Animalia"), , drop = FALSE])` (sub)species from `r format_included_data_number(microorganisms[which(microorganisms$kingdom == "Animalia"), "genus", drop = TRUE])` other relevant genera from the kingdom of Animalia (such as *Strongyloides* and *Taenia*)
 #' - All `r format_included_data_number(microorganisms.old)` previously accepted names of all included (sub)species (these were taxonomically renamed)
 #' - The complete taxonomic tree of all included (sub)species: from kingdom to subspecies
 #' - The responsible author(s) and year of scientific publication
@@ -59,7 +59,6 @@ format_included_data_number <- function(data) {
 #' The Catalogue of Life (<http://www.catalogueoflife.org>) is the most comprehensive and authoritative global index of species currently available. It holds essential information on the names, relationships and distributions of over 1.9 million species. The Catalogue of Life is used to support the major biodiversity and conservation information services such as the Global Biodiversity Information Facility (GBIF), Encyclopedia of Life (EoL) and the International Union for Conservation of Nature Red List. It is recognised by the Convention on Biological Diversity as a significant component of the Global Taxonomy Initiative and a contribution to Target 1 of the Global Strategy for Plant Conservation.
 #'
 #' The syntax used to transform the original data to a cleansed \R format, can be found here: <https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R>.
-#' @inheritSection AMR Read more on Our Website!
 #' @name catalogue_of_life
 #' @rdname catalogue_of_life
 #' @seealso Data set [microorganisms] for the actual data. \cr
@@ -71,28 +70,19 @@ format_included_data_number <- function(data) {
 #'
 #' # Get a note when a species was renamed
 #' mo_shortname("Chlamydophila psittaci")
-#' # Note: 'Chlamydophila psittaci' (Everett et al., 1999) was renamed back to
-#' #       'Chlamydia psittaci' (Page, 1968)
-#' #> [1] "C. psittaci"
 #'
 #' # Get any property from the entire taxonomic tree for all included species
-#' mo_class("E. coli")
-#' #> [1] "Gammaproteobacteria"
+#' mo_class("Escherichia coli")
 #'
-#' mo_family("E. coli")
-#' #> [1] "Enterobacteriaceae"
+#' mo_family("Escherichia coli")
 #'
-#' mo_gramstain("E. coli") # based on kingdom and phylum, see ?mo_gramstain
-#' #> [1] "Gram-negative"
+#' mo_gramstain("Escherichia coli") # based on kingdom and phylum, see ?mo_gramstain
 #'
-#' mo_ref("E. coli")
-#' #> [1] "Castellani et al., 1919"
+#' mo_ref("Escherichia coli")
 #'
 #' # Do not get mistaken - this package is about microorganisms
 #' mo_kingdom("C. elegans")
-#' #> [1] "Fungi"                 # Fungi?!
 #' mo_name("C. elegans")
-#' #> [1] "Cladosporium elegans"  # Because a microorganism was found
 NULL
 
 #' Version info of included Catalogue of Life
@@ -102,44 +92,54 @@ NULL
 #' @details For LPSN, see [microorganisms].
 #' @return a [list], which prints in pretty format
 #' @inheritSection catalogue_of_life Catalogue of Life
-#' @inheritSection AMR Read more on Our Website!
 #' @export
 catalogue_of_life_version <- function() {
-  
   check_dataset_integrity()
-  
+
   # see the `CATALOGUE_OF_LIFE` list in R/globals.R
-  lst <- list(CoL =
-                list(version = gsub("{year}", CATALOGUE_OF_LIFE$year, CATALOGUE_OF_LIFE$version, fixed = TRUE),
-                     url = gsub("{year}", CATALOGUE_OF_LIFE$year, CATALOGUE_OF_LIFE$url_CoL, fixed = TRUE),
-                     n = nrow(pm_filter(microorganisms, source == "CoL"))),
-              LPSN =
-                list(version = "List of Prokaryotic names with Standing in Nomenclature",
-                     url = CATALOGUE_OF_LIFE$url_LPSN,
-                     yearmonth = CATALOGUE_OF_LIFE$yearmonth_LPSN,
-                     n = nrow(pm_filter(microorganisms, source == "LPSN"))),
-              total_included =
-                list(
-                  n_total_species = nrow(microorganisms),
-                  n_total_synonyms = nrow(microorganisms.old)))
-  
+  lst <- list(
+    CoL =
+      list(
+        version = gsub("{year}", CATALOGUE_OF_LIFE$year, CATALOGUE_OF_LIFE$version, fixed = TRUE),
+        url = gsub("{year}", CATALOGUE_OF_LIFE$year, CATALOGUE_OF_LIFE$url_CoL, fixed = TRUE),
+        n = nrow(pm_filter(microorganisms, source == "CoL"))
+      ),
+    LPSN =
+      list(
+        version = "List of Prokaryotic names with Standing in Nomenclature",
+        url = CATALOGUE_OF_LIFE$url_LPSN,
+        yearmonth = CATALOGUE_OF_LIFE$yearmonth_LPSN,
+        n = nrow(pm_filter(microorganisms, source == "LPSN"))
+      ),
+    total_included =
+      list(
+        n_total_species = nrow(microorganisms),
+        n_total_synonyms = nrow(microorganisms.old)
+      )
+  )
+
   set_clean_class(lst,
-                  new_class = c("catalogue_of_life_version", "list"))
+    new_class = c("catalogue_of_life_version", "list")
+  )
 }
 
 #' @method print catalogue_of_life_version
 #' @export
 #' @noRd
 print.catalogue_of_life_version <- function(x, ...) {
-  cat(paste0(font_bold("Included in this AMR package (v", utils::packageDescription("AMR")$Version, ") are:\n\n", collapse = ""),
-             font_underline(x$CoL$version), "\n",
-             "  Available at: ", font_blue(x$CoL$url), "\n",
-             "  Number of included microbial species: ", format(x$CoL$n, big.mark = ","), "\n",
-             font_underline(paste0(x$LPSN$version, " (",
-                                   x$LPSN$yearmonth, ")")), "\n",
-             "  Available at: ", font_blue(x$LPSN$url), "\n",
-             "  Number of included bacterial species: ", format(x$LPSN$n, big.mark = ","), "\n\n",
-             "=> Total number of species included:  ", format(x$total_included$n_total_species, big.mark = ","), "\n",
-             "=> Total number of synonyms included: ", format(x$total_included$n_total_synonyms, big.mark = ","), "\n\n",
-             "See for more info ", font_grey_bg("`?microorganisms`"), " and ", font_grey_bg("`?catalogue_of_life`"), ".\n"))
+  cat(paste0(
+    font_bold("Included in this AMR package (v", utils::packageDescription("AMR")$Version, ") are:\n\n", collapse = ""),
+    font_underline(x$CoL$version), "\n",
+    "  Available at: ", font_blue(x$CoL$url), "\n",
+    "  Number of included microbial species: ", format(x$CoL$n, big.mark = ","), "\n",
+    font_underline(paste0(
+      x$LPSN$version, " (",
+      x$LPSN$yearmonth, ")"
+    )), "\n",
+    "  Available at: ", font_blue(x$LPSN$url), "\n",
+    "  Number of included bacterial species: ", format(x$LPSN$n, big.mark = ","), "\n\n",
+    "=> Total number of species included:  ", format(x$total_included$n_total_species, big.mark = ","), "\n",
+    "=> Total number of synonyms included: ", format(x$total_included$n_total_synonyms, big.mark = ","), "\n\n",
+    "See for more info ", font_grey_bg("`?microorganisms`"), " and ", font_grey_bg("`?catalogue_of_life`"), ".\n"
+  ))
 }

R/count.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -28,12 +28,11 @@
 #' @description These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, see *Examples*.
 #'
 #' [count_resistant()] should be used to count resistant isolates, [count_susceptible()] should be used to count susceptible isolates.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with [as.rsi()] if needed.
 #' @inheritParams proportion
 #' @inheritSection as.rsi Interpretation of R and S/I
 #' @details These functions are meant to count isolates. Use the [resistance()]/[susceptibility()] functions to calculate microbial resistance/susceptibility.
-#' 
+#'
 #' The function [count_resistant()] is equal to the function [count_R()]. The function [count_susceptible()] is equal to the function [count_SI()].
 #'
 #' The function [n_rsi()] is an alias of [count_all()]. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to `n_distinct()`. Their function is equal to `count_susceptible(...) + count_resistant(...)`.
@@ -45,14 +44,14 @@
 #' @rdname count
 #' @name count
 #' @export
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' # example_isolates is a data set available in the AMR package.
-#' ?example_isolates
-#' 
-#' count_resistant(example_isolates$AMX)   # counts "R"
+#' # run ?example_isolates for more info.
+#'
+#' # base R ------------------------------------------------------------
+#' count_resistant(example_isolates$AMX) # counts "R"
 #' count_susceptible(example_isolates$AMX) # counts "S" and "I"
-#' count_all(example_isolates$AMX)         # counts "S", "I" and "R"
+#' count_all(example_isolates$AMX) # counts "S", "I" and "R"
 #'
 #' # be more specific
 #' count_S(example_isolates$AMX)
@@ -72,54 +71,59 @@
 #' count_susceptible(example_isolates$AMX)
 #' susceptibility(example_isolates$AMX) * n_rsi(example_isolates$AMX)
 #'
+#' # dplyr -------------------------------------------------------------
 #' \donttest{
 #' if (require("dplyr")) {
 #'   example_isolates %>%
-#'     group_by(hospital_id) %>%
-#'     summarise(R  = count_R(CIP),
-#'               I  = count_I(CIP),
-#'               S  = count_S(CIP),
-#'               n1 = count_all(CIP),  # the actual total; sum of all three
-#'               n2 = n_rsi(CIP),      # same - analogous to n_distinct
-#'               total = n())          # NOT the number of tested isolates!
-#'               
+#'     group_by(ward) %>%
+#'     summarise(
+#'       R = count_R(CIP),
+#'       I = count_I(CIP),
+#'       S = count_S(CIP),
+#'       n1 = count_all(CIP), # the actual total; sum of all three
+#'       n2 = n_rsi(CIP), # same - analogous to n_distinct
+#'       total = n()
+#'     ) # NOT the number of tested isolates!
+#'
 #'   # Number of available isolates for a whole antibiotic class
 #'   # (i.e., in this data set columns GEN, TOB, AMK, KAN)
 #'   example_isolates %>%
-#'     group_by(hospital_id) %>%
+#'     group_by(ward) %>%
 #'     summarise(across(aminoglycosides(), n_rsi))
-#'  
+#'
 #'   # Count co-resistance between amoxicillin/clav acid and gentamicin,
 #'   # so we can see that combination therapy does a lot more than mono therapy.
 #'   # Please mind that `susceptibility()` calculates percentages right away instead.
 #'   example_isolates %>% count_susceptible(AMC) # 1433
-#'   example_isolates %>% count_all(AMC)         # 1879
-#'  
+#'   example_isolates %>% count_all(AMC) # 1879
+#'
 #'   example_isolates %>% count_susceptible(GEN) # 1399
-#'   example_isolates %>% count_all(GEN)         # 1855
-#'  
+#'   example_isolates %>% count_all(GEN) # 1855
+#'
 #'   example_isolates %>% count_susceptible(AMC, GEN) # 1764
-#'   example_isolates %>% count_all(AMC, GEN)         # 1936
-#'  
+#'   example_isolates %>% count_all(AMC, GEN) # 1936
+#'
 #'   # Get number of S+I vs. R immediately of selected columns
 #'   example_isolates %>%
 #'     select(AMX, CIP) %>%
 #'     count_df(translate = FALSE)
-#'  
+#'
 #'   # It also supports grouping variables
 #'   example_isolates %>%
-#'     select(hospital_id, AMX, CIP) %>%
-#'     group_by(hospital_id) %>%
+#'     select(ward, AMX, CIP) %>%
+#'     group_by(ward) %>%
 #'     count_df(translate = FALSE)
 #' }
 #' }
 count_resistant <- function(..., only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = "R",
-             only_all_tested = only_all_tested,
-             only_count = TRUE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = "R",
+      only_all_tested = only_all_tested,
+      only_count = TRUE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname count
@@ -127,10 +131,12 @@ count_resistant <- function(..., only_all_tested = FALSE) {
 count_susceptible <- function(..., only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = c("S", "I"),
-             only_all_tested = only_all_tested,
-             only_count = TRUE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = c("S", "I"),
+      only_all_tested = only_all_tested,
+      only_count = TRUE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname count
@@ -138,10 +144,12 @@ count_susceptible <- function(..., only_all_tested = FALSE) {
 count_R <- function(..., only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = "R",
-             only_all_tested = only_all_tested,
-             only_count = TRUE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = "R",
+      only_all_tested = only_all_tested,
+      only_count = TRUE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname count
@@ -152,10 +160,12 @@ count_IR <- function(..., only_all_tested = FALSE) {
   }
   tryCatch(
     rsi_calc(...,
-             ab_result = c("I", "R"),
-             only_all_tested = only_all_tested,
-             only_count = TRUE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = c("I", "R"),
+      only_all_tested = only_all_tested,
+      only_count = TRUE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname count
@@ -163,10 +173,12 @@ count_IR <- function(..., only_all_tested = FALSE) {
 count_I <- function(..., only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = "I",
-             only_all_tested = only_all_tested,
-             only_count = TRUE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = "I",
+      only_all_tested = only_all_tested,
+      only_count = TRUE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname count
@@ -174,10 +186,12 @@ count_I <- function(..., only_all_tested = FALSE) {
 count_SI <- function(..., only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = c("S", "I"),
-             only_all_tested = only_all_tested,
-             only_count = TRUE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = c("S", "I"),
+      only_all_tested = only_all_tested,
+      only_count = TRUE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname count
@@ -188,10 +202,12 @@ count_S <- function(..., only_all_tested = FALSE) {
   }
   tryCatch(
     rsi_calc(...,
-             ab_result = "S",
-             only_all_tested = only_all_tested,
-             only_count = TRUE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = "S",
+      only_all_tested = only_all_tested,
+      only_count = TRUE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname count
@@ -199,10 +215,12 @@ count_S <- function(..., only_all_tested = FALSE) {
 count_all <- function(..., only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = c("S", "I", "R"),
-             only_all_tested = only_all_tested,
-             only_count = TRUE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = c("S", "I", "R"),
+      only_all_tested = only_all_tested,
+      only_count = TRUE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname count
@@ -217,12 +235,15 @@ count_df <- function(data,
                      combine_SI = TRUE,
                      combine_IR = FALSE) {
   tryCatch(
-    rsi_calc_df(type = "count",
-                data = data,
-                translate_ab = translate_ab,
-                language = language,
-                combine_SI = combine_SI,
-                combine_IR = combine_IR,
-                combine_SI_missing = missing(combine_SI)),
-    error = function(e) stop_(e$message, call = -5))
+    rsi_calc_df(
+      type = "count",
+      data = data,
+      translate_ab = translate_ab,
+      language = language,
+      combine_SI = combine_SI,
+      combine_IR = combine_IR,
+      combine_SI_missing = missing(combine_SI)
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }

R/custom_eucast_rules.R

@@ -24,102 +24,96 @@
 # ==================================================================== #
 
 #' Define Custom EUCAST Rules
-#' 
+#'
 #' Define custom EUCAST rules for your organisation or specific analysis and use the output of this function in [eucast_rules()].
-#' @inheritSection lifecycle Stable Lifecycle
-#' @param ... rules in formula notation, see *Examples*
+#' @param ... rules in [formula][base::tilde] notation, see *Examples*
 #' @details
 #' Some organisations have their own adoption of EUCAST rules. This function can be used to define custom EUCAST rules to be used in the [eucast_rules()] function.
-#' 
 #' @section How it works:
-#' 
+#'
 #' ### Basics
-#' 
+#'
 #' If you are familiar with the [`case_when()`][dplyr::case_when()] function of the `dplyr` package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written *before* the tilde (`~`) and the consequence of the rule is written *after* the tilde:
-#' 
-#' ```
+#'
+#' ```{r}
 #' x <- custom_eucast_rules(TZP == "S" ~ aminopenicillins == "S",
 #'                          TZP == "R" ~ aminopenicillins == "R")
 #' ```
-#' 
+#'
 #' These are two custom EUCAST rules: if TZP (piperacillin/tazobactam) is "S", all aminopenicillins (ampicillin and amoxicillin) must be made "S", and if TZP is "R", aminopenicillins must be made "R". These rules can also be printed to the console, so it is immediately clear how they work:
-#' 
-#' ```
+#'
+#' ```{r}
 #' x
-#' #> A set of custom EUCAST rules:
-#' #> 
-#' #>   1. If TZP is S then set to S:
-#' #>      amoxicillin (AMX), ampicillin (AMP)
-#' #> 
-#' #>   2. If TZP is R then set to R:
-#' #>      amoxicillin (AMX), ampicillin (AMP)
 #' ```
-#' 
+#'
 #' The rules (the part *before* the tilde, in above example `TZP == "S"` and `TZP == "R"`) must be evaluable in your data set: it should be able to run as a filter in your data set without errors. This means for the above example that the column `TZP` must exist. We will create a sample data set and test the rules set:
-#' 
-#' ```
-#' df <- data.frame(mo = c("E. coli", "K. pneumoniae"),
-#'                  TZP = "R",
-#'                  amox = "",
-#'                  AMP = "")
+#'
+#' ```{r}
+#' df <- data.frame(mo = c("Escherichia coli", "Klebsiella pneumoniae"),
+#'                  TZP = as.rsi("R"),
+#'                  ampi = as.rsi("S"),
+#'                  cipro = as.rsi("S"))
 #' df
-#' #>              mo TZP amox AMP
-#' #> 1       E. coli   R         
-#' #> 2 K. pneumoniae   R         
-#'                  
-#' eucast_rules(df, rules = "custom", custom_rules = x)
-#' #>              mo TZP amox AMP
-#' #> 1       E. coli   R    R   R     
-#' #> 2 K. pneumoniae   R    R   R  
+#'
+#' eucast_rules(df, rules = "custom", custom_rules = x, info = FALSE)
 #' ```
-#' 
+#'
 #' ### Using taxonomic properties in rules
-#' 
-#' There is one exception in variables used for the rules: all column names of the [microorganisms] data set can also be used, but do not have to exist in the data set. These column names are: `r vector_and(colnames(microorganisms), quote = "``", sort = FALSE)`. Thus, this next example will work as well, despite the fact that the `df` data set does not contain a column `genus`:
-#' 
-#' ```
+#'
+#' There is one exception in variables used for the rules: all column names of the [microorganisms] data set can also be used, but do not have to exist in the data set. These column names are: `r vector_and(colnames(microorganisms), sort = FALSE)`. Thus, this next example will work as well, despite the fact that the `df` data set does not contain a column `genus`:
+#'
+#' ```{r}
 #' y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
 #'                          TZP == "R" & genus == "Klebsiella" ~ aminopenicillins == "R")
 #'
-#' eucast_rules(df, rules = "custom", custom_rules = y)
-#' #>              mo TZP amox AMP
-#' #> 1       E. coli   R         
-#' #> 2 K. pneumoniae   R    R   R
+#' eucast_rules(df, rules = "custom", custom_rules = y, info = FALSE)
 #' ```
-#' 
+#'
 #' ### Usage of antibiotic group names
-#' 
+#'
 #' It is possible to define antibiotic groups instead of single antibiotics for the rule consequence, the part *after* the tilde. In above examples, the antibiotic group `aminopenicillins` is used to include ampicillin and amoxicillin. The following groups are allowed (case-insensitive). Within parentheses are the agents that will be matched when running the rule.
-#' 
-#' `r paste0("  * ", sapply(DEFINED_AB_GROUPS, function(x) paste0("``", tolower(gsub("^AB_", "", x)), "``\\cr(", vector_and(ab_name(eval(parse(text = x), envir = asNamespace("AMR")), language = NULL, tolower = TRUE), quotes = FALSE), ")"), USE.NAMES = FALSE), "\n", collapse = "")`
+#'
+#' `r paste0("  * ", sapply(DEFINED_AB_GROUPS, function(x) paste0("\"", tolower(gsub("^AB_", "", x)), "\"\\cr(", vector_and(ab_name(eval(parse(text = x), envir = asNamespace("AMR")), language = NULL, tolower = TRUE), quotes = FALSE), ")"), USE.NAMES = FALSE), "\n", collapse = "")`
 #' @returns A [list] containing the custom rules
-#' @inheritSection AMR Read more on Our Website!
 #' @export
 #' @examples
-#' x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
-#'                          AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
+#' x <- custom_eucast_rules(
+#'   AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
+#'   AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I"
+#' )
+#' x
+#'
+#' # run the custom rule set (verbose = TRUE will return a logbook instead of the data set):
 #' eucast_rules(example_isolates,
-#'              rules = "custom",
-#'              custom_rules = x,
-#'              info = FALSE)
-#'              
+#'   rules = "custom",
+#'   custom_rules = x,
+#'   info = FALSE,
+#'   verbose = TRUE
+#' )
+#'
 #' # combine rule sets
-#' x2 <- c(x,
-#'         custom_eucast_rules(TZP == "R" ~ carbapenems == "R"))
+#' x2 <- c(
+#'   x,
+#'   custom_eucast_rules(TZP == "R" ~ carbapenems == "R")
+#' )
 #' x2
 custom_eucast_rules <- function(...) {
-  
   dots <- tryCatch(list(...),
-                   error = function(e) "error")
-  stop_if(identical(dots, "error"),
-          "rules must be a valid formula inputs (e.g., using '~'), see `?custom_eucast_rules`")
+    error = function(e) "error"
+  )
+  stop_if(
+    identical(dots, "error"),
+    "rules must be a valid formula inputs (e.g., using '~'), see `?custom_eucast_rules`"
+  )
   n_dots <- length(dots)
   stop_if(n_dots == 0, "no custom rules were set. Please read the documentation using `?custom_eucast_rules`.")
   out <- vector("list", n_dots)
   for (i in seq_len(n_dots)) {
-    stop_ifnot(inherits(dots[[i]], "formula"), 
-               "rule ", i, " must be a valid formula input (e.g., using '~'), see `?custom_eucast_rules`")
-    
+    stop_ifnot(
+      inherits(dots[[i]], "formula"),
+      "rule ", i, " must be a valid formula input (e.g., using '~'), see `?custom_eucast_rules`"
+    )
+
     # Query
     qry <- dots[[i]][[2]]
     if (inherits(qry, "call")) {
@@ -134,11 +128,13 @@ custom_eucast_rules <- function(...) {
     qry <- gsub(" ?, ?", ", ", qry)
     qry <- gsub("'", "\"", qry, fixed = TRUE)
     out[[i]]$query <- as.expression(qry)
-    
+
     # Resulting rule
     result <- dots[[i]][[3]]
-    stop_ifnot(deparse(result) %like% "==", 
-               "the result of rule ", i, " (the part after the `~`) must contain `==`, such as in `... ~ ampicillin == \"R\"`, see `?custom_eucast_rules`")
+    stop_ifnot(
+      deparse(result) %like% "==",
+      "the result of rule ", i, " (the part after the `~`) must contain `==`, such as in `... ~ ampicillin == \"R\"`, see `?custom_eucast_rules`"
+    )
     result_group <- as.character(result)[[2]]
     if (paste0("AB_", toupper(result_group), "S") %in% DEFINED_AB_GROUPS) {
       # support for e.g. 'aminopenicillin' if user meant 'aminopenicillins'
@@ -149,25 +145,31 @@ custom_eucast_rules <- function(...) {
     } else {
       result_group <- tryCatch(
         suppressWarnings(as.ab(result_group,
-                               fast_mode = TRUE,
-                               flag_multiple_results = FALSE)),
-        error = function(e) NA_character_)
+          fast_mode = TRUE,
+          flag_multiple_results = FALSE
+        )),
+        error = function(e) NA_character_
+      )
     }
-    
-    stop_if(any(is.na(result_group)),
-            "this result of rule ", i, " could not be translated to a single antimicrobial agent/group: \"", 
-            as.character(result)[[2]], "\".\n\nThe input can be a name or code of an antimicrobial agent, or be one of: ", 
-            vector_or(tolower(gsub("AB_", "", DEFINED_AB_GROUPS)), quotes = FALSE), ".")
+
+    stop_if(
+      any(is.na(result_group)),
+      "this result of rule ", i, " could not be translated to a single antimicrobial agent/group: \"",
+      as.character(result)[[2]], "\".\n\nThe input can be a name or code of an antimicrobial agent, or be one of: ",
+      vector_or(tolower(gsub("AB_", "", DEFINED_AB_GROUPS)), quotes = FALSE), "."
+    )
     result_value <- as.character(result)[[3]]
     result_value[result_value == "NA"] <- NA
-    stop_ifnot(result_value %in% c("R", "S", "I", NA),
-               "the resulting value of rule ", i, " must be either \"R\", \"S\", \"I\" or NA")
+    stop_ifnot(
+      result_value %in% c("R", "S", "I", NA),
+      "the resulting value of rule ", i, " must be either \"R\", \"S\", \"I\" or NA"
+    )
     result_value <- as.rsi(result_value)
-    
+
     out[[i]]$result_group <- result_group
     out[[i]]$result_value <- result_value
   }
-  
+
   names(out) <- paste0("rule", seq_len(n_dots))
   set_clean_class(out, new_class = c("custom_eucast_rules", "list"))
 }
@@ -211,13 +213,19 @@ print.custom_eucast_rules <- function(x, ...) {
     } else {
       val <- font_rsi_I_bg(font_black(" I "))
     }
-    agents <- paste0(font_blue(ab_name(rule$result_group, language = NULL, tolower = TRUE),
-                               collapse = NULL),
-                     " (", rule$result_group, ")")
+    agents <- paste0(
+      font_blue(ab_name(rule$result_group, language = NULL, tolower = TRUE),
+        collapse = NULL
+      ),
+      " (", rule$result_group, ")"
+    )
     agents <- sort(agents)
-    rule_if <- word_wrap(paste0(i, ". ", font_bold("If "), font_blue(rule$query), font_bold(" then "),
-                            "set to {result}:"),
-                     extra_indent = 5)
+    rule_if <- word_wrap(paste0(
+      i, ". ", font_bold("If "), font_blue(rule$query), font_bold(" then "),
+      "set to {result}:"
+    ),
+    extra_indent = 5
+    )
     rule_if <- gsub("{result}", val, rule_if, fixed = TRUE)
     rule_then <- paste0("     ", word_wrap(paste0(agents, collapse = ", "), extra_indent = 5))
     cat("\n  ", rule_if, "\n", rule_then, "\n", sep = "")

R/data.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -27,7 +27,7 @@
 #'
 #' Two data sets containing all antibiotics/antimycotics and antivirals. Use [as.ab()] or one of the [`ab_*`][ab_property()] functions to retrieve values from the [antibiotics] data set. Three identifiers are included in this data set: an antibiotic ID (`ab`, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (`atc`) as defined by the WHO, and a Compound ID (`cid`) as found in PubChem. Other properties in this data set are derived from one or more of these codes. Note that some drugs have multiple ATC codes.
 #' @format
-#' ## For the [antibiotics] data set: a [data.frame] with `r nrow(antibiotics)` observations and `r ncol(antibiotics)` variables:
+#' ## For the [antibiotics] data set: a [tibble][tibble::tibble] with `r nrow(antibiotics)` observations and `r ncol(antibiotics)` variables:
 #' - `ab`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
 #' - `cid`\cr Compound ID as found in PubChem
 #' - `name`\cr Official name as used by WHONET/EARS-Net or the WHO
@@ -42,8 +42,8 @@
 #' - `iv_ddd`\cr Defined Daily Dose (DDD), parenteral (intravenous) treatment, currently available for `r sum(!is.na(antibiotics$iv_ddd))` drugs
 #' - `iv_units`\cr Units of `iv_ddd`
 #' - `loinc`\cr All LOINC codes (Logical Observation Identifiers Names and Codes) associated with the name of the antimicrobial agent. Use [ab_loinc()] to retrieve them quickly, see [ab_property()].
-#' 
-#' ## For the [antivirals] data set: a [data.frame] with `r nrow(antivirals)` observations and `r ncol(antivirals)` variables:
+#'
+#' ## For the [antivirals] data set: a [tibble][tibble::tibble] with `r nrow(antivirals)` observations and `r ncol(antivirals)` variables:
 #' - `atc`\cr ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC
 #' - `cid`\cr Compound ID as found in PubChem
 #' - `name`\cr Official name as used by WHONET/EARS-Net or the WHO
@@ -56,24 +56,17 @@
 #' @details Properties that are based on an ATC code are only available when an ATC is available. These properties are: `atc_group1`, `atc_group2`, `oral_ddd`, `oral_units`, `iv_ddd` and `iv_units`.
 #'
 #' Synonyms (i.e. trade names) were derived from the Compound ID (`cid`) and consequently only available where a CID is available.
-#' 
+#'
 #' ## Direct download
-#' These data sets are available as 'flat files' for use even without \R - you can find the files here:
-#' 
-#' * <https://github.com/msberends/AMR/raw/main/data-raw/antibiotics.txt>
-#' * <https://github.com/msberends/AMR/raw/main/data-raw/antivirals.txt>
-#' 
-#' Files in \R format (with preserved data structure) can be found here:
-#' 
-#' * <https://github.com/msberends/AMR/raw/main/data/antibiotics.rda>
-#' * <https://github.com/msberends/AMR/raw/main/data/antivirals.rda>
+#' Like all data sets in this package, these data sets are publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
 #' @source World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): <https://www.whocc.no/atc_ddd_index/>
 #'
 #' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm>
-#' @inheritSection AMR Reference Data Publicly Available
 #' @inheritSection WHOCC WHOCC
-#' @inheritSection AMR Read more on Our Website!
 #' @seealso [microorganisms], [intrinsic_resistant]
+#' @examples
+#' antibiotics
+#' antivirals
 "antibiotics"
 
 #' @rdname antibiotics
@@ -83,7 +76,7 @@
 #'
 #' A data set containing the full microbial taxonomy (**last updated: `r CATALOGUE_OF_LIFE$yearmonth_LPSN`**) of `r nr2char(length(unique(microorganisms$kingdom[!microorganisms$kingdom %like% "unknown"])))` kingdoms from the Catalogue of Life (CoL) and the List of Prokaryotic names with Standing in Nomenclature (LPSN). MO codes can be looked up using [as.mo()].
 #' @inheritSection catalogue_of_life Catalogue of Life
-#' @format A [data.frame] with `r format(nrow(microorganisms), big.mark = ",")` observations and `r ncol(microorganisms)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(microorganisms), big.mark = ",")` observations and `r ncol(microorganisms)` variables:
 #' - `mo`\cr ID of microorganism as used by this package
 #' - `fullname`\cr Full name, like `"Escherichia coli"`
 #' - `kingdom`, `phylum`, `class`, `order`, `family`, `genus`, `species`, `subspecies`\cr Taxonomic rank of the microorganism
@@ -93,119 +86,119 @@
 #' - `source`\cr Either `r vector_or(microorganisms$source)` (see *Source*)
 #' - `prevalence`\cr Prevalence of the microorganism, see [as.mo()]
 #' - `snomed`\cr Systematized Nomenclature of Medicine (SNOMED) code of the microorganism, according to the `r SNOMED_VERSION$current_source` (see *Source*). Use [mo_snomed()] to retrieve it quickly, see [mo_property()].
-#' @details 
+#' @details
 #' Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.
-#' 
+#'
 #' For example, *Staphylococcus pettenkoferi* was described for the first time in Diagnostic Microbiology and Infectious Disease in 2002 (\doi{10.1016/s0732-8893(02)00399-1}), but it was not before 2007 that a publication in IJSEM followed (\doi{10.1099/ijs.0.64381-0}). Consequently, the `AMR` package returns 2007 for `mo_year("S. pettenkoferi")`.
-#' 
+#'
 #' ## Manual additions
 #' For convenience, some entries were added manually:
-#' 
+#'
 #' - 11 entries of *Streptococcus* (beta-haemolytic: groups A, B, C, D, F, G, H, K and unspecified; other: viridans, milleri)
 #' - 2 entries of *Staphylococcus* (coagulase-negative (CoNS) and coagulase-positive (CoPS))
 #' - 3 entries of *Trichomonas* (*T. vaginalis*, and its family and genus)
+#' - 4 entries of *Toxoplasma* (*T. gondii*, and its order, family and genus)
 #' - 1 entry of *Candida* (*C.  krusei*), that is not (yet) in the Catalogue of Life
 #' - 1 entry of *Blastocystis* (*B.  hominis*), although it officially does not exist (Noel *et al.* 2005, PMID 15634993)
 #' - 1 entry of *Moraxella* (*M. catarrhalis*), which was formally named *Branhamella catarrhalis* (Catlin, 1970) though this change was never accepted within the field of clinical microbiology
 #' - 5 other 'undefined' entries (unknown, unknown Gram negatives, unknown Gram positives, unknown yeast and unknown fungus)
 #' - 6 families under the Enterobacterales order, according to Adeolu *et al.* (2016, PMID 27620848), that are not (yet) in the Catalogue of Life
-#' 
+#'
 #' ## Direct download
-#' This data set is available as 'flat file' for use even without \R - you can find the file here:
-#' 
-#' * <https://github.com/msberends/AMR/raw/main/data-raw/microorganisms.txt>
-#' 
-#' The file in \R format (with preserved data structure) can be found here:
-#' 
-#' * <https://github.com/msberends/AMR/raw/main/data/microorganisms.rda>
+#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
 #' @section About the Records from LPSN (see *Source*):
 #' The List of Prokaryotic names with Standing in Nomenclature (LPSN) provides comprehensive information on the nomenclature of prokaryotes. LPSN is a free to use service founded by Jean P. Euzeby in 1997 and later on maintained by Aidan C. Parte.
-#' 
+#'
 #' As of February 2020, the regularly augmented LPSN database at DSMZ is the basis of the new LPSN service. The new database was implemented for the Type-Strain Genome Server and augmented in 2018 to store all kinds of nomenclatural information. Data from the previous version of LPSN and from the Prokaryotic Nomenclature Up-to-date (PNU) service were imported into the new system. PNU had been established in 1993 as a service of the Leibniz Institute DSMZ, and was curated by Norbert Weiss, Manfred Kracht and Dorothea Gleim.
-#' @source 
+#' @source
 #' `r gsub("{year}", CATALOGUE_OF_LIFE$year, CATALOGUE_OF_LIFE$version, fixed = TRUE)` as currently implemented in this `AMR` package:
-#' 
+#'
 #' * Annual Checklist (public online taxonomic database), <http://www.catalogueoflife.org>
-#' 
+#'
 #' List of Prokaryotic names with Standing in Nomenclature (`r CATALOGUE_OF_LIFE$yearmonth_LPSN`) as currently implemented in this `AMR` package:
-#' 
+#'
 #' * Parte, A.C., Sarda Carbasse, J., Meier-Kolthoff, J.P., Reimer, L.C. and Goker, M. (2020). List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ. International Journal of Systematic and Evolutionary Microbiology, 70, 5607-5612; \doi{10.1099/ijsem.0.004332}
 #' * Parte, A.C. (2018). LPSN - List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68, 1825-1829; \doi{10.1099/ijsem.0.002786}
 #' * Parte, A.C. (2014). LPSN - List of Prokaryotic names with Standing in Nomenclature. Nucleic Acids Research, 42, Issue D1, D613-D616; \doi{10.1093/nar/gkt1111}
 #' * Euzeby, J.P. (1997). List of Bacterial Names with Standing in Nomenclature: a Folder Available on the Internet. International Journal of Systematic Bacteriology, 47, 590-592; \doi{10.1099/00207713-47-2-590}
-#' 
+#'
 #' `r SNOMED_VERSION$current_source` as currently implemented in this `AMR` package:
-#' 
+#'
 #' * Retrieved from the `r SNOMED_VERSION$title`, OID `r SNOMED_VERSION$current_oid`, version `r SNOMED_VERSION$current_version`; url: <`r SNOMED_VERSION$url`>
-#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
 #' @seealso [as.mo()], [mo_property()], [microorganisms.codes], [intrinsic_resistant]
+#' @examples
+#' microorganisms
 "microorganisms"
 
 #' Data Set with Previously Accepted Taxonomic Names
 #'
 #' A data set containing old (previously valid or accepted) taxonomic names according to the Catalogue of Life. This data set is used internally by [as.mo()].
 #' @inheritSection catalogue_of_life Catalogue of Life
-#' @format A [data.frame] with `r format(nrow(microorganisms.old), big.mark = ",")` observations and `r ncol(microorganisms.old)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(microorganisms.old), big.mark = ",")` observations and `r ncol(microorganisms.old)` variables:
 #' - `fullname`\cr Old full taxonomic name of the microorganism
 #' - `fullname_new`\cr New full taxonomic name of the microorganism
 #' - `ref`\cr Author(s) and year of concerning scientific publication
 #' - `prevalence`\cr Prevalence of the microorganism, see [as.mo()]
+#' @details
+#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
 #' @source Catalogue of Life: Annual Checklist (public online taxonomic database), <http://www.catalogueoflife.org> (check included annual version with [catalogue_of_life_version()]).
-#' 
+#'
 #' Parte, A.C. (2018). LPSN - List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68, 1825-1829; \doi{10.1099/ijsem.0.002786}
-#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
 #' @seealso [as.mo()] [mo_property()] [microorganisms]
+#' @examples
+#' microorganisms.old
 "microorganisms.old"
 
 #' Data Set with `r format(nrow(microorganisms.codes), big.mark = ",")` Common Microorganism Codes
 #'
 #' A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with [set_mo_source()]. They will all be searched when using [as.mo()] and consequently all the [`mo_*`][mo_property()] functions.
-#' @format A [data.frame] with `r format(nrow(microorganisms.codes), big.mark = ",")` observations and `r ncol(microorganisms.codes)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(microorganisms.codes), big.mark = ",")` observations and `r ncol(microorganisms.codes)` variables:
 #' - `code`\cr Commonly used code of a microorganism
 #' - `mo`\cr ID of the microorganism in the [microorganisms] data set
-#' @inheritSection AMR Reference Data Publicly Available
+#' @details
+#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
 #' @inheritSection catalogue_of_life Catalogue of Life
-#' @inheritSection AMR Read more on Our Website!
 #' @seealso [as.mo()] [microorganisms]
+#' @examples
+#' microorganisms.codes
 "microorganisms.codes"
 
 #' Data Set with `r format(nrow(example_isolates), big.mark = ",")` Example Isolates
 #'
-#' A data set containing `r format(nrow(example_isolates), big.mark = ",")` microbial isolates with their full antibiograms. The data set reflects reality and can be used to practice AMR data analysis. For examples, please read [the tutorial on our website](https://msberends.github.io/AMR/articles/AMR.html).
-#' @format A [data.frame] with `r format(nrow(example_isolates), big.mark = ",")` observations and `r ncol(example_isolates)` variables:
-#' - `date`\cr date of receipt at the laboratory
-#' - `hospital_id`\cr ID of the hospital, from A to D
-#' - `ward_icu`\cr [logical] to determine if ward is an intensive care unit
-#' - `ward_clinical`\cr [logical] to determine if ward is a regular clinical ward
-#' - `ward_outpatient`\cr [logical] to determine if ward is an outpatient clinic
-#' - `age`\cr age of the patient
-#' - `gender`\cr gender of the patient
-#' - `patient_id`\cr ID of the patient
-#' - `mo`\cr ID of microorganism created with [as.mo()], see also [microorganisms]
-#' - `PEN:RIF`\cr `r sum(vapply(FUN.VALUE = logical(1), example_isolates, is.rsi))` different antibiotics with class [`rsi`] (see [as.rsi()]); these column names occur in the [antibiotics] data set and can be translated with [ab_name()]
-#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+#' A data set containing `r format(nrow(example_isolates), big.mark = ",")` microbial isolates with their full antibiograms. This data set contains randomised fictitious data, but reflects reality and can be used to practise AMR data analysis. For examples, please read [the tutorial on our website](https://msberends.github.io/AMR/articles/AMR.html).
+#' @format A [tibble][tibble::tibble] with `r format(nrow(example_isolates), big.mark = ",")` observations and `r ncol(example_isolates)` variables:
+#' - `date`\cr Date of receipt at the laboratory
+#' - `patient`\cr ID of the patient
+#' - `age`\cr Age of the patient
+#' - `gender`\cr Gender of the patient, either `r vector_or(example_isolates$gender)`
+#' - `ward`\cr Ward type where the patient was admitted, either `r vector_or(example_isolates$ward)`
+#' - `mo`\cr ID of microorganism created with [as.mo()], see also the [microorganisms] data set
+#' - `PEN:RIF`\cr `r sum(vapply(FUN.VALUE = logical(1), example_isolates, is.rsi))` different antibiotics with class [`rsi`] (see [as.rsi()]); these column names occur in the [antibiotics] data set and can be translated with [set_ab_names()] or [ab_name()]
+#' @details
+#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
+#' @examples
+#' example_isolates
 "example_isolates"
 
 #' Data Set with Unclean Data
 #'
 #' A data set containing `r format(nrow(example_isolates_unclean), big.mark = ",")` microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice.
-#' @format A [data.frame] with `r format(nrow(example_isolates_unclean), big.mark = ",")` observations and `r ncol(example_isolates_unclean)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(example_isolates_unclean), big.mark = ",")` observations and `r ncol(example_isolates_unclean)` variables:
 #' - `patient_id`\cr ID of the patient
 #' - `date`\cr date of receipt at the laboratory
 #' - `hospital`\cr ID of the hospital, from A to C
 #' - `bacteria`\cr info about microorganism that can be transformed with [as.mo()], see also [microorganisms]
 #' - `AMX:GEN`\cr 4 different antibiotics that have to be transformed with [as.rsi()]
-#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+#' @details
+#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
+#' @examples
+#' example_isolates_unclean
 "example_isolates_unclean"
 
 #' Data Set with `r format(nrow(WHONET), big.mark = ",")` Isolates - WHONET Example
 #'
 #' This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antibiotic results are from our [example_isolates] data set. All patient names are created using online surname generators and are only in place for practice purposes.
-#' @format A [data.frame] with `r format(nrow(WHONET), big.mark = ",")` observations and `r ncol(WHONET)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(WHONET), big.mark = ",")` observations and `r ncol(WHONET)` variables:
 #' - `Identification number`\cr ID of the sample
 #' - `Specimen number`\cr ID of the specimen
 #' - `Organism`\cr Name of the microorganism. Before analysis, you should transform this to a valid microbial class, using [as.mo()].
@@ -232,14 +225,16 @@
 #' - `Comment`\cr Other comments
 #' - `Date of data entry`\cr [Date] this data was entered in WHONET
 #' - `AMP_ND10:CIP_EE`\cr `r sum(vapply(FUN.VALUE = logical(1), WHONET, is.rsi))` different antibiotics. You can lookup the abbreviations in the [antibiotics] data set, or use e.g. [`ab_name("AMP")`][ab_name()] to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using [as.rsi()].
-#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+#' @details
+#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
+#' @examples
+#' WHONET
 "WHONET"
 
 #' Data Set for R/SI Interpretation
 #'
 #' Data set containing reference data to interpret MIC and disk diffusion to R/SI values, according to international guidelines. Currently implemented guidelines are EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`). Use [as.rsi()] to transform MICs or disks measurements to R/SI values.
-#' @format A [data.frame] with `r format(nrow(rsi_translation), big.mark = ",")` observations and `r ncol(rsi_translation)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(rsi_translation), big.mark = ",")` observations and `r ncol(rsi_translation)` variables:
 #' - `guideline`\cr Name of the guideline
 #' - `method`\cr Either `r vector_or(rsi_translation$method)`
 #' - `site`\cr Body site, e.g. "Oral" or "Respiratory"
@@ -251,40 +246,36 @@
 #' - `breakpoint_S`\cr Lowest MIC value or highest number of millimetres that leads to "S"
 #' - `breakpoint_R`\cr Highest MIC value or lowest number of millimetres that leads to "R"
 #' - `uti`\cr A [logical] value (`TRUE`/`FALSE`) to indicate whether the rule applies to a urinary tract infection (UTI)
-#' @details The repository of this `AMR` package contains a file comprising this exact data set: <https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt>. This file **allows for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically and the `mo` and `ab` columns have been transformed to contain the full official names instead of codes.
-#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+#' @details
+#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
+#'
+#' They **allow for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the MS Excel and PDF files distributed by EUCAST and CLSI.
 #' @seealso [intrinsic_resistant]
+#' @examples
+#' rsi_translation
 "rsi_translation"
 
 #' Data Set with Bacterial Intrinsic Resistance
 #'
 #' Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations.
-#' @format A [data.frame] with `r format(nrow(intrinsic_resistant), big.mark = ",")` observations and `r ncol(intrinsic_resistant)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(intrinsic_resistant), big.mark = ",")` observations and `r ncol(intrinsic_resistant)` variables:
 #' - `mo`\cr Microorganism ID
 #' - `ab`\cr Antibiotic ID
-#' @details The repository of this `AMR` package contains a file comprising this data set with full taxonomic and antibiotic names: <https://github.com/msberends/AMR/blob/main/data-raw/intrinsic_resistant.txt>. This file **allows for machine reading EUCAST guidelines about intrinsic resistance**, which is almost impossible with the Excel and PDF files distributed by EUCAST. The file is updated automatically.
-#' 
+#' @details
 #' This data set is based on `r format_eucast_version_nr(3.3)`.
-#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+#'
+#' ## Direct download
+#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
+#'
+#' They **allow for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the MS Excel and PDF files distributed by EUCAST and CLSI.
 #' @examples
-#' \donttest{
-#' if (require("dplyr")) {
-#'   intrinsic_resistant %>%
-#'     mutate(mo = mo_name(mo),
-#'            ab = ab_name(mo))
-#'     filter(ab == "Vancomycin" & mo %like% "Enterococcus") %>% 
-#'     pull(mo)
-#'   #> [1] "Enterococcus casseliflavus" "Enterococcus gallinarum"
-#' }
-#' }
+#' intrinsic_resistant
 "intrinsic_resistant"
 
 #' Data Set with Treatment Dosages as Defined by EUCAST
 #'
 #' EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with [eucast_dosage()].
-#' @format A [data.frame] with `r format(nrow(dosage), big.mark = ",")` observations and `r ncol(dosage)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(dosage), big.mark = ",")` observations and `r ncol(dosage)` variables:
 #' - `ab`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
 #' - `name`\cr Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO
 #' - `type`\cr Type of the dosage, either `r vector_or(dosage$type)`
@@ -294,7 +285,11 @@
 #' - `notes`\cr Additional dosage notes
 #' - `original_txt`\cr Original text in the PDF file of EUCAST
 #' - `eucast_version`\cr Version number of the EUCAST Clinical Breakpoints guideline to which these dosages apply
-#' @details `r format_eucast_version_nr(11.0)` are based on the dosages in this data set.
-#' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
+#' @details
+#' This data set is based on `r format_eucast_version_nr(11.0)`.
+#'
+#' ## Direct download
+#' Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
+#' @examples
+#' dosage
 "dosage"

R/deprecated.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,8 +26,6 @@
 #' Deprecated Functions
 #'
 #' These functions are so-called '[Deprecated]'. **They will be removed in a future release.** Using the functions will give a warning with the name of the function it has been replaced by (if there is one).
-#' @inheritSection lifecycle Retired Lifecycle
-#' @inheritSection AMR Read more on Our Website!
 #' @keywords internal
 #' @name AMR-deprecated
 # @export

R/disk.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' Transform Input to Disk Diffusion Diameters
 #'
 #' This transforms a vector to a new class [`disk`], which is a disk diffusion growth zone size (around an antibiotic disk) in millimetres between 6 and 50.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @rdname as.disk
 #' @param x vector
 #' @param na.rm a [logical] indicating whether missing values should be removed
@@ -35,40 +34,49 @@
 #' @aliases disk
 #' @export
 #' @seealso [as.rsi()]
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
-#' \donttest{
-#' # transform existing disk zones to the `disk` class
-#' df <- data.frame(microorganism = "E. coli",
-#'                  AMP = 20,
-#'                  CIP = 14,
-#'                  GEN = 18,
-#'                  TOB = 16)
+#' # transform existing disk zones to the `disk` class (using base R)
+#' df <- data.frame(
+#'   microorganism = "Escherichia coli",
+#'   AMP = 20,
+#'   CIP = 14,
+#'   GEN = 18,
+#'   TOB = 16
+#' )
 #' df[, 2:5] <- lapply(df[, 2:5], as.disk)
-#' # same with dplyr:
-#' # df %>% mutate(across(AMP:TOB, as.disk))
-#' 
-#' # interpret disk values, see ?as.rsi
-#' as.rsi(x = as.disk(18),
-#'        mo = "Strep pneu",  # `mo` will be coerced with as.mo()
-#'        ab = "ampicillin",  # and `ab` with as.ab()
-#'        guideline = "EUCAST")
-#'        
-#' as.rsi(df)
+#' str(df)
+#'
+#' \donttest{
+#' # transforming is easier with dplyr:
+#' if (require("dplyr")) {
+#'   df %>% mutate(across(AMP:TOB, as.disk))
 #' }
+#' }
+#'
+#' # interpret disk values, see ?as.rsi
+#' as.rsi(
+#'   x = as.disk(18),
+#'   mo = "Strep pneu", # `mo` will be coerced with as.mo()
+#'   ab = "ampicillin", # and `ab` with as.ab()
+#'   guideline = "EUCAST"
+#' )
+#'
+#' # interpret whole data set, pretend to be all from urinary tract infections:
+#' as.rsi(df, uti = TRUE)
 as.disk <- function(x, na.rm = FALSE) {
   meet_criteria(x, allow_class = c("disk", "character", "numeric", "integer"), allow_NA = TRUE)
   meet_criteria(na.rm, allow_class = "logical", has_length = 1)
-  
+
   if (!is.disk(x)) {
     x <- unlist(x)
     if (na.rm == TRUE) {
       x <- x[!is.na(x)]
     }
+    x[trimws(x) == ""] <- NA
     x.bak <- x
-    
+
     na_before <- length(x[is.na(x)])
-    
+
     # heavily based on cleaner::clean_double():
     clean_double2 <- function(x, remove = "[^0-9.,-]", fixed = FALSE) {
       x <- gsub(",", ".", x)
@@ -76,38 +84,44 @@ as.disk <- function(x, na.rm = FALSE) {
       x <- gsub("[,.]$", "", x)
       # only keep last dot/comma
       reverse <- function(x) vapply(FUN.VALUE = character(1), lapply(strsplit(x, NULL), rev), paste, collapse = "")
-      x <- sub("{{dot}}", ".", 
-               gsub(".", "",
-                    reverse(sub(".", "}}tod{{",
-                                reverse(x), 
-                                fixed = TRUE)),
-                    fixed = TRUE), 
-               fixed = TRUE)
+      x <- sub("{{dot}}", ".",
+        gsub(".", "",
+          reverse(sub(".", "}}tod{{",
+            reverse(x),
+            fixed = TRUE
+          )),
+          fixed = TRUE
+        ),
+        fixed = TRUE
+      )
       x_clean <- gsub(remove, "", x, ignore.case = TRUE, fixed = fixed)
       # remove everything that is not a number or dot
       as.double(gsub("[^0-9.]+", "", x_clean))
     }
-    
+
     # round up and make it an integer
     x <- as.integer(ceiling(clean_double2(x)))
-    
+
     # disks can never be less than 6 mm (size of smallest disk) or more than 50 mm
     x[x < 6 | x > 50] <- NA_integer_
     na_after <- length(x[is.na(x)])
-    
+
     if (na_before != na_after) {
       list_missing <- x.bak[is.na(x) & !is.na(x.bak)] %pm>%
         unique() %pm>%
         sort() %pm>%
         vector_and(quotes = TRUE)
-      warning_("in `as.disk()`: ", na_after - na_before, " results truncated (",
-               round(((na_after - na_before) / length(x)) * 100),
-               "%) that were invalid disk zones: ",
-               list_missing)
+      warning_(
+        "in `as.disk()`: ", na_after - na_before, " results truncated (",
+        round(((na_after - na_before) / length(x)) * 100),
+        "%) that were invalid disk zones: ",
+        list_missing
+      )
     }
   }
   set_clean_class(as.integer(x),
-                  new_class = c("disk", "integer"))
+    new_class = c("disk", "integer")
+  )
 }
 
 all_valid_disks <- function(x) {
@@ -115,7 +129,8 @@ all_valid_disks <- function(x) {
     return(FALSE)
   }
   x_disk <- tryCatch(suppressWarnings(as.disk(x[!is.na(x)])),
-                     error = function(e) NA)
+    error = function(e) NA
+  )
   !any(is.na(x_disk)) && !all(is.na(x))
 }
 
@@ -123,7 +138,8 @@ all_valid_disks <- function(x) {
 #' @details `NA_disk_` is a missing value of the new `<disk>` class.
 #' @export
 NA_disk_ <- set_clean_class(as.integer(NA_real_),
-                            new_class = c("disk", "integer"))
+  new_class = c("disk", "integer")
+)
 
 #' @rdname as.disk
 #' @export
@@ -214,10 +230,10 @@ rep.disk <- function(x, ...) {
 get_skimmers.disk <- function(column) {
   skimr::sfl(
     skim_type = "disk",
-    min = ~min(as.double(.), na.rm = TRUE),
-    max = ~max(as.double(.), na.rm = TRUE),
-    median = ~stats::median(as.double(.), na.rm = TRUE),
-    n_unique = ~length(unique(stats::na.omit(.))),
-    hist = ~skimr::inline_hist(stats::na.omit(as.double(.)))
+    min = ~ min(as.double(.), na.rm = TRUE),
+    max = ~ max(as.double(.), na.rm = TRUE),
+    median = ~ stats::median(as.double(.), na.rm = TRUE),
+    n_unique = ~ length(unique(stats::na.omit(.))),
+    hist = ~ skimr::inline_hist(stats::na.omit(as.double(.)))
   )
 }

R/episode.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -24,94 +24,112 @@
 # ==================================================================== #
 
 #' Determine (New) Episodes for Patients
-#' 
+#'
 #' These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument `episode_days`. This can be used to determine clinical episodes for any epidemiological analysis. The [get_episode()] function returns the index number of the episode per group, while the [is_new_episode()] function returns values `TRUE`/`FALSE` to indicate whether an item in a vector is the start of a new episode.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x vector of dates (class `Date` or `POSIXt`), will be sorted internally to determine episodes
 #' @param episode_days required episode length in days, can also be less than a day or `Inf`, see *Details*
 #' @param ... ignored, only in place to allow future extensions
-#' @details 
+#' @details
 #' Dates are first sorted from old to new. The oldest date will mark the start of the first episode. After this date, the next date will be marked that is at least `episode_days` days later than the start of the first episode. From that second marked date on, the next date will be marked that is at least `episode_days` days later than the start of the second episode which will be the start of the third episode, and so on. Before the vector is being returned, the original order will be restored.
-#' 
+#'
 #' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but is more efficient for data sets containing microorganism codes or names and allows for different isolate selection methods.
-#' 
+#'
 #' The `dplyr` package is not required for these functions to work, but these functions do support [variable grouping][dplyr::group_by()] and work conveniently inside `dplyr` verbs such as [`filter()`][dplyr::filter()], [`mutate()`][dplyr::mutate()] and [`summarise()`][dplyr::summarise()].
-#' @return 
+#' @return
 #' * [get_episode()]: a [double] vector
 #' * [is_new_episode()]: a [logical] vector
 #' @seealso [first_isolate()]
 #' @rdname get_episode
 #' @export
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' # `example_isolates` is a data set available in the AMR package.
-#' # See ?example_isolates.
-#' 
-#' get_episode(example_isolates$date, episode_days = 60)    # indices
-#' is_new_episode(example_isolates$date, episode_days = 60) # TRUE/FALSE
-#' 
+#' # See ?example_isolates
+#' df <- example_isolates[sample(seq_len(2000), size = 200), ]
+#'
+#' get_episode(df$date, episode_days = 60) # indices
+#' is_new_episode(df$date, episode_days = 60) # TRUE/FALSE
+#'
 #' # filter on results from the third 60-day episode only, using base R
-#' example_isolates[which(get_episode(example_isolates$date, 60) == 3), ]
-#' 
+#' df[which(get_episode(df$date, 60) == 3), ]
+#'
 #' # the functions also work for less than a day, e.g. to include one per hour:
-#' get_episode(c(Sys.time(),
-#'               Sys.time() + 60 * 60),
-#'             episode_days = 1/24)
-#' 
+#' get_episode(c(
+#'   Sys.time(),
+#'   Sys.time() + 60 * 60
+#' ),
+#' episode_days = 1 / 24
+#' )
+#'
 #' \donttest{
 #' if (require("dplyr")) {
 #'   # is_new_episode() can also be used in dplyr verbs to determine patient
 #'   # episodes based on any (combination of) grouping variables:
-#'   example_isolates %>%
-#'     mutate(condition = sample(x = c("A", "B", "C"), 
-#'                               size = 2000,
-#'                               replace = TRUE)) %>% 
+#'   df %>%
+#'     mutate(condition = sample(
+#'       x = c("A", "B", "C"),
+#'       size = 200,
+#'       replace = TRUE
+#'     )) %>%
 #'     group_by(condition) %>%
-#'     mutate(new_episode = is_new_episode(date, 365))
-#'     
-#'   example_isolates %>%
-#'     group_by(hospital_id, patient_id) %>%
-#'     transmute(date, 
-#'               patient_id,
-#'               new_index = get_episode(date, 60),
-#'               new_logical = is_new_episode(date, 60))
-#'   
-#'   
-#'   example_isolates %>%
-#'     group_by(hospital_id) %>% 
-#'     summarise(patients = n_distinct(patient_id),
-#'               n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),
-#'               n_episodes_60  = sum(is_new_episode(date, episode_days = 60)),
-#'               n_episodes_30  = sum(is_new_episode(date, episode_days = 30)))
-#'     
-#'     
+#'     mutate(new_episode = is_new_episode(date, 365)) %>%
+#'     select(patient, date, condition, new_episode)
+#' }
+#' if (require("dplyr")) {
+#'   df %>%
+#'     group_by(ward, patient) %>%
+#'     transmute(date,
+#'       patient,
+#'       new_index = get_episode(date, 60),
+#'       new_logical = is_new_episode(date, 60)
+#'     )
+#' }
+#' if (require("dplyr")) {
+#'   df %>%
+#'     group_by(ward) %>%
+#'     summarise(
+#'       n_patients = n_distinct(patient),
+#'       n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),
+#'       n_episodes_60 = sum(is_new_episode(date, episode_days = 60)),
+#'       n_episodes_30 = sum(is_new_episode(date, episode_days = 30))
+#'     )
+#' }
+#' if (require("dplyr")) {
+#'
 #'   # grouping on patients and microorganisms leads to the same
 #'   # results as first_isolate() when using 'episode-based':
-#'   x <- example_isolates %>%
-#'     filter_first_isolate(include_unknown = TRUE,
-#'                          method = "episode-based")
-#'     
-#'   y <- example_isolates %>%
-#'     group_by(patient_id, mo) %>%
-#'     filter(is_new_episode(date, 365))
+#'   x <- df %>%
+#'     filter_first_isolate(
+#'       include_unknown = TRUE,
+#'       method = "episode-based"
+#'     )
+#'
+#'   y <- df %>%
+#'     group_by(patient, mo) %>%
+#'     filter(is_new_episode(date, 365)) %>%
+#'     ungroup()
+#'
+#'   identical(x, y)
+#' }
+#' if (require("dplyr")) {
 #'
-#'   identical(x$patient_id, y$patient_id)
-#'   
 #'   # but is_new_episode() has a lot more flexibility than first_isolate(),
 #'   # since you can now group on anything that seems relevant:
-#'   example_isolates %>%
-#'     group_by(patient_id, mo, hospital_id, ward_icu) %>%
-#'     mutate(flag_episode = is_new_episode(date, 365))
+#'   df %>%
+#'     group_by(patient, mo, ward) %>%
+#'     mutate(flag_episode = is_new_episode(date, 365)) %>%
+#'     select(group_vars(.), flag_episode)
 #' }
 #' }
 get_episode <- function(x, episode_days, ...) {
   meet_criteria(x, allow_class = c("Date", "POSIXt"), allow_NA = TRUE)
   meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
-  
-  exec_episode(x = x, 
-               type = "sequential",
-               episode_days = episode_days,
-               ... = ...)
+
+  exec_episode(
+    x = x,
+    type = "sequential",
+    episode_days = episode_days,
+    ... = ...
+  )
 }
 
 #' @rdname get_episode
@@ -119,18 +137,20 @@ get_episode <- function(x, episode_days, ...) {
 is_new_episode <- function(x, episode_days, ...) {
   meet_criteria(x, allow_class = c("Date", "POSIXt"), allow_NA = TRUE)
   meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
-  
-  exec_episode(x = x, 
-               type = "logical",
-               episode_days = episode_days,
-               ... = ...)
+
+  exec_episode(
+    x = x,
+    type = "logical",
+    episode_days = episode_days,
+    ... = ...
+  )
 }
 
 exec_episode <- function(x, type, episode_days, ...) {
   x <- as.double(as.POSIXct(x)) # as.POSIXct() required for Date classes
   # since x is now in seconds, get seconds from episode_days as well
   episode_seconds <- episode_days * 60 * 60 * 24
-  
+
   if (length(x) == 1) { # this will also match 1 NA, which is fine
     if (type == "logical") {
       return(TRUE)
@@ -152,7 +172,7 @@ exec_episode <- function(x, type, episode_days, ...) {
       }
     }
   }
-  
+
   # I asked on StackOverflow:
   # https://stackoverflow.com/questions/42122245/filter-one-row-every-year
   run_episodes <- function(x, episode_seconds) {
@@ -180,7 +200,7 @@ exec_episode <- function(x, type, episode_days, ...) {
       indices
     }
   }
-  
+
   ord <- order(x)
   out <- run_episodes(x[ord], episode_seconds)[order(ord)]
   out[is.na(x) & ord != 1] <- NA # every NA but the first must remain NA

R/first_isolate.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,16 +26,15 @@
 #' Determine First Isolates
 #'
 #' Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler *et al.* in 2007 (\doi{10.1086/511864}). To determine patient episodes not necessarily based on microorganisms, use [is_new_episode()] that also supports grouping with the `dplyr` package.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x a [data.frame] containing isolates. Can be left blank for automatic determination, see *Examples*.
 #' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column with a date class
 #' @param col_patient_id column name of the unique IDs of the patients, defaults to the first column that starts with 'patient' or 'patid' (case insensitive)
 #' @param col_mo column name of the IDs of the microorganisms (see [as.mo()]), defaults to the first column of class [`mo`]. Values will be coerced using [as.mo()].
 #' @param col_testcode column name of the test codes. Use `col_testcode = NULL` to **not** exclude certain test codes (such as test codes for screening). In that case `testcodes_exclude` will be ignored.
 #' @param col_specimen column name of the specimen type or group
-#' @param col_icu column name of the logicals (`TRUE`/`FALSE`) whether a ward or department is an Intensive Care Unit (ICU)
+#' @param col_icu column name of the logicals (`TRUE`/`FALSE`) whether a ward or department is an Intensive Care Unit (ICU). This can also be a [logical] vector with the same length as rows in `x`.
 #' @param col_keyantimicrobials (only useful when `method = "phenotype-based"`) column name of the key antimicrobials to determine first isolates, see [key_antimicrobials()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use `col_keyantimicrobials = FALSE` to prevent this. Can also be the output of [key_antimicrobials()].
-#' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see *Source*. 
+#' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see *Source*.
 #' @param testcodes_exclude a [character] vector with test codes that should be excluded (case-insensitive)
 #' @param icu_exclude a [logical] to indicate whether ICU isolates should be excluded (rows with value `TRUE` in the column set with `col_icu`)
 #' @param specimen_group value in the column set with `col_specimen` to filter on
@@ -47,22 +46,22 @@
 #' @param include_unknown a [logical] to indicate whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
 #' @param include_untested_rsi a [logical] to indicate whether also rows without antibiotic results are still eligible for becoming a first isolate. Use `include_untested_rsi = FALSE` to always return `FALSE` for such rows. This checks the data set for columns of class `<rsi>` and consequently requires transforming columns with antibiotic results using [as.rsi()] first.
 #' @param ... arguments passed on to [first_isolate()] when using [filter_first_isolate()], otherwise arguments passed on to [key_antimicrobials()] (such as `universal`, `gram_negative`, `gram_positive`)
-#' @details 
+#' @details
 #' To conduct epidemiological analyses on antimicrobial resistance data, only so-called first isolates should be included to prevent overestimation and underestimation of antimicrobial resistance. Different methods can be used to do so, see below.
-#' 
+#'
 #' These functions are context-aware. This means that the `x` argument can be left blank if used inside a [data.frame] call, see *Examples*.
-#' 
+#'
 #' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but more efficient for data sets containing microorganism codes or names.
-#' 
+#'
 #' All isolates with a microbial ID of `NA` will be excluded as first isolate.
-#' 
+#'
 #' ## Different methods
-#' 
-#' According to Hindler *et al.* (2007, \doi{10.1086/511864}), there are different methods (algorithms) to select first isolates with increasing reliability: isolate-based, patient-based, episode-based and phenotype-based. All methods select on a combination of the taxonomic genus and species (not subspecies). 
-#' 
+#'
+#' According to Hindler *et al.* (2007, \doi{10.1086/511864}), there are different methods (algorithms) to select first isolates with increasing reliability: isolate-based, patient-based, episode-based and phenotype-based. All methods select on a combination of the taxonomic genus and species (not subspecies).
+#'
 #' All mentioned methods are covered in the [first_isolate()] function:
-#' 
-#' 
+#'
+#'
 #' | **Method**                                       | **Function to apply**                                 |
 #' |--------------------------------------------------|-------------------------------------------------------|
 #' | **Isolate-based**                                | `first_isolate(x, method = "isolate-based")`          |
@@ -83,89 +82,76 @@
 #' | *(= first isolate per phenotype)*                |                                                       |
 #' | - Major difference in any antimicrobial result   | - `first_isolate(x, type = "points")`                 |
 #' | - Any difference in key antimicrobial results    | - `first_isolate(x, type = "keyantimicrobials")`      |
-#' 
+#'
 #' ### Isolate-based
-#' 
+#'
 #' This method does not require any selection, as all isolates should be included. It does, however, respect all arguments set in the [first_isolate()] function. For example, the default setting for `include_unknown` (`FALSE`) will omit selection of rows without a microbial ID.
-#' 
+#'
 #' ### Patient-based
-#' 
+#'
 #' To include every genus-species combination per patient once, set the `episode_days` to `Inf`. Although often inappropriate, this method makes sure that no duplicate isolates are selected from the same patient. In a large longitudinal data set, this could mean that isolates are *excluded* that were found years after the initial isolate.
-#' 
+#'
 #' ### Episode-based
-#' 
+#'
 #' To include every genus-species combination per patient episode once, set the `episode_days` to a sensible number of days. Depending on the type of analysis, this could be 14, 30, 60 or 365. Short episodes are common for analysing specific hospital or ward data, long episodes are common for analysing regional and national data.
-#' 
+#'
 #' This is the most common method to correct for duplicate isolates. Patients are categorised into episodes based on their ID and dates (e.g., the date of specimen receipt or laboratory result). While this is a common method, it does not take into account antimicrobial test results. This means that e.g. a methicillin-resistant *Staphylococcus aureus* (MRSA) isolate cannot be differentiated from a wildtype *Staphylococcus aureus* isolate.
-#' 
+#'
 #' ### Phenotype-based
-#' 
+#'
 #' This is a more reliable method, since it also *weighs* the antibiogram (antimicrobial test results) yielding so-called 'first weighted isolates'. There are two different methods to weigh the antibiogram:
-#' 
+#'
 #' 1. Using `type = "points"` and argument `points_threshold` (default)
-#' 
+#'
 #'    This method weighs *all* antimicrobial agents available in the data set. Any difference from I to S or R (or vice versa) counts as `0.5` points, a difference from S to R (or vice versa) counts as `1` point. When the sum of points exceeds `points_threshold`, which defaults to `2`, an isolate will be selected as a first weighted isolate.
-#'    
+#'
 #'    All antimicrobials are internally selected using the [all_antimicrobials()] function. The output of this function does not need to be passed to the [first_isolate()] function.
-#' 
-#'       
+#'
+#'
 #' 2. Using `type = "keyantimicrobials"` and argument `ignore_I`
-#' 
-#'    This method only weighs specific antimicrobial agents, called *key antimicrobials*. Any difference from S to R (or vice versa) in these key antimicrobials will select an isolate as a first weighted isolate. With `ignore_I = FALSE`, also differences from I to S or R (or vice versa) will lead to this. 
-#'    
+#'
+#'    This method only weighs specific antimicrobial agents, called *key antimicrobials*. Any difference from S to R (or vice versa) in these key antimicrobials will select an isolate as a first weighted isolate. With `ignore_I = FALSE`, also differences from I to S or R (or vice versa) will lead to this.
+#'
 #'    Key antimicrobials are internally selected using the [key_antimicrobials()] function, but can also be added manually as a variable to the data and set in the `col_keyantimicrobials` argument. Another option is to pass the output of the [key_antimicrobials()] function directly to the `col_keyantimicrobials` argument.
-#'    
-#'    
+#'
+#'
 #' The default method is phenotype-based (using `type = "points"`) and episode-based (using `episode_days = 365`). This makes sure that every genus-species combination is selected per patient once per year, while taking into account all antimicrobial test results. If no antimicrobial test results are available in the data set, only the episode-based method is applied at default.
 #' @rdname first_isolate
 #' @seealso [key_antimicrobials()]
 #' @export
-#' @return A [`logical`] vector
+#' @return A [logical] vector
 #' @source Methodology of this function is strictly based on:
-#' 
+#'
 #' - **M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition**, 2014, *Clinical and Laboratory Standards Institute (CLSI)*. <https://clsi.org/standards/products/microbiology/documents/m39/>.
-#' 
+#'
 #' - Hindler JF and Stelling J (2007). **Analysis and Presentation of Cumulative Antibiograms: A New Consensus Guideline from the Clinical and Laboratory Standards Institute.** Clinical Infectious Diseases, 44(6), 867-873. \doi{10.1086/511864}
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' # `example_isolates` is a data set available in the AMR package.
 #' # See ?example_isolates.
-#' 
+#'
 #' example_isolates[first_isolate(), ]
 #' \donttest{
 #' # get all first Gram-negatives
-#' example_isolates[which(first_isolate() & mo_is_gram_negative()), ]
+#' example_isolates[which(first_isolate(info = FALSE) & mo_is_gram_negative()), ]
 #'
 #' if (require("dplyr")) {
 #'   # filter on first isolates using dplyr:
 #'   example_isolates %>%
 #'     filter(first_isolate())
-#'  
+#' }
+#' if (require("dplyr")) {
+#'
 #'   # short-hand version:
 #'   example_isolates %>%
-#'     filter_first_isolate()
-#'     
-#'  # grouped determination of first isolates (also prints group names):
-#'  example_isolates %>%
-#'    group_by(hospital_id) %>%
-#'    mutate(first = first_isolate())
-#'   
-#'   # now let's see if first isolates matter:
-#'   A <- example_isolates %>%
-#'     group_by(hospital_id) %>%
-#'     summarise(count = n_rsi(GEN),            # gentamicin availability
-#'               resistance = resistance(GEN))  # gentamicin resistance
-#'  
-#'   B <- example_isolates %>%
-#'     filter_first_isolate() %>%               # the 1st isolate filter
-#'     group_by(hospital_id) %>%
-#'     summarise(count = n_rsi(GEN),            # gentamicin availability
-#'               resistance = resistance(GEN))  # gentamicin resistance
-#'  
-#'   # Have a look at A and B.
-#'   # B is more reliable because every isolate is counted only once.
-#'   # Gentamicin resistance in hospital D appears to be 4.2% higher than
-#'   # when you (erroneously) would have used all isolates for analysis.
+#'     filter_first_isolate(info = FALSE)
+#' }
+#' if (require("dplyr")) {
+#'
+#'   # flag the first isolates per group:
+#'   example_isolates %>%
+#'     group_by(ward) %>%
+#'     mutate(first = first_isolate()) %>%
+#'     select(ward, date, patient, mo, first)
 #' }
 #' }
 first_isolate <- function(x = NULL,
@@ -188,7 +174,6 @@ first_isolate <- function(x = NULL,
                           include_unknown = FALSE,
                           include_untested_rsi = TRUE,
                           ...) {
-  
   dots <- unlist(list(...))
   if (length(dots) != 0) {
     # backwards compatibility with old arguments
@@ -200,7 +185,7 @@ first_isolate <- function(x = NULL,
       col_keyantimicrobials <- dots[which(dots.names == "col_keyantibiotics")]
     }
   }
-  
+
   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)
@@ -215,7 +200,15 @@ first_isolate <- function(x = NULL,
     col_specimen <- NULL
   }
   meet_criteria(col_specimen, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
-  meet_criteria(col_icu, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
+  if (is.logical(col_icu)) {
+    meet_criteria(col_icu, allow_class = "logical", has_length = c(1, nrow(x)), allow_NULL = TRUE)
+    if (length(col_icu) == 1) {
+      col_icu <- rep(col_icu, nrow(x))
+    }
+  } else {
+    meet_criteria(col_icu, allow_class = c("character", "logical"), has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
+    col_icu <- x[, col_icu, drop = TRUE]
+  }
   # method
   method <- coerce_method(method)
   meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based"))
@@ -244,36 +237,43 @@ first_isolate <- function(x = NULL,
   meet_criteria(info, allow_class = "logical", has_length = 1)
   meet_criteria(include_unknown, allow_class = "logical", has_length = 1)
   meet_criteria(include_untested_rsi, allow_class = "logical", has_length = 1)
-  
+
   # remove data.table, grouping from tibbles, etc.
   x <- as.data.frame(x, stringsAsFactors = FALSE)
-  
-  any_col_contains_rsi <- any(vapply(FUN.VALUE = logical(1), 
-                                     X = x, 
-                                     # check only first 10,000 rows
-                                     FUN = function(x) any(as.character(x[1:10000]) %in% c("R", "S", "I"), na.rm = TRUE),
-                                     USE.NAMES = FALSE))
+
+  any_col_contains_rsi <- any(vapply(
+    FUN.VALUE = logical(1),
+    X = x,
+    # check only first 10,000 rows
+    FUN = function(x) any(as.character(x[1:10000]) %in% c("R", "S", "I"), na.rm = TRUE),
+    USE.NAMES = FALSE
+  ))
   if (method == "phenotype-based" & !any_col_contains_rsi) {
     method <- "episode-based"
   }
   if (info == TRUE & message_not_thrown_before("first_isolate", "method")) {
-    message_(paste0("Determining first isolates ",
-                    ifelse(method %in% c("episode-based", "phenotype-based"),
-                           ifelse(is.infinite(episode_days),
-                                  "without a specified episode length",
-                                  paste("using an episode length of", episode_days, "days")),
-                           "")),
-             as_note = FALSE,
-             add_fn = font_black)
+    message_(paste0(
+      "Determining first isolates ",
+      ifelse(method %in% c("episode-based", "phenotype-based"),
+        ifelse(is.infinite(episode_days),
+          "without a specified episode length",
+          paste("using an episode length of", episode_days, "days")
+        ),
+        ""
+      )
+    ),
+    as_note = FALSE,
+    add_fn = font_black
+    )
   }
-  
+
   # try to find columns based on type
   # -- mo
   if (is.null(col_mo)) {
     col_mo <- search_type_in_df(x = x, type = "mo", info = info)
     stop_if(is.null(col_mo), "`col_mo` must be set")
   }
-  
+
   # methods ----
   if (method == "isolate-based") {
     episode_days <- Inf
@@ -304,13 +304,13 @@ first_isolate <- function(x = NULL,
       }
     }
   }
-  
+
   # -- date
   if (is.null(col_date)) {
     col_date <- search_type_in_df(x = x, type = "date", info = info)
     stop_if(is.null(col_date), "`col_date` must be set")
   }
-  
+
   # -- patient id
   if (is.null(col_patient_id)) {
     if (all(c("First name", "Last name", "Sex") %in% colnames(x))) {
@@ -328,79 +328,86 @@ first_isolate <- function(x = NULL,
   if (is.null(col_specimen) & !is.null(specimen_group)) {
     col_specimen <- search_type_in_df(x = x, type = "specimen", info = info)
   }
-  
+
   # check if columns exist
   check_columns_existance <- function(column, tblname = x) {
     if (!is.null(column)) {
       stop_ifnot(column %in% colnames(tblname),
-                 "Column '", column, "' not found.", call = FALSE)
+        "Column '", column, "' not found.",
+        call = FALSE
+      )
     }
   }
-  
+
   check_columns_existance(col_date)
   check_columns_existance(col_patient_id)
   check_columns_existance(col_mo)
   check_columns_existance(col_testcode)
-  check_columns_existance(col_icu)
   check_columns_existance(col_keyantimicrobials)
-  
+
   # convert dates to Date
   dates <- as.Date(x[, col_date, drop = TRUE])
   dates[is.na(dates)] <- as.Date("1970-01-01")
   x[, col_date] <- dates
-  
+
   # create original row index
   x$newvar_row_index <- seq_len(nrow(x))
   x$newvar_mo <- as.mo(x[, col_mo, drop = TRUE])
   x$newvar_genus_species <- paste(mo_genus(x$newvar_mo), mo_species(x$newvar_mo))
   x$newvar_date <- x[, col_date, drop = TRUE]
   x$newvar_patient_id <- x[, col_patient_id, drop = TRUE]
-  
+
   if (is.null(col_testcode)) {
     testcodes_exclude <- NULL
   }
   # remove testcodes
   if (!is.null(testcodes_exclude) & info == TRUE & message_not_thrown_before("first_isolate", "excludingtestcodes")) {
     message_("Excluding test codes: ", vector_and(testcodes_exclude, quotes = TRUE),
-             add_fn = font_black,
-             as_note = FALSE)
+      add_fn = font_black,
+      as_note = FALSE
+    )
   }
-  
+
   if (is.null(col_specimen)) {
     specimen_group <- NULL
   }
-  
+
   # filter on specimen group and keyantibiotics when they are filled in
   if (!is.null(specimen_group)) {
     check_columns_existance(col_specimen, x)
     if (info == TRUE & message_not_thrown_before("first_isolate", "excludingspecimen")) {
       message_("Excluding other than specimen group '", specimen_group, "'",
-               add_fn = font_black,
-               as_note = FALSE)
+        add_fn = font_black,
+        as_note = FALSE
+      )
     }
   }
   if (!is.null(col_keyantimicrobials)) {
     x$newvar_key_ab <- x[, col_keyantimicrobials, drop = TRUE]
   }
-  
+
   if (is.null(testcodes_exclude)) {
     testcodes_exclude <- ""
   }
-  
+
   # arrange data to the right sorting
   if (is.null(specimen_group)) {
-    x <- x[order(x$newvar_patient_id, 
-                 x$newvar_genus_species,
-                 x$newvar_date), ]
+    x <- x[order(
+      x$newvar_patient_id,
+      x$newvar_genus_species,
+      x$newvar_date
+    ), ]
     rownames(x) <- NULL
     row.start <- 1
     row.end <- nrow(x)
   } else {
     # filtering on specimen and only analyse these rows to save time
-    x <- x[order(pm_pull(x, col_specimen),
-                 x$newvar_patient_id, 
-                 x$newvar_genus_species,
-                 x$newvar_date), ]
+    x <- x[order(
+      pm_pull(x, col_specimen),
+      x$newvar_patient_id,
+      x$newvar_genus_species,
+      x$newvar_date
+    ), ]
     rownames(x) <- NULL
     suppressWarnings(
       row.start <- which(x %pm>% pm_pull(col_specimen) == specimen_group) %pm>% min(na.rm = TRUE)
@@ -409,95 +416,111 @@ first_isolate <- function(x = NULL,
       row.end <- which(x %pm>% pm_pull(col_specimen) == specimen_group) %pm>% max(na.rm = TRUE)
     )
   }
-  
+
   # speed up - return immediately if obvious
   if (abs(row.start) == Inf | abs(row.end) == Inf) {
     if (info == TRUE) {
       message_("=> Found ", font_bold("no isolates"),
-               add_fn = font_black, 
-               as_note = FALSE)
+        add_fn = font_black,
+        as_note = FALSE
+      )
     }
     return(rep(FALSE, nrow(x)))
   }
   if (row.start == row.end) {
     if (info == TRUE) {
-      message_("=> Found ", font_bold("1 first isolate"), ", as the data only contained 1 row", 
-               add_fn = font_black,
-               as_note = FALSE)
+      message_("=> Found ", font_bold("1 first isolate"), ", as the data only contained 1 row",
+        add_fn = font_black,
+        as_note = FALSE
+      )
     }
     return(TRUE)
   }
   if (length(c(row.start:row.end)) == pm_n_distinct(x[c(row.start:row.end), col_mo, drop = TRUE])) {
     if (info == TRUE) {
       message_("=> Found ", font_bold(paste(length(c(row.start:row.end)), "first isolates")),
-               ", as all isolates were different microbial species",
-               add_fn = font_black,
-               as_note = FALSE)
+        ", as all isolates were different microbial species",
+        add_fn = font_black,
+        as_note = FALSE
+      )
     }
     return(rep(TRUE, length(c(row.start:row.end))))
   }
-  
+
   # did find some isolates - add new index numbers of rows
   x$newvar_row_index_sorted <- seq_len(nrow(x))
-  
+
   scope.size <- nrow(x[which(x$newvar_row_index_sorted %in% c(row.start + 1:row.end) &
-                               !is.na(x$newvar_mo)), , drop = FALSE])
-  
+    !is.na(x$newvar_mo)), , drop = FALSE])
+
   # Analysis of first isolate ----
   if (!is.null(col_keyantimicrobials)) {
     if (info == TRUE & message_not_thrown_before("first_isolate", "type")) {
       if (type == "keyantimicrobials") {
         message_("Basing inclusion on key antimicrobials, ",
-                 ifelse(ignore_I == FALSE, "not ", ""),
-                 "ignoring I",
-                 add_fn = font_black,
-                 as_note = FALSE)
+          ifelse(ignore_I == FALSE, "not ", ""),
+          "ignoring I",
+          add_fn = font_black,
+          as_note = FALSE
+        )
       }
       if (type == "points") {
         message_("Basing inclusion on all antimicrobial results, using a points threshold of ",
-                 points_threshold,
-                 add_fn = font_black,
-                 as_note = FALSE)
+          points_threshold,
+          add_fn = font_black,
+          as_note = FALSE
+        )
       }
     }
   }
-  
+
   x$other_pat_or_mo <- ifelse(x$newvar_patient_id == pm_lag(x$newvar_patient_id) &
-                                x$newvar_genus_species == pm_lag(x$newvar_genus_species),
-                              FALSE,
-                              TRUE)
-  
+    x$newvar_genus_species == pm_lag(x$newvar_genus_species),
+  FALSE,
+  TRUE
+  )
+
   x$episode_group <- paste(x$newvar_patient_id, x$newvar_genus_species)
-  x$more_than_episode_ago <- unlist(lapply(split(x$newvar_date,
-                                                 x$episode_group),
-                                           exec_episode, # this will skip meet_criteria() in is_new_episode(), saving time
-                                           type = "logical",
-                                           episode_days = episode_days),
-                                    use.names = FALSE)
-  
+  x$more_than_episode_ago <- unlist(lapply(split(
+    x$newvar_date,
+    x$episode_group
+  ),
+  exec_episode, # this will skip meet_criteria() in is_new_episode(), saving time
+  type = "logical",
+  episode_days = episode_days
+  ),
+  use.names = FALSE
+  )
+
   if (!is.null(col_keyantimicrobials)) {
     # with key antibiotics
-    x$other_key_ab <- !antimicrobials_equal(y = x$newvar_key_ab,
-                                            z = pm_lag(x$newvar_key_ab),
-                                            type = type,
-                                            ignore_I = ignore_I,
-                                            points_threshold = points_threshold)
-    x$newvar_first_isolate <- pm_if_else(x$newvar_row_index_sorted >= row.start &
-                                           x$newvar_row_index_sorted <= row.end &
-                                           x$newvar_genus_species != "" & 
-                                           (x$other_pat_or_mo | x$more_than_episode_ago | x$other_key_ab),
-                                         TRUE,
-                                         FALSE)
+    x$other_key_ab <- !antimicrobials_equal(
+      y = x$newvar_key_ab,
+      z = pm_lag(x$newvar_key_ab),
+      type = type,
+      ignore_I = ignore_I,
+      points_threshold = points_threshold
+    )
+    x$newvar_first_isolate <- pm_if_else(
+      x$newvar_row_index_sorted >= row.start &
+        x$newvar_row_index_sorted <= row.end &
+        x$newvar_genus_species != "" &
+        (x$other_pat_or_mo | x$more_than_episode_ago | x$other_key_ab),
+      TRUE,
+      FALSE
+    )
   } else {
     # no key antibiotics
-    x$newvar_first_isolate <- pm_if_else(x$newvar_row_index_sorted >= row.start &
-                                           x$newvar_row_index_sorted <= row.end &
-                                           x$newvar_genus_species != "" & 
-                                           (x$other_pat_or_mo | x$more_than_episode_ago),
-                                         TRUE,
-                                         FALSE)
+    x$newvar_first_isolate <- pm_if_else(
+      x$newvar_row_index_sorted >= row.start &
+        x$newvar_row_index_sorted <= row.end &
+        x$newvar_genus_species != "" &
+        (x$other_pat_or_mo | x$more_than_episode_ago),
+      TRUE,
+      FALSE
+    )
   }
-  
+
   # first one as TRUE
   x[row.start, "newvar_first_isolate"] <- TRUE
   # no tests that should be included, or ICU
@@ -506,20 +529,22 @@ first_isolate <- function(x = NULL,
   }
   if (!is.null(col_icu)) {
     if (icu_exclude == TRUE) {
-      message_("Excluding isolates from ICU.",
-               add_fn = font_black,
-               as_note = FALSE)
-      x[which(as.logical(x[, col_icu, drop = TRUE])), "newvar_first_isolate"] <- FALSE
+      message_("Excluding ", format(sum(col_icu, na.rm = TRUE), big.mark = ","), " isolates from ICU.",
+        add_fn = font_black,
+        as_note = FALSE
+      )
+      x[which(col_icu), "newvar_first_isolate"] <- FALSE
     } else {
       message_("Including isolates from ICU.",
-               add_fn = font_black,
-               as_note = FALSE)
+        add_fn = font_black,
+        as_note = FALSE
+      )
     }
   }
-  
+
   decimal.mark <- getOption("OutDec")
   big.mark <- ifelse(decimal.mark != ",", ",", ".")
-  
+
   if (info == TRUE) {
     # print group name if used in dplyr::group_by()
     cur_group <- import_fn("cur_group", "dplyr", error_on_fail = FALSE)
@@ -537,41 +562,50 @@ first_isolate <- function(x = NULL,
           }
         })
         message_("\nGroup: ", paste0(names(group), " = ", group, collapse = ", "), "\n",
-                 as_note = FALSE,
-                 add_fn = font_red)
+          as_note = FALSE,
+          add_fn = font_red
+        )
       }
     }
   }
-  
+
   # handle empty microorganisms
   if (any(x$newvar_mo == "UNKNOWN", na.rm = TRUE) & info == TRUE) {
-    message_(ifelse(include_unknown == TRUE, "Included ", "Excluded "), 
-             format(sum(x$newvar_mo == "UNKNOWN", na.rm = TRUE),
-                    decimal.mark = decimal.mark, big.mark = big.mark), 
-             " isolates with a microbial ID 'UNKNOWN' (in column '", font_bold(col_mo), "')")
+    message_(
+      ifelse(include_unknown == TRUE, "Included ", "Excluded "),
+      format(sum(x$newvar_mo == "UNKNOWN", na.rm = TRUE),
+        decimal.mark = decimal.mark, big.mark = big.mark
+      ),
+      " isolates with a microbial ID 'UNKNOWN' (in column '", font_bold(col_mo), "')"
+    )
   }
   x[which(x$newvar_mo == "UNKNOWN"), "newvar_first_isolate"] <- include_unknown
-  
+
   # exclude all NAs
   if (any(is.na(x$newvar_mo)) & info == TRUE) {
-    message_("Excluded ", format(sum(is.na(x$newvar_mo), na.rm = TRUE),
-                                 decimal.mark = decimal.mark, big.mark = big.mark), 
-             " isolates with a microbial ID 'NA' (in column '", font_bold(col_mo), "')")
+    message_(
+      "Excluded ", format(sum(is.na(x$newvar_mo), na.rm = TRUE),
+        decimal.mark = decimal.mark, big.mark = big.mark
+      ),
+      " isolates with a microbial ID 'NA' (in column '", font_bold(col_mo), "')"
+    )
   }
   x[which(is.na(x$newvar_mo)), "newvar_first_isolate"] <- FALSE
-  
+
   # handle isolates without antibiogram
   if (include_untested_rsi == FALSE && any(is.rsi(x))) {
-    rsi_all_NA <- which(unname(vapply(FUN.VALUE = logical(1), 
-                                      as.data.frame(t(x[, is.rsi(x), drop = FALSE])),
-                                      function(rsi_values) all(is.na(rsi_values)))))
+    rsi_all_NA <- which(unname(vapply(
+      FUN.VALUE = logical(1),
+      as.data.frame(t(x[, is.rsi(x), drop = FALSE])),
+      function(rsi_values) all(is.na(rsi_values))
+    )))
     x[rsi_all_NA, "newvar_first_isolate"] <- FALSE
   }
-  
+
   # arrange back according to original sorting again
   x <- x[order(x$newvar_row_index), , drop = FALSE]
   rownames(x) <- NULL
-  
+
   if (info == TRUE) {
     n_found <- sum(x$newvar_first_isolate, na.rm = TRUE)
     p_found_total <- percentage(n_found / nrow(x[which(!is.na(x$newvar_mo)), , drop = FALSE]), digits = 1)
@@ -584,20 +618,25 @@ first_isolate <- function(x = NULL,
     }
     # mark up number of found
     n_found <- format(n_found, big.mark = big.mark, decimal.mark = decimal.mark)
-    message_(paste0("=> Found ",
-                    font_bold(paste0(n_found,
-                                     ifelse(method == "isolate-based", "", paste0(" '", method, "'")),
-                                     " first isolates")),
-                    " (",
-                    ifelse(p_found_total != p_found_scope,
-                           paste0(p_found_scope, " within scope and "),
-                           ""),
-                    p_found_total, " of total where a microbial ID was available)"),
-             add_fn = font_black, as_note = FALSE)
+    message_(paste0(
+      "=> Found ",
+      font_bold(paste0(
+        n_found,
+        ifelse(method == "isolate-based", "", paste0(" '", method, "'")),
+        " first isolates"
+      )),
+      " (",
+      ifelse(p_found_total != p_found_scope,
+        paste0(p_found_scope, " within scope and "),
+        ""
+      ),
+      p_found_total, " of total where a microbial ID was available)"
+    ),
+    add_fn = font_black, as_note = FALSE
+    )
   }
-  
+
   x$newvar_first_isolate
-  
 }
 
 #' @rdname first_isolate
@@ -621,14 +660,16 @@ filter_first_isolate <- function(x = NULL,
   meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
   method <- coerce_method(method)
   meet_criteria(method, allow_class = "character", has_length = 1, is_in = c("phenotype-based", "episode-based", "patient-based", "isolate-based"))
-  
-  subset(x, first_isolate(x = x,
-                          col_date = col_date,
-                          col_patient_id = col_patient_id,
-                          col_mo = col_mo,
-                          episode_days = episode_days,
-                          method = method,
-                          ...))
+
+  subset(x, first_isolate(
+    x = x,
+    col_date = col_date,
+    col_patient_id = col_patient_id,
+    col_mo = col_mo,
+    episode_days = episode_days,
+    method = method,
+    ...
+  ))
 }
 
 coerce_method <- function(method) {

R/g.test.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' *G*-test for Count Data
 #'
 #' [g.test()] performs chi-squared contingency table tests and goodness-of-fit tests, just like [chisq.test()] but is more reliable (1). A *G*-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a ***G*-test of goodness-of-fit**), or to see whether the proportions of one variable are different for different values of the other variable (called a ***G*-test of independence**).
-#' @inheritSection lifecycle Questioning Lifecycle
 #' @inherit stats::chisq.test params return
 #' @details If `x` is a [matrix] with one row or column, or if `x` is a vector and `y` is not given, then a *goodness-of-fit test* is performed (`x` is treated as a one-dimensional contingency table). The entries of `x` must be non-negative integers. In this case, the hypothesis tested is whether the population probabilities equal those in `p`, or are all equal if `p` is not given.
 #'
@@ -37,7 +36,7 @@
 #' In the contingency table case simulation is done by random sampling from the set of all contingency tables with given marginals, and works only if the marginals are strictly positive. Note that this is not the usual sampling situation assumed for a chi-squared test (such as the *G*-test) but rather that for Fisher's exact test.
 #'
 #' In the goodness-of-fit case simulation is done by random sampling from the discrete distribution specified by `p`, each sample being of size `n = sum(x)`. This simulation is done in \R and may be slow.
-#'   
+#'
 #' ## *G*-test Of Goodness-of-Fit (Likelihood Ratio Test)
 #' Use the *G*-test of goodness-of-fit when you have one nominal variable with two or more values (such as male and female, or red, pink and white flowers). You compare the observed counts of numbers of observations in each category with the expected counts, which you calculate using some kind of theoretical expectation (such as a 1:1 sex ratio or a 1:2:1 ratio in a genetic cross).
 #'
@@ -58,9 +57,9 @@
 #' Unlike the exact test of goodness-of-fit ([fisher.test()]), the *G*-test does not directly calculate the probability of obtaining the observed results or something more extreme. Instead, like almost all statistical tests, the *G*-test has an intermediate step; it uses the data to calculate a test statistic that measures how far the observed data are from the null expectation. You then use a mathematical relationship, in this case the chi-square distribution, to estimate the probability of obtaining that value of the test statistic.
 #'
 #' The *G*-test uses the log of the ratio of two likelihoods as the test statistic, which is why it is also called a likelihood ratio test or log-likelihood ratio test. The formula to calculate a *G*-statistic is:
-#' 
+#'
 #' \eqn{G = 2 * sum(x * log(x / E))}
-#' 
+#'
 #' where `E` are the expected values. Since this is chi-square distributed, the p value can be calculated in \R with:
 #' ```
 #' p <- stats::pchisq(G, df, lower.tail = FALSE)
@@ -76,7 +75,6 @@
 #' - The possibility to simulate p values with `simulate.p.value` was removed
 #' @export
 #' @importFrom stats pchisq complete.cases
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' # = EXAMPLE 1 =
 #' # Shivrain et al. (2006) crossed clearfield rice (which are resistant
@@ -88,8 +86,7 @@
 #' # ratio.
 #'
 #' x <- c(772, 1611, 737)
-#' G <- g.test(x, p = c(1, 2, 1) / 4)
-#' # G$p.value = 0.12574.
+#' g.test(x, p = c(1, 2, 1) / 4)
 #'
 #' # There is no significant difference from a 1:2:1 ratio.
 #' # Meaning: resistance controlled by a single gene with two co-dominant
@@ -105,103 +102,121 @@
 #'
 #' x <- c(1752, 1895)
 #' g.test(x)
-#' # p = 0.01787343
 #'
 #' # There is a significant difference from a 1:1 ratio.
 #' # Meaning: there are significantly more left-billed birds.
-#'
 g.test <- function(x,
                    y = NULL,
                    # correct = TRUE,
                    p = rep(1 / length(x), length(x)),
                    rescale.p = FALSE) {
   DNAME <- deparse(substitute(x))
-  if (is.data.frame(x))
+  if (is.data.frame(x)) {
     x <- as.matrix(x)
+  }
   if (is.matrix(x)) {
-    if (min(dim(x)) == 1L)
+    if (min(dim(x)) == 1L) {
       x <- as.vector(x)
+    }
   }
   if (!is.matrix(x) && !is.null(y)) {
-    if (length(x) != length(y))
+    if (length(x) != length(y)) {
       stop("'x' and 'y' must have the same length")
+    }
     DNAME2 <- deparse(substitute(y))
     xname <- if (length(DNAME) > 1L || nchar(DNAME, "w") >
-                 30)
+      30) {
       ""
-    else DNAME
+    } else {
+      DNAME
+    }
     yname <- if (length(DNAME2) > 1L || nchar(DNAME2, "w") >
-                 30)
+      30) {
       ""
-    else DNAME2
+    } else {
+      DNAME2
+    }
     OK <- complete.cases(x, y)
     x <- factor(x[OK])
     y <- factor(y[OK])
-    if ((nlevels(x) < 2L) || (nlevels(y) < 2L))
+    if ((nlevels(x) < 2L) || (nlevels(y) < 2L)) {
       stop("'x' and 'y' must have at least 2 levels")
+    }
     x <- table(x, y)
     names(dimnames(x)) <- c(xname, yname)
-    DNAME <- paste(paste(DNAME, collapse = "\n"), "and",
-                   paste(DNAME2, collapse = "\n"))
+    DNAME <- paste(
+      paste(DNAME, collapse = "\n"), "and",
+      paste(DNAME2, collapse = "\n")
+    )
   }
-  if (any(x < 0) || any(is.na((x)))) # this last one was anyNA, but only introduced in R 3.1.0
+  if (any(x < 0) || any(is.na((x)))) { # this last one was anyNA, but only introduced in R 3.1.0
     stop("all entries of 'x' must be nonnegative and finite")
-  if ((n <- sum(x)) == 0)
+  }
+  if ((n <- sum(x)) == 0) {
     stop("at least one entry of 'x' must be positive")
-  
-  
+  }
+
+
   if (is.matrix(x)) {
     METHOD <- "G-test of independence"
     nr <- as.integer(nrow(x))
     nc <- as.integer(ncol(x))
-    if (is.na(nr) || is.na(nc) || is.na(nr * nc))
+    if (is.na(nr) || is.na(nc) || is.na(nr * nc)) {
       stop("invalid nrow(x) or ncol(x)", domain = NA)
+    }
     # add fisher.test suggestion
-    if (nr == 2 && nc == 2)
+    if (nr == 2 && nc == 2) {
       warning("`fisher.test()` is always more reliable for 2x2 tables and although much slower, often only takes seconds.")
+    }
     sr <- rowSums(x)
     sc <- colSums(x)
     E <- outer(sr, sc, "*") / n
-    v <- function(r, c, n) c * r * (n - r) * (n - c) / n ^ 3
+    v <- function(r, c, n) c * r * (n - r) * (n - c) / n^3
     V <- outer(sr, sc, v, n)
     dimnames(E) <- dimnames(x)
-    
+
     STATISTIC <- 2 * sum(x * log(x / E)) # sum((abs(x - E) - YATES)^2/E) for chisq.test
     PARAMETER <- (nr - 1L) * (nc - 1L)
     PVAL <- pchisq(STATISTIC, PARAMETER, lower.tail = FALSE)
-    
-  }
-  else {
-    if (length(dim(x)) > 2L)
+  } else {
+    if (length(dim(x)) > 2L) {
       stop("invalid 'x'")
-    if (length(x) == 1L)
+    }
+    if (length(x) == 1L) {
       stop("'x' must at least have 2 elements")
-    if (length(x) != length(p))
+    }
+    if (length(x) != length(p)) {
       stop("'x' and 'p' must have the same number of elements")
-    if (any(p < 0))
+    }
+    if (any(p < 0)) {
       stop("probabilities must be non-negative.")
+    }
     if (abs(sum(p) - 1) > sqrt(.Machine$double.eps)) {
-      if (rescale.p)
+      if (rescale.p) {
         p <- p / sum(p)
-      else stop("probabilities must sum to 1.")
+      } else {
+        stop("probabilities must sum to 1.")
+      }
     }
     METHOD <- "G-test of goodness-of-fit (likelihood ratio test)"
     E <- n * p
     V <- n * p * (1 - p)
     STATISTIC <- 2 * sum(x * log(x / E)) # sum((x - E)^2/E) for chisq.test
     names(E) <- names(x)
-    
+
     PARAMETER <- length(x) - 1
     PVAL <- pchisq(STATISTIC, PARAMETER, lower.tail = FALSE)
-    
   }
   names(STATISTIC) <- "X-squared"
   names(PARAMETER) <- "df"
-  if (any(E < 5) && is.finite(PARAMETER))
+  if (any(E < 5) && is.finite(PARAMETER)) {
     warning("G-statistic approximation may be incorrect due to E < 5")
-  
-  structure(list(statistic = STATISTIC, argument = PARAMETER,
-                 p.value = PVAL, method = METHOD, data.name = DNAME,
-                 observed = x, expected = E, residuals = (x - E) / sqrt(E),
-                 stdres = (x - E) / sqrt(V)), class = "htest")
+  }
+
+  structure(list(
+    statistic = STATISTIC, argument = PARAMETER,
+    p.value = PVAL, method = METHOD, data.name = DNAME,
+    observed = x, expected = E, residuals = (x - E) / sqrt(E),
+    stdres = (x - E) / sqrt(V)
+  ), class = "htest")
 }

R/ggplot_pca.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' PCA Biplot with `ggplot2`
 #'
 #' Produces a `ggplot2` variant of a so-called [biplot](https://en.wikipedia.org/wiki/Biplot) for PCA (principal component analysis), but is more flexible and more appealing than the base \R [biplot()] function.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x an object returned by [pca()], [prcomp()] or [princomp()]
 #' @inheritParams stats::biplot.prcomp
 #' @param labels an optional vector of labels for the observations. If set, the labels will be placed below their respective points. When using the [pca()] function as input for `x`, this will be determined automatically based on the attribute `non_numeric_cols`, see [pca()].
@@ -49,8 +48,8 @@
 #' @param base_textsize the text size for all plot elements except the labels and arrows
 #' @param ... arguments passed on to functions
 #' @source The [ggplot_pca()] function is based on the `ggbiplot()` function from the `ggbiplot` package by Vince Vu, as found on GitHub: <https://github.com/vqv/ggbiplot> (retrieved: 2 March 2020, their latest commit: [`7325e88`](https://github.com/vqv/ggbiplot/commit/7325e880485bea4c07465a0304c470608fffb5d9); 12 February 2015).
-#' 
-#' As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were: 
+#'
+#' As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were:
 #' 1. Rewritten code to remove the dependency on packages `plyr`, `scales` and `grid`
 #' 2. Parametrised more options, like arrow and ellipse settings
 #' 3. Hardened all input possibilities by defining the exact type of user input for every argument
@@ -60,27 +59,34 @@
 #' @details The colours for labels and points can be changed by adding another scale layer for colour, such as `scale_colour_viridis_d()` and `scale_colour_brewer()`.
 #' @rdname ggplot_pca
 #' @export
-#' @examples 
+#' @examples
 #' # `example_isolates` is a data set available in the AMR package.
 #' # See ?example_isolates.
 #'
-#' # See ?pca for more info about Principal Component Analysis (PCA).
 #' \donttest{
 #' if (require("dplyr")) {
-#'   pca_model <- example_isolates %>% 
-#'     filter(mo_genus(mo) == "Staphylococcus") %>% 
-#'     group_by(species = mo_shortname(mo)) %>%
-#'     summarise_if (is.rsi, resistance) %>%
-#'     pca(FLC, AMC, CXM, GEN, TOB, TMP, SXT, CIP, TEC, TCY, ERY)
-#'     
-#'   # old (base R)
-#'   biplot(pca_model)
-#'   
-#'   # new 
-#'   ggplot_pca(pca_model)
-#'   
+#'   # calculate the resistance per group first
+#'   resistance_data <- example_isolates %>%
+#'     group_by(
+#'       order = mo_order(mo), # group on anything, like order
+#'       genus = mo_genus(mo)
+#'     ) %>% #   and genus as we do here;
+#'     filter(n() >= 30) %>% # filter on only 30 results per group
+#'     summarise_if(is.rsi, resistance) # then get resistance of all drugs
+#'
+#'   # now conduct PCA for certain antimicrobial agents
+#'   pca_result <- resistance_data %>%
+#'     pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)
+#'
+#'   summary(pca_result)
+#'
+#'   # old base R plotting method:
+#'   biplot(pca_result)
+#'   # new ggplot2 plotting method using this package:
+#'   ggplot_pca(pca_result)
+#'
 #'   if (require("ggplot2")) {
-#'     ggplot_pca(pca_model) +
+#'     ggplot_pca(pca_result) +
 #'       scale_colour_viridis_d() +
 #'       labs(title = "Title here")
 #'   }
@@ -108,7 +114,6 @@ ggplot_pca <- function(x,
                        arrows_alpha = 0.75,
                        base_textsize = 10,
                        ...) {
-  
   stop_ifnot_installed("ggplot2")
   meet_criteria(x, allow_class = c("prcomp", "princomp", "PCA", "lda"))
   meet_criteria(choices, allow_class = c("numeric", "integer"), has_length = 2, is_positive = TRUE, is_finite = TRUE)
@@ -131,17 +136,19 @@ ggplot_pca <- function(x,
   meet_criteria(arrows_textangled, allow_class = "logical", has_length = 1)
   meet_criteria(arrows_alpha, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
   meet_criteria(base_textsize, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
-  
-  calculations <- pca_calculations(pca_model = x,
-                                   groups = groups, 
-                                   groups_missing = missing(groups),
-                                   labels = labels,
-                                   labels_missing = missing(labels),
-                                   choices = choices,
-                                   scale = scale,
-                                   pc.biplot = pc.biplot,
-                                   ellipse_prob = ellipse_prob,
-                                   labels_text_placement = labels_text_placement)
+
+  calculations <- pca_calculations(
+    pca_model = x,
+    groups = groups,
+    groups_missing = missing(groups),
+    labels = labels,
+    labels_missing = missing(labels),
+    choices = choices,
+    scale = scale,
+    pc.biplot = pc.biplot,
+    ellipse_prob = ellipse_prob,
+    labels_text_placement = labels_text_placement
+  )
   choices <- calculations$choices
   df.u <- calculations$df.u
   df.v <- calculations$df.v
@@ -149,111 +156,141 @@ ggplot_pca <- function(x,
   groups <- calculations$groups
   group_name <- calculations$group_name
   labels <- calculations$labels
-  
+
   # Append the proportion of explained variance to the axis labels
   if ((1 - as.integer(scale)) == 0) {
     u.axis.labs <- paste0("Standardised PC", choices)
   } else {
     u.axis.labs <- paste0("PC", choices)
   }
-  u.axis.labs <- paste0(u.axis.labs,
-                        paste0("\n(explained var: ", 
-                               percentage(x$sdev[choices] ^ 2 / sum(x$sdev ^ 2)),
-                               ")"))
-  
+  u.axis.labs <- paste0(
+    u.axis.labs,
+    paste0(
+      "\n(explained var: ",
+      percentage(x$sdev[choices]^2 / sum(x$sdev^2)),
+      ")"
+    )
+  )
+
   # Score Labels
   if (!is.null(labels)) {
     df.u$labels <- labels
   }
-  
+
   # Grouping variable
   if (!is.null(groups)) {
     df.u$groups <- groups
   }
-  
+
   # Base plot
-  g <- ggplot2::ggplot(data = df.u, 
-                       ggplot2::aes(x = xvar, y = yvar)) + 
-    ggplot2::xlab(u.axis.labs[1]) + 
-    ggplot2::ylab(u.axis.labs[2]) + 
-    ggplot2::expand_limits(x = c(-1.15, 1.15),
-                           y = c(-1.15, 1.15))
-  
+  g <- ggplot2::ggplot(
+    data = df.u,
+    ggplot2::aes(x = xvar, y = yvar)
+  ) +
+    ggplot2::xlab(u.axis.labs[1]) +
+    ggplot2::ylab(u.axis.labs[2]) +
+    ggplot2::expand_limits(
+      x = c(-1.15, 1.15),
+      y = c(-1.15, 1.15)
+    )
+
   # Draw either labels or points
   if (!is.null(df.u$labels)) {
     if (!is.null(df.u$groups)) {
       g <- g + ggplot2::geom_point(ggplot2::aes(colour = groups),
-                                   alpha = points_alpha, 
-                                   size = points_size) +
+        alpha = points_alpha,
+        size = points_size
+      ) +
         ggplot2::geom_text(ggplot2::aes(label = labels, colour = groups),
-                           nudge_y = -0.05,
-                           size = labels_textsize) +
+          nudge_y = -0.05,
+          size = labels_textsize
+        ) +
         ggplot2::labs(colour = group_name)
     } else {
-      g <- g + ggplot2::geom_point(alpha = points_alpha, 
-                                   size = points_size) +
+      g <- g + ggplot2::geom_point(
+        alpha = points_alpha,
+        size = points_size
+      ) +
         ggplot2::geom_text(ggplot2::aes(label = labels),
-                           nudge_y = -0.05,
-                           size = labels_textsize)      
+          nudge_y = -0.05,
+          size = labels_textsize
+        )
     }
   } else {
     if (!is.null(df.u$groups)) {
       g <- g + ggplot2::geom_point(ggplot2::aes(colour = groups),
-                                   alpha = points_alpha,
-                                   size = points_size) +
+        alpha = points_alpha,
+        size = points_size
+      ) +
         ggplot2::labs(colour = group_name)
     } else {
-      g <- g + ggplot2::geom_point(alpha = points_alpha,
-                                   size = points_size)      
+      g <- g + ggplot2::geom_point(
+        alpha = points_alpha,
+        size = points_size
+      )
     }
   }
-  
+
   # Overlay a concentration ellipse if there are groups
   if (!is.null(df.u$groups) & !is.null(ell) & isTRUE(ellipse)) {
-    g <- g + ggplot2::geom_path(data = ell, 
-                                ggplot2::aes(colour = groups, group = groups),
-                                size = ellipse_size,
-                                alpha = points_alpha)
+    g <- g + ggplot2::geom_path(
+      data = ell,
+      ggplot2::aes(colour = groups, group = groups),
+      size = ellipse_size,
+      alpha = points_alpha
+    )
   }
-  
+
   # Label the variable axes
   if (arrows == TRUE) {
-    g <- g + ggplot2::geom_segment(data = df.v,
-                                   ggplot2::aes(x = 0, y = 0, xend = xvar, yend = yvar),
-                                   arrow = ggplot2::arrow(length = ggplot2::unit(0.5, "picas"),
-                                                          angle = 20,
-                                                          ends = "last",
-                                                          type = "open"), 
-                                   colour = arrows_colour, 
-                                   size = arrows_size,
-                                   alpha = arrows_alpha)
+    g <- g + ggplot2::geom_segment(
+      data = df.v,
+      ggplot2::aes(x = 0, y = 0, xend = xvar, yend = yvar),
+      arrow = ggplot2::arrow(
+        length = ggplot2::unit(0.5, "picas"),
+        angle = 20,
+        ends = "last",
+        type = "open"
+      ),
+      colour = arrows_colour,
+      size = arrows_size,
+      alpha = arrows_alpha
+    )
     if (arrows_textangled == TRUE) {
-      g <- g + ggplot2::geom_text(data = df.v, 
-                                  ggplot2::aes(label = varname, x = xvar, y = yvar, angle = angle, hjust = hjust), 
-                                  colour = arrows_colour,
-                                  size = arrows_textsize,
-                                  alpha = arrows_alpha)
+      g <- g + ggplot2::geom_text(
+        data = df.v,
+        ggplot2::aes(label = varname, x = xvar, y = yvar, angle = angle, hjust = hjust),
+        colour = arrows_colour,
+        size = arrows_textsize,
+        alpha = arrows_alpha
+      )
     } else {
-      g <- g + ggplot2::geom_text(data = df.v, 
-                                  ggplot2::aes(label = varname, x = xvar, y = yvar, hjust = hjust), 
-                                  colour = arrows_colour,
-                                  size = arrows_textsize,
-                                  alpha = arrows_alpha)
+      g <- g + ggplot2::geom_text(
+        data = df.v,
+        ggplot2::aes(label = varname, x = xvar, y = yvar, hjust = hjust),
+        colour = arrows_colour,
+        size = arrows_textsize,
+        alpha = arrows_alpha
+      )
     }
   }
-  
+
   # Add caption label about total explained variance
-  g <- g + ggplot2::labs(caption = paste0("Total explained variance: ",
-                                          percentage(sum(x$sdev[choices] ^ 2 / sum(x$sdev ^ 2)))))
-  
+  g <- g + ggplot2::labs(caption = paste0(
+    "Total explained variance: ",
+    percentage(sum(x$sdev[choices]^2 / sum(x$sdev^2)))
+  ))
+
   # mark-up nicely
   g <- g + ggplot2::theme_minimal(base_size = base_textsize) +
-    ggplot2::theme(panel.grid.major = ggplot2::element_line(colour = "grey85"),
-                   panel.grid.minor = ggplot2::element_blank(),
-                   # centre title and subtitle
-                   plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5))
-  
+    ggplot2::theme(
+      panel.grid.major = ggplot2::element_line(colour = "grey85"),
+      panel.grid.minor = ggplot2::element_blank(),
+      # centre title and subtitle
+      plot.title = ggplot2::element_text(hjust = 0.5),
+      plot.subtitle = ggplot2::element_text(hjust = 0.5)
+    )
+
   g
 }
 
@@ -268,17 +305,19 @@ pca_calculations <- function(pca_model,
                              pc.biplot = TRUE,
                              ellipse_prob = 0.68,
                              labels_text_placement = 1.5) {
-  
   non_numeric_cols <- attributes(pca_model)$non_numeric_cols
   if (groups_missing) {
     groups <- tryCatch(non_numeric_cols[[1]],
-                       error = function(e) NULL)
+      error = function(e) NULL
+    )
     group_name <- tryCatch(colnames(non_numeric_cols[1]),
-                           error = function(e) NULL)
+      error = function(e) NULL
+    )
   }
   if (labels_missing) {
     labels <- tryCatch(non_numeric_cols[[2]],
-                       error = function(e) NULL)
+      error = function(e) NULL
+    )
   }
   if (!is.null(groups) & is.null(labels)) {
     # turn them around
@@ -286,7 +325,7 @@ pca_calculations <- function(pca_model,
     groups <- NULL
     group_name <- NULL
   }
-  
+
   # Recover the SVD
   if (inherits(pca_model, "prcomp")) {
     nobs.factor <- sqrt(nrow(pca_model$x) - 1)
@@ -311,66 +350,72 @@ pca_calculations <- function(pca_model,
   } else {
     stop("Expected an object of class prcomp, princomp, PCA, or lda")
   }
-  
+
   # Scores
   choices <- pmin(choices, ncol(u))
   obs.scale <- 1 - as.integer(scale)
-  df.u <- as.data.frame(sweep(u[, choices], 2, d[choices] ^ obs.scale, FUN = "*"),
-                        stringsAsFactors = FALSE)
-  
+  df.u <- as.data.frame(sweep(u[, choices], 2, d[choices]^obs.scale, FUN = "*"),
+    stringsAsFactors = FALSE
+  )
+
   # Directions
-  v <- sweep(v, 2, d ^ as.integer(scale), FUN = "*")
+  v <- sweep(v, 2, d^as.integer(scale), FUN = "*")
   df.v <- as.data.frame(v[, choices],
-                        stringsAsFactors = FALSE)
-  
+    stringsAsFactors = FALSE
+  )
+
   names(df.u) <- c("xvar", "yvar")
   names(df.v) <- names(df.u)
-  
+
   if (isTRUE(pc.biplot)) {
     df.u <- df.u * nobs.factor
   }
-  
-  # Scale the radius of the correlation circle so that it corresponds to 
+
+  # Scale the radius of the correlation circle so that it corresponds to
   # a data ellipse for the standardized PC scores
   circle_prob <- 0.69
-  r <- sqrt(qchisq(circle_prob, df = 2)) * prod(colMeans(df.u ^ 2)) ^ (0.25)
-  
+  r <- sqrt(qchisq(circle_prob, df = 2)) * prod(colMeans(df.u^2))^(0.25)
+
   # Scale directions
-  v.scale <- rowSums(v ^ 2)
+  v.scale <- rowSums(v^2)
   df.v <- r * df.v / sqrt(max(v.scale))
-  
+
   # Grouping variable
   if (!is.null(groups)) {
     df.u$groups <- groups
   }
-  
+
   df.v$varname <- rownames(v)
-  
+
   # Variables for text label placement
   df.v$angle <- with(df.v, (180 / pi) * atan(yvar / xvar))
   df.v$hjust <- with(df.v, (1 - labels_text_placement * sign(xvar)) / 2)
-  
+
   if (!is.null(df.u$groups)) {
     theta <- c(seq(-pi, pi, length = 50), seq(pi, -pi, length = 50))
     circle <- cbind(cos(theta), sin(theta))
-    
+
     df.groups <- lapply(unique(df.u$groups), function(g, df = df.u) {
       x <- df[which(df$groups == g), , drop = FALSE]
       if (nrow(x) <= 2) {
-        return(data.frame(X1 = numeric(0),
-                          X2 = numeric(0),
-                          groups = character(0),
-                          stringsAsFactors = FALSE))
+        return(data.frame(
+          X1 = numeric(0),
+          X2 = numeric(0),
+          groups = character(0),
+          stringsAsFactors = FALSE
+        ))
       }
       sigma <- var(cbind(x$xvar, x$yvar))
       mu <- c(mean(x$xvar), mean(x$yvar))
       ed <- sqrt(qchisq(ellipse_prob, df = 2))
       data.frame(sweep(circle %*% chol(sigma) * ed,
-                       MARGIN = 2,
-                       STATS = mu, 
-                       FUN = "+"), 
-                 groups = x$groups[1],
-                 stringsAsFactors = FALSE)
+        MARGIN = 2,
+        STATS = mu,
+        FUN = "+"
+      ),
+      groups = x$groups[1],
+      stringsAsFactors = FALSE
+      )
     })
     ell <- do.call(rbind, df.groups)
     if (NROW(ell) == 0) {
@@ -381,13 +426,14 @@ pca_calculations <- function(pca_model,
   } else {
     ell <- NULL
   }
-  
-  list(choices = choices,
-       df.u = df.u,
-       df.v = df.v,
-       ell = ell,
-       groups = groups,
-       group_name = group_name,
-       labels = labels
+
+  list(
+    choices = choices,
+    df.u = df.u,
+    df.v = df.v,
+    ell = ell,
+    groups = groups,
+    group_name = group_name,
+    labels = labels
   )
 }

R/ggplot_rsi.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' AMR Plots with `ggplot2`
 #'
 #' Use these functions to create bar plots for AMR data analysis. All functions rely on [ggplot2][ggplot2::ggplot()] functions.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param data a [data.frame] with column(s) of class [`rsi`] (see [as.rsi()])
 #' @param position position adjustment of bars, either `"fill"`, `"stack"` or `"dodge"`
 #' @param x variable to show on x axis, either `"antibiotic"` (default) or `"interpretation"` or a grouping variable
@@ -65,15 +64,16 @@
 #' [ggplot_rsi()] is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (`%>%`). See *Examples*.
 #' @rdname ggplot_rsi
 #' @export
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' \donttest{
-#' if (require("ggplot2") & require("dplyr")) {
-#'  
+#' if (require("ggplot2") && require("dplyr")) {
+#'
 #'   # get antimicrobial results for drugs against a UTI:
 #'   ggplot(example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)) +
 #'     geom_rsi()
-#'  
+#' }
+#' if (require("ggplot2") && require("dplyr")) {
+#'
 #'   # prettify the plot using some additional functions:
 #'   df <- example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)
 #'   ggplot(df) +
@@ -82,68 +82,91 @@
 #'     scale_rsi_colours() +
 #'     labels_rsi_count() +
 #'     theme_rsi()
-#'  
+#' }
+#' if (require("ggplot2") && require("dplyr")) {
+#'
 #'   # or better yet, simplify this using the wrapper function - a single command:
 #'   example_isolates %>%
 #'     select(AMX, NIT, FOS, TMP, CIP) %>%
 #'     ggplot_rsi()
-#'  
+#' }
+#' if (require("ggplot2") && require("dplyr")) {
+#'
 #'   # get only proportions and no counts:
 #'   example_isolates %>%
 #'     select(AMX, NIT, FOS, TMP, CIP) %>%
 #'     ggplot_rsi(datalabels = FALSE)
-#'  
+#' }
+#' if (require("ggplot2") && require("dplyr")) {
+#'
 #'   # add other ggplot2 arguments as you like:
 #'   example_isolates %>%
 #'     select(AMX, NIT, FOS, TMP, CIP) %>%
-#'     ggplot_rsi(width = 0.5,
-#'                colour = "black",
-#'                size = 1,
-#'                linetype = 2,
-#'                alpha = 0.25)
+#'     ggplot_rsi(
+#'       width = 0.5,
+#'       colour = "black",
+#'       size = 1,
+#'       linetype = 2,
+#'       alpha = 0.25
+#'     )
+#' }
+#' if (require("ggplot2") && require("dplyr")) {
 #'
 #'   # you can alter the colours with colour names:
 #'   example_isolates %>%
 #'     select(AMX) %>%
 #'     ggplot_rsi(colours = c(SI = "yellow"))
+#' }
+#' if (require("ggplot2") && require("dplyr")) {
 #'
 #'   # but you can also use the built-in colour-blind friendly colours for
 #'   # your plots, where "S" is green, "I" is yellow and "R" is red:
-#'   data.frame(x = c("Value1", "Value2", "Value3"),
-#'              y = c(1, 2, 3),
-#'              z = c("Value4", "Value5", "Value6")) %>%
+#'   data.frame(
+#'     x = c("Value1", "Value2", "Value3"),
+#'     y = c(1, 2, 3),
+#'     z = c("Value4", "Value5", "Value6")
+#'   ) %>%
 #'     ggplot() +
 #'     geom_col(aes(x = x, y = y, fill = z)) +
 #'     scale_rsi_colours(Value4 = "S", Value5 = "I", Value6 = "R")
-#'   
+#' }
+#' if (require("ggplot2") && require("dplyr")) {
+#'
 #'   # resistance of ciprofloxacine per age group
 #'   example_isolates %>%
 #'     mutate(first_isolate = first_isolate()) %>%
-#'     filter(first_isolate == TRUE,
-#'            mo == as.mo("E. coli")) %>%
+#'     filter(
+#'       first_isolate == TRUE,
+#'       mo == as.mo("Escherichia coli")
+#'     ) %>%
 #'     # age_groups() is also a function in this AMR package:
 #'     group_by(age_group = age_groups(age)) %>%
 #'     select(age_group, CIP) %>%
 #'     ggplot_rsi(x = "age_group")
-#'   
+#' }
+#' if (require("ggplot2") && require("dplyr")) {
+#'
 #'   # a shorter version which also adjusts data label colours:
 #'   example_isolates %>%
 #'     select(AMX, NIT, FOS, TMP, CIP) %>%
 #'     ggplot_rsi(colours = FALSE)
-#'
+#' }
+#' if (require("ggplot2") && require("dplyr")) {
 #'
 #'   # it also supports groups (don't forget to use the group var on `x` or `facet`):
 #'   example_isolates %>%
-#'     filter(mo_is_gram_negative()) %>% 
+#'     filter(mo_is_gram_negative(), ward != "Outpatient") %>%
 #'     # select only UTI-specific drugs
-#'     select(hospital_id, AMX, NIT, FOS, TMP, CIP) %>%
-#'     group_by(hospital_id) %>%
-#'     ggplot_rsi(x = "hospital_id",
-#'                facet = "antibiotic",
-#'                nrow = 1,
-#'                title = "AMR of Anti-UTI Drugs Per Hospital",
-#'                x.title = "Hospital",
-#'                datalabels = FALSE)
+#'     select(ward, AMX, NIT, FOS, TMP, CIP) %>%
+#'     group_by(ward) %>%
+#'     ggplot_rsi(
+#'       x = "ward",
+#'       facet = "antibiotic",
+#'       nrow = 1,
+#'       title = "AMR of Anti-UTI Drugs Per Ward",
+#'       x.title = "Ward",
+#'       datalabels = FALSE
+#'     )
 #' }
 #' }
 ggplot_rsi <- function(data,
@@ -160,11 +183,13 @@ ggplot_rsi <- function(data,
                        minimum = 30,
                        language = get_AMR_locale(),
                        nrow = NULL,
-                       colours = c(S = "#3CAEA3",
-                                   SI = "#3CAEA3",
-                                   I = "#F6D55C",
-                                   IR = "#ED553B",
-                                   R = "#ED553B"),
+                       colours = c(
+                         S = "#3CAEA3",
+                         SI = "#3CAEA3",
+                         I = "#F6D55C",
+                         IR = "#ED553B",
+                         R = "#ED553B"
+                       ),
                        datalabels = TRUE,
                        datalabels.size = 2.5,
                        datalabels.colour = "grey15",
@@ -174,7 +199,6 @@ ggplot_rsi <- function(data,
                        x.title = "Antimicrobial",
                        y.title = "Proportion",
                        ...) {
-  
   stop_ifnot_installed("ggplot2")
   meet_criteria(data, allow_class = "data.frame", contains_column_class = "rsi")
   meet_criteria(position, allow_class = "character", has_length = 1, is_in = c("fill", "stack", "dodge"), allow_NULL = TRUE)
@@ -217,48 +241,54 @@ ggplot_rsi <- function(data,
   if (facet %in% c("NULL", "")) {
     facet <- NULL
   }
-  
+
   if (is.null(position)) {
     position <- "fill"
   }
-  
+
   p <- ggplot2::ggplot(data = data) +
-    geom_rsi(position = position, x = x, fill = fill, translate_ab = translate_ab,
-             minimum = minimum, language = language,
-             combine_SI = combine_SI, combine_IR = combine_IR, ...) +
+    geom_rsi(
+      position = position, x = x, fill = fill, translate_ab = translate_ab,
+      minimum = minimum, language = language,
+      combine_SI = combine_SI, combine_IR = combine_IR, ...
+    ) +
     theme_rsi()
-  
+
   if (fill == "interpretation") {
     p <- p + scale_rsi_colours(colours = colours)
   }
-  
+
   if (identical(position, "fill")) {
     # proportions, so use y scale with percentage
     p <- p + scale_y_percent(breaks = breaks, limits = limits)
   }
-  
+
   if (datalabels == TRUE) {
-    p <- p + labels_rsi_count(position = position,
-                              x = x,
-                              translate_ab = translate_ab,
-                              minimum = minimum,
-                              language = language,
-                              combine_SI = combine_SI,
-                              combine_IR = combine_IR,
-                              datalabels.size = datalabels.size,
-                              datalabels.colour = datalabels.colour)
+    p <- p + labels_rsi_count(
+      position = position,
+      x = x,
+      translate_ab = translate_ab,
+      minimum = minimum,
+      language = language,
+      combine_SI = combine_SI,
+      combine_IR = combine_IR,
+      datalabels.size = datalabels.size,
+      datalabels.colour = datalabels.colour
+    )
   }
-  
+
   if (!is.null(facet)) {
     p <- p + facet_rsi(facet = facet, nrow = nrow)
   }
-  
-  p <- p + ggplot2::labs(title = title,
-                         subtitle = subtitle,
-                         caption = caption,
-                         x = x.title,
-                         y = y.title)
-  
+
+  p <- p + ggplot2::labs(
+    title = title,
+    subtitle = subtitle,
+    caption = caption,
+    x = x.title,
+    y = y.title
+  )
+
   p
 }
 
@@ -272,7 +302,7 @@ geom_rsi <- function(position = NULL,
                      language = get_AMR_locale(),
                      combine_SI = TRUE,
                      combine_IR = FALSE,
-                     ...)  {
+                     ...) {
   x <- x[1]
   stop_ifnot_installed("ggplot2")
   stop_if(is.data.frame(position), "`position` is invalid. Did you accidentally use '%>%' instead of '+'?")
@@ -284,16 +314,16 @@ geom_rsi <- function(position = NULL,
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
   meet_criteria(combine_IR, allow_class = "logical", has_length = 1)
-  
+
   y <- "value"
   if (missing(position) | is.null(position)) {
     position <- "fill"
   }
-  
+
   if (identical(position, "fill")) {
     position <- ggplot2::position_fill(vjust = 0.5, reverse = TRUE)
   }
-  
+
   # we work with aes_string later on
   x_deparse <- deparse(substitute(x))
   if (x_deparse != "x") {
@@ -302,21 +332,23 @@ geom_rsi <- function(position = NULL,
   if (x %like% '".*"') {
     x <- substr(x, 2, nchar(x) - 1)
   }
-  
+
   if (tolower(x) %in% tolower(c("ab", "abx", "antibiotics"))) {
     x <- "antibiotic"
   } else if (tolower(x) %in% tolower(c("SIR", "RSI", "interpretations", "result"))) {
     x <- "interpretation"
   }
-  
+
   ggplot2::geom_col(
     data = function(x) {
-      rsi_df(data = x,
-             translate_ab = translate_ab,
-             language = language,
-             minimum = minimum,
-             combine_SI = combine_SI,
-             combine_IR = combine_IR)
+      rsi_df(
+        data = x,
+        translate_ab = translate_ab,
+        language = language,
+        minimum = minimum,
+        combine_SI = combine_SI,
+        combine_IR = combine_IR
+      )
     },
     mapping = ggplot2::aes_string(x = x, y = y, fill = fill),
     position = position,
@@ -331,7 +363,7 @@ facet_rsi <- function(facet = c("interpretation", "antibiotic"), nrow = NULL) {
   stop_ifnot_installed("ggplot2")
   meet_criteria(facet, allow_class = "character", has_length = 1)
   meet_criteria(nrow, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
-  
+
   # we work with aes_string later on
   facet_deparse <- deparse(substitute(facet))
   if (facet_deparse != "facet") {
@@ -340,13 +372,13 @@ facet_rsi <- function(facet = c("interpretation", "antibiotic"), nrow = NULL) {
   if (facet %like% '".*"') {
     facet <- substr(facet, 2, nchar(facet) - 1)
   }
-  
+
   if (tolower(facet) %in% tolower(c("SIR", "RSI", "interpretations", "result"))) {
     facet <- "interpretation"
   } else if (tolower(facet) %in% tolower(c("ab", "abx", "antibiotics"))) {
     facet <- "antibiotic"
   }
-  
+
   ggplot2::facet_wrap(facets = facet, scales = "free_x", nrow = nrow)
 }
 
@@ -356,13 +388,15 @@ scale_y_percent <- function(breaks = seq(0, 1, 0.1), limits = NULL) {
   stop_ifnot_installed("ggplot2")
   meet_criteria(breaks, allow_class = c("numeric", "integer"))
   meet_criteria(limits, allow_class = c("numeric", "integer"), has_length = 2, allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   if (all(breaks[breaks != 0] > 1)) {
     breaks <- breaks / 100
   }
-  ggplot2::scale_y_continuous(breaks = breaks,
-                              labels = percentage(breaks),
-                              limits = limits)
+  ggplot2::scale_y_continuous(
+    breaks = breaks,
+    labels = percentage(breaks),
+    limits = limits
+  )
 }
 
 #' @rdname ggplot_rsi
@@ -373,11 +407,13 @@ scale_rsi_colours <- function(...,
   meet_criteria(aesthetics, allow_class = "character", is_in = c("alpha", "colour", "color", "fill", "linetype", "shape", "size"))
   # behaviour until AMR pkg v1.5.0 and also when coming from ggplot_rsi()
   if ("colours" %in% names(list(...))) {
-    original_cols <- c(S = "#3CAEA3",
-                       SI = "#3CAEA3",
-                       I = "#F6D55C",
-                       IR = "#ED553B",
-                       R = "#ED553B")
+    original_cols <- c(
+      S = "#3CAEA3",
+      SI = "#3CAEA3",
+      I = "#F6D55C",
+      IR = "#ED553B",
+      R = "#ED553B"
+    )
     colours <- replace(original_cols, names(list(...)$colours), list(...)$colours)
     # limits = force is needed in ggplot2 3.3.4 and 3.3.5, see here;
     # https://github.com/tidyverse/ggplot2/issues/4511#issuecomment-866185530
@@ -386,28 +422,42 @@ scale_rsi_colours <- function(...,
   if (identical(unlist(list(...)), FALSE)) {
     return(invisible())
   }
-  
-  names_susceptible <- c("S", "SI", "IS", "S+I", "I+S", "susceptible", "Susceptible",
-                         unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible"),
-                                                  "replacement", drop = TRUE]))
-  names_incr_exposure <- c("I", "intermediate", "increased exposure", "incr. exposure",
-                           "Increased exposure", "Incr. exposure", "Susceptible, incr. exp.",
-                           unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Intermediate"),
-                                                    "replacement", drop = TRUE]),
-                           unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible, incr. exp."),
-                                                    "replacement", drop = TRUE]))
-  names_resistant <- c("R", "IR", "RI", "R+I", "I+R", "resistant", "Resistant",
-                       unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Resistant"), 
-                                                "replacement", drop = TRUE]))
-  
+
+  names_susceptible <- c(
+    "S", "SI", "IS", "S+I", "I+S", "susceptible", "Susceptible",
+    unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible"),
+      "replacement",
+      drop = TRUE
+    ])
+  )
+  names_incr_exposure <- c(
+    "I", "intermediate", "increased exposure", "incr. exposure",
+    "Increased exposure", "Incr. exposure", "Susceptible, incr. exp.",
+    unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Intermediate"),
+      "replacement",
+      drop = TRUE
+    ]),
+    unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Susceptible, incr. exp."),
+      "replacement",
+      drop = TRUE
+    ])
+  )
+  names_resistant <- c(
+    "R", "IR", "RI", "R+I", "I+R", "resistant", "Resistant",
+    unique(TRANSLATIONS[which(TRANSLATIONS$pattern == "Resistant"),
+      "replacement",
+      drop = TRUE
+    ])
+  )
+
   susceptible <- rep("#3CAEA3", length(names_susceptible))
   names(susceptible) <- names_susceptible
   incr_exposure <- rep("#F6D55C", length(names_incr_exposure))
   names(incr_exposure) <- names_incr_exposure
   resistant <- rep("#ED553B", length(names_resistant))
   names(resistant) <- names_resistant
-  
-  original_cols = c(susceptible, incr_exposure, resistant)
+
+  original_cols <- c(susceptible, incr_exposure, resistant)
   dots <- c(...)
   # replace S, I, R as colours: scale_rsi_colours(mydatavalue = "S")
   dots[dots == "S"] <- "#3CAEA3"
@@ -424,12 +474,14 @@ scale_rsi_colours <- function(...,
 theme_rsi <- function() {
   stop_ifnot_installed("ggplot2")
   ggplot2::theme_minimal(base_size = 10) +
-    ggplot2::theme(panel.grid.major.x = ggplot2::element_blank(),
-                   panel.grid.minor = ggplot2::element_blank(),
-                   panel.grid.major.y = ggplot2::element_line(colour = "grey75"),
-                   # center title and subtitle
-                   plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5))
+    ggplot2::theme(
+      panel.grid.major.x = ggplot2::element_blank(),
+      panel.grid.minor = ggplot2::element_blank(),
+      panel.grid.major.y = ggplot2::element_line(colour = "grey75"),
+      # center title and subtitle
+      plot.title = ggplot2::element_text(hjust = 0.5),
+      plot.subtitle = ggplot2::element_text(hjust = 0.5)
+    )
 }
 
 #' @rdname ggplot_rsi
@@ -453,7 +505,7 @@ labels_rsi_count <- function(position = NULL,
   meet_criteria(combine_IR, allow_class = "logical", has_length = 1)
   meet_criteria(datalabels.size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
   meet_criteria(datalabels.colour, allow_class = "character", has_length = 1)
-  
+
   if (is.null(position)) {
     position <- "fill"
   }
@@ -461,26 +513,32 @@ labels_rsi_count <- function(position = NULL,
     position <- ggplot2::position_fill(vjust = 0.5, reverse = TRUE)
   }
   x_name <- x
-  ggplot2::geom_text(mapping = ggplot2::aes_string(label = "lbl",
-                                                   x = x,
-                                                   y = "value"),
-                     position = position,
-                     inherit.aes = FALSE,
-                     size = datalabels.size,
-                     colour = datalabels.colour,
-                     lineheight = 0.75,
-                     data = function(x) {
-                       transformed <- rsi_df(data = x,
-                                             translate_ab = translate_ab,
-                                             combine_SI = combine_SI,
-                                             combine_IR = combine_IR,
-                                             minimum = minimum,
-                                             language = language)
-                       transformed$gr <- transformed[, x_name, drop = TRUE]
-                       transformed %pm>% 
-                         pm_group_by(gr) %pm>% 
-                         pm_mutate(lbl = paste0("n=", isolates)) %pm>% 
-                         pm_ungroup() %pm>% 
-                         pm_select(-gr)
-                     })
+  ggplot2::geom_text(
+    mapping = ggplot2::aes_string(
+      label = "lbl",
+      x = x,
+      y = "value"
+    ),
+    position = position,
+    inherit.aes = FALSE,
+    size = datalabels.size,
+    colour = datalabels.colour,
+    lineheight = 0.75,
+    data = function(x) {
+      transformed <- rsi_df(
+        data = x,
+        translate_ab = translate_ab,
+        combine_SI = combine_SI,
+        combine_IR = combine_IR,
+        minimum = minimum,
+        language = language
+      )
+      transformed$gr <- transformed[, x_name, drop = TRUE]
+      transformed %pm>%
+        pm_group_by(gr) %pm>%
+        pm_mutate(lbl = paste0("n=", isolates)) %pm>%
+        pm_ungroup() %pm>%
+        pm_select(-gr)
+    }
+  )
 }

R/guess_ab_col.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,72 +26,67 @@
 #' Guess Antibiotic Column
 #'
 #' This tries to find a column name in a data set based on information from the [antibiotics] data set. Also supports WHONET abbreviations.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x a [data.frame]
 #' @param search_string a text to search `x` for, will be checked with [as.ab()] if this value is not a column in `x`
 #' @param verbose a [logical] to indicate whether additional info should be printed
 #' @param only_rsi_columns a [logical] to indicate whether only antibiotic columns must be detected that were transformed to class `<rsi>` (see [as.rsi()]) on beforehand (defaults to `FALSE`)
-#' @details You can look for an antibiotic (trade) name or abbreviation and it will search `x` and the [antibiotics] data set for any column containing a name or code of that antibiotic. **Longer columns names take precedence over shorter column names.**
+#' @details You can look for an antibiotic (trade) name or abbreviation and it will search `x` and the [antibiotics] data set for any column containing a name or code of that antibiotic.
 #' @return A column name of `x`, or `NULL` when no result is found.
 #' @export
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
-#' df <- data.frame(amox = "S",
-#'                  tetr = "R")
+#' df <- data.frame(
+#'   amox = "S",
+#'   tetr = "R"
+#' )
 #'
 #' guess_ab_col(df, "amoxicillin")
-#' # [1] "amox"
 #' guess_ab_col(df, "J01AA07") # ATC code of tetracycline
-#' # [1] "tetr"
 #'
 #' guess_ab_col(df, "J01AA07", verbose = TRUE)
 #' # NOTE: Using column 'tetr' as input for J01AA07 (tetracycline).
-#' # [1] "tetr"
 #'
 #' # WHONET codes
-#' df <- data.frame(AMP_ND10 = "R",
-#'                  AMC_ED20 = "S")
+#' df <- data.frame(
+#'   AMP_ND10 = "R",
+#'   AMC_ED20 = "S"
+#' )
 #' guess_ab_col(df, "ampicillin")
-#' # [1] "AMP_ND10"
 #' guess_ab_col(df, "J01CR02")
-#' # [1] "AMC_ED20"
 #' guess_ab_col(df, as.ab("augmentin"))
-#' # [1] "AMC_ED20"
-#'
-#' # Longer names take precendence:
-#' df <- data.frame(AMP_ED2 = "S",
-#'                  AMP_ED20 = "S")
-#' guess_ab_col(df, "ampicillin")
-#' # [1] "AMP_ED20"
 guess_ab_col <- function(x = NULL, search_string = NULL, verbose = FALSE, only_rsi_columns = FALSE) {
   meet_criteria(x, allow_class = "data.frame", allow_NULL = TRUE)
   meet_criteria(search_string, allow_class = "character", has_length = 1, allow_NULL = TRUE)
   meet_criteria(verbose, allow_class = "logical", has_length = 1)
   meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
-  
+
   if (is.null(x) & is.null(search_string)) {
     return(as.name("guess_ab_col"))
   } else {
     meet_criteria(search_string, allow_class = "character", has_length = 1, allow_NULL = FALSE)
   }
-  
-  all_found <- get_column_abx(x, info = verbose, only_rsi_columns = only_rsi_columns,
-                              verbose = verbose, fn = "guess_ab_col")
+
+  all_found <- get_column_abx(x,
+    info = verbose, only_rsi_columns = only_rsi_columns,
+    verbose = verbose, fn = "guess_ab_col"
+  )
   search_string.ab <- suppressWarnings(as.ab(search_string))
   ab_result <- unname(all_found[names(all_found) == search_string.ab])
-  
+
   if (length(ab_result) == 0) {
     if (verbose == TRUE) {
       message_("No column found as input for ", search_string,
-               " (", ab_name(search_string, language = NULL, tolower = TRUE), ").",
-               add_fn = font_black,
-               as_note = FALSE)
+        " (", ab_name(search_string, language = NULL, tolower = TRUE), ").",
+        add_fn = font_black,
+        as_note = FALSE
+      )
     }
     return(NULL)
   } else {
     if (verbose == TRUE) {
-      message_("Using column '", font_bold(ab_result), "' as input for ", search_string,
-               " (", ab_name(search_string, language = NULL, tolower = TRUE), ").")
+      message_(
+        "Using column '", font_bold(ab_result), "' as input for ", search_string,
+        " (", ab_name(search_string, language = NULL, tolower = TRUE), ")."
+      )
     }
     return(ab_result)
   }
@@ -108,16 +103,20 @@ get_column_abx <- function(x,
                            reuse_previous_result = TRUE,
                            fn = NULL) {
   # check if retrieved before, then get it from package environment
-  if (isTRUE(reuse_previous_result) && identical(unique_call_id(entire_session = FALSE,
-                                                                match_fn = fn),
-                                                 pkg_env$get_column_abx.call)) {
+  if (isTRUE(reuse_previous_result) && identical(
+    unique_call_id(
+      entire_session = FALSE,
+      match_fn = fn
+    ),
+    pkg_env$get_column_abx.call
+  )) {
     # so within the same call, within the same environment, we got here again.
     # but we could've come from another function within the same call, so now only check the columns that changed
-    
+
     # first remove the columns that are not existing anymore
     previous <- pkg_env$get_column_abx.out
     current <- previous[previous %in% colnames(x)]
-    
+
     # then compare columns in current call with columns in original call
     new_cols <- colnames(x)[!colnames(x) %in% pkg_env$get_column_abx.checked_cols]
     if (length(new_cols) > 0) {
@@ -127,7 +126,7 @@ get_column_abx <- function(x,
       # order according to columns in current call
       current <- current[match(colnames(x)[colnames(x) %in% current], current)]
     }
-    
+
     # update pkg environment to improve speed on next run
     pkg_env$get_column_abx.out <- current
     pkg_env$get_column_abx.checked_cols <- colnames(x)
@@ -135,7 +134,7 @@ get_column_abx <- function(x,
     # and return right values
     return(pkg_env$get_column_abx.out)
   }
-  
+
   meet_criteria(x, allow_class = "data.frame")
   meet_criteria(soft_dependencies, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(hard_dependencies, allow_class = "character", allow_NULL = TRUE)
@@ -143,11 +142,11 @@ get_column_abx <- function(x,
   meet_criteria(info, allow_class = "logical", has_length = 1)
   meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
   meet_criteria(sort, allow_class = "logical", has_length = 1)
-  
+
   if (info == TRUE) {
     message_("Auto-guessing columns suitable for analysis", appendLF = FALSE, as_note = FALSE)
   }
-  
+
   x <- as.data.frame(x, stringsAsFactors = FALSE)
   x.bak <- x
   if (only_rsi_columns == TRUE) {
@@ -158,8 +157,9 @@ get_column_abx <- function(x,
     # only test maximum of 10,000 values per column
     if (info == TRUE) {
       message_(" (using only ", font_bold("the first 10,000 rows"), ")...",
-               appendLF = FALSE, 
-               as_note = FALSE)
+        appendLF = FALSE,
+        as_note = FALSE
+      )
     }
     x <- x[1:10000, , drop = FALSE]
   } else if (info == TRUE) {
@@ -167,32 +167,36 @@ get_column_abx <- function(x,
   }
 
   # only check columns that are a valid AB code, ATC code, name, abbreviation or synonym,
-  # or already have the <rsi> class (as.rsi) 
+  # or already have the <rsi> class (as.rsi)
   # and that they have no more than 50% invalid values
   vectr_antibiotics <- unlist(AB_lookup$generalised_all)
   vectr_antibiotics <- vectr_antibiotics[!is.na(vectr_antibiotics) & nchar(vectr_antibiotics) >= 3]
-  x_columns <- vapply(FUN.VALUE = character(1), 
-                      colnames(x),
-                      function(col, df = x) {
-                        if (generalise_antibiotic_name(col) %in% vectr_antibiotics || 
-                            is.rsi(x[, col, drop = TRUE]) ||
-                            is.rsi.eligible(x[, col, drop = TRUE], threshold = 0.5)
-                        ) {
-                          return(col)
-                        } else {
-                          return(NA_character_)
-                        }
-                      }, USE.NAMES = FALSE)
-  
+  x_columns <- vapply(
+    FUN.VALUE = character(1),
+    colnames(x),
+    function(col, df = x) {
+      if (generalise_antibiotic_name(col) %in% vectr_antibiotics ||
+        is.rsi(x[, col, drop = TRUE]) ||
+        is.rsi.eligible(x[, col, drop = TRUE], threshold = 0.5)
+      ) {
+        return(col)
+      } else {
+        return(NA_character_)
+      }
+    }, USE.NAMES = FALSE
+  )
+
   x_columns <- x_columns[!is.na(x_columns)]
   x <- x[, x_columns, drop = FALSE] # without drop = FALSE, x will become a vector when x_columns is length 1
-  df_trans <- data.frame(colnames = colnames(x),
-                         abcode = suppressWarnings(as.ab(colnames(x), info = FALSE)),
-                         stringsAsFactors = FALSE)
+  df_trans <- data.frame(
+    colnames = colnames(x),
+    abcode = suppressWarnings(as.ab(colnames(x), info = FALSE)),
+    stringsAsFactors = FALSE
+  )
   df_trans <- df_trans[!is.na(df_trans$abcode), , drop = FALSE]
   out <- as.character(df_trans$colnames)
   names(out) <- df_trans$abcode
-  
+
   # add from self-defined dots (...):
   # such as get_column_abx(example_isolates %>% rename(thisone = AMX), amox = "thisone")
   all_okay <- TRUE
@@ -206,8 +210,9 @@ get_column_abx <- function(x,
         message_(" WARNING", add_fn = list(font_yellow, font_bold), as_note = FALSE)
       }
       warning_("Invalid antibiotic reference(s): ", vector_and(names(dots)[is.na(newnames)], quotes = FALSE),
-               call = FALSE,
-               immediate = TRUE)
+        call = FALSE,
+        immediate = TRUE
+      )
       all_okay <- FALSE
     }
     unexisting_cols <- which(!vapply(FUN.VALUE = logical(1), dots, function(col) all(col %in% x_columns)))
@@ -216,7 +221,8 @@ get_column_abx <- function(x,
         message_(" ERROR", add_fn = list(font_red, font_bold), as_note = FALSE)
       }
       stop_("Column(s) not found: ", vector_and(unlist(dots[[unexisting_cols]]), quotes = FALSE),
-            call = FALSE)
+        call = FALSE
+      )
       all_okay <- FALSE
     }
     # turn all NULLs to NAs
@@ -228,7 +234,7 @@ get_column_abx <- function(x,
     # delete NAs, this will make e.g. eucast_rules(... TMP = NULL) work to prevent TMP from being used
     out <- out[!is.na(out)]
   }
-  
+
   if (length(out) == 0) {
     if (info == TRUE & all_okay == TRUE) {
       message_("No columns found.")
@@ -238,7 +244,7 @@ get_column_abx <- function(x,
     pkg_env$get_column_abx.out <- out
     return(out)
   }
-  
+
   # sort on name
   if (sort == TRUE) {
     out <- out[order(names(out), out)]
@@ -248,7 +254,7 @@ get_column_abx <- function(x,
   if (length(duplicates) > 0) {
     all_okay <- FALSE
   }
-  
+
   if (info == TRUE) {
     if (all_okay == TRUE) {
       message_(" OK.", add_fn = list(font_green, font_bold), as_note = FALSE)
@@ -257,27 +263,32 @@ get_column_abx <- function(x,
     }
     for (i in seq_len(length(out))) {
       if (verbose == TRUE & !names(out[i]) %in% names(duplicates)) {
-        message_("Using column '", font_bold(out[i]), "' as input for ", names(out)[i],
-                 " (", ab_name(names(out)[i], tolower = TRUE, language = NULL), ").")
+        message_(
+          "Using column '", font_bold(out[i]), "' as input for ", names(out)[i],
+          " (", ab_name(names(out)[i], tolower = TRUE, language = NULL), ")."
+        )
       }
       if (names(out[i]) %in% names(duplicates)) {
         already_set_as <- out[unname(out) == unname(out[i])][1L]
-        warning_(paste0("Column '", font_bold(out[i]), "' will not be used for ", 
-                        names(out)[i], " (", ab_name(names(out)[i], tolower = TRUE, language = NULL), ")",
-                        ", as it is already set for ", 
-                        names(already_set_as), " (", ab_name(names(already_set_as), tolower = TRUE, language = NULL), ")"),
-                 add_fn = font_red,
-                 immediate = verbose)
+        warning_(paste0(
+          "Column '", font_bold(out[i]), "' will not be used for ",
+          names(out)[i], " (", ab_name(names(out)[i], tolower = TRUE, language = NULL), ")",
+          ", as it is already set for ",
+          names(already_set_as), " (", ab_name(names(already_set_as), tolower = TRUE, language = NULL), ")"
+        ),
+        add_fn = font_red,
+        immediate = verbose
+        )
       }
     }
   }
-  
+
   out <- out[!duplicated(names(out))]
   out <- out[!duplicated(unname(out))]
   if (sort == TRUE) {
     out <- out[order(names(out), out)]
   }
-  
+
   if (!is.null(hard_dependencies)) {
     hard_dependencies <- unique(hard_dependencies)
     if (!all(hard_dependencies %in% names(out))) {
@@ -292,14 +303,19 @@ get_column_abx <- function(x,
     if (info == TRUE & !all(soft_dependencies %in% names(out))) {
       # missing a soft dependency may lower the reliability
       missing <- soft_dependencies[!soft_dependencies %in% names(out)]
-      missing_msg <- vector_and(paste0(ab_name(missing, tolower = TRUE, language = NULL), 
-                                       " (", font_bold(missing, collapse = NULL), ")"), 
-                                quotes = FALSE)
-      message_("Reliability would be improved if these antimicrobial results would be available too: ",
-               missing_msg)
+      missing_msg <- vector_and(paste0(
+        ab_name(missing, tolower = TRUE, language = NULL),
+        " (", font_bold(missing, collapse = NULL), ")"
+      ),
+      quotes = FALSE
+      )
+      message_(
+        "Reliability would be improved if these antimicrobial results would be available too: ",
+        missing_msg
+      )
     }
   }
-  
+
   pkg_env$get_column_abx.call <- unique_call_id(entire_session = FALSE, match_fn = fn)
   pkg_env$get_column_abx.checked_cols <- colnames(x.bak)
   pkg_env$get_column_abx.out <- out
@@ -308,12 +324,12 @@ get_column_abx <- function(x,
 
 get_ab_from_namespace <- function(x, cols_ab) {
   # cols_ab comes from get_column_abx()
-  
+
   x <- trimws(unique(toupper(unlist(strsplit(x, ",")))))
   x_new <- character()
   for (val in x) {
     if (paste0("AB_", val) %in% ls(envir = asNamespace("AMR"))) {
-      # antibiotic group names, as defined in data-raw/_internals.R, such as `AB_CARBAPENEMS`
+      # antibiotic group names, as defined in data-raw/_pre_commit_hook.R, such as `AB_CARBAPENEMS`
       val <- eval(parse(text = paste0("AB_", val)), envir = asNamespace("AMR"))
     } else if (val %in% AB_lookup$ab) {
       # separate drugs, such as `AMX`
@@ -335,7 +351,10 @@ generate_warning_abs_missing <- function(missing, any = FALSE) {
   } else {
     any_txt <- c("", "are")
   }
-  warning_(paste0("Introducing NAs since", any_txt[1], " these antimicrobials ", any_txt[2], " required: ",
-                  vector_and(missing, quotes = FALSE)),
-           immediate = TRUE)
+  warning_(paste0(
+    "Introducing NAs since", any_txt[1], " these antimicrobials ", any_txt[2], " required: ",
+    vector_and(missing, quotes = FALSE)
+  ),
+  immediate = TRUE
+  )
 }

R/italicise_taxonomy.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -24,41 +24,29 @@
 # ==================================================================== #
 
 #' Italicise Taxonomic Families, Genera, Species, Subspecies
-#' 
-#' According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italic. This function finds taxonomic names within strings and makes them italic.
-#' @inheritSection lifecycle Stable Lifecycle
+#'
+#' According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italics. This function finds taxonomic names within strings and makes them italic.
 #' @param string a [character] (vector)
 #' @param type type of conversion of the taxonomic names, either "markdown" or "ansi", see *Details*
-#' @details 
+#' @details
 #' This function finds the taxonomic names and makes them italic based on the [microorganisms] data set.
-#' 
+#'
 #' The taxonomic names can be italicised using markdown (the default) by adding `*` before and after the taxonomic names, or using ANSI colours by adding `\033[3m` before and `\033[23m` after the taxonomic names. If multiple ANSI colours are not available, no conversion will occur.
-#' 
+#'
 #' This function also supports abbreviation of the genus if it is followed by a species, such as "E. coli" and "K. pneumoniae ozaenae".
-#' @inheritSection AMR Read more on Our Website!
 #' @export
 #' @examples
 #' italicise_taxonomy("An overview of Staphylococcus aureus isolates")
 #' italicise_taxonomy("An overview of S. aureus isolates")
-#' 
+#'
 #' cat(italicise_taxonomy("An overview of S. aureus isolates", type = "ansi"))
-#' 
-#' # since ggplot2 supports no markdown (yet), use
-#' # italicise_taxonomy() and the `ggtext` package for titles:
-#' \donttest{
-#' if (require("ggplot2") && require("ggtext")) {
-#'   autoplot(example_isolates$AMC,
-#'            title = italicise_taxonomy("Amoxi/clav in E. coli")) +
-#'     theme(plot.title = ggtext::element_markdown())
-#' }
-#' }
 italicise_taxonomy <- function(string, type = c("markdown", "ansi")) {
   if (missing(type)) {
     type <- "markdown"
   }
   meet_criteria(string, allow_class = "character")
   meet_criteria(type, allow_class = "character", has_length = 1, is_in = c("markdown", "ansi"))
-  
+
   if (type == "markdown") {
     before <- "*"
     after <- "*"
@@ -69,57 +57,70 @@ italicise_taxonomy <- function(string, type = c("markdown", "ansi")) {
     before <- "\033[3m"
     after <- "\033[23m"
   }
-  
-  vapply(FUN.VALUE = character(1),
-         string,
-         function(s) {
-           s_split <- unlist(strsplit(s, " "))
-           
-           search_strings <- gsub("[^a-zA-Z-]", "", s_split)
-           
-           ind_species <- search_strings != "" &
-             search_strings %in% MO_lookup[which(MO_lookup$rank %in% c("family",
-                                                                       "genus",
-                                                                       "species",
-                                                                       "subspecies",
-                                                                       "infraspecies",
-                                                                       "subsp.")),
-                                           "species",
-                                           drop = TRUE]
-           
-           ind_fullname <- search_strings != "" &
-             search_strings %in% c(MO_lookup[which(MO_lookup$rank %in% c("family",
-                                                                         "genus",
-                                                                         "species",
-                                                                         "subspecies",
-                                                                         "infraspecies",
-                                                                         "subsp.")),
-                                             "fullname",
-                                             drop = TRUE],
-                                   MO_lookup[which(MO_lookup$rank %in% c("family",
-                                                                         "genus",
-                                                                         "species",
-                                                                         "subspecies",
-                                                                         "infraspecies",
-                                                                         "subsp.")),
-                                             "subspecies",
-                                             drop = TRUE])
 
-           # also support E. coli, add "E." to indices
-           has_previous_genera_abbr <- s_split[which(ind_species) - 1] %like_case% "^[A-Z][.]?$"
-           ind_species <- c(which(ind_species), which(ind_species)[has_previous_genera_abbr] - 1)
-           
-           ind <- c(ind_species, which(ind_fullname))
-           
-           s_split[ind] <- paste0(before, s_split[ind], after)
-           s_paste <- paste(s_split, collapse = " ")
-           
-           # clean up a bit
-           s_paste <- gsub(paste0(after, " ", before), " ", s_paste, fixed = TRUE)
-           
-           s_paste
-         },
-         USE.NAMES = FALSE)
+  vapply(
+    FUN.VALUE = character(1),
+    string,
+    function(s) {
+      s_split <- unlist(strsplit(s, " "))
+
+      search_strings <- gsub("[^a-zA-Z-]", "", s_split)
+
+      ind_species <- search_strings != "" &
+        search_strings %in% MO_lookup[which(MO_lookup$rank %in% c(
+          "family",
+          "genus",
+          "species",
+          "subspecies",
+          "infraspecies",
+          "subsp."
+        )),
+        "species",
+        drop = TRUE
+        ]
+
+      ind_fullname <- search_strings != "" &
+        search_strings %in% c(
+          MO_lookup[which(MO_lookup$rank %in% c(
+            "family",
+            "genus",
+            "species",
+            "subspecies",
+            "infraspecies",
+            "subsp."
+          )),
+          "fullname",
+          drop = TRUE
+          ],
+          MO_lookup[which(MO_lookup$rank %in% c(
+            "family",
+            "genus",
+            "species",
+            "subspecies",
+            "infraspecies",
+            "subsp."
+          )),
+          "subspecies",
+          drop = TRUE
+          ]
+        )
+
+      # also support E. coli, add "E." to indices
+      has_previous_genera_abbr <- s_split[which(ind_species) - 1] %like_case% "^[A-Z][.]?$"
+      ind_species <- c(which(ind_species), which(ind_species)[has_previous_genera_abbr] - 1)
+
+      ind <- c(ind_species, which(ind_fullname))
+
+      s_split[ind] <- paste0(before, s_split[ind], after)
+      s_paste <- paste(s_split, collapse = " ")
+
+      # clean up a bit
+      s_paste <- gsub(paste0(after, " ", before), " ", s_paste, fixed = TRUE)
+
+      s_paste
+    },
+    USE.NAMES = FALSE
+  )
 }
 
 #' @rdname italicise_taxonomy

R/join_microorganisms.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' Join [microorganisms] to a Data Set
 #'
 #' Join the data set [microorganisms] easily to an existing data set or to a [character] vector.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @rdname join
 #' @name join
 #' @aliases join inner_join
@@ -34,38 +33,44 @@
 #' @param by a variable to join by - if left empty will search for a column with class [`mo`] (created with [as.mo()]) or will be `"mo"` if that column name exists in `x`, could otherwise be a column name of `x` with values that exist in `microorganisms$mo` (such as `by = "bacteria_id"`), or another column in [microorganisms] (but then it should be named, like `by = c("bacteria_id" = "fullname")`)
 #' @param suffix if there are non-joined duplicate variables in `x` and `y`, these suffixes will be added to the output to disambiguate them. Should be a [character] vector of length 2.
 #' @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. 
-#' 
+#' @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.
-#' @inheritSection AMR Read more on Our Website!
 #' @return a [data.frame]
 #' @export
 #' @examples
 #' left_join_microorganisms(as.mo("K. pneumoniae"))
 #' left_join_microorganisms("B_KLBSL_PNMN")
 #'
+#' df <- data.frame(
+#'   date = seq(
+#'     from = as.Date("2018-01-01"),
+#'     to = as.Date("2018-01-07"),
+#'     by = 1
+#'   ),
+#'   bacteria = as.mo(c(
+#'     "S. aureus", "MRSA", "MSSA", "STAAUR",
+#'     "E. coli", "E. coli", "E. coli"
+#'   )),
+#'   stringsAsFactors = FALSE
+#' )
+#' colnames(df)
+#'
+#' df_joined <- left_join_microorganisms(df, "bacteria")
+#' colnames(df_joined)
+#'
 #' \donttest{
 #' if (require("dplyr")) {
 #'   example_isolates %>%
-#'     left_join_microorganisms() %>% 
+#'     left_join_microorganisms() %>%
 #'     colnames()
-#'  
-#'   df <- data.frame(date = seq(from = as.Date("2018-01-01"),
-#'                               to = as.Date("2018-01-07"),
-#'                               by = 1),
-#'                    bacteria = as.mo(c("S. aureus", "MRSA", "MSSA", "STAAUR",
-#'                                       "E. coli", "E. coli", "E. coli")),
-#'                    stringsAsFactors = FALSE)
-#'   colnames(df)
-#'   df_joined <- left_join_microorganisms(df, "bacteria")
-#'   colnames(df_joined)
 #' }
 #' }
 inner_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
   meet_criteria(x, allow_class = c("data.frame", "character"))
   meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(suffix, allow_class = "character", has_length = 2)
-  
+
   join_microorganisms(type = "inner_join", x = x, by = by, suffix = suffix, ...)
 }
 
@@ -75,7 +80,7 @@ left_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
   meet_criteria(x, allow_class = c("data.frame", "character"))
   meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(suffix, allow_class = "character", has_length = 2)
-  
+
   join_microorganisms(type = "left_join", x = x, by = by, suffix = suffix, ...)
 }
 
@@ -85,7 +90,7 @@ right_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
   meet_criteria(x, allow_class = c("data.frame", "character"))
   meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(suffix, allow_class = "character", has_length = 2)
-  
+
   join_microorganisms(type = "right_join", x = x, by = by, suffix = suffix, ...)
 }
 
@@ -95,7 +100,7 @@ full_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
   meet_criteria(x, allow_class = c("data.frame", "character"))
   meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(suffix, allow_class = "character", has_length = 2)
-  
+
   join_microorganisms(type = "full_join", x = x, by = by, suffix = suffix, ...)
 }
 
@@ -104,7 +109,7 @@ full_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
 semi_join_microorganisms <- function(x, by = NULL, ...) {
   meet_criteria(x, allow_class = c("data.frame", "character"))
   meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
-  
+
   join_microorganisms(type = "semi_join", x = x, by = by, ...)
 }
 
@@ -113,17 +118,22 @@ semi_join_microorganisms <- function(x, by = NULL, ...) {
 anti_join_microorganisms <- function(x, by = NULL, ...) {
   meet_criteria(x, allow_class = c("data.frame", "character"))
   meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
-  
+
   join_microorganisms(type = "anti_join", x = x, by = by, ...)
 }
 
 join_microorganisms <- function(type, x, by, suffix, ...) {
   check_dataset_integrity()
-  
+
   if (!is.data.frame(x)) {
-    x <- data.frame(mo = x, stringsAsFactors = FALSE)
+    if (pkg_is_available("tibble", also_load = FALSE)) {
+      x <- import_fn("tibble", "tibble")(mo = x)
+    } else {
+      x <- data.frame(mo = x, stringsAsFactors = FALSE)
+    }
     by <- "mo"
   }
+  x.bak <- x
   if (is.null(by)) {
     by <- search_type_in_df(x, "mo", info = FALSE)
     if (is.null(by) && NCOL(x) == 1) {
@@ -139,12 +149,12 @@ join_microorganisms <- function(type, x, by, suffix, ...) {
   } else {
     x[, by] <- as.mo(x[, by, drop = TRUE])
   }
-  
+
   if (is.null(names(by))) {
     # will always be joined to microorganisms$mo, so add name to that
     by <- stats::setNames("mo", by)
   }
-  
+
   # use dplyr if available - it's much faster than poorman alternatives
   dplyr_join <- import_fn(name = type, pkg = "dplyr", error_on_fail = FALSE)
   if (!is.null(dplyr_join)) {
@@ -158,7 +168,7 @@ join_microorganisms <- function(type, x, by, suffix, ...) {
   } else {
     joined <- join_fn(x = x, y = AMR::microorganisms, by = by, ...)
   }
-  
+
   if ("join.mo" %in% colnames(joined)) {
     if ("mo" %in% colnames(joined)) {
       ind_mo <- which(colnames(joined) %in% c("mo", "join.mo"))
@@ -168,10 +178,10 @@ join_microorganisms <- function(type, x, by, suffix, ...) {
       colnames(joined)[colnames(joined) == "join.mo"] <- "mo"
     }
   }
-  
+
   if (type %like% "full|left|right|inner" && NROW(joined) > NROW(x)) {
     warning_("in `", type, "_join()`: the newly joined data set contains ", nrow(joined) - nrow(x), " rows more than the number of rows of `x`.")
   }
-  
-  joined
+
+  as_original_data_class(joined, class(x.bak))
 }

R/key_antimicrobials.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' (Key) Antimicrobials for First Weighted Isolates
 #'
 #' These functions can be used to determine first weighted isolates by considering the phenotype for isolate selection (see [first_isolate()]). Using a phenotype-based method to determine first isolates is more reliable than methods that disregard phenotypes.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x a [data.frame] with antibiotics columns, like `AMX` or `amox`. Can be left blank to determine automatically
 #' @param y,z [character] vectors to compare
 #' @inheritParams first_isolate
@@ -36,15 +35,15 @@
 #' @param antifungal names of antifungal agents for **fungi**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
 #' @param only_rsi_columns a [logical] to indicate whether only columns must be included that were transformed to class `<rsi>` (see [as.rsi()]) on beforehand (defaults to `FALSE`)
 #' @param ... ignored, only in place to allow future extensions
-#' @details 
+#' @details
 #' The [key_antimicrobials()] and [all_antimicrobials()] functions are context-aware. This means that the `x` argument can be left blank if used inside a [data.frame] call, see *Examples*.
-#' 
+#'
 #' The function [key_antimicrobials()] returns a [character] vector with 12 antimicrobial results for every isolate. The function [all_antimicrobials()] returns a [character] vector with all antimicrobial results for every isolate. These vectors can then be compared using [antimicrobials_equal()], to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (`"."`) by [key_antimicrobials()] and ignored by [antimicrobials_equal()].
-#' 
+#'
 #' Please see the [first_isolate()] function how these important functions enable the 'phenotype-based' method for determination of first isolates.
 #'
 #' The default antimicrobial agents used for **all rows** (set in `universal`) are:
-#' 
+#'
 #' - Ampicillin
 #' - Amoxicillin/clavulanic acid
 #' - Cefuroxime
@@ -53,7 +52,7 @@
 #' - Trimethoprim/sulfamethoxazole
 #'
 #' The default antimicrobial agents used for **Gram-negative bacteria** (set in `gram_negative`) are:
-#' 
+#'
 #' - Cefotaxime
 #' - Ceftazidime
 #' - Colistin
@@ -62,17 +61,17 @@
 #' - Tobramycin
 #'
 #' The default antimicrobial agents used for **Gram-positive bacteria** (set in `gram_positive`) are:
-#' 
+#'
 #' - Erythromycin
 #' - Oxacillin
 #' - Rifampin
 #' - Teicoplanin
 #' - Tetracycline
 #' - Vancomycin
-#' 
-#' 
+#'
+#'
 #' The default antimicrobial agents used for **fungi** (set in `antifungal`) are:
-#' 
+#'
 #' - Anidulafungin
 #' - Caspofungin
 #' - Fluconazole
@@ -82,11 +81,10 @@
 #' @rdname key_antimicrobials
 #' @export
 #' @seealso [first_isolate()]
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' # `example_isolates` is a data set available in the AMR package.
 #' # See ?example_isolates.
-#' 
+#'
 #' # output of the `key_antimicrobials()` function could be like this:
 #' strainA <- "SSSRR.S.R..S"
 #' strainB <- "SSSIRSSSRSSS"
@@ -109,22 +107,30 @@
 #'       # and first WEIGHTED isolates
 #'       first_weighted = first_isolate(col_keyantimicrobials = "keyab")
 #'     )
-#'  
-#'   # Check the difference, in this data set it results in more isolates:
+#'
+#'   # Check the difference in this data set, 'weighted' results in more isolates:
 #'   sum(my_patients$first_regular, na.rm = TRUE)
 #'   sum(my_patients$first_weighted, na.rm = TRUE)
 #' }
 #' }
 key_antimicrobials <- function(x = NULL,
                                col_mo = NULL,
-                               universal = c("ampicillin", "amoxicillin/clavulanic acid", "cefuroxime",
-                                             "piperacillin/tazobactam", "ciprofloxacin", "trimethoprim/sulfamethoxazole"),
-                               gram_negative = c("gentamicin", "tobramycin", "colistin",
-                                                 "cefotaxime", "ceftazidime", "meropenem"),
-                               gram_positive = c("vancomycin", "teicoplanin", "tetracycline",
-                                                 "erythromycin", "oxacillin", "rifampin"),
-                               antifungal = c("anidulafungin", "caspofungin", "fluconazole",
-                                              "miconazole", "nystatin", "voriconazole"),
+                               universal = c(
+                                 "ampicillin", "amoxicillin/clavulanic acid", "cefuroxime",
+                                 "piperacillin/tazobactam", "ciprofloxacin", "trimethoprim/sulfamethoxazole"
+                               ),
+                               gram_negative = c(
+                                 "gentamicin", "tobramycin", "colistin",
+                                 "cefotaxime", "ceftazidime", "meropenem"
+                               ),
+                               gram_positive = c(
+                                 "vancomycin", "teicoplanin", "tetracycline",
+                                 "erythromycin", "oxacillin", "rifampin"
+                               ),
+                               antifungal = c(
+                                 "anidulafungin", "caspofungin", "fluconazole",
+                                 "miconazole", "nystatin", "voriconazole"
+                               ),
                                only_rsi_columns = FALSE,
                                ...) {
   if (is_null_or_grouped_tbl(x)) {
@@ -139,11 +145,11 @@ key_antimicrobials <- function(x = NULL,
   meet_criteria(gram_positive, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(antifungal, allow_class = "character", allow_NULL = TRUE)
   meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
-  
+
   # force regular data.frame, not a tibble or data.table
   x <- as.data.frame(x, stringsAsFactors = FALSE)
   cols <- get_column_abx(x, info = FALSE, only_rsi_columns = only_rsi_columns, fn = "key_antimicrobials")
-  
+
   # try to find columns based on type
   # -- mo
   if (is.null(col_mo)) {
@@ -158,68 +164,79 @@ key_antimicrobials <- function(x = NULL,
     gramstain <- mo_gramstain(x.mo, language = NULL)
     kingdom <- mo_kingdom(x.mo, language = NULL)
   }
-  
+
   AMR_string <- function(x, values, name, filter, cols = cols) {
     if (is.null(values)) {
       return(rep(NA_character_, length(which(filter))))
     }
-    
+
     values_old_length <- length(values)
     values <- as.ab(values, flag_multiple_results = FALSE, info = FALSE)
     values <- cols[names(cols) %in% values]
     values_new_length <- length(values)
-    
+
     if (values_new_length < values_old_length &
-        any(filter, na.rm = TRUE) &
-        message_not_thrown_before("key_antimicrobials", name)) {
-      warning_("in `key_antimicrobials()`: ",
-               ifelse(values_new_length == 0,
-                      "No columns available ",
-                      paste0("Only using ", values_new_length, " out of ", values_old_length, " defined columns ")),
-               "as key antimicrobials for ", name, "s. See ?key_antimicrobials.")
+      any(filter, na.rm = TRUE) &
+      message_not_thrown_before("key_antimicrobials", name)) {
+      warning_(
+        "in `key_antimicrobials()`: ",
+        ifelse(values_new_length == 0,
+          "No columns available ",
+          paste0("Only using ", values_new_length, " out of ", values_old_length, " defined columns ")
+        ),
+        "as key antimicrobials for ", name, "s. See ?key_antimicrobials."
+      )
     }
-    
+
     generate_antimcrobials_string(x[which(filter), c(universal, values), drop = FALSE])
   }
-  
+
   if (is.null(universal)) {
     universal <- character(0)
   } else {
     universal <- as.ab(universal, flag_multiple_results = FALSE, info = FALSE)
     universal <- cols[names(cols) %in% universal]
   }
-  
+
   key_ab <- rep(NA_character_, nrow(x))
-  
-  key_ab[which(gramstain == "Gram-negative")] <- AMR_string(x = x,
-                                                            values = gram_negative,
-                                                            name = "Gram-negative",
-                                                            filter = gramstain == "Gram-negative",
-                                                            cols = cols)
-  
-  key_ab[which(gramstain == "Gram-positive")] <- AMR_string(x = x,
-                                                            values = gram_positive,
-                                                            name = "Gram-positive",
-                                                            filter = gramstain == "Gram-positive",
-                                                            cols = cols)
-  
-  key_ab[which(kingdom == "Fungi")] <- AMR_string(x = x,
-                                                  values = antifungal,
-                                                  name = "antifungal",
-                                                  filter = kingdom == "Fungi",
-                                                  cols = cols)
-  
+
+  key_ab[which(gramstain == "Gram-negative")] <- AMR_string(
+    x = x,
+    values = gram_negative,
+    name = "Gram-negative",
+    filter = gramstain == "Gram-negative",
+    cols = cols
+  )
+
+  key_ab[which(gramstain == "Gram-positive")] <- AMR_string(
+    x = x,
+    values = gram_positive,
+    name = "Gram-positive",
+    filter = gramstain == "Gram-positive",
+    cols = cols
+  )
+
+  key_ab[which(kingdom == "Fungi")] <- AMR_string(
+    x = x,
+    values = antifungal,
+    name = "antifungal",
+    filter = kingdom == "Fungi",
+    cols = cols
+  )
+
   # back-up - only use `universal`
-  key_ab[which(is.na(key_ab))] <- AMR_string(x = x,
-                                             values = character(0),
-                                             name = "",
-                                             filter = is.na(key_ab),
-                                             cols = cols)
-  
+  key_ab[which(is.na(key_ab))] <- AMR_string(
+    x = x,
+    values = character(0),
+    name = "",
+    filter = is.na(key_ab),
+    cols = cols
+  )
+
   if (length(unique(key_ab)) == 1) {
     warning_("in `key_antimicrobials()`: no distinct key antibiotics determined.")
   }
-  
+
   key_ab
 }
 
@@ -235,13 +252,15 @@ all_antimicrobials <- function(x = NULL,
   }
   meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
   meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
-  
+
   # force regular data.frame, not a tibble or data.table
   x <- as.data.frame(x, stringsAsFactors = FALSE)
-  cols <- get_column_abx(x, only_rsi_columns = only_rsi_columns, info = FALSE,
-                         sort = FALSE, fn = "all_antimicrobials")
-  
-  generate_antimcrobials_string(x[ , cols, drop = FALSE])
+  cols <- get_column_abx(x,
+    only_rsi_columns = only_rsi_columns, info = FALSE,
+    sort = FALSE, fn = "all_antimicrobials"
+  )
+
+  generate_antimcrobials_string(x[, cols, drop = FALSE])
 }
 
 generate_antimcrobials_string <- function(df) {
@@ -251,26 +270,32 @@ generate_antimcrobials_string <- function(df) {
   if (NROW(df) == 0) {
     return(character(0))
   }
-  tryCatch({
-    do.call(paste0,
-            lapply(as.list(df),
-                   function(x) {
-                     x <- toupper(as.character(x))
-                     x[!x %in% c("R", "S", "I")] <- "."
-                     paste(x)
-                   }))
-  },
-  error = function(e) rep(strrep(".", NCOL(df)), NROW(df)))
+  tryCatch(
+    {
+      do.call(
+        paste0,
+        lapply(
+          as.list(df),
+          function(x) {
+            x <- toupper(as.character(x))
+            x[!x %in% c("R", "S", "I")] <- "."
+            paste(x)
+          }
+        )
+      )
+    },
+    error = function(e) rep(strrep(".", NCOL(df)), NROW(df))
+  )
 }
 
 #' @rdname key_antimicrobials
 #' @export
 antimicrobials_equal <- function(y,
-                                  z,
-                                  type = c("points", "keyantimicrobials"),
-                                  ignore_I = TRUE,
-                                  points_threshold = 2,
-                                  ...) {
+                                 z,
+                                 type = c("points", "keyantimicrobials"),
+                                 ignore_I = TRUE,
+                                 points_threshold = 2,
+                                 ...) {
   meet_criteria(y, allow_class = "character")
   meet_criteria(z, allow_class = "character")
   stop_if(missing(type), "argument \"type\" is missing, with no default")
@@ -291,10 +316,10 @@ antimicrobials_equal <- function(y,
   uniq <- unique(c(y, z))
   uniq_list <- lapply(uniq, key2rsi)
   names(uniq_list) <- uniq
-  
+
   y <- uniq_list[match(y, names(uniq_list))]
   z <- uniq_list[match(z, names(uniq_list))]
-  
+
   determine_equality <- function(a, b, type, points_threshold, ignore_I) {
     if (length(a) != length(b)) {
       # incomparable, so not equal
@@ -304,7 +329,7 @@ antimicrobials_equal <- function(y,
     NA_ind <- which(is.na(a) | is.na(b))
     a[NA_ind] <- NA_real_
     b[NA_ind] <- NA_real_
-    
+
     if (type == "points") {
       # count points for every single character:
       # - no change is 0 points
@@ -322,14 +347,18 @@ antimicrobials_equal <- function(y,
       all(a == b, na.rm = TRUE)
     }
   }
-  out <- unlist(mapply(FUN = determine_equality,
-                       y,
-                       z,
-                       MoreArgs = list(type = type,
-                                       points_threshold = points_threshold,
-                                       ignore_I = ignore_I),
-                       SIMPLIFY = FALSE,
-                       USE.NAMES = FALSE))
+  out <- unlist(mapply(
+    FUN = determine_equality,
+    y,
+    z,
+    MoreArgs = list(
+      type = type,
+      points_threshold = points_threshold,
+      ignore_I = ignore_I
+    ),
+    SIMPLIFY = FALSE,
+    USE.NAMES = FALSE
+  ))
   out[is.na(y) | is.na(z)] <- NA
   out
 }

R/kurtosis.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,14 +26,15 @@
 #' Kurtosis of the Sample
 #'
 #' @description Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. A normal distribution has a kurtosis of 3 and a excess kurtosis of 0.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x a vector of values, a [matrix] or a [data.frame]
 #' @param na.rm a [logical] to indicate whether `NA` values should be stripped before the computation proceeds
 #' @param excess a [logical] to indicate whether the *excess kurtosis* should be returned, defined as the kurtosis minus 3.
 #' @seealso [skewness()]
 #' @rdname kurtosis
-#' @inheritSection AMR Read more on Our Website!
 #' @export
+#' @examples
+#' kurtosis(rnorm(10000))
+#' kurtosis(rnorm(10000), excess = TRUE)
 kurtosis <- function(x, na.rm = FALSE, excess = FALSE) {
   meet_criteria(na.rm, allow_class = "logical", has_length = 1)
   meet_criteria(excess, allow_class = "logical", has_length = 1)

R/lifecycle.R

@@ -1,54 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Data Analysis for R                   #
-#                                                                      #
-# SOURCE                                                               #
-# https://github.com/msberends/AMR                                     #
-#                                                                      #
-# LICENCE                                                              #
-# (c) 2018-2022 Berends MS, Luz CF et al.                              #
-# Developed at the University of Groningen, the Netherlands, in        #
-# collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
-#                                                                      #
-# This R package is free software; you can freely use and distribute   #
-# it for both personal and commercial purposes under the terms of the  #
-# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
-# the Free Software Foundation.                                        #
-# We created this package for both routine data analysis and academic  #
-# research and it was publicly released in the hope that it will be    #
-# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
-#                                                                      #
-# Visit our website for the full manual and a complete tutorial about  #
-# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
-# ==================================================================== #
-
-###############
-# NOTE TO SELF: could also have done this with the 'lifecycle' package, but why add a package dependency for such an easy job??
-###############
-
-#' Lifecycles of Functions in the `AMR` Package
-#' @name lifecycle
-#' @rdname lifecycle
-#' @description Functions in this `AMR` package are categorised using [the lifecycle circle of the Tidyverse as found on www.tidyverse.org/lifecycle](https://lifecycle.r-lib.org/articles/stages.html).
-#' 
-#' \if{html}{\figure{lifecycle_tidyverse.svg}{options: height="200" style=margin-bottom:"5"} \cr}
-#' This page contains a section for every lifecycle (with text borrowed from the aforementioned Tidyverse website), so they can be used in the manual pages of the functions. 
-#' @section Experimental Lifecycle:
-#' \if{html}{\figure{lifecycle_experimental.svg}{options: style=margin-bottom:"5"} \cr}
-#' The [lifecycle][AMR::lifecycle] of this function is **experimental**. An experimental function is in early stages of development. The unlying code might be changing frequently. Experimental functions might be removed without deprecation, so you are generally best off waiting until a function is more mature before you use it in production code. Experimental functions are only available in development versions of this `AMR` package and will thus not be included in releases that are submitted to CRAN, since such functions have not yet matured enough.
-#' @section Maturing Lifecycle:
-#' \if{html}{\figure{lifecycle_maturing.svg}{options: style=margin-bottom:"5"} \cr}
-#' The [lifecycle][AMR::lifecycle] of this function is **maturing**. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome [to suggest changes at our repository](https://github.com/msberends/AMR/issues) or [write us an email (see section 'Contact Us')][AMR::AMR].
-#' @section Stable Lifecycle:
-#' \if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
-#' The [lifecycle][AMR::lifecycle] of this function is **stable**. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
-#' 
-#' If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
-#' @section Retired Lifecycle:
-#' \if{html}{\figure{lifecycle_retired.svg}{options: style=margin-bottom:"5"} \cr}
-#' The [lifecycle][AMR::lifecycle] of this function is **retired**. A retired function is no longer under active development, and (if appropiate) a better alternative is available. No new arguments will be added, and only the most critical bugs will be fixed. In a future version, this function will be removed.
-#' @section Questioning Lifecycle:
-#' \if{html}{\figure{lifecycle_questioning.svg}{options: style=margin-bottom:"5"} \cr}
-#' The [lifecycle][AMR::lifecycle] of this function is **questioning**. This function might be no longer be optimal approach, or is it questionable whether this function should be in this `AMR` package at all.
-NULL

R/like.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' Vectorised Pattern Matching with Keyboard Shortcut
 #'
 #' Convenient wrapper around [grepl()] to match a pattern: `x %like% pattern`. It always returns a [`logical`] vector and is always case-insensitive (use `x %like_case% pattern` for case-sensitive matching). Also, `pattern` can be as long as `x` to compare items of each index in both vectors, or they both can have the same length to iterate over all cases.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x a [character] vector where matches are sought, or an object which can be coerced by [as.character()] to a [character] vector.
 #' @param pattern a [character] vector containing regular expressions (or a [character] string for `fixed = TRUE`) to be matched in the given [character] vector. Coerced by [as.character()] to a [character] string if possible.
 #' @param ignore.case if `FALSE`, the pattern matching is *case sensitive* and if `TRUE`, case is ignored during matching.
@@ -40,38 +39,30 @@
 #' * Support multiple patterns
 #' * Check if `pattern` is a valid regular expression and sets `fixed = TRUE` if not, to greatly improve speed (vectorised over `pattern`)
 #' * Always use compatibility with Perl unless `fixed = TRUE`, to greatly improve speed
-#' 
+#'
 #' Using RStudio? The `%like%`/`%unlike%` functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like `Shift+Ctrl+L` or `Shift+Cmd+L` (see menu `Tools` > `Modify Keyboard Shortcuts...`). If you keep pressing your shortcut, the inserted text will be iterated over `%like%` -> `%unlike%` -> `%like_case%` -> `%unlike_case%`.
 #' @source Idea from the [`like` function from the `data.table` package](https://github.com/Rdatatable/data.table/blob/ec1259af1bf13fc0c96a1d3f9e84d55d8106a9a4/R/like.R), although altered as explained in *Details*.
 #' @seealso [grepl()]
-#' @inheritSection AMR Read more on Our Website!
+
 #' @examples
 #' a <- "This is a test"
 #' b <- "TEST"
 #' a %like% b
-#' #> TRUE
 #' b %like% a
-#' #> FALSE
-#' 
+#'
 #' # also supports multiple patterns
 #' a <- c("Test case", "Something different", "Yet another thing")
-#' b <- c(     "case",           "diff",      "yet")
+#' b <- c("case", "diff", "yet")
 #' a %like% b
-#' #> TRUE TRUE TRUE
 #' a %unlike% b
-#' #> FALSE FALSE FALSE
-#' 
+#'
 #' a[1] %like% b
-#' #> TRUE FALSE FALSE
 #' a %like% b[1]
-#' #> TRUE FALSE FALSE
-#' 
-#' # get isolates whose name start with 'Ent' or 'ent'
-#' example_isolates[which(mo_name(example_isolates$mo) %like% "^ent"), ]
+#'
 #' \donttest{
-#' # faster way, since mo_name() is context-aware:
-#' example_isolates[which(mo_name() %like% "^ent"), ]
-#' 
+#' # get isolates whose name start with 'Entero' (case-insensitive)
+#' example_isolates[which(mo_name() %like% "^entero"), ]
+#'
 #' if (require("dplyr")) {
 #'   example_isolates %>%
 #'     filter(mo_name() %like% "^ent")
@@ -81,7 +72,7 @@ like <- function(x, pattern, ignore.case = TRUE) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(pattern, allow_NA = FALSE)
   meet_criteria(ignore.case, allow_class = "logical", has_length = 1)
-  
+
   if (all(is.na(x))) {
     return(rep(FALSE, length(x)))
   }
@@ -105,18 +96,22 @@ like <- function(x, pattern, ignore.case = TRUE) {
     if (length(x) == 1) {
       x <- rep(x, length(pattern))
     } else if (length(pattern) != length(x)) {
-      stop_("arguments `x` and `pattern` must be of same length, or either one must be 1 ",
-            "(`x` has length ", length(x), " and `pattern` has length ", length(pattern), ")")
+      stop_(
+        "arguments `x` and `pattern` must be of same length, or either one must be 1 ",
+        "(`x` has length ", length(x), " and `pattern` has length ", length(pattern), ")"
+      )
     }
     unlist(
-      mapply(FUN = grepl,
-             x = x,
-             pattern = pattern,
-             fixed = fixed,
-             perl = !fixed,
-             MoreArgs = list(ignore.case = FALSE),
-             SIMPLIFY = FALSE,
-             USE.NAMES = FALSE)
+      mapply(
+        FUN = grepl,
+        x = x,
+        pattern = pattern,
+        fixed = fixed,
+        perl = !fixed,
+        MoreArgs = list(ignore.case = FALSE),
+        SIMPLIFY = FALSE,
+        USE.NAMES = FALSE
+      )
     )
   }
 }

R/mic.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -25,55 +25,77 @@
 
 # these are allowed MIC values and will become [factor] levels
 ops <- c("<", "<=", "", ">=", ">")
-valid_mic_levels <- c(c(t(vapply(FUN.VALUE = character(9), ops,
-                                 function(x) paste0(x, "0.00", 1:9)))),
-                      unique(c(t(vapply(FUN.VALUE = character(104), ops,
-                                        function(x) paste0(x, sort(as.double(paste0("0.0", 
-                                                                                    sort(c(1:99, 125, 128, 256, 512, 625)))))))))),
-                      unique(c(t(vapply(FUN.VALUE = character(103), ops,
-                                        function(x) paste0(x, sort(as.double(paste0("0.", 
-                                                                                    c(1:99, 125, 128, 256, 512))))))))),
-                      c(t(vapply(FUN.VALUE = character(10), ops,
-                                 function(x) paste0(x, sort(c(1:9, 1.5)))))),
-                      c(t(vapply(FUN.VALUE = character(45), ops,
-                                 function(x) paste0(x, c(10:98)[9:98 %% 2 == TRUE])))),
-                      c(t(vapply(FUN.VALUE = character(17), ops,
-                                 function(x) paste0(x, sort(c(2 ^ c(7:11), 192, 80 * c(2:12))))))))
+valid_mic_levels <- c(
+  c(t(vapply(
+    FUN.VALUE = character(9), ops,
+    function(x) paste0(x, "0.00", 1:9)
+  ))),
+  unique(c(t(vapply(
+    FUN.VALUE = character(104), ops,
+    function(x) {
+      paste0(x, sort(as.double(paste0(
+        "0.0",
+        sort(c(1:99, 125, 128, 256, 512, 625))
+      ))))
+    }
+  )))),
+  unique(c(t(vapply(
+    FUN.VALUE = character(103), ops,
+    function(x) {
+      paste0(x, sort(as.double(paste0(
+        "0.",
+        c(1:99, 125, 128, 256, 512)
+      ))))
+    }
+  )))),
+  c(t(vapply(
+    FUN.VALUE = character(10), ops,
+    function(x) paste0(x, sort(c(1:9, 1.5)))
+  ))),
+  c(t(vapply(
+    FUN.VALUE = character(45), ops,
+    function(x) paste0(x, c(10:98)[9:98 %% 2 == TRUE])
+  ))),
+  c(t(vapply(
+    FUN.VALUE = character(17), ops,
+    function(x) paste0(x, sort(c(2^c(7:11), 192, 80 * c(2:12))))
+  )))
+)
 
 #' Transform Input to Minimum Inhibitory Concentrations (MIC)
 #'
 #' This transforms vectors to a new class [`mic`], which treats the input as decimal numbers, while maintaining operators (such as ">=") and only allowing valid MIC values known to the field of (medical) microbiology.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @rdname as.mic
 #' @param x a [character] or [numeric] vector
 #' @param na.rm a [logical] indicating whether missing values should be removed
-#' @details To interpret MIC values as RSI values, use [as.rsi()] on MIC values. It supports guidelines from EUCAST and CLSI.
-#' 
+#' @param ... arguments passed on to methods
+#' @details To interpret MIC values as RSI values, use [as.rsi()] on MIC values. It supports guidelines from EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "CLSI")$guideline)))`).
+#'
 #' This class for MIC values is a quite a special data type: formally it is an ordered [factor] with valid MIC values as [factor] levels (to make sure only valid MIC values are retained), but for any mathematical operation it acts as decimal numbers:
-#' 
+#'
 #' ```
 #' x <- random_mic(10)
 #' x
 #' #> Class <mic>
 #' #>  [1] 16     1      8      8      64     >=128  0.0625 32     32     16
-#' 
+#'
 #' is.factor(x)
 #' #> [1] TRUE
-#' 
+#'
 #' x[1] * 2
 #' #> [1] 32
-#' 
+#'
 #' median(x)
 #' #> [1] 26
 #' ```
-#' 
+#'
 #' This makes it possible to maintain operators that often come with MIC values, such ">=" and "<=", even when filtering using [numeric] values in data analysis, e.g.:
-#' 
+#'
 #' ```
 #' x[x > 4]
 #' #> Class <mic>
 #' #> [1] 16    8     8     64    >=128 32    32    16
-#' 
+#'
 #' df <- data.frame(x, hospital = "A")
 #' subset(df, x > 4) # or with dplyr: df %>% filter(x > 4)
 #' #>        x hospital
@@ -84,42 +106,60 @@ valid_mic_levels <- c(c(t(vapply(FUN.VALUE = character(9), ops,
 #' #> 9     32        A
 #' #> 10    16        A
 #' ```
-#' 
+#'
 #' The following [generic functions][groupGeneric()] are implemented for the MIC class: `!`, `!=`, `%%`, `%/%`, `&`, `*`, `+`, `-`, `/`, `<`, `<=`, `==`, `>`, `>=`, `^`, `|`, [abs()], [acos()], [acosh()], [all()], [any()], [asin()], [asinh()], [atan()], [atanh()], [ceiling()], [cos()], [cosh()], [cospi()], [cummax()], [cummin()], [cumprod()], [cumsum()], [digamma()], [exp()], [expm1()], [floor()], [gamma()], [lgamma()], [log()], [log1p()], [log2()], [log10()], [max()], [mean()], [min()], [prod()], [range()], [round()], [sign()], [signif()], [sin()], [sinh()], [sinpi()], [sqrt()], [sum()], [tan()], [tanh()], [tanpi()], [trigamma()] and [trunc()]. Some functions of the `stats` package are also implemented: [median()], [quantile()], [mad()], [IQR()], [fivenum()]. Also, [boxplot.stats()] is supported. Since [sd()] and [var()] are non-generic functions, these could not be extended. Use [mad()] as an alternative, or use e.g. `sd(as.numeric(x))` where `x` is your vector of MIC values.
+#'
+#' Using [as.double()] or [as.numeric()] on MIC values will remove the operators and return a numeric vector. Do **not** use [as.integer()] on MIC values as by the \R convention on [factor]s, it will return the index of the factor levels (which is often useless for regular users).
+#'
+#' Use [droplevels()] to drop unused levels. At default, it will return a plain factor. Use `droplevels(..., as.mic = TRUE)` to maintain the `<mic>` class.
 #' @return Ordered [factor] with additional class [`mic`], that in mathematical operations acts as decimal numbers. Bare in mind that the outcome of any mathematical operation on MICs will return a [numeric] value.
 #' @aliases mic
 #' @export
 #' @seealso [as.rsi()]
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
+#' mic_data
 #' is.mic(mic_data)
 #'
 #' # this can also coerce combined MIC/RSI values:
-#' as.mic("<=0.002; S") # will return <=0.002
-#' 
-#' # mathematical processing treats MICs as [numeric] values
+#' as.mic("<=0.002; S")
+#'
+#' # mathematical processing treats MICs as numeric values
 #' fivenum(mic_data)
 #' quantile(mic_data)
 #' all(mic_data < 512)
 #'
 #' # interpret MIC values
-#' as.rsi(x = as.mic(2),
-#'        mo = as.mo("S. pneumoniae"),
-#'        ab = "AMX",
-#'        guideline = "EUCAST")
-#' as.rsi(x = as.mic(4),
-#'        mo = as.mo("S. pneumoniae"),
-#'        ab = "AMX",
-#'        guideline = "EUCAST")
+#' as.rsi(
+#'   x = as.mic(2),
+#'   mo = as.mo("Streptococcus pneumoniae"),
+#'   ab = "AMX",
+#'   guideline = "EUCAST"
+#' )
+#' as.rsi(
+#'   x = as.mic(c(0.01, 2, 4, 8)),
+#'   mo = as.mo("Streptococcus pneumoniae"),
+#'   ab = "AMX",
+#'   guideline = "EUCAST"
+#' )
 #'
 #' # plot MIC values, see ?plot
 #' plot(mic_data)
 #' plot(mic_data, mo = "E. coli", ab = "cipro")
+#'
+#' if (require("ggplot2")) {
+#'   autoplot(mic_data, mo = "E. coli", ab = "cipro")
+#' }
+#' if (require("ggplot2")) {
+#'   autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "nl") # Dutch
+#' }
+#' if (require("ggplot2")) {
+#'   autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "uk") # Ukrainian
+#' }
 as.mic <- function(x, na.rm = FALSE) {
   meet_criteria(x, allow_class = c("mic", "character", "numeric", "integer", "factor"), allow_NA = TRUE)
   meet_criteria(na.rm, allow_class = "logical", has_length = 1)
-  
+
   if (is.mic(x)) {
     x
   } else {
@@ -127,8 +167,9 @@ as.mic <- function(x, na.rm = FALSE) {
     if (na.rm == TRUE) {
       x <- x[!is.na(x)]
     }
+    x[trimws(x) == ""] <- NA
     x.bak <- x
-    
+
     # comma to period
     x <- gsub(",", ".", x, fixed = TRUE)
     # transform Unicode for >= and <=
@@ -162,27 +203,30 @@ as.mic <- function(x, na.rm = FALSE) {
     x <- gsub("[.]$", "", x, perl = TRUE)
     # trim it
     x <- trimws(x)
-    
+
     ## previously unempty values now empty - should return a warning later on
     x[x.bak != "" & x == ""] <- "invalid"
-    
+
     na_before <- x[is.na(x) | x == ""] %pm>% length()
     x[!x %in% valid_mic_levels] <- NA
     na_after <- x[is.na(x) | x == ""] %pm>% length()
-    
+
     if (na_before != na_after) {
       list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ""] %pm>%
         unique() %pm>%
         sort() %pm>%
         vector_and(quotes = TRUE)
       warning_("in `as.mic()`: ", na_after - na_before, " results truncated (",
-               round(((na_after - na_before) / length(x)) * 100),
-               "%) that were invalid MICs: ",
-               list_missing, call = FALSE)
+        round(((na_after - na_before) / length(x)) * 100),
+        "%) that were invalid MICs: ",
+        list_missing,
+        call = FALSE
+      )
     }
-    
+
     set_clean_class(factor(x, levels = valid_mic_levels, ordered = TRUE),
-                    new_class =  c("mic", "ordered", "factor"))
+      new_class = c("mic", "ordered", "factor")
+    )
   }
 }
 
@@ -191,15 +235,18 @@ all_valid_mics <- function(x) {
     return(FALSE)
   }
   x_mic <- tryCatch(suppressWarnings(as.mic(x[!is.na(x)])),
-                    error = function(e) NA)
+    error = function(e) NA
+  )
   !any(is.na(x_mic)) && !all(is.na(x))
 }
 
 #' @rdname as.mic
-#' @details `NA_mic_` is a missing value of the new `<mic>` class.
+#' @details `NA_mic_` is a missing value of the new `<mic>` class, analogous to e.g. base \R's [`NA_character_`][base::NA].
+#' @format NULL
 #' @export
 NA_mic_ <- set_clean_class(factor(NA, levels = valid_mic_levels, ordered = TRUE),
-                           new_class =  c("mic", "ordered", "factor"))
+  new_class = c("mic", "ordered", "factor")
+)
 
 #' @rdname as.mic
 #' @export
@@ -214,13 +261,6 @@ as.double.mic <- function(x, ...) {
   as.double(gsub("[<=>]+", "", as.character(x), perl = TRUE))
 }
 
-#' @method as.integer mic
-#' @export
-#' @noRd
-as.integer.mic <- function(x, ...) {
-  as.integer(gsub("[<=>]+", "", as.character(x), perl = TRUE))
-}
-
 #' @method as.numeric mic
 #' @export
 #' @noRd
@@ -228,11 +268,12 @@ as.numeric.mic <- function(x, ...) {
   as.numeric(gsub("[<=>]+", "", as.character(x), perl = TRUE))
 }
 
+#' @rdname as.mic
 #' @method droplevels mic
+#' @param as.mic a [logical] to indicate whether the `<mic>` class should be kept, defaults to `FALSE`
 #' @export
-#' @noRd
-droplevels.mic <- function(x, exclude = if (any(is.na(levels(x)))) NULL else NA, as.mic = TRUE, ...) {
-  x <- droplevels.factor(x, exclude = exclude, ...)
+droplevels.mic <- function(x, as.mic = FALSE, ...) {
+  x <- droplevels.factor(x, ...)
   if (as.mic == TRUE) {
     class(x) <- c("mic", "ordered", "factor")
   }
@@ -260,7 +301,11 @@ type_sum.mic <- function(x, ...) {
 #' @export
 #' @noRd
 print.mic <- function(x, ...) {
-  cat("Class <mic>\n")
+  cat("Class <mic>",
+    ifelse(length(levels(x)) < length(valid_mic_levels), font_red(" with dropped levels"), ""),
+    "\n",
+    sep = ""
+  )
   print(as.character(x), quote = FALSE)
   att <- attributes(x)
   if ("na.action" %in% names(att)) {
@@ -366,12 +411,12 @@ hist.mic <- function(x, ...) {
 get_skimmers.mic <- function(column) {
   skimr::sfl(
     skim_type = "mic",
-    p0 = ~stats::quantile(., probs = 0, na.rm = TRUE, names = FALSE),
-    p25 = ~stats::quantile(., probs = 0.25, na.rm = TRUE, names = FALSE),
-    p50 = ~stats::quantile(., probs = 0.5, na.rm = TRUE, names = FALSE),
-    p75 = ~stats::quantile(., probs = 0.75, na.rm = TRUE, names = FALSE),
-    p100 = ~stats::quantile(., probs = 1, na.rm = TRUE, names = FALSE),
-    hist = ~skimr::inline_hist(log2(stats::na.omit(.)), 5)
+    p0 = ~ stats::quantile(., probs = 0, na.rm = TRUE, names = FALSE),
+    p25 = ~ stats::quantile(., probs = 0.25, na.rm = TRUE, names = FALSE),
+    p50 = ~ stats::quantile(., probs = 0.5, na.rm = TRUE, names = FALSE),
+    p75 = ~ stats::quantile(., probs = 0.75, na.rm = TRUE, names = FALSE),
+    p100 = ~ stats::quantile(., probs = 1, na.rm = TRUE, names = FALSE),
+    hist = ~ skimr::inline_hist(log2(stats::na.omit(.)), 5)
   )
 }
 
@@ -667,7 +712,7 @@ is_lower <- function(el) {
 #' @export
 #' @noRd
 `^.mic` <- function(e1, e2) {
-  as.double(e1) ^ as.double(e2)
+  as.double(e1)^as.double(e2)
 }
 
 #' @method %% mic

R/mo_matching_score.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -24,59 +24,63 @@
 # ==================================================================== #
 
 #' Calculate the Matching Score for Microorganisms
-#' 
-#' This algorithm is used by [as.mo()] and all the [`mo_*`][mo_property()] functions to determine the most probable match of taxonomic records based on user input. 
-#' @inheritSection lifecycle Stable Lifecycle
-#' @author Dr Matthijs Berends
+#'
+#' This algorithm is used by [as.mo()] and all the [`mo_*`][mo_property()] functions to determine the most probable match of taxonomic records based on user input.
+#' @author Dr. Matthijs Berends
 #' @param x Any user input value(s)
 #' @param n A full taxonomic name, that exists in [`microorganisms$fullname`][microorganisms]
 #' @section Matching Score for Microorganisms:
 #' With ambiguous user input in [as.mo()] and all the [`mo_*`][mo_property()] functions, the returned results are chosen based on their matching score using [mo_matching_score()]. This matching score \eqn{m}, is calculated as:
-#' 
+#'
 #' \ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}}
-#' 
+#'
 #' where:
-#' 
+#'
 #' * \ifelse{html}{\out{<i>x</i> is the user input;}}{\eqn{x} is the user input;}
 #' * \ifelse{html}{\out{<i>n</i> is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
 #' * \ifelse{html}{\out{<i>l<sub>n</sub></i> is the length of <i>n</i>;}}{l_n is the length of \eqn{n};}
 #' * \ifelse{html}{\out{<i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;}}{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};}
 #' * \ifelse{html}{\out{<i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
 #' * \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
-#' 
+#'
 #' The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. **Group 1** (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is *Enterococcus*, *Staphylococcus* or *Streptococcus*. This group consequently contains all common Gram-negative bacteria, such as *Pseudomonas* and *Legionella* and all species within the order Enterobacterales. **Group 2** consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is *Absidia*, *Acremonium*, *Actinotignum*, *Alternaria*, *Anaerosalibacter*, *Apophysomyces*, *Arachnia*, *Aspergillus*, *Aureobacterium*, *Aureobasidium*, *Bacteroides*, *Basidiobolus*, *Beauveria*, *Blastocystis*, *Branhamella*, *Calymmatobacterium*, *Candida*, *Capnocytophaga*, *Catabacter*, *Chaetomium*, *Chryseobacterium*, *Chryseomonas*, *Chrysonilia*, *Cladophialophora*, *Cladosporium*, *Conidiobolus*, *Cryptococcus*, *Curvularia*, *Exophiala*, *Exserohilum*, *Flavobacterium*, *Fonsecaea*, *Fusarium*, *Fusobacterium*, *Hendersonula*, *Hypomyces*, *Koserella*, *Lelliottia*, *Leptosphaeria*, *Leptotrichia*, *Malassezia*, *Malbranchea*, *Mortierella*, *Mucor*, *Mycocentrospora*, *Mycoplasma*, *Nectria*, *Ochroconis*, *Oidiodendron*, *Phoma*, *Piedraia*, *Pithomyces*, *Pityrosporum*, *Prevotella*, *Pseudallescheria*, *Rhizomucor*, *Rhizopus*, *Rhodotorula*, *Scolecobasidium*, *Scopulariopsis*, *Scytalidium*, *Sporobolomyces*, *Stachybotrys*, *Stomatococcus*, *Treponema*, *Trichoderma*, *Trichophyton*, *Trichosporon*, *Tritirachium* or *Ureaplasma*. **Group 3** consists of all other microorganisms.
-#' 
+#'
 #' All characters in \eqn{x} and \eqn{n} are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.
-#' 
-#' All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., `"E. coli"` will return the microbial ID of *Escherichia coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Escherichia coli"), 3)`}, a highly prevalent microorganism found in humans) and not *Entamoeba coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Entamoeba coli"), 3)`}, a less prevalent microorganism in humans), although the latter would alphabetically come first. 
-#' 
+#'
+#' All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., `"E. coli"` will return the microbial ID of *Escherichia coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Escherichia coli"), 3)`}, a highly prevalent microorganism found in humans) and not *Entamoeba coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Entamoeba coli"), 3)`}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
+#'
 #' Since `AMR` version 1.8.1, common microorganism abbreviations are ignored in determining the matching score. These abbreviations are currently: `r vector_and(pkg_env$mo_field_abbreviations, quotes = FALSE)`.
 #' @export
 #' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
-#' @examples 
+#' @examples
 #' as.mo("E. coli")
 #' mo_uncertainties()
-#' 
-#' mo_matching_score(x = "E. coli",
-#'                   n = c("Escherichia coli", "Entamoeba coli"))
+#'
+#' mo_matching_score(
+#'   x = "E. coli",
+#'   n = c("Escherichia coli", "Entamoeba coli")
+#' )
 mo_matching_score <- function(x, n) {
   meet_criteria(x, allow_class = c("character", "data.frame", "list"))
   meet_criteria(n, allow_class = "character")
-  
+
   x <- parse_and_convert(x)
   # no dots and other non-whitespace characters
   x <- gsub("[^a-zA-Z0-9 \\(\\)]+", "", x)
-  
+
   # remove abbreviations known to the field
-  x <- gsub(paste0("(^|[^a-z0-9]+)(",
-                   paste0(pkg_env$mo_field_abbreviations, collapse = "|"),
-                   ")([^a-z0-9]+|$)"),
-            "", x, perl = TRUE, ignore.case = TRUE)
-  
+  x <- gsub(paste0(
+    "(^|[^a-z0-9]+)(",
+    paste0(pkg_env$mo_field_abbreviations, collapse = "|"),
+    ")([^a-z0-9]+|$)"
+  ),
+  "", x,
+  perl = TRUE, ignore.case = TRUE
+  )
+
   # only keep one space
   x <- gsub(" +", " ", x)
-  
+
   # n is always a taxonomically valid full name
   if (length(n) == 1) {
     n <- rep(n, length(x))
@@ -84,7 +88,7 @@ mo_matching_score <- function(x, n) {
   if (length(x) == 1) {
     x <- rep(x, length(n))
   }
-  
+
   # length of fullname
   l_n <- nchar(n)
   lev <- double(length = length(x))
@@ -99,7 +103,7 @@ mo_matching_score <- function(x, n) {
   p_n <- MO_lookup[match(n, MO_lookup$fullname), "prevalence", drop = TRUE]
   # kingdom index (Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5)
   k_n <- MO_lookup[match(n, MO_lookup$fullname), "kingdom_index", drop = TRUE]
-  
+
   # matching score:
   (l_n - 0.5 * l_n.lev) / (l_n * p_n * k_n)
 }

R/mo_property.R

@@ -26,7 +26,6 @@
 #' Get Properties of a Microorganism
 #'
 #' Use these functions to return a specific property of a microorganism based on the latest accepted taxonomy. All input values will be evaluated internally with [as.mo()], which makes it possible to use microbial abbreviations, codes and names as input. See *Examples*.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x any [character] (vector) that can be coerced to a valid microorganism code with [as.mo()]. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, see *Examples*.
 #' @param property one of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, quotes = TRUE)`, or must be `"shortname"`
 #' @param language language of the returned text, defaults to system language (see [get_AMR_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Also used to translate text like "no growth". Use `language = NULL` or `language = ""` to prevent translation.
@@ -43,15 +42,15 @@
 #' Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions [mo_kingdom()] and [mo_domain()] return the exact same results.
 #'
 #' The Gram stain - [mo_gramstain()] - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318)), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive, except for members of the class Negativicutes which are Gram-negative. Members of other bacterial phyla are all considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [mo_is_gram_negative()] and [mo_is_gram_positive()] always return `TRUE` or `FALSE` (except when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
-#' 
+#'
 #' Determination of yeasts - [mo_is_yeast()] - will be based on the taxonomic kingdom and class. *Budding yeasts* are fungi of the phylum Ascomycetes, class Saccharomycetes (also called Hemiascomycetes). *True yeasts* are aggregated into the underlying order Saccharomycetales. Thus, for all microorganisms that are fungi and member of the taxonomic class Saccharomycetes, the function will return `TRUE`. It returns `FALSE` otherwise (except when the input is `NA` or the MO code is `UNKNOWN`).
-#' 
+#'
 #' Intrinsic resistance - [mo_is_intrinsic_resistant()] - will be determined based on the [intrinsic_resistant] data set, which is based on `r format_eucast_version_nr(3.3)`. The [mo_is_intrinsic_resistant()] functions can be vectorised over arguments `x` (input for microorganisms) and over `ab` (input for antibiotics).
 #'
 #' All output [will be translated][translate] where possible.
 #'
 #' The function [mo_url()] will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.
-#' 
+#'
 #' SNOMED codes - [mo_snomed()] - are from the `r SNOMED_VERSION$current_source`. See *Source* and the [microorganisms] data set for more info.
 #' @inheritSection mo_matching_score Matching Score for Microorganisms
 #' @inheritSection catalogue_of_life Catalogue of Life
@@ -67,108 +66,108 @@
 #' @export
 #' @seealso Data set [microorganisms]
 #' @inheritSection AMR Reference Data Publicly Available
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' # taxonomic tree -----------------------------------------------------------
-#' mo_kingdom("E. coli")         # "Bacteria"
-#' mo_phylum("E. coli")          # "Proteobacteria"
-#' mo_class("E. coli")           # "Gammaproteobacteria"
-#' mo_order("E. coli")           # "Enterobacterales"
-#' mo_family("E. coli")          # "Enterobacteriaceae"
-#' mo_genus("E. coli")           # "Escherichia"
-#' mo_species("E. coli")         # "coli"
-#' mo_subspecies("E. coli")      # ""
+#' mo_kingdom("Klebsiella pneumoniae")
+#' mo_phylum("Klebsiella pneumoniae")
+#' mo_class("Klebsiella pneumoniae")
+#' mo_order("Klebsiella pneumoniae")
+#' mo_family("Klebsiella pneumoniae")
+#' mo_genus("Klebsiella pneumoniae")
+#' mo_species("Klebsiella pneumoniae")
+#' mo_subspecies("Klebsiella pneumoniae")
 #'
 #' # colloquial properties ----------------------------------------------------
-#' mo_name("E. coli")            # "Escherichia coli"
-#' mo_fullname("E. coli")        # "Escherichia coli" - same as mo_name()
-#' mo_shortname("E. coli")       # "E. coli"
+#' mo_name("Klebsiella pneumoniae")
+#' mo_fullname("Klebsiella pneumoniae")
+#' mo_shortname("Klebsiella pneumoniae")
 #'
 #' # other properties ---------------------------------------------------------
-#' mo_gramstain("E. coli")       # "Gram-negative"
-#' mo_snomed("E. coli")          # 112283007, 116395006, ... (SNOMED codes)
-#' mo_type("E. coli")            # "Bacteria" (equal to kingdom, but may be translated)
-#' mo_rank("E. coli")            # "species"
-#' mo_url("E. coli")             # get the direct url to the online database entry
-#' mo_synonyms("E. coli")        # get previously accepted taxonomic names
+#' mo_gramstain("Klebsiella pneumoniae")
+#' mo_snomed("Klebsiella pneumoniae")
+#' mo_type("Klebsiella pneumoniae")
+#' mo_rank("Klebsiella pneumoniae")
+#' mo_url("Klebsiella pneumoniae")
+#' mo_synonyms("Klebsiella pneumoniae")
 #'
 #' # scientific reference -----------------------------------------------------
-#' mo_ref("E. coli")             # "Castellani et al., 1919"
-#' mo_authors("E. coli")         # "Castellani et al."
-#' mo_year("E. coli")            # 1919
-#' mo_lpsn("E. coli")            # 776057 (LPSN record ID)
+#' mo_ref("Klebsiella pneumoniae")
+#' mo_authors("Klebsiella pneumoniae")
+#' mo_year("Klebsiella pneumoniae")
+#' mo_lpsn("Klebsiella pneumoniae")
 #'
 #' # abbreviations known in the field -----------------------------------------
-#' mo_genus("MRSA")              # "Staphylococcus"
-#' mo_species("MRSA")            # "aureus"
-#' mo_shortname("VISA")          # "S. aureus"
-#' mo_gramstain("VISA")          # "Gram-positive"
+#' mo_genus("MRSA")
+#' mo_species("MRSA")
+#' mo_shortname("VISA")
+#' mo_gramstain("VISA")
 #'
-#' mo_genus("EHEC")              # "Escherichia"
-#' mo_species("EHEC")            # "coli"
+#' mo_genus("EHEC")
+#' mo_species("EHEC")
 #'
 #' # known subspecies ---------------------------------------------------------
-#' mo_name("doylei")             # "Campylobacter jejuni doylei"
-#' mo_genus("doylei")            # "Campylobacter"
-#' mo_species("doylei")          # "jejuni"
-#' mo_subspecies("doylei")       # "doylei"
+#' mo_name("doylei")
+#' mo_genus("doylei")
+#' mo_species("doylei")
+#' mo_subspecies("doylei")
 #'
-#' mo_fullname("K. pneu rh")     # "Klebsiella pneumoniae rhinoscleromatis"
-#' mo_shortname("K. pneu rh")    # "K. pneumoniae"
+#' mo_fullname("K. pneu rh")
+#' mo_shortname("K. pneu rh")
 #'
 #' \donttest{
 #' # Becker classification, see ?as.mo ----------------------------------------
-#' mo_fullname("S. epi")                     # "Staphylococcus epidermidis"
-#' mo_fullname("S. epi", Becker = TRUE)      # "Coagulase-negative Staphylococcus (CoNS)"
-#' mo_shortname("S. epi")                    # "S. epidermidis"
-#' mo_shortname("S. epi", Becker = TRUE)     # "CoNS"
+#' mo_fullname("S. epi")
+#' mo_fullname("S. epi", Becker = TRUE)
+#' mo_shortname("S. epi")
+#' mo_shortname("S. epi", Becker = TRUE)
 #'
 #' # Lancefield classification, see ?as.mo ------------------------------------
-#' mo_fullname("S. pyo")                     # "Streptococcus pyogenes"
-#' mo_fullname("S. pyo", Lancefield = TRUE)  # "Streptococcus group A"
-#' mo_shortname("S. pyo")                    # "S. pyogenes"
-#' mo_shortname("S. pyo", Lancefield = TRUE) # "GAS" (='Group A Streptococci')
+#' mo_fullname("S. pyo")
+#' mo_fullname("S. pyo", Lancefield = TRUE)
+#' mo_shortname("S. pyo")
+#' mo_shortname("S. pyo", Lancefield = TRUE)
 #'
 #'
 #' # language support  --------------------------------------------------------
-#' mo_gramstain("E. coli", language = "de")  # "Gramnegativ"
-#' mo_gramstain("E. coli", language = "nl")  # "Gram-negatief"
-#' mo_gramstain("E. coli", language = "es")  # "Gram negativo"
+#' mo_gramstain("Klebsiella pneumoniae", language = "de")
+#' mo_gramstain("Klebsiella pneumoniae", language = "nl")
+#' mo_gramstain("Klebsiella pneumoniae", language = "es")
 #'
 #' # mo_type is equal to mo_kingdom, but mo_kingdom will remain official
-#' mo_kingdom("E. coli")                     # "Bacteria" on a German system
-#' mo_type("E. coli")                        # "Bakterien" on a German system
-#' mo_type("E. coli")                        # "Bacteria" on an English system
+#' mo_kingdom("Klebsiella pneumoniae")
+#' mo_type("Klebsiella pneumoniae")
+#' mo_type("Klebsiella pneumoniae")
 #'
 #' mo_fullname("S. pyogenes",
-#'             Lancefield = TRUE,
-#'             language = "de")              # "Streptococcus Gruppe A"
+#'   Lancefield = TRUE,
+#'   language = "de"
+#' )
 #' mo_fullname("S. pyogenes",
-#'             Lancefield = TRUE,
-#'             language = "nl")              # "Streptococcus groep A"
+#'   Lancefield = TRUE,
+#'   language = "nl"
+#' )
 #'
 #'
 #' # other --------------------------------------------------------------------
-#' 
-#' mo_is_yeast(c("Candida", "E. coli"))      # TRUE, FALSE
-#' 
-#' # gram stains and intrinsic resistance can also be used as a filter in dplyr verbs
-#' \donttest{
+#'
+#' mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
+#'
+#' # gram stains and intrinsic resistance can be used as a filter in dplyr verbs
 #' if (require("dplyr")) {
 #'   example_isolates %>%
 #'     filter(mo_is_gram_positive())
-#'     
+#'
 #'   example_isolates %>%
 #'     filter(mo_is_intrinsic_resistant(ab = "vanco"))
 #' }
-#' 
-#' 
+#'
+#'
 #' # get a list with the complete taxonomy (from kingdom to subspecies)
-#' mo_taxonomy("E. coli")
+#' mo_taxonomy("Klebsiella pneumoniae")
+#'
 #' # get a list with the taxonomy, the authors, Gram-stain,
-#' #   SNOMED codes, and URL to the online database
-#' mo_info("E. coli")
-#' }
+#' # SNOMED codes, and URL to the online database
+#' mo_info("Klebsiella pneumoniae")
 #' }
 mo_name <- function(x, language = get_AMR_locale(), ...) {
   if (missing(x)) {
@@ -177,11 +176,12 @@ mo_name <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
-  translate_AMR(mo_validate(x = x, property = "fullname", language = language, ...),
-                language = language,
-                only_unknown = FALSE,
-                only_affect_mo_names = TRUE)
+
+  translate_into_language(mo_validate(x = x, property = "fullname", language = language, ...),
+    language = language,
+    only_unknown = FALSE,
+    only_affect_mo_names = TRUE
+  )
 }
 
 #' @rdname mo_property
@@ -197,20 +197,20 @@ mo_shortname <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x.mo <- as.mo(x, language = language, ...)
-  
+
   metadata <- get_mo_failures_uncertainties_renamed()
-  
+
   replace_empty <- function(x) {
     x[x == ""] <- "spp."
     x
   }
-  
+
   # get first char of genus and complete species in English
   genera <- mo_genus(x.mo, language = NULL)
   shortnames <- paste0(substr(genera, 1, 1), ". ", replace_empty(mo_species(x.mo, language = NULL)))
-  
+
   # exceptions for where no species is known
   shortnames[shortnames %like% ".[.] spp[.]"] <- genera[shortnames %like% ".[.] spp[.]"]
   # exceptions for staphylococci
@@ -220,10 +220,10 @@ mo_shortname <- function(x, language = get_AMR_locale(), ...) {
   shortnames[shortnames %like% "S. group [ABCDFGHK]"] <- paste0("G", gsub("S. group ([ABCDFGHK])", "\\1", shortnames[shortnames %like% "S. group [ABCDFGHK]"], perl = TRUE), "S")
   # unknown species etc.
   shortnames[shortnames %like% "unknown"] <- paste0("(", trimws(gsub("[^a-zA-Z -]", "", shortnames[shortnames %like% "unknown"], perl = TRUE)), ")")
-  
+
   shortnames[is.na(x.mo)] <- NA_character_
   load_mo_failures_uncertainties_renamed(metadata)
-  translate_AMR(shortnames, language = language, only_unknown = FALSE, only_affect_mo_names = TRUE)
+  translate_into_language(shortnames, language = language, only_unknown = FALSE, only_affect_mo_names = TRUE)
 }
 
 
@@ -237,8 +237,8 @@ mo_subspecies <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
-  translate_AMR(mo_validate(x = x, property = "subspecies", language = language, ...), language = language, only_unknown = TRUE)
+
+  translate_into_language(mo_validate(x = x, property = "subspecies", language = language, ...), language = language, only_unknown = TRUE)
 }
 
 #' @rdname mo_property
@@ -250,8 +250,8 @@ mo_species <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
-  translate_AMR(mo_validate(x = x, property = "species", language = language, ...), language = language, only_unknown = TRUE)
+
+  translate_into_language(mo_validate(x = x, property = "species", language = language, ...), language = language, only_unknown = TRUE)
 }
 
 #' @rdname mo_property
@@ -263,8 +263,8 @@ mo_genus <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
-  translate_AMR(mo_validate(x = x, property = "genus", language = language, ...), language = language, only_unknown = TRUE)
+
+  translate_into_language(mo_validate(x = x, property = "genus", language = language, ...), language = language, only_unknown = TRUE)
 }
 
 #' @rdname mo_property
@@ -276,8 +276,8 @@ mo_family <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
-  translate_AMR(mo_validate(x = x, property = "family", language = language, ...), language = language, only_unknown = TRUE)
+
+  translate_into_language(mo_validate(x = x, property = "family", language = language, ...), language = language, only_unknown = TRUE)
 }
 
 #' @rdname mo_property
@@ -289,8 +289,8 @@ mo_order <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
-  translate_AMR(mo_validate(x = x, property = "order", language = language, ...), language = language, only_unknown = TRUE)
+
+  translate_into_language(mo_validate(x = x, property = "order", language = language, ...), language = language, only_unknown = TRUE)
 }
 
 #' @rdname mo_property
@@ -302,8 +302,8 @@ mo_class <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
-  translate_AMR(mo_validate(x = x, property = "class", language = language, ...), language = language, only_unknown = TRUE)
+
+  translate_into_language(mo_validate(x = x, property = "class", language = language, ...), language = language, only_unknown = TRUE)
 }
 
 #' @rdname mo_property
@@ -315,8 +315,8 @@ mo_phylum <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
-  translate_AMR(mo_validate(x = x, property = "phylum", language = language, ...), language = language, only_unknown = TRUE)
+
+  translate_into_language(mo_validate(x = x, property = "phylum", language = language, ...), language = language, only_unknown = TRUE)
 }
 
 #' @rdname mo_property
@@ -328,8 +328,8 @@ mo_kingdom <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
-  translate_AMR(mo_validate(x = x, property = "kingdom", language = language, ...), language = language, only_unknown = TRUE)
+
+  translate_into_language(mo_validate(x = x, property = "kingdom", language = language, ...), language = language, only_unknown = TRUE)
 }
 
 #' @rdname mo_property
@@ -345,11 +345,11 @@ mo_type <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x.mo <- as.mo(x, language = language, ...)
   out <- mo_kingdom(x.mo, language = NULL)
   out[which(mo_is_yeast(x.mo))] <- "Yeasts"
-  translate_AMR(out, language = language, only_unknown = FALSE)
+  translate_into_language(out, language = language, only_unknown = FALSE)
 }
 
 #' @rdname mo_property
@@ -361,26 +361,28 @@ mo_gramstain <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x.mo <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
+
   x <- rep(NA_character_, length(x))
   # make all bacteria Gram negative
   x[mo_kingdom(x.mo) == "Bacteria"] <- "Gram-negative"
   # overwrite these 4 phyla with Gram-positives
   # Source: https://itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=956097 (Cavalier-Smith, 2002)
-  x[(mo_phylum(x.mo) %in% c("Actinobacteria",
-                            "Chloroflexi",
-                            "Firmicutes",
-                            "Tenericutes") &
-       # but class Negativicutes (of phylum Firmicutes) are Gram-negative!
-       mo_class(x.mo) != "Negativicutes")
-    # and of course our own ID for Gram-positives
-    | x.mo == "B_GRAMP"] <- "Gram-positive"
-  
+  x[(mo_phylum(x.mo) %in% c(
+    "Actinobacteria",
+    "Chloroflexi",
+    "Firmicutes",
+    "Tenericutes"
+  ) &
+    # but class Negativicutes (of phylum Firmicutes) are Gram-negative!
+    mo_class(x.mo) != "Negativicutes")
+  # and of course our own ID for Gram-positives
+  | x.mo == "B_GRAMP"] <- "Gram-positive"
+
   load_mo_failures_uncertainties_renamed(metadata)
-  translate_AMR(x, language = language, only_unknown = FALSE)
+  translate_into_language(x, language = language, only_unknown = FALSE)
 }
 
 #' @rdname mo_property
@@ -392,7 +394,7 @@ mo_is_gram_negative <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x.mo <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
   grams <- mo_gramstain(x.mo, language = NULL)
@@ -411,7 +413,7 @@ mo_is_gram_positive <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x.mo <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
   grams <- mo_gramstain(x.mo, language = NULL)
@@ -430,17 +432,15 @@ mo_is_yeast <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x.mo <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
+
   x.kingdom <- mo_kingdom(x.mo, language = NULL)
-  x.phylum <- mo_phylum(x.mo, language = NULL)
   x.class <- mo_class(x.mo, language = NULL)
-  x.order <- mo_order(x.mo, language = NULL)
-  
+
   load_mo_failures_uncertainties_renamed(metadata)
-  
+
   out <- rep(FALSE, length(x))
   out[x.kingdom == "Fungi" & x.class == "Saccharomycetes"] <- TRUE
   out[x.mo %in% c(NA_character_, "UNKNOWN")] <- NA
@@ -457,10 +457,10 @@ mo_is_intrinsic_resistant <- function(x, ab, language = get_AMR_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(ab, allow_NA = FALSE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- as.mo(x, language = language, ...)
   ab <- as.ab(ab, language = NULL, flag_multiple_results = FALSE, info = FALSE)
-  
+
   if (length(x) == 1 & length(ab) > 1) {
     x <- rep(x, length(ab))
   } else if (length(ab) == 1 & length(x) > 1) {
@@ -469,14 +469,16 @@ mo_is_intrinsic_resistant <- function(x, ab, language = get_AMR_locale(), ...) {
   if (length(x) != length(ab)) {
     stop_("length of `x` and `ab` must be equal, or one of them must be of length 1.")
   }
-  
+
   # show used version number once per session (pkg_env will reload every session)
   if (message_not_thrown_before("mo_is_intrinsic_resistant", "version.mo", entire_session = TRUE)) {
-    message_("Determining intrinsic resistance based on ",
-             format_eucast_version_nr(3.3, markdown = FALSE), ". ",
-             font_red("This note will be shown once per session."))
+    message_(
+      "Determining intrinsic resistance based on ",
+      format_eucast_version_nr(3.3, markdown = FALSE), ". ",
+      font_red("This note will be shown once per session.")
+    )
   }
-  
+
   # runs against internal vector: INTRINSIC_R (see zzz.R)
   paste(x, ab) %in% INTRINSIC_R
 }
@@ -490,7 +492,7 @@ mo_snomed <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   mo_validate(x = x, property = "snomed", language = language, ...)
 }
 
@@ -503,7 +505,7 @@ mo_ref <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   mo_validate(x = x, property = "ref", language = language, ...)
 }
 
@@ -516,7 +518,7 @@ mo_authors <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- mo_validate(x = x, property = "ref", language = language, ...)
   # remove last 4 digits and presumably the comma and space that preceed them
   x[!is.na(x)] <- gsub(",? ?[0-9]{4}", "", x[!is.na(x)], perl = TRUE)
@@ -532,7 +534,7 @@ mo_year <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- mo_validate(x = x, property = "ref", language = language, ...)
   # get last 4 digits
   x[!is.na(x)] <- gsub(".*([0-9]{4})$", "\\1", x[!is.na(x)], perl = TRUE)
@@ -548,7 +550,7 @@ mo_lpsn <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   mo_validate(x = x, property = "species_id", language = language, ...)
 }
 
@@ -561,32 +563,34 @@ mo_rank <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   mo_validate(x = x, property = "rank", language = language, ...)
 }
 
 #' @rdname mo_property
 #' @export
-mo_taxonomy <- function(x, language = get_AMR_locale(),  ...) {
+mo_taxonomy <- function(x, language = get_AMR_locale(), ...) {
   if (missing(x)) {
     # this tries to find the data and an <mo> column
     x <- find_mo_col(fn = "mo_taxonomy")
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
-  out <- list(kingdom = mo_kingdom(x, language = language),
-              phylum = mo_phylum(x, language = language),
-              class = mo_class(x, language = language),
-              order = mo_order(x, language = language),
-              family = mo_family(x, language = language),
-              genus = mo_genus(x, language = language),
-              species = mo_species(x, language = language),
-              subspecies = mo_subspecies(x, language = language))
-  
+
+  out <- list(
+    kingdom = mo_kingdom(x, language = language),
+    phylum = mo_phylum(x, language = language),
+    class = mo_class(x, language = language),
+    order = mo_order(x, language = language),
+    family = mo_family(x, language = language),
+    genus = mo_genus(x, language = language),
+    species = mo_species(x, language = language),
+    subspecies = mo_subspecies(x, language = language)
+  )
+
   load_mo_failures_uncertainties_renamed(metadata)
   out
 }
@@ -600,13 +604,13 @@ mo_synonyms <- function(x, language = get_AMR_locale(), ...) {
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
+
   IDs <- mo_name(x = x, language = NULL)
   syns <- lapply(IDs, function(newname) {
-    res <- sort(microorganisms.old[which(microorganisms.old$fullname_new == newname), "fullname"])
+    res <- sort(microorganisms.old[which(microorganisms.old$fullname_new == newname), "fullname", drop = TRUE])
     if (length(res) == 0) {
       NULL
     } else {
@@ -619,38 +623,43 @@ mo_synonyms <- function(x, language = get_AMR_locale(), ...) {
   } else {
     result <- unlist(syns)
   }
-  
+
   load_mo_failures_uncertainties_renamed(metadata)
   result
 }
 
 #' @rdname mo_property
 #' @export
-mo_info <- function(x, language = get_AMR_locale(),  ...) {
+mo_info <- function(x, language = get_AMR_locale(), ...) {
   if (missing(x)) {
     # this tries to find the data and an <mo> column
     x <- find_mo_col(fn = "mo_info")
   }
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x <- as.mo(x, language = language, ...)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
-  info <- lapply(x, function(y)
-    c(mo_taxonomy(y, language = language),
-      list(synonyms = mo_synonyms(y),
-           gramstain = mo_gramstain(y, language = language),
-           url = unname(mo_url(y, open = FALSE)),
-           ref = mo_ref(y),
-           snomed = unlist(mo_snomed(y)))))
+
+  info <- lapply(x, function(y) {
+    c(
+      mo_taxonomy(y, language = language),
+      list(
+        synonyms = mo_synonyms(y),
+        gramstain = mo_gramstain(y, language = language),
+        url = unname(mo_url(y, open = FALSE)),
+        ref = mo_ref(y),
+        snomed = unlist(mo_snomed(y))
+      )
+    )
+  })
   if (length(info) > 1) {
     names(info) <- mo_name(x)
     result <- info
   } else {
     result <- info[[1L]]
   }
-  
+
   load_mo_failures_uncertainties_renamed(metadata)
   result
 }
@@ -665,30 +674,31 @@ mo_url <- function(x, open = FALSE, language = get_AMR_locale(), ...) {
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(open, allow_class = "logical", has_length = 1)
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
+
   x.mo <- as.mo(x = x, language = language, ... = ...)
   metadata <- get_mo_failures_uncertainties_renamed()
-  
-  df <- microorganisms[match(x.mo, microorganisms$mo), c("mo", "fullname", "source", "kingdom", "rank")]
+
+  df <- microorganisms[match(x.mo, microorganisms$mo), c("mo", "fullname", "source", "kingdom", "rank"), drop = FALSE]
   df$url <- ifelse(df$source == "LPSN",
-                   paste0(CATALOGUE_OF_LIFE$url_LPSN, "/species/", gsub(" ", "-", tolower(df$fullname), fixed = TRUE)),
-                   paste0(CATALOGUE_OF_LIFE$url_CoL, "/data/search?type=EXACT&q=", gsub(" ", "%20", df$fullname, fixed = TRUE)))
-  
+    paste0(CATALOGUE_OF_LIFE$url_LPSN, "/species/", gsub(" ", "-", tolower(df$fullname), fixed = TRUE)),
+    paste0(CATALOGUE_OF_LIFE$url_CoL, "/data/search?type=EXACT&q=", gsub(" ", "%20", df$fullname, fixed = TRUE))
+  )
+
   genera <- which(df$kingdom == "Bacteria" & df$rank == "genus")
   df$url[genera] <- gsub("/species/", "/genus/", df$url[genera], fixed = TRUE)
   subsp <- which(df$kingdom == "Bacteria" & df$rank %in% c("subsp.", "infraspecies"))
   df$url[subsp] <- gsub("/species/", "/subspecies/", df$url[subsp], fixed = TRUE)
-  
+
   u <- df$url
   names(u) <- df$fullname
-  
+
   if (isTRUE(open)) {
     if (length(u) > 1) {
       warning_("in `mo_url()`: only the first URL will be opened, as `browseURL()` only suports one string.")
     }
     utils::browseURL(u[1L])
   }
-  
+
   load_mo_failures_uncertainties_renamed(metadata)
   u
 }
@@ -704,8 +714,8 @@ mo_property <- function(x, property = "fullname", language = get_AMR_locale(), .
   meet_criteria(x, allow_NA = TRUE)
   meet_criteria(property, allow_class = "character", has_length = 1, is_in = colnames(microorganisms))
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  
-  translate_AMR(mo_validate(x = x, property = property, language = language, ...), language = language, only_unknown = TRUE)
+
+  translate_into_language(mo_validate(x = x, property = property, language = language, ...), language = language, only_unknown = TRUE)
 }
 
 mo_validate <- function(x, property, language, ...) {
@@ -720,22 +730,22 @@ mo_validate <- function(x, property, language, ...) {
     Lancefield <- FALSE
   }
   has_Becker_or_Lancefield <- Becker %in% c(TRUE, "all") | Lancefield %in% c(TRUE, "all")
-  
+
   if (tryCatch(all(x[!is.na(x)] %in% MO_lookup$mo) & !has_Becker_or_Lancefield, error = function(e) FALSE)) {
     # special case for mo_* functions where class is already <mo>
     x <- MO_lookup[match(x, MO_lookup$mo), property, drop = TRUE]
-
   } else {
     # try to catch an error when inputting an invalid argument
     # so the 'call.' can be set to FALSE
     tryCatch(x[1L] %in% MO_lookup[1, property, drop = TRUE],
-             error = function(e) stop(e$message, call. = FALSE))
-    
+      error = function(e) stop(e$message, call. = FALSE)
+    )
+
     if (!all(x[!is.na(x)] %in% MO_lookup[, property, drop = TRUE]) | has_Becker_or_Lancefield) {
       x <- exec_as.mo(x, property = property, language = language, ...)
     }
   }
-  
+
   if (property == "mo") {
     return(set_clean_class(x, new_class = c("mo", "character")))
   } else if (property == "species_id") {
@@ -752,9 +762,12 @@ find_mo_col <- function(fn) {
   # which is useful when functions are used within dplyr verbs
   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)
+  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, "()`")

R/mo_source.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -28,48 +28,47 @@
 #' @description These functions can be used to predefine your own reference to be used in [as.mo()] and consequently all [`mo_*`][mo_property()] functions (such as [mo_genus()] and [mo_gramstain()]).
 #'
 #' This is **the fastest way** to have your organisation (or analysis) specific codes picked up and translated by this package, since you don't have to bother about it again after setting it up once.
-#' @inheritSection lifecycle Stable Lifecycle
-#' @param path location of your reference file, see *Details*. Can be `""`, `NULL` or `FALSE` to delete the reference file.
+#' @param path location of your reference file, this can be any text file (comma-, tab- or pipe-separated) or an Excel file (see *Details*). Can also be `""`, `NULL` or `FALSE` to delete the reference file.
 #' @param destination destination of the compressed data file, default to the user's home directory.
 #' @rdname mo_source
 #' @name mo_source
 #' @aliases set_mo_source get_mo_source
 #' @details The reference file can be a text file separated with commas (CSV) or tabs or pipes, an Excel file (either 'xls' or 'xlsx' format) or an \R object file (extension '.rds'). To use an Excel file, you will need to have the `readxl` package installed.
 #'
-#' [set_mo_source()] will check the file for validity: it must be a [data.frame], must have a column named `"mo"` which contains values from [`microorganisms$mo`][microorganisms] and must have a reference column with your own defined values. If all tests pass, [set_mo_source()] will read the file into \R and will ask to export it to `"~/mo_source.rds"`. The CRAN policy disallows packages to write to the file system, although '*exceptions may be allowed in interactive sessions if the package obtains confirmation from the user*'. For this reason, this function only works in interactive sessions so that the user can **specifically confirm and allow** that this file will be created. The destination of this file can be set with the `destination` argument and defaults to the user's home directory. It can also be set as an \R option, using `options(AMR_mo_source = "my/location/file.rds")`.
-#' 
-#' The created compressed data file `"mo_source.rds"` will be used at default for MO determination (function [as.mo()] and consequently all `mo_*` functions like [mo_genus()] and [mo_gramstain()]). The location and timestamp of the original file will be saved as an attribute to the compressed data file. 
-#' 
+#' [set_mo_source()] will check the file for validity: it must be a [data.frame], must have a column named `"mo"` which contains values from [`microorganisms$mo`][microorganisms] or [`microorganisms$fullname`][microorganisms] and must have a reference column with your own defined values. If all tests pass, [set_mo_source()] will read the file into \R and will ask to export it to `"~/mo_source.rds"`. The CRAN policy disallows packages to write to the file system, although '*exceptions may be allowed in interactive sessions if the package obtains confirmation from the user*'. For this reason, this function only works in interactive sessions so that the user can **specifically confirm and allow** that this file will be created. The destination of this file can be set with the `destination` argument and defaults to the user's home directory. It can also be set as an \R option, using `options(AMR_mo_source = "my/location/file.rds")`.
+#'
+#' The created compressed data file `"mo_source.rds"` will be used at default for MO determination (function [as.mo()] and consequently all `mo_*` functions like [mo_genus()] and [mo_gramstain()]). The location and timestamp of the original file will be saved as an [attribute][base::attributes()] to the compressed data file.
+#'
 #' The function [get_mo_source()] will return the data set by reading `"mo_source.rds"` with [readRDS()]. If the original file has changed (by checking the location and timestamp of the original file), it will call [set_mo_source()] to update the data file automatically if used in an interactive session.
 #'
 #' Reading an Excel file (`.xlsx`) with only one row has a size of 8-9 kB. The compressed file created with [set_mo_source()] will then have a size of 0.1 kB and can be read by [get_mo_source()] in only a couple of microseconds (millionths of a second).
-#' 
+#'
 #' @section How to Setup:
-#' 
-#' Imagine this data on a sheet of an Excel file (mo codes were looked up in the [microorganisms] data set). The first column contains the organisation specific codes, the second column contains an MO code from this package:
-#' 
+#'
+#' Imagine this data on a sheet of an Excel file. The first column contains the organisation specific codes, the second column contains valid taxonomic names:
+#'
 #' ```
-#'   |         A          |       B      |
-#' --|--------------------|--------------|
-#' 1 | Organisation XYZ   | mo           |
-#' 2 | lab_mo_ecoli       | B_ESCHR_COLI |
-#' 3 | lab_mo_kpneumoniae | B_KLBSL_PNMN |
-#' 4 |                    |              |
+#'   |         A          |            B          |
+#' --|--------------------|-----------------------|
+#' 1 | Organisation XYZ   | mo                    |
+#' 2 | lab_mo_ecoli       | Escherichia coli      |
+#' 3 | lab_mo_kpneumoniae | Klebsiella pneumoniae |
+#' 4 |                    |                       |
 #' ```
 #'
 #' We save it as `"home/me/ourcodes.xlsx"`. Now we have to set it as a source:
-#' 
+#'
 #' ```
 #' set_mo_source("home/me/ourcodes.xlsx")
 #' #> NOTE: Created mo_source file '/Users/me/mo_source.rds' (0.3 kB) from
-#' #>       '/Users/me/Documents/ourcodes.xlsx' (9 kB), columns 
+#' #>       '/Users/me/Documents/ourcodes.xlsx' (9 kB), columns
 #' #>       "Organisation XYZ" and "mo"
 #' ```
 #'
 #' It has now created a file `"~/mo_source.rds"` with the contents of our Excel file. Only the first column with foreign values and the 'mo' column will be kept when creating the RDS file.
 #'
 #' And now we can use it in our functions:
-#' 
+#'
 #' ```
 #' as.mo("lab_mo_ecoli")
 #' #> Class <mo>
@@ -87,22 +86,22 @@
 #' ```
 #'
 #' If we edit the Excel file by, let's say, adding row 4 like this:
-#' 
+#'
 #' ```
-#'   |         A          |       B      |
-#' --|--------------------|--------------|
-#' 1 | Organisation XYZ   | mo           |
-#' 2 | lab_mo_ecoli       | B_ESCHR_COLI |
-#' 3 | lab_mo_kpneumoniae | B_KLBSL_PNMN |
-#' 4 | lab_Staph_aureus   | B_STPHY_AURS |
-#' 5 |                    |              |
+#'   |         A          |            B          |
+#' --|--------------------|-----------------------|
+#' 1 | Organisation XYZ   | mo                    |
+#' 2 | lab_mo_ecoli       | Escherichia coli      |
+#' 3 | lab_mo_kpneumoniae | Klebsiella pneumoniae |
+#' 4 | lab_Staph_aureus   | Staphylococcus aureus |
+#' 5 |                    |                       |
 #' ```
 #'
 #' ...any new usage of an MO function in this package will update your data file:
-#' 
+#'
 #' ```
 #' as.mo("lab_mo_ecoli")
-#' #> NOTE: Updated mo_source file '/Users/me/mo_source.rds' (0.3 kB) from 
+#' #> NOTE: Updated mo_source file '/Users/me/mo_source.rds' (0.3 kB) from
 #' #>       '/Users/me/Documents/ourcodes.xlsx' (9 kB), columns
 #' #>        "Organisation XYZ" and "mo"
 #' #> Class <mo>
@@ -113,22 +112,21 @@
 #' ```
 #'
 #' To delete the reference data file, just use `""`, `NULL` or `FALSE` as input for [set_mo_source()]:
-#' 
+#'
 #' ```
 #' set_mo_source(NULL)
 #' #> Removed mo_source file '/Users/me/mo_source.rds'
 #' ```
-#' 
+#'
 #' If the original file (in the previous case an Excel file) is moved or deleted, the `mo_source.rds` file will be removed upon the next use of [as.mo()] or any [`mo_*`][mo_property()] function.
 #' @export
-#' @inheritSection AMR Read more on Our Website!
 set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_source.rds")) {
   meet_criteria(path, allow_class = "character", has_length = 1, allow_NULL = TRUE)
   meet_criteria(destination, allow_class = "character", has_length = 1)
   stop_ifnot(destination %like% "[.]rds$", "the `destination` must be a file location with file extension .rds.")
-  
+
   mo_source_destination <- path.expand(destination)
-  
+
   stop_ifnot(interactive(), "this function can only be used in interactive mode, since it must ask for the user's permission to write a file to their home folder.")
 
   if (is.null(path) || path %in% c(FALSE, "")) {
@@ -136,70 +134,81 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s
     if (file.exists(mo_source_destination)) {
       unlink(mo_source_destination)
       message_("Removed mo_source file '", font_bold(mo_source_destination), "'",
-               add_fn = font_red,
-               as_note = FALSE)
+        add_fn = font_red,
+        as_note = FALSE
+      )
     }
     return(invisible())
   }
-  
+
   stop_ifnot(file.exists(path), "file not found: ", path)
-  
+
+  df <- NULL
   if (path %like% "[.]rds$") {
     df <- readRDS(path)
-    
   } else if (path %like% "[.]xlsx?$") {
     # is Excel file (old or new)
     stop_ifnot_installed("readxl")
     df <- readxl::read_excel(path)
-    
   } else if (path %like% "[.]tsv$") {
-    df <- utils::read.table(header = TRUE, sep = "\t", stringsAsFactors = FALSE)
-    
+    df <- utils::read.table(file = path, header = TRUE, sep = "\t", stringsAsFactors = FALSE)
+  } else if (path %like% "[.]csv$") {
+    df <- utils::read.table(file = path, header = TRUE, sep = ",", stringsAsFactors = FALSE)
   } else {
     # try comma first
     try(
-      df <- utils::read.table(header = TRUE, sep = ",", stringsAsFactors = FALSE),
-      silent = TRUE)
+      df <- utils::read.table(file = path, header = TRUE, sep = ",", stringsAsFactors = FALSE),
+      silent = TRUE
+    )
     if (!check_validity_mo_source(df, stop_on_error = FALSE)) {
       # try tab
       try(
-        df <- utils::read.table(header = TRUE, sep = "\t", stringsAsFactors = FALSE),
-        silent = TRUE)
+        df <- utils::read.table(file = path, header = TRUE, sep = "\t", stringsAsFactors = FALSE),
+        silent = TRUE
+      )
     }
     if (!check_validity_mo_source(df, stop_on_error = FALSE)) {
       # try pipe
       try(
-        df <- utils::read.table(header = TRUE, sep = "|", stringsAsFactors = FALSE),
-        silent = TRUE)
+        df <- utils::read.table(file = path, header = TRUE, sep = "|", stringsAsFactors = FALSE),
+        silent = TRUE
+      )
     }
   }
-  
+
   # check integrity
+  if (is.null(df)) {
+    stop_("the path '", path, "' could not be imported as a dataset.")
+  }
   check_validity_mo_source(df)
-  
+
   df <- subset(df, !is.na(mo))
-  
+
   # keep only first two columns, second must be mo
   if (colnames(df)[1] == "mo") {
     df <- df[, c(colnames(df)[2], "mo")]
   } else {
     df <- df[, c(colnames(df)[1], "mo")]
   }
-  
+
   df <- as.data.frame(df, stringAsFactors = FALSE)
-  df[, "mo"] <- set_clean_class(df[, "mo", drop = TRUE], c("mo", "character"))
-  
+  df[, "mo"] <- as.mo(df[, "mo", drop = TRUE])
+
   # success
   if (file.exists(mo_source_destination)) {
     action <- "Updated"
   } else {
     action <- "Created"
     # only ask when file is created, not when it is updated
-    txt <- paste0(word_wrap(paste0("This will write create the new file '", 
-                                   mo_source_destination, 
-                                   "', for which your permission is needed.")),
-                  "\n\n",
-                  word_wrap("Do you agree that this file will be created?"))
+    txt <- paste0(
+      word_wrap(paste0(
+        "This will write create the new file '",
+        mo_source_destination,
+        "', for which your permission is needed."
+      )),
+      "\n\n",
+      word_wrap("Do you agree that this file will be created?")
+    )
     showQuestion <- import_fn("showQuestion", "rstudioapi", error_on_fail = FALSE)
     if (!is.null(showQuestion)) {
       q_continue <- showQuestion("Create new file in home directory", txt)
@@ -215,11 +224,13 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s
   attr(df, "mo_source_timestamp") <- file.mtime(path)
   saveRDS(df, mo_source_destination)
   pkg_env$mo_source <- df
-  message_(action, " mo_source file '", font_bold(mo_source_destination),
-           "' (", formatted_filesize(mo_source_destination),
-           ") from '", font_bold(path),
-           "' (", formatted_filesize(path),
-           '), columns "', colnames(df)[1], '" and "', colnames(df)[2], '"')
+  message_(
+    action, " mo_source file '", font_bold(mo_source_destination),
+    "' (", formatted_filesize(mo_source_destination),
+    ") from '", font_bold(path),
+    "' (", formatted_filesize(path),
+    '), columns "', colnames(df)[1], '" and "', colnames(df)[2], '"'
+  )
 }
 
 #' @rdname mo_source
@@ -235,7 +246,7 @@ get_mo_source <- function(destination = getOption("AMR_mo_source", "~/mo_source.
   if (is.null(pkg_env$mo_source)) {
     pkg_env$mo_source <- readRDS(path.expand(destination))
   }
-  
+
   old_time <- attributes(pkg_env$mo_source)$mo_source_timestamp
   new_time <- file.mtime(attributes(pkg_env$mo_source)$mo_source_location)
   if (interactive() && !identical(old_time, new_time)) {
@@ -247,7 +258,7 @@ get_mo_source <- function(destination = getOption("AMR_mo_source", "~/mo_source.
 
 check_validity_mo_source <- function(x, refer_to_name = "`reference_df`", stop_on_error = TRUE) {
   check_dataset_integrity()
-  
+
   if (paste(deparse(substitute(x)), collapse = "") == "get_mo_source()") {
     return(TRUE)
   }
@@ -275,18 +286,19 @@ check_validity_mo_source <- function(x, refer_to_name = "`reference_df`", stop_o
       return(FALSE)
     }
   }
-  if (!all(x$mo %in% c("", microorganisms$mo), na.rm = TRUE)) {
+  if (!all(x$mo %in% c("", microorganisms$mo, microorganisms$fullname), na.rm = TRUE)) {
     if (stop_on_error == TRUE) {
-      invalid <- x[which(!x$mo %in% c("", microorganisms$mo)), , drop = FALSE]
+      invalid <- x[which(!x$mo %in% c("", microorganisms$mo, microorganisms$fullname)), , drop = FALSE]
       if (nrow(invalid) > 1) {
         plural <- "s"
       } else {
         plural <- ""
       }
-      stop_("Value", plural, " ", vector_and(invalid[, 1, drop = TRUE], quotes = TRUE), 
-           " found in ", tolower(refer_to_name), 
-           ", but with invalid microorganism code", plural, " ", vector_and(invalid$mo, quotes = TRUE),
-           call = FALSE)
+      stop_("Value", plural, " ", vector_and(invalid[, 1, drop = TRUE], quotes = TRUE),
+        " found in ", tolower(refer_to_name),
+        ", but with invalid microorganism code", plural, " ", vector_and(invalid$mo, quotes = TRUE),
+        call = FALSE
+      )
     } else {
       return(FALSE)
     }

R/pca.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -24,45 +24,55 @@
 # ==================================================================== #
 
 #' Principal Component Analysis (for AMR)
-#' 
+#'
 #' Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x a [data.frame] containing [numeric] columns
 #' @param ... columns of `x` to be selected for PCA, can be unquoted since it supports quasiquotation.
 #' @inheritParams stats::prcomp
 #' @details The [pca()] function takes a [data.frame] as input and performs the actual PCA with the \R function [prcomp()].
-#' 
+#'
 #' The result of the [pca()] function is a [prcomp] object, with an additional attribute `non_numeric_cols` which is a vector with the column names of all columns that do not contain [numeric] values. These are probably the groups and labels, and will be used by [ggplot_pca()].
 #' @return An object of classes [pca] and [prcomp]
 #' @importFrom stats prcomp
 #' @export
-#' @inheritSection AMR Read more on Our Website!
-#' @examples 
+#' @examples
 #' # `example_isolates` is a data set available in the AMR package.
 #' # See ?example_isolates.
 #'
 #' \donttest{
 #' if (require("dplyr")) {
-#'   # calculate the resistance per group first 
-#'   resistance_data <- example_isolates %>% 
-#'     group_by(order = mo_order(mo),       # group on anything, like order
-#'              genus = mo_genus(mo)) %>%   #   and genus as we do here;
-#'     summarise_if(is.rsi, resistance)     # then get resistance of all drugs
-#'     
+#'   # calculate the resistance per group first
+#'   resistance_data <- example_isolates %>%
+#'     group_by(
+#'       order = mo_order(mo), # group on anything, like order
+#'       genus = mo_genus(mo)
+#'     ) %>% #   and genus as we do here;
+#'     filter(n() >= 30) %>% # filter on only 30 results per group
+#'     summarise_if(is.rsi, resistance) # then get resistance of all drugs
+#'
 #'   # now conduct PCA for certain antimicrobial agents
-#'   pca_result <- resistance_data %>%         
-#'     pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT) 
-#'     
+#'   pca_result <- resistance_data %>%
+#'     pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)
+#'
 #'   pca_result
 #'   summary(pca_result)
+#'
+#'   # old base R plotting method:
 #'   biplot(pca_result)
-#'   ggplot_pca(pca_result) # a new and convenient plot function
+#'   # new ggplot2 plotting method using this package:
+#'   ggplot_pca(pca_result)
+#'
+#'   if (require("ggplot2")) {
+#'     ggplot_pca(pca_result) +
+#'       scale_colour_viridis_d() +
+#'       labs(title = "Title here")
+#'   }
 #' }
 #' }
 pca <- function(x,
                 ...,
                 retx = TRUE,
-                center = TRUE, 
+                center = TRUE,
                 scale. = TRUE,
                 tol = NULL,
                 rank. = NULL) {
@@ -72,19 +82,20 @@ pca <- function(x,
   meet_criteria(scale., allow_class = "logical", has_length = 1)
   meet_criteria(tol, allow_class = "numeric", has_length = 1, allow_NULL = TRUE)
   meet_criteria(rank., allow_class = "numeric", has_length = 1, allow_NULL = TRUE)
-  
+
   # unset data.table, tibble, etc.
   # also removes groups made by dplyr::group_by
   x <- as.data.frame(x, stringsAsFactors = FALSE)
   x.bak <- x
-  
+
   # defuse R expressions, this replaces rlang::enquos()
   dots <- substitute(list(...))
   if (length(dots) > 1) {
     new_list <- list(0)
     for (i in seq_len(length(dots) - 1)) {
       new_list[[i]] <- tryCatch(eval(dots[[i + 1]], envir = x),
-                                error = function(e) stop(e$message, call. = FALSE))
+        error = function(e) stop(e$message, call. = FALSE)
+      )
       if (length(new_list[[i]]) == 1) {
         if (is.character(new_list[[i]]) & new_list[[i]] %in% colnames(x)) {
           # this is to support quoted variables: df %pm>% pca("mycol1", "mycol2")
@@ -95,30 +106,33 @@ pca <- function(x,
         }
       }
     }
-    
+
     x <- as.data.frame(new_list, stringsAsFactors = FALSE)
     if (any(vapply(FUN.VALUE = logical(1), x, function(y) !is.numeric(y)))) {
       warning_("in `pca()`: be sure to first calculate the resistance (or susceptibility) of variables with antimicrobial test results, since PCA works with numeric variables only. See Examples in ?pca.", call = FALSE)
     }
-    
+
     # set column names
     tryCatch(colnames(x) <- as.character(dots)[2:length(dots)],
-             error = function(e) warning("column names could not be set"))
-    
+      error = function(e) warning("column names could not be set")
+    )
+
     # keep only numeric columns
-    x <- x[, vapply(FUN.VALUE = logical(1), x, function(y) is.numeric(y))]
+    x <- x[, vapply(FUN.VALUE = logical(1), x, function(y) is.numeric(y)), drop = FALSE]
     # bind the data set with the non-numeric columns
     x <- cbind(x.bak[, vapply(FUN.VALUE = logical(1), x.bak, function(y) !is.numeric(y) & !all(is.na(y))), drop = FALSE], x)
   }
-  
-  x <- pm_ungroup(x)  # would otherwise select the grouping vars
+
+  x <- pm_ungroup(x) # would otherwise select the grouping vars
   x <- x[rowSums(is.na(x)) == 0, ] # remove columns containing NAs
-  
-  pca_data <- x[, which(vapply(FUN.VALUE = logical(1), x, function(x) is.numeric(x)))]
-  
-  message_("Columns selected for PCA: ", vector_and(font_bold(colnames(pca_data), collapse = NULL), quotes = TRUE),
-           ". Total observations available: ", nrow(pca_data), ".")
-  
+
+  pca_data <- x[, which(vapply(FUN.VALUE = logical(1), x, function(x) is.numeric(x))), drop = FALSE]
+
+  message_(
+    "Columns selected for PCA: ", vector_and(font_bold(colnames(pca_data), collapse = NULL), quotes = TRUE),
+    ". Total observations available: ", nrow(pca_data), "."
+  )
+
   if (getRversion() < "3.4.0") {
     # stats::prcomp prior to 3.4.0 does not have the 'rank.' argument
     pca_model <- prcomp(pca_data, retx = retx, center = center, scale. = scale., tol = tol)

R/plot.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -24,10 +24,9 @@
 # ==================================================================== #
 
 #' Plotting for Classes `rsi`, `mic` and `disk`
-#' 
+#'
 #' 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,object values created with [as.mic()], [as.disk()] or [as.rsi()] (or their `random_*` variants, such as [random_mic()])
 #' @param mo any (vector of) text that can be coerced to a valid microorganism code with [as.mo()]
 #' @param ab any (vector of) text that can be coerced to a valid antimicrobial code with [as.ab()]
@@ -39,33 +38,38 @@
 #' @param expand a [logical] to indicate whether the range on the x axis should be expanded between the lowest and highest value. For MIC values, intermediate values will be factors of 2 starting from the highest MIC value. For disk diameters, the whole diameter range will be filled.
 #' @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.
-#' 
+#'
 #' For interpreting MIC values as well as disk diffusion diameters, supported guidelines to be used as input for the `guideline` argument are: `r vector_and(AMR::rsi_translation$guideline, quotes = TRUE, reverse = TRUE)`.
-#' 
+#'
 #' Simply using `"CLSI"` or `"EUCAST"` as input will automatically select the latest version of that guideline.
 #' @name plot
 #' @rdname plot
 #' @return The `autoplot()` functions return a [`ggplot`][ggplot2::ggplot()] model that is extendible with any `ggplot2` function.
-#' 
+#'
 #' The `fortify()` functions return a [data.frame] as an extension for usage in the [ggplot2::ggplot()] function.
 #' @param ... arguments passed on to methods
-#' @examples 
+#' @examples
 #' some_mic_values <- random_mic(size = 100)
 #' some_disk_values <- random_disk(size = 100, mo = "Escherichia coli", ab = "cipro")
 #' some_rsi_values <- random_rsi(50, prob_RSI = c(0.30, 0.55, 0.05))
-#' 
+#'
 #' plot(some_mic_values)
 #' plot(some_disk_values)
 #' plot(some_rsi_values)
-#' 
+#'
 #' # when providing the microorganism and antibiotic, colours will show interpretations:
 #' plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
 #' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
-#' 
+#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "uk")
+#'
 #' \donttest{
 #' if (require("ggplot2")) {
 #'   autoplot(some_mic_values)
+#' }
+#' if (require("ggplot2")) {
 #'   autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
+#' }
+#' if (require("ggplot2")) {
 #'   autoplot(some_rsi_values)
 #' }
 #' }
@@ -79,7 +83,7 @@ plot.mic <- function(x,
                      mo = NULL,
                      ab = NULL,
                      guideline = "EUCAST",
-                     main = paste("MIC values of", deparse(substitute(x))),
+                     main = deparse(substitute(x)),
                      ylab = "Frequency",
                      xlab = "Minimum Inhibitory Concentration (mg/L)",
                      colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
@@ -95,42 +99,45 @@ plot.mic <- function(x,
   meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
-  
+
   # translate if not specifically set
   if (missing(ylab)) {
-    ylab <- translate_AMR(ylab, language = language)
+    ylab <- translate_into_language(ylab, language = language)
   }
   if (missing(xlab)) {
-    xlab <- translate_AMR(xlab, language = language)
+    xlab <- translate_into_language(xlab, language = language)
   }
-  
+
   if (length(colours_RSI) == 1) {
     colours_RSI <- rep(colours_RSI, 3)
   }
   main <- gsub(" +", " ", paste0(main, collapse = " "))
-  
+
   x <- plot_prepare_table(x, expand = expand)
-  
-  cols_sub <- plot_colours_subtitle_guideline(x = x, 
-                                              mo = mo, 
-                                              ab = ab,
-                                              guideline = guideline,
-                                              colours_RSI = colours_RSI, 
-                                              fn = as.mic,
-                                              language = language,
-                                              ...)
+
+  cols_sub <- plot_colours_subtitle_guideline(
+    x = x,
+    mo = mo,
+    ab = ab,
+    guideline = guideline,
+    colours_RSI = colours_RSI,
+    fn = as.mic,
+    language = language,
+    ...
+  )
   barplot(x,
-          col = cols_sub$cols,
-          main = main,
-          ylim = c(0, max(x) * ifelse(any(colours_RSI %in% cols_sub$cols), 1.1, 1)),
-          ylab = ylab,
-          xlab = xlab,
-          axes = FALSE)
+    col = cols_sub$cols,
+    main = main,
+    ylim = c(0, max(x) * ifelse(any(colours_RSI %in% cols_sub$cols), 1.1, 1)),
+    ylab = ylab,
+    xlab = xlab,
+    axes = FALSE
+  )
   axis(2, seq(0, max(x)))
   if (!is.null(cols_sub$sub)) {
     mtext(side = 3, line = 0.5, adj = 0.5, cex = 0.75, cols_sub$sub)
   }
-  
+
   if (any(colours_RSI %in% cols_sub$cols)) {
     legend_txt <- character(0)
     legend_col <- character(0)
@@ -146,16 +153,17 @@ plot.mic <- function(x,
       legend_txt <- c(legend_txt, "Resistant")
       legend_col <- c(legend_col, colours_RSI[1])
     }
-    
+
     legend("top",
-           x.intersp = 0.5,
-           legend = translate_AMR(legend_txt, language = language),
-           fill = legend_col,
-           horiz = TRUE,
-           cex = 0.75,
-           box.lwd = 0,
-           box.col = "#FFFFFF55",
-           bg = "#FFFFFF55")
+      x.intersp = 0.5,
+      legend = translate_into_language(legend_txt, language = language),
+      fill = legend_col,
+      horiz = TRUE,
+      cex = 0.75,
+      box.lwd = 0,
+      box.col = "#FFFFFF55",
+      bg = "#FFFFFF55"
+    )
   }
 }
 
@@ -166,7 +174,7 @@ barplot.mic <- function(height,
                         mo = NULL,
                         ab = NULL,
                         guideline = "EUCAST",
-                        main = paste("MIC values of", deparse(substitute(height))),
+                        main = deparse(substitute(height)),
                         ylab = "Frequency",
                         xlab = "Minimum Inhibitory Concentration (mg/L)",
                         colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
@@ -182,26 +190,28 @@ barplot.mic <- function(height,
   meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
-  
+
   # translate if not specifically set
   if (missing(ylab)) {
-    ylab <- translate_AMR(ylab, language = language)
+    ylab <- translate_into_language(ylab, language = language)
   }
   if (missing(xlab)) {
-    xlab <- translate_AMR(xlab, language = language)
+    xlab <- translate_into_language(xlab, language = language)
   }
-  
+
   main <- gsub(" +", " ", paste0(main, collapse = " "))
-  
-  plot(x = height,
-       main = main,
-       ylab = ylab,
-       xlab = xlab,
-       mo = mo,
-       ab = ab,
-       guideline = guideline,
-       colours_RSI = colours_RSI,
-       ...)
+
+  plot(
+    x = height,
+    main = main,
+    ylab = ylab,
+    xlab = xlab,
+    mo = mo,
+    ab = ab,
+    guideline = guideline,
+    colours_RSI = colours_RSI,
+    ...
+  )
 }
 
 #' @method autoplot mic
@@ -211,7 +221,7 @@ autoplot.mic <- function(object,
                          mo = NULL,
                          ab = NULL,
                          guideline = "EUCAST",
-                         title = paste("MIC values of", deparse(substitute(object))),
+                         title = deparse(substitute(object)),
                          ylab = "Frequency",
                          xlab = "Minimum Inhibitory Concentration (mg/L)",
                          colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
@@ -228,60 +238,68 @@ autoplot.mic <- function(object,
   meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
-  
+
   # translate if not specifically set
   if (missing(ylab)) {
-    ylab <- translate_AMR(ylab, language = language)
+    ylab <- translate_into_language(ylab, language = language)
   }
   if (missing(xlab)) {
-    xlab <- translate_AMR(xlab, language = language)
+    xlab <- translate_into_language(xlab, language = language)
   }
-  
+
   if ("main" %in% names(list(...))) {
     title <- list(...)$main
   }
   if (!is.null(title)) {
     title <- gsub(" +", " ", paste0(title, collapse = " "))
   }
-  
+
   x <- plot_prepare_table(object, expand = expand)
-  cols_sub <- plot_colours_subtitle_guideline(x = x, 
-                                              mo = mo, 
-                                              ab = ab,
-                                              guideline = guideline,
-                                              colours_RSI = colours_RSI, 
-                                              fn = as.mic,
-                                              language = language,
-                                              ...)
+  cols_sub <- plot_colours_subtitle_guideline(
+    x = x,
+    mo = mo,
+    ab = ab,
+    guideline = guideline,
+    colours_RSI = colours_RSI,
+    fn = as.mic,
+    language = language,
+    ...
+  )
   df <- as.data.frame(x, stringsAsFactors = TRUE)
   colnames(df) <- c("mic", "count")
   df$cols <- cols_sub$cols
   df$cols[df$cols == colours_RSI[1]] <- "Resistant"
   df$cols[df$cols == colours_RSI[2]] <- "Susceptible"
   df$cols[df$cols == colours_RSI[3]] <- plot_name_of_I(cols_sub$guideline)
-  df$cols <- factor(translate_AMR(df$cols, language = language),
-                    levels = translate_AMR(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
-                                           language = language),
-                    ordered = TRUE)
+  df$cols <- factor(translate_into_language(df$cols, language = language),
+    levels = translate_into_language(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
+      language = language
+    ),
+    ordered = TRUE
+  )
   p <- ggplot2::ggplot(df)
-  
+
   if (any(colours_RSI %in% cols_sub$cols)) {
-    vals <- c("Resistant" = colours_RSI[1],
-              "Susceptible" = colours_RSI[2],
-              "Susceptible, incr. exp." = colours_RSI[3],
-              "Intermediate" = colours_RSI[3])
-    names(vals) <- translate_AMR(names(vals), language = language)
+    vals <- c(
+      "Resistant" = colours_RSI[1],
+      "Susceptible" = colours_RSI[2],
+      "Susceptible, incr. exp." = colours_RSI[3],
+      "Intermediate" = colours_RSI[3]
+    )
+    names(vals) <- translate_into_language(names(vals), language = language)
     p <- p +
-      ggplot2::geom_col(ggplot2::aes(x = mic, y = count, fill = cols)) + 
+      ggplot2::geom_col(ggplot2::aes(x = mic, y = count, fill = cols)) +
       # limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
-      ggplot2::scale_fill_manual(values = vals,
-                                 name = NULL,
-                                 limits = force)
+      ggplot2::scale_fill_manual(
+        values = vals,
+        name = NULL,
+        limits = force
+      )
   } else {
     p <- p +
       ggplot2::geom_col(ggplot2::aes(x = mic, y = count))
   }
-  
+
   p +
     ggplot2::labs(title = title, x = xlab, y = ylab, subtitle = cols_sub$sub)
 }
@@ -290,8 +308,10 @@ autoplot.mic <- function(object,
 #' @rdname plot
 # will be exported using s3_register() in R/zzz.R
 fortify.mic <- function(object, ...) {
-  stats::setNames(as.data.frame(plot_prepare_table(object, expand = FALSE)),
-                  c("x", "y"))
+  stats::setNames(
+    as.data.frame(plot_prepare_table(object, expand = FALSE)),
+    c("x", "y")
+  )
 }
 
 #' @method plot disk
@@ -299,7 +319,7 @@ fortify.mic <- function(object, ...) {
 #' @importFrom graphics barplot axis mtext legend
 #' @rdname plot
 plot.disk <- function(x,
-                      main = paste("Disk zones of", deparse(substitute(x))),
+                      main = deparse(substitute(x)),
                       ylab = "Frequency",
                       xlab = "Disk diffusion diameter (mm)",
                       mo = NULL,
@@ -318,43 +338,46 @@ plot.disk <- function(x,
   meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
-  
+
   # translate if not specifically set
   if (missing(ylab)) {
-    ylab <- translate_AMR(ylab, language = language)
+    ylab <- translate_into_language(ylab, language = language)
   }
   if (missing(xlab)) {
-    xlab <- translate_AMR(xlab, language = language)
+    xlab <- translate_into_language(xlab, language = language)
   }
-  
+
   if (length(colours_RSI) == 1) {
     colours_RSI <- rep(colours_RSI, 3)
   }
   main <- gsub(" +", " ", paste0(main, collapse = " "))
-  
+
   x <- plot_prepare_table(x, expand = expand)
-  
-  cols_sub <- plot_colours_subtitle_guideline(x = x, 
-                                              mo = mo, 
-                                              ab = ab,
-                                              guideline = guideline,
-                                              colours_RSI = colours_RSI, 
-                                              fn = as.disk,
-                                              language = language,
-                                              ...)
-  
+
+  cols_sub <- plot_colours_subtitle_guideline(
+    x = x,
+    mo = mo,
+    ab = ab,
+    guideline = guideline,
+    colours_RSI = colours_RSI,
+    fn = as.disk,
+    language = language,
+    ...
+  )
+
   barplot(x,
-          col = cols_sub$cols,
-          main = main,
-          ylim = c(0, max(x) * ifelse(any(colours_RSI %in% cols_sub$cols), 1.1, 1)),
-          ylab = ylab,
-          xlab = xlab,
-          axes = FALSE)
+    col = cols_sub$cols,
+    main = main,
+    ylim = c(0, max(x) * ifelse(any(colours_RSI %in% cols_sub$cols), 1.1, 1)),
+    ylab = ylab,
+    xlab = xlab,
+    axes = FALSE
+  )
   axis(2, seq(0, max(x)))
   if (!is.null(cols_sub$sub)) {
     mtext(side = 3, line = 0.5, adj = 0.5, cex = 0.75, cols_sub$sub)
   }
-  
+
   if (any(colours_RSI %in% cols_sub$cols)) {
     legend_txt <- character(0)
     legend_col <- character(0)
@@ -370,15 +393,16 @@ plot.disk <- function(x,
       legend_txt <- c(legend_txt, "Susceptible")
       legend_col <- c(legend_col, colours_RSI[2])
     }
-    legend("top", 
-           x.intersp = 0.5,
-           legend = translate_AMR(legend_txt, language = language),
-           fill = legend_col,
-           horiz = TRUE,
-           cex = 0.75,
-           box.lwd = 0,
-           box.col = "#FFFFFF55",
-           bg = "#FFFFFF55")
+    legend("top",
+      x.intersp = 0.5,
+      legend = translate_into_language(legend_txt, language = language),
+      fill = legend_col,
+      horiz = TRUE,
+      cex = 0.75,
+      box.lwd = 0,
+      box.col = "#FFFFFF55",
+      bg = "#FFFFFF55"
+    )
   }
 }
 
@@ -386,7 +410,7 @@ plot.disk <- function(x,
 #' @export
 #' @noRd
 barplot.disk <- function(height,
-                         main = paste("Disk zones of", deparse(substitute(height))),
+                         main = deparse(substitute(height)),
                          ylab = "Frequency",
                          xlab = "Disk diffusion diameter (mm)",
                          mo = NULL,
@@ -405,26 +429,28 @@ barplot.disk <- function(height,
   meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
-  
+
   # translate if not specifically set
   if (missing(ylab)) {
-    ylab <- translate_AMR(ylab, language = language)
+    ylab <- translate_into_language(ylab, language = language)
   }
   if (missing(xlab)) {
-    xlab <- translate_AMR(xlab, language = language)
+    xlab <- translate_into_language(xlab, language = language)
   }
-  
+
   main <- gsub(" +", " ", paste0(main, collapse = " "))
-  
-  plot(x = height,
-       main = main,
-       ylab = ylab,
-       xlab = xlab,
-       mo = mo,
-       ab = ab,
-       guideline = guideline,
-       colours_RSI = colours_RSI,
-       ...)
+
+  plot(
+    x = height,
+    main = main,
+    ylab = ylab,
+    xlab = xlab,
+    mo = mo,
+    ab = ab,
+    guideline = guideline,
+    colours_RSI = colours_RSI,
+    ...
+  )
 }
 
 #' @method autoplot disk
@@ -433,7 +459,7 @@ barplot.disk <- function(height,
 autoplot.disk <- function(object,
                           mo = NULL,
                           ab = NULL,
-                          title = paste("Disk zones of", deparse(substitute(object))),
+                          title = deparse(substitute(object)),
                           ylab = "Frequency",
                           xlab = "Disk diffusion diameter (mm)",
                           guideline = "EUCAST",
@@ -451,61 +477,69 @@ autoplot.disk <- function(object,
   meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
-  
+
   # translate if not specifically set
   if (missing(ylab)) {
-    ylab <- translate_AMR(ylab, language = language)
+    ylab <- translate_into_language(ylab, language = language)
   }
   if (missing(xlab)) {
-    xlab <- translate_AMR(xlab, language = language)
+    xlab <- translate_into_language(xlab, language = language)
   }
-  
+
   if ("main" %in% names(list(...))) {
     title <- list(...)$main
   }
   if (!is.null(title)) {
     title <- gsub(" +", " ", paste0(title, collapse = " "))
   }
-  
+
   x <- plot_prepare_table(object, expand = expand)
-  cols_sub <- plot_colours_subtitle_guideline(x = x,
-                                              mo = mo,
-                                              ab = ab,
-                                              guideline = guideline,
-                                              colours_RSI = colours_RSI,
-                                              fn = as.disk,
-                                              language = language,
-                                              ...)
+  cols_sub <- plot_colours_subtitle_guideline(
+    x = x,
+    mo = mo,
+    ab = ab,
+    guideline = guideline,
+    colours_RSI = colours_RSI,
+    fn = as.disk,
+    language = language,
+    ...
+  )
   df <- as.data.frame(x, stringsAsFactors = TRUE)
   colnames(df) <- c("disk", "count")
   df$cols <- cols_sub$cols
-  
+
   df$cols[df$cols == colours_RSI[1]] <- "Resistant"
   df$cols[df$cols == colours_RSI[2]] <- "Susceptible"
   df$cols[df$cols == colours_RSI[3]] <- plot_name_of_I(cols_sub$guideline)
-  df$cols <- factor(translate_AMR(df$cols, language = language),
-                    levels = translate_AMR(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
-                                           language = language),
-                    ordered = TRUE)
+  df$cols <- factor(translate_into_language(df$cols, language = language),
+    levels = translate_into_language(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
+      language = language
+    ),
+    ordered = TRUE
+  )
   p <- ggplot2::ggplot(df)
-  
+
   if (any(colours_RSI %in% cols_sub$cols)) {
-    vals <- c("Resistant" = colours_RSI[1],
-              "Susceptible" = colours_RSI[2],
-              "Susceptible, incr. exp." = colours_RSI[3],
-              "Intermediate" = colours_RSI[3])
-    names(vals) <- translate_AMR(names(vals), language = language)
+    vals <- c(
+      "Resistant" = colours_RSI[1],
+      "Susceptible" = colours_RSI[2],
+      "Susceptible, incr. exp." = colours_RSI[3],
+      "Intermediate" = colours_RSI[3]
+    )
+    names(vals) <- translate_into_language(names(vals), language = language)
     p <- p +
-      ggplot2::geom_col(ggplot2::aes(x = disk, y = count, fill = cols)) + 
+      ggplot2::geom_col(ggplot2::aes(x = disk, y = count, fill = cols)) +
       # limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
-      ggplot2::scale_fill_manual(values = vals,
-                                 name = NULL,
-                                 limits = force)
+      ggplot2::scale_fill_manual(
+        values = vals,
+        name = NULL,
+        limits = force
+      )
   } else {
     p <- p +
       ggplot2::geom_col(ggplot2::aes(x = disk, y = count))
   }
-  
+
   p +
     ggplot2::labs(title = title, x = xlab, y = ylab, subtitle = cols_sub$sub)
 }
@@ -514,8 +548,10 @@ autoplot.disk <- function(object,
 #' @rdname plot
 # will be exported using s3_register() in R/zzz.R
 fortify.disk <- function(object, ...) {
-  stats::setNames(as.data.frame(plot_prepare_table(object, expand = FALSE)),
-                  c("x", "y"))
+  stats::setNames(
+    as.data.frame(plot_prepare_table(object, expand = FALSE)),
+    c("x", "y")
+  )
 }
 
 #' @method plot rsi
@@ -525,49 +561,65 @@ fortify.disk <- function(object, ...) {
 plot.rsi <- function(x,
                      ylab = "Percentage",
                      xlab = "Antimicrobial Interpretation",
-                     main = paste("Resistance Overview of", deparse(substitute(x))),
+                     main = deparse(substitute(x)),
+                     language = get_AMR_locale(),
                      ...) {
   meet_criteria(ylab, allow_class = "character", has_length = 1)
   meet_criteria(xlab, allow_class = "character", has_length = 1)
   meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
-  
+
+  # translate if not specifically set
+  if (missing(ylab)) {
+    ylab <- translate_into_language(ylab, language = language)
+  }
+  if (missing(xlab)) {
+    xlab <- translate_into_language(xlab, language = language)
+  }
+
   data <- as.data.frame(table(x), stringsAsFactors = FALSE)
   colnames(data) <- c("x", "n")
   data$s <- round((data$n / sum(data$n)) * 100, 1)
-  
+
   if (!"S" %in% data$x) {
     data <- rbind(data, data.frame(x = "S", n = 0, s = 0, stringsAsFactors = FALSE),
-                  stringsAsFactors = FALSE)
+      stringsAsFactors = FALSE
+    )
   }
   if (!"I" %in% data$x) {
     data <- rbind(data, data.frame(x = "I", n = 0, s = 0, stringsAsFactors = FALSE),
-                  stringsAsFactors = FALSE)
+      stringsAsFactors = FALSE
+    )
   }
   if (!"R" %in% data$x) {
     data <- rbind(data, data.frame(x = "R", n = 0, s = 0, stringsAsFactors = FALSE),
-                  stringsAsFactors = FALSE)
+      stringsAsFactors = FALSE
+    )
   }
-  
+
   data$x <- factor(data$x, levels = c("S", "I", "R"), ordered = TRUE)
-  
+
   ymax <- pm_if_else(max(data$s) > 95, 105, 100)
-  
-  plot(x = data$x,
-       y = data$s,
-       lwd = 2,
-       ylim = c(0, ymax),
-       ylab = ylab,
-       xlab = xlab,
-       main = main,
-       axes = FALSE)
+
+  plot(
+    x = data$x,
+    y = data$s,
+    lwd = 2,
+    ylim = c(0, ymax),
+    ylab = ylab,
+    xlab = xlab,
+    main = main,
+    axes = FALSE
+  )
   # x axis
   axis(side = 1, at = 1:pm_n_distinct(data$x), labels = levels(data$x), lwd = 0)
   # y axis, 0-100%
   axis(side = 2, at = seq(0, 100, 5))
-  
-  text(x = data$x,
-       y = data$s + 4,
-       labels = paste0(data$s, "% (n = ", data$n, ")"))
+
+  text(
+    x = data$x,
+    y = data$s + 4,
+    labels = paste0(data$s, "% (n = ", data$n, ")")
+  )
 }
 
 
@@ -576,7 +628,7 @@ plot.rsi <- function(x,
 #' @export
 #' @noRd
 barplot.rsi <- function(height,
-                        main = paste("Resistance Overview of", deparse(substitute(height))),
+                        main = deparse(substitute(height)),
                         xlab = "Antimicrobial Interpretation",
                         ylab = "Frequency",
                         colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
@@ -589,30 +641,31 @@ barplot.rsi <- function(height,
   meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
   meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
   meet_criteria(expand, allow_class = "logical", has_length = 1)
-  
+
   # translate if not specifically set
   if (missing(ylab)) {
-    ylab <- translate_AMR(ylab, language = language)
+    ylab <- translate_into_language(ylab, language = language)
   }
   if (missing(xlab)) {
-    xlab <- translate_AMR(xlab, language = language)
+    xlab <- translate_into_language(xlab, language = language)
   }
-  
+
   if (length(colours_RSI) == 1) {
     colours_RSI <- rep(colours_RSI, 3)
   } else {
     colours_RSI <- c(colours_RSI[2], colours_RSI[3], colours_RSI[1])
   }
   main <- gsub(" +", " ", paste0(main, collapse = " "))
-  
+
   x <- table(height)
   x <- x[c(1, 2, 3)]
   barplot(x,
-          col = colours_RSI,
-          xlab = xlab,
-          main = main,
-          ylab = ylab,
-          axes = FALSE)
+    col = colours_RSI,
+    xlab = xlab,
+    main = main,
+    ylab = ylab,
+    axes = FALSE
+  )
   axis(2, seq(0, max(x)))
 }
 
@@ -620,7 +673,7 @@ barplot.rsi <- function(height,
 #' @rdname plot
 # will be exported using s3_register() in R/zzz.R
 autoplot.rsi <- function(object,
-                         title = paste("Resistance Overview of", deparse(substitute(object))),
+                         title = deparse(substitute(object)),
                          xlab = "Antimicrobial Interpretation",
                          ylab = "Frequency",
                          colours_RSI = c("#ED553B", "#3CAEA3", "#F6D55C"),
@@ -631,35 +684,39 @@ autoplot.rsi <- function(object,
   meet_criteria(ylab, allow_class = "character", has_length = 1)
   meet_criteria(xlab, allow_class = "character", has_length = 1)
   meet_criteria(colours_RSI, allow_class = "character", has_length = c(1, 3))
-  
+
   # translate if not specifically set
   if (missing(ylab)) {
-    ylab <- translate_AMR(ylab, language = language)
+    ylab <- translate_into_language(ylab, language = language)
   }
   if (missing(xlab)) {
-    xlab <- translate_AMR(xlab, language = language)
+    xlab <- translate_into_language(xlab, language = language)
   }
-  
+
   if ("main" %in% names(list(...))) {
     title <- list(...)$main
   }
   if (!is.null(title)) {
     title <- gsub(" +", " ", paste0(title, collapse = " "))
   }
-  
+
   if (length(colours_RSI) == 1) {
     colours_RSI <- rep(colours_RSI, 3)
   }
-  
+
   df <- as.data.frame(table(object), stringsAsFactors = TRUE)
   colnames(df) <- c("rsi", "count")
   ggplot2::ggplot(df) +
-    ggplot2::geom_col(ggplot2::aes(x = rsi, y = count, fill = rsi)) + 
+    ggplot2::geom_col(ggplot2::aes(x = rsi, y = count, fill = rsi)) +
     # limits = force is needed because of a ggplot2 >= 3.3.4 bug (#4511)
-    ggplot2::scale_fill_manual(values = c("R" = colours_RSI[1],
-                                          "S" = colours_RSI[2],
-                                          "I" = colours_RSI[3]),
-                               limits = force) +
+    ggplot2::scale_fill_manual(
+      values = c(
+        "R" = colours_RSI[1],
+        "S" = colours_RSI[2],
+        "I" = colours_RSI[3]
+      ),
+      limits = force
+    ) +
     ggplot2::labs(title = title, x = xlab, y = ylab) +
     ggplot2::theme(legend.position = "none")
 }
@@ -668,8 +725,10 @@ autoplot.rsi <- function(object,
 #' @rdname plot
 # will be exported using s3_register() in R/zzz.R
 fortify.rsi <- function(object, ...) {
-  stats::setNames(as.data.frame(table(object)),
-                  c("x", "y"))
+  stats::setNames(
+    as.data.frame(table(object)),
+    c("x", "y")
+  )
 }
 
 plot_prepare_table <- function(x, expand) {
@@ -734,13 +793,19 @@ plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_RSI, f
     moname <- mo_name(mo, language = language)
     abname <- ab_name(ab, language = language)
     if (all(cols == "#BEBEBE")) {
-      message_("No ", guideline, " interpretations found for ", 
-               ab_name(ab, language = NULL, tolower = TRUE), " in ", moname)
+      message_(
+        "No ", guideline, " interpretations found for ",
+        ab_name(ab, language = NULL, tolower = TRUE), " in ", moname
+      )
       guideline_txt <- ""
     } else {
-      guideline_txt <- paste0("(", guideline, ")")
+      guideline_txt <- guideline
+      if (isTRUE(list(...)$uti)) {
+        guideline_txt <- paste("UTIs,", guideline_txt)
+      }
+      guideline_txt <- paste0("(", guideline_txt, ")")
     }
-    sub <- bquote(.(abname)~"-"~italic(.(moname))~.(guideline_txt))
+    sub <- bquote(.(abname) ~ "-" ~ italic(.(moname)) ~ .(guideline_txt))
   } else {
     cols <- "#BEBEBE"
     sub <- NULL

R/proportion.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -28,7 +28,6 @@
 #' @description These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, see *Examples*.
 #'
 #' [resistance()] should be used to calculate resistance, [susceptibility()] should be used to calculate susceptibility.\cr
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with [as.rsi()] if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See *Examples*.
 #' @param minimum the minimum allowed number of available (tested) isolates. Any isolate count lower than `minimum` will return `NA` with a warning. The default number of `30` isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see *Source*.
 #' @param as_percent a [logical] to indicate whether the output must be returned as a hundred fold with % sign (a character). A value of `0.123456` will then be returned as `"12.3%"`.
@@ -41,7 +40,7 @@
 #' @inheritSection as.rsi Interpretation of R and S/I
 #' @details
 #' The function [resistance()] is equal to the function [proportion_R()]. The function [susceptibility()] is equal to the function [proportion_SI()].
-#'  
+#'
 #' **Remember that you should filter your data to let it contain only first isolates!** This is needed to exclude duplicates and to reduce selection bias. Use [first_isolate()] to determine them in your data set.
 #'
 #' These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the [`count()`][AMR::count()] functions to count isolates. The function [susceptibility()] is essentially equal to `count_susceptible() / count_all()`. *Low counts can influence the outcome - the `proportion` functions may camouflage this, since they only return the proportion (albeit being dependent on the `minimum` argument).*
@@ -88,12 +87,12 @@
 #' @aliases portion
 #' @name proportion
 #' @export
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
 #' # example_isolates is a data set available in the AMR package.
-#' ?example_isolates
-#' 
-#' resistance(example_isolates$AMX)     # determines %R
+#' # run ?example_isolates for more info.
+#'
+#' # base R ------------------------------------------------------------
+#' resistance(example_isolates$AMX) # determines %R
 #' susceptibility(example_isolates$AMX) # determines %S+I
 #'
 #' # be more specific
@@ -103,64 +102,76 @@
 #' proportion_IR(example_isolates$AMX)
 #' proportion_R(example_isolates$AMX)
 #'
+#' # dplyr -------------------------------------------------------------
 #' \donttest{
 #' if (require("dplyr")) {
 #'   example_isolates %>%
-#'     group_by(hospital_id) %>%
-#'     summarise(r = resistance(CIP),
-#'               n = n_rsi(CIP)) # n_rsi works like n_distinct in dplyr, see ?n_rsi
-#'  
+#'     group_by(ward) %>%
+#'     summarise(
+#'       r = resistance(CIP),
+#'       n = n_rsi(CIP)
+#'     ) # n_rsi works like n_distinct in dplyr, see ?n_rsi
+#'
 #'   example_isolates %>%
-#'     group_by(hospital_id) %>%
-#'     summarise(R  = resistance(CIP, as_percent = TRUE),
-#'               SI = susceptibility(CIP, as_percent = TRUE),
-#'               n1 = count_all(CIP),  # the actual total; sum of all three
-#'               n2 = n_rsi(CIP),      # same - analogous to n_distinct
-#'               total = n())          # NOT the number of tested isolates!
-#'  
+#'     group_by(ward) %>%
+#'     summarise(
+#'       R = resistance(CIP, as_percent = TRUE),
+#'       SI = susceptibility(CIP, as_percent = TRUE),
+#'       n1 = count_all(CIP), # the actual total; sum of all three
+#'       n2 = n_rsi(CIP), # same - analogous to n_distinct
+#'       total = n()
+#'     ) # NOT the number of tested isolates!
+#'
 #'   # Calculate co-resistance between amoxicillin/clav acid and gentamicin,
 #'   # so we can see that combination therapy does a lot more than mono therapy:
-#'   example_isolates %>% susceptibility(AMC)  # %SI = 76.3%
-#'   example_isolates %>% count_all(AMC)       #   n = 1879
-#'  
-#'   example_isolates %>% susceptibility(GEN)  # %SI = 75.4%
-#'   example_isolates %>% count_all(GEN)       #   n = 1855
-#'  
+#'   example_isolates %>% susceptibility(AMC) # %SI = 76.3%
+#'   example_isolates %>% count_all(AMC) #   n = 1879
+#'
+#'   example_isolates %>% susceptibility(GEN) # %SI = 75.4%
+#'   example_isolates %>% count_all(GEN) #   n = 1855
+#'
 #'   example_isolates %>% susceptibility(AMC, GEN) # %SI = 94.1%
-#'   example_isolates %>% count_all(AMC, GEN)      #   n = 1939
-#'  
-#'  
+#'   example_isolates %>% count_all(AMC, GEN) #   n = 1939
+#'
+#'
 #'   # See Details on how `only_all_tested` works. Example:
 #'   example_isolates %>%
-#'     summarise(numerator = count_susceptible(AMC, GEN),
-#'               denominator = count_all(AMC, GEN),
-#'               proportion = susceptibility(AMC, GEN))
-#'  
+#'     summarise(
+#'       numerator = count_susceptible(AMC, GEN),
+#'       denominator = count_all(AMC, GEN),
+#'       proportion = susceptibility(AMC, GEN)
+#'     )
+#'
 #'   example_isolates %>%
-#'     summarise(numerator = count_susceptible(AMC, GEN, only_all_tested = TRUE),
-#'               denominator = count_all(AMC, GEN, only_all_tested = TRUE),
-#'               proportion = susceptibility(AMC, GEN, only_all_tested = TRUE))
-#'  
-#'  
+#'     summarise(
+#'       numerator = count_susceptible(AMC, GEN, only_all_tested = TRUE),
+#'       denominator = count_all(AMC, GEN, only_all_tested = TRUE),
+#'       proportion = susceptibility(AMC, GEN, only_all_tested = TRUE)
+#'     )
+#'
+#'
 #'   example_isolates %>%
-#'     group_by(hospital_id) %>%
-#'     summarise(cipro_p = susceptibility(CIP, as_percent = TRUE),
-#'               cipro_n = count_all(CIP),
-#'               genta_p = susceptibility(GEN, as_percent = TRUE),
-#'               genta_n = count_all(GEN),
-#'               combination_p = susceptibility(CIP, GEN, as_percent = TRUE),
-#'               combination_n = count_all(CIP, GEN))
-#'  
+#'     group_by(ward) %>%
+#'     summarise(
+#'       cipro_p = susceptibility(CIP, as_percent = TRUE),
+#'       cipro_n = count_all(CIP),
+#'       genta_p = susceptibility(GEN, as_percent = TRUE),
+#'       genta_n = count_all(GEN),
+#'       combination_p = susceptibility(CIP, GEN, as_percent = TRUE),
+#'       combination_n = count_all(CIP, GEN)
+#'     )
+#'
 #'   # Get proportions S/I/R immediately of all rsi columns
 #'   example_isolates %>%
 #'     select(AMX, CIP) %>%
 #'     proportion_df(translate = FALSE)
-#'  
+#'
 #'   # It also supports grouping variables
+#'   # (use rsi_df to also include the count)
 #'   example_isolates %>%
-#'     select(hospital_id, AMX, CIP) %>%
-#'     group_by(hospital_id) %>%
-#'     proportion_df(translate = FALSE)
+#'     select(ward, AMX, CIP) %>%
+#'     group_by(ward) %>%
+#'     rsi_df(translate = FALSE)
 #' }
 #' }
 resistance <- function(...,
@@ -169,12 +180,14 @@ resistance <- function(...,
                        only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = "R",
-             minimum = minimum,
-             as_percent = as_percent,
-             only_all_tested = only_all_tested,
-             only_count = FALSE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = "R",
+      minimum = minimum,
+      as_percent = as_percent,
+      only_all_tested = only_all_tested,
+      only_count = FALSE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname proportion
@@ -185,12 +198,14 @@ susceptibility <- function(...,
                            only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = c("S", "I"),
-             minimum = minimum,
-             as_percent = as_percent,
-             only_all_tested = only_all_tested,
-             only_count = FALSE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = c("S", "I"),
+      minimum = minimum,
+      as_percent = as_percent,
+      only_all_tested = only_all_tested,
+      only_count = FALSE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname proportion
@@ -201,12 +216,14 @@ proportion_R <- function(...,
                          only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = "R",
-             minimum = minimum,
-             as_percent = as_percent,
-             only_all_tested = only_all_tested,
-             only_count = FALSE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = "R",
+      minimum = minimum,
+      as_percent = as_percent,
+      only_all_tested = only_all_tested,
+      only_count = FALSE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname proportion
@@ -217,12 +234,14 @@ proportion_IR <- function(...,
                           only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = c("I", "R"),
-             minimum = minimum,
-             as_percent = as_percent,
-             only_all_tested = only_all_tested,
-             only_count = FALSE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = c("I", "R"),
+      minimum = minimum,
+      as_percent = as_percent,
+      only_all_tested = only_all_tested,
+      only_count = FALSE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname proportion
@@ -233,12 +252,14 @@ proportion_I <- function(...,
                          only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = "I",
-             minimum = minimum,
-             as_percent = as_percent,
-             only_all_tested = only_all_tested,
-             only_count = FALSE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = "I",
+      minimum = minimum,
+      as_percent = as_percent,
+      only_all_tested = only_all_tested,
+      only_count = FALSE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname proportion
@@ -249,12 +270,14 @@ proportion_SI <- function(...,
                           only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = c("S", "I"),
-             minimum = minimum,
-             as_percent = as_percent,
-             only_all_tested = only_all_tested,
-             only_count = FALSE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = c("S", "I"),
+      minimum = minimum,
+      as_percent = as_percent,
+      only_all_tested = only_all_tested,
+      only_count = FALSE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname proportion
@@ -265,12 +288,14 @@ proportion_S <- function(...,
                          only_all_tested = FALSE) {
   tryCatch(
     rsi_calc(...,
-             ab_result = "S",
-             minimum = minimum,
-             as_percent = as_percent,
-             only_all_tested = only_all_tested,
-             only_count = FALSE),
-    error = function(e) stop_(e$message, call = -5))
+      ab_result = "S",
+      minimum = minimum,
+      as_percent = as_percent,
+      only_all_tested = only_all_tested,
+      only_count = FALSE
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }
 
 #' @rdname proportion
@@ -283,14 +308,17 @@ proportion_df <- function(data,
                           combine_SI = TRUE,
                           combine_IR = FALSE) {
   tryCatch(
-    rsi_calc_df(type = "proportion",
-                data = data,
-                translate_ab = translate_ab,
-                language = language,
-                minimum = minimum,
-                as_percent = as_percent,
-                combine_SI = combine_SI,
-                combine_IR = combine_IR,
-                combine_SI_missing = missing(combine_SI)),
-    error = function(e) stop_(e$message, call = -5))
+    rsi_calc_df(
+      type = "proportion",
+      data = data,
+      translate_ab = translate_ab,
+      language = language,
+      minimum = minimum,
+      as_percent = as_percent,
+      combine_SI = combine_SI,
+      combine_IR = combine_IR,
+      combine_SI_missing = missing(combine_SI)
+    ),
+    error = function(e) stop_(e$message, call = -5)
+  )
 }

R/random.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,34 +26,32 @@
 #' Random MIC Values/Disk Zones/RSI Generation
 #'
 #' 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.
-#' @inheritSection lifecycle Stable Lifecycle 
 #' @param size desired size of the returned vector. If used in a [data.frame] call or `dplyr` verb, will get the current (group) size if left blank.
 #' @param mo any [character] that can be coerced to a valid microorganism code with [as.mo()]
 #' @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.
-#' 
-#' 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.
+#'
+#' Generated values are based on the EUCAST `r max(as.integer(gsub("[^0-9]", "", subset(rsi_translation, guideline %like% "EUCAST")$guideline)))` guideline as 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()])
 #' @name random
 #' @rdname random
 #' @export
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
-#' random_mic(100)
-#' random_disk(100)
-#' random_rsi(100)
-#' 
+#' random_mic(25)
+#' random_disk(25)
+#' random_rsi(25)
+#'
 #' \donttest{
 #' # make the random generation more realistic by setting a bug and/or drug:
-#' random_mic(100, "Klebsiella pneumoniae")                 # range 0.0625-64
-#' random_mic(100, "Klebsiella pneumoniae", "meropenem")    # range 0.0625-16
-#' random_mic(100, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
-#' 
-#' random_disk(100, "Klebsiella pneumoniae")                  # range 8-50
-#' random_disk(100, "Klebsiella pneumoniae", "ampicillin")    # range 11-17
-#' random_disk(100, "Streptococcus pneumoniae", "ampicillin") # range 12-27
+#' random_mic(25, "Klebsiella pneumoniae") # range 0.0625-64
+#' random_mic(25, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
+#' random_mic(25, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
+#'
+#' random_disk(25, "Klebsiella pneumoniae") # range 8-50
+#' random_disk(25, "Klebsiella pneumoniae", "ampicillin") # range 11-17
+#' random_disk(25, "Streptococcus pneumoniae", "ampicillin") # range 12-27
 #' }
 random_mic <- function(size = NULL, mo = NULL, ab = NULL, ...) {
   meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE, allow_NULL = TRUE)
@@ -89,18 +87,21 @@ random_rsi <- function(size = NULL, prob_RSI = c(0.33, 0.33, 0.33), ...) {
 }
 
 random_exec <- function(type, size, mo = NULL, ab = NULL) {
+  check_dataset_integrity()
   df <- rsi_translation %pm>%
     pm_filter(guideline %like% "EUCAST") %pm>%
     pm_arrange(pm_desc(guideline)) %pm>%
     subset(guideline == max(guideline) &
-              method == type)
-  
+      method == type)
+
   if (!is.null(mo)) {
     mo_coerced <- as.mo(mo)
-    mo_include <- c(mo_coerced,
-                    as.mo(mo_genus(mo_coerced)),
-                    as.mo(mo_family(mo_coerced)),
-                    as.mo(mo_order(mo_coerced)))
+    mo_include <- c(
+      mo_coerced,
+      as.mo(mo_genus(mo_coerced)),
+      as.mo(mo_family(mo_coerced)),
+      as.mo(mo_order(mo_coerced))
+    )
     df_new <- df %pm>%
       subset(mo %in% mo_include)
     if (nrow(df_new) > 0) {
@@ -109,7 +110,7 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) {
       warning_("in `random_", tolower(type), "()`: no rows found that match mo '", mo, "', ignoring argument `mo`")
     }
   }
-  
+
   if (!is.null(ab)) {
     ab_coerced <- as.ab(ab)
     df_new <- df %pm>%
@@ -120,16 +121,20 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) {
       warning_("in `random_", tolower(type), "()`: no rows found that match ab '", ab, "', ignoring argument `ab`")
     }
   }
- 
+
   if (type == "MIC") {
     # set range
     mic_range <- c(0.001, 0.002, 0.005, 0.010, 0.025, 0.0625, 0.125, 0.250, 0.5, 1, 2, 4, 8, 16, 32, 64, 128, 256)
 
     # get highest/lowest +/- random 1 to 3 higher factors of two
-    max_range <- mic_range[min(length(mic_range),
-                               which(mic_range == max(df$breakpoint_R)) + sample(c(1:3), 1))]
-    min_range <- mic_range[max(1,
-                               which(mic_range == min(df$breakpoint_S)) - sample(c(1:3), 1))]
+    max_range <- mic_range[min(
+      length(mic_range),
+      which(mic_range == max(df$breakpoint_R)) + sample(c(1:3), 1)
+    )]
+    min_range <- mic_range[max(
+      1,
+      which(mic_range == min(df$breakpoint_S)) - sample(c(1:3), 1)
+    )]
 
     mic_range_new <- mic_range[mic_range <= max_range & mic_range >= min_range]
     if (length(mic_range_new) == 0) {
@@ -145,9 +150,11 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) {
     }
     return(out)
   } else if (type == "DISK") {
-    set_range <- seq(from = as.integer(min(df$breakpoint_R) / 1.25),
-                     to = as.integer(max(df$breakpoint_S) * 1.25),
-                     by = 1)
+    set_range <- seq(
+      from = as.integer(min(df$breakpoint_R) / 1.25),
+      to = as.integer(max(df$breakpoint_S) * 1.25),
+      by = 1
+    )
     out <- sample(set_range, size = size, replace = TRUE)
     out[out < 6] <- sample(c(6:10), length(out[out < 6]), replace = TRUE)
     out[out > 50] <- sample(c(40:50), length(out[out > 50]), replace = TRUE)

R/resistance_predict.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,7 +26,6 @@
 #' Predict Antimicrobial Resistance
 #'
 #' Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns `se_min` and `se_max`. See *Examples* for a real live example.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param object model data to be plotted
 #' @param col_ab column name of `x` containing antimicrobial interpretations (`"R"`, `"I"` and `"S"`)
 #' @param col_date column name of the date, will be used to calculate years if this column doesn't consist of years already, defaults to the first column of with a date class
@@ -34,8 +33,8 @@
 #' @param year_max highest year to use in the prediction model, defaults to 10 years after today
 #' @param year_every unit of sequence between lowest year found in the data and `year_max`
 #' @param minimum minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.
-#' @param model the statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using `glm(..., family = binomial)``, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See *Details* for all valid options.
-#' @param I_as_S a [logical] to indicate whether values `"I"` should be treated as `"S"` (will otherwise be treated as `"R"`). The default, `TRUE`, follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section *Interpretation of S, I and R* below. 
+#' @param model the statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using `glm(..., family = binomial)`, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See *Details* for all valid options.
+#' @param I_as_S a [logical] to indicate whether values `"I"` should be treated as `"S"` (will otherwise be treated as `"R"`). The default, `TRUE`, follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section *Interpretation of S, I and R* below.
 #' @param preserve_measurements a [logical] to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be `NA`.
 #' @param info a [logical] to indicate whether textual analysis should be printed with the name and [summary()] of the statistical model.
 #' @param main title of the plot
@@ -56,20 +55,20 @@
 #' - `observations`, the total number of available observations in that year, i.e. \eqn{S + I + R}
 #' - `observed`, the original observed resistant percentages
 #' - `estimated`, the estimated resistant percentages, calculated by the model
-#'   
+#'
 #' Furthermore, the model itself is available as an attribute: `attributes(x)$model`, see *Examples*.
 #' @seealso The [proportion()] functions to calculate resistance
-#' 
+#'
 #' Models: [lm()] [glm()]
 #' @rdname resistance_predict
 #' @export
 #' @importFrom stats predict glm lm
-#' @inheritSection AMR Read more on Our Website!
 #' @examples
-#' x <- resistance_predict(example_isolates, 
-#'                         col_ab = "AMX",
-#'                         year_min = 2010,
-#'                         model = "binomial")
+#' x <- resistance_predict(example_isolates,
+#'   col_ab = "AMX",
+#'   year_min = 2010,
+#'   model = "binomial"
+#' )
 #' plot(x)
 #' \donttest{
 #' if (require("ggplot2")) {
@@ -82,7 +81,7 @@
 #'     filter_first_isolate() %>%
 #'     filter(mo_genus(mo) == "Staphylococcus") %>%
 #'     resistance_predict("PEN", model = "binomial")
-#'   plot(x)
+#'   print(plot(x))
 #'
 #'   # get the model from the object
 #'   mymodel <- attributes(x)$model
@@ -90,33 +89,18 @@
 #' }
 #'
 #' # create nice plots with ggplot2 yourself
-#' if (require("dplyr") & require("ggplot2")) {
-#' 
+#' if (require("dplyr") && require("ggplot2")) {
 #'   data <- example_isolates %>%
 #'     filter(mo == as.mo("E. coli")) %>%
-#'     resistance_predict(col_ab = "AMX",
-#'                        col_date = "date",
-#'                        model = "binomial",
-#'                        info = FALSE,
-#'                        minimum = 15)
-#'                        
+#'     resistance_predict(
+#'       col_ab = "AMX",
+#'       col_date = "date",
+#'       model = "binomial",
+#'       info = FALSE,
+#'       minimum = 15
+#'     )
+#'   head(data)
 #'   autoplot(data)
-#'
-#'   ggplot(data,
-#'          aes(x = year)) +
-#'     geom_col(aes(y = value),
-#'              fill = "grey75") +
-#'     geom_errorbar(aes(ymin = se_min,
-#'                       ymax = se_max),
-#'                   colour = "grey50") +
-#'     scale_y_continuous(limits = c(0, 1),
-#'                        breaks = seq(0, 1, 0.1),
-#'                        labels = paste0(seq(0, 100, 10), "%")) +
-#'     labs(title = expression(paste("Forecast of Amoxicillin Resistance in ",
-#'                                   italic("E. coli"))),
-#'          y = "%R",
-#'          x = "Year") +
-#'     theme_minimal(base_size = 13)
 #' }
 #' }
 resistance_predict <- function(x,
@@ -142,9 +126,12 @@ resistance_predict <- function(x,
   meet_criteria(I_as_S, allow_class = "logical", has_length = 1)
   meet_criteria(preserve_measurements, allow_class = "logical", has_length = 1)
   meet_criteria(info, allow_class = "logical", has_length = 1)
-  
+
   stop_if(is.null(model), 'choose a regression model with the `model` argument, e.g. resistance_predict(..., model = "binomial")')
-  
+
+  x.bak <- x
+  x <- as.data.frame(x, stringsAsFactors = FALSE)
+
   dots <- unlist(list(...))
   if (length(dots) != 0) {
     # backwards compatibility with old arguments
@@ -156,18 +143,17 @@ resistance_predict <- function(x,
       warning_("in `resistance_predict()`: I_as_R is deprecated - use I_as_S instead.")
     }
   }
-  
+
   # -- date
   if (is.null(col_date)) {
     col_date <- search_type_in_df(x = x, type = "date")
     stop_if(is.null(col_date), "`col_date` must be set")
   }
-  stop_ifnot(col_date %in% colnames(x),
-             "column '", col_date, "' not found")
-  
-  # no grouped tibbles
-  x <- as.data.frame(x, stringsAsFactors = FALSE)
-  
+  stop_ifnot(
+    col_date %in% colnames(x),
+    "column '", col_date, "' not found"
+  )
+
   year <- function(x) {
     # don't depend on lubridate or so, would be overkill for only this function
     if (all(grepl("^[0-9]{4}$", x))) {
@@ -176,7 +162,7 @@ resistance_predict <- function(x,
       as.integer(format(as.Date(x), "%Y"))
     }
   }
-  
+
   df <- x
   df[, col_ab] <- droplevels(as.rsi(df[, col_ab, drop = TRUE]))
   if (I_as_S == TRUE) {
@@ -187,22 +173,23 @@ resistance_predict <- function(x,
     df[, col_ab] <- gsub("I", "R", df[, col_ab, drop = TRUE])
   }
   df[, col_ab] <- ifelse(is.na(df[, col_ab, drop = TRUE]), 0, df[, col_ab, drop = TRUE])
-  
+
   # remove rows with NAs
   df <- subset(df, !is.na(df[, col_ab, drop = TRUE]))
   df$year <- year(df[, col_date, drop = TRUE])
-  df <- as.data.frame(rbind(table(df[, c("year", col_ab)])),
-                      stringsAsFactors = FALSE)
+  df <- as.data.frame(rbind(table(df[, c("year", col_ab), drop = FALSE])),
+    stringsAsFactors = FALSE
+  )
   df$year <- as.integer(rownames(df))
   rownames(df) <- NULL
-  
+
   df <- subset(df, sum(df$R + df$S, na.rm = TRUE) >= minimum)
   # nolint start
   df_matrix <- as.matrix(df[, c("R", "S"), drop = FALSE])
   # nolint end
-  
+
   stop_if(NROW(df) == 0, "there are no observations")
-  
+
   year_lowest <- min(df$year)
   if (is.null(year_min)) {
     year_min <- year_lowest
@@ -212,9 +199,9 @@ resistance_predict <- function(x,
   if (is.null(year_max)) {
     year_max <- year(Sys.Date()) + 10
   }
-  
+
   years <- list(year = seq(from = year_min, to = year_max, by = year_every))
-  
+
   if (model %in% c("binomial", "binom", "logit")) {
     model <- "binomial"
     model_lm <- with(df, glm(df_matrix ~ year, family = binomial))
@@ -223,11 +210,10 @@ resistance_predict <- function(x,
       cat("\n------------------------------------------------------------\n")
       print(summary(model_lm))
     }
-    
+
     predictmodel <- predict(model_lm, newdata = years, type = "response", se.fit = TRUE)
     prediction <- predictmodel$fit
     se <- predictmodel$se.fit
-    
   } else if (model %in% c("loglin", "poisson")) {
     model <- "poisson"
     model_lm <- with(df, glm(R ~ year, family = poisson))
@@ -236,11 +222,10 @@ resistance_predict <- function(x,
       cat("\n--------------------------------------------------------------\n")
       print(summary(model_lm))
     }
-    
+
     predictmodel <- predict(model_lm, newdata = years, type = "response", se.fit = TRUE)
     prediction <- predictmodel$fit
     se <- predictmodel$se.fit
-    
   } else if (model %in% c("lin", "linear")) {
     model <- "linear"
     model_lm <- with(df, lm((R / (R + S)) ~ year))
@@ -249,55 +234,57 @@ resistance_predict <- function(x,
       cat("\n-----------------------\n")
       print(summary(model_lm))
     }
-    
+
     predictmodel <- predict(model_lm, newdata = years, se.fit = TRUE)
     prediction <- predictmodel$fit
     se <- predictmodel$se.fit
-    
   } else {
     stop("no valid model selected. See ?resistance_predict.")
   }
-  
+
   # prepare the output dataframe
-  df_prediction <- data.frame(year = unlist(years),
-                              value = prediction,
-                              se_min = prediction - se,
-                              se_max = prediction + se,
-                              stringsAsFactors = FALSE)
-  
+  df_prediction <- data.frame(
+    year = unlist(years),
+    value = prediction,
+    se_min = prediction - se,
+    se_max = prediction + se,
+    stringsAsFactors = FALSE
+  )
+
   if (model == "poisson") {
     df_prediction$value <- as.integer(format(df_prediction$value, scientific = FALSE))
     df_prediction$se_min <- as.integer(df_prediction$se_min)
     df_prediction$se_max <- as.integer(df_prediction$se_max)
-    
   } else {
     # se_max not above 1
     df_prediction$se_max <- ifelse(df_prediction$se_max > 1, 1, df_prediction$se_max)
   }
   # se_min not below 0
   df_prediction$se_min <- ifelse(df_prediction$se_min < 0, 0, df_prediction$se_min)
-  
-  df_observations <- data.frame(year = df$year,
-                                observations = df$R + df$S,
-                                observed = df$R / (df$R + df$S),
-                                stringsAsFactors = FALSE)
+
+  df_observations <- data.frame(
+    year = df$year,
+    observations = df$R + df$S,
+    observed = df$R / (df$R + df$S),
+    stringsAsFactors = FALSE
+  )
   df_prediction <- df_prediction %pm>%
     pm_left_join(df_observations, by = "year")
   df_prediction$estimated <- df_prediction$value
-  
+
   if (preserve_measurements == TRUE) {
     # replace estimated data by observed data
     df_prediction$value <- ifelse(!is.na(df_prediction$observed), df_prediction$observed, df_prediction$value)
     df_prediction$se_min <- ifelse(!is.na(df_prediction$observed), NA, df_prediction$se_min)
     df_prediction$se_max <- ifelse(!is.na(df_prediction$observed), NA, df_prediction$se_max)
   }
-  
+
   df_prediction$value <- ifelse(df_prediction$value > 1, 1, ifelse(df_prediction$value < 0, 0, df_prediction$value))
-  df_prediction <- df_prediction[order(df_prediction$year), ]
-  
-  structure(
-    .Data = df_prediction,
-    class = c("resistance_predict", "data.frame"),
+  df_prediction <- df_prediction[order(df_prediction$year), , drop = FALSE]
+
+  out <- as_original_data_class(df_prediction, class(x.bak))
+  structure(out,
+    class = c("resistance_predict", class(out)),
     I_as_S = I_as_S,
     model_title = model,
     model = model_lm,
@@ -316,40 +303,48 @@ rsi_predict <- resistance_predict
 plot.resistance_predict <- function(x, main = paste("Resistance Prediction of", x_name), ...) {
   x_name <- paste0(ab_name(attributes(x)$ab), " (", attributes(x)$ab, ")")
   meet_criteria(main, allow_class = "character", has_length = 1)
-  
+
   if (attributes(x)$I_as_S == TRUE) {
     ylab <- "%R"
   } else {
     ylab <- "%IR"
   }
-  
-  plot(x = x$year,
-       y = x$value,
-       ylim = c(0, 1),
-       yaxt = "n", # no y labels
-       pch = 19, # closed dots
-       ylab = paste0("Percentage (", ylab, ")"),
-       xlab = "Year",
-       main = main,
-       sub = paste0("(n = ", sum(x$observations, na.rm = TRUE),
-                    ", model: ", attributes(x)$model_title, ")"),
-       cex.sub = 0.75)
-  
-  
+
+  plot(
+    x = x$year,
+    y = x$value,
+    ylim = c(0, 1),
+    yaxt = "n", # no y labels
+    pch = 19, # closed dots
+    ylab = paste0("Percentage (", ylab, ")"),
+    xlab = "Year",
+    main = main,
+    sub = paste0(
+      "(n = ", sum(x$observations, na.rm = TRUE),
+      ", model: ", attributes(x)$model_title, ")"
+    ),
+    cex.sub = 0.75
+  )
+
+
   axis(side = 2, at = seq(0, 1, 0.1), labels = paste0(0:10 * 10, "%"))
-  
+
   # hack for error bars: https://stackoverflow.com/a/22037078/4575331
-  arrows(x0 = x$year,
-         y0 = x$se_min,
-         x1 = x$year,
-         y1 = x$se_max,
-         length = 0.05, angle = 90, code = 3, lwd = 1.5)
-  
+  arrows(
+    x0 = x$year,
+    y0 = x$se_min,
+    x1 = x$year,
+    y1 = x$se_max,
+    length = 0.05, angle = 90, code = 3, lwd = 1.5
+  )
+
   # overlay grey points for prediction
-  points(x = subset(x, is.na(observations))$year,
-         y = subset(x, is.na(observations))$value,
-         pch = 19,
-         col = "grey40")
+  points(
+    x = subset(x, is.na(observations))$year,
+    y = subset(x, is.na(observations))$value,
+    pch = 19,
+    col = "grey40"
+  )
 }
 
 #' @rdname resistance_predict
@@ -361,27 +356,35 @@ ggplot_rsi_predict <- function(x,
   x_name <- paste0(ab_name(attributes(x)$ab), " (", attributes(x)$ab, ")")
   meet_criteria(main, allow_class = "character", has_length = 1)
   meet_criteria(ribbon, allow_class = "logical", has_length = 1)
-  
+
   stop_ifnot_installed("ggplot2")
   stop_ifnot(inherits(x, "resistance_predict"), "`x` must be a resistance prediction model created with resistance_predict()")
-  
+
   if (attributes(x)$I_as_S == TRUE) {
     ylab <- "%R"
   } else {
     ylab <- "%IR"
   }
-  
-  p <- ggplot2::ggplot(as.data.frame(x, stringsAsFactors = FALSE),
-                       ggplot2::aes(x = year, y = value)) +
-    ggplot2::geom_point(data = subset(x, !is.na(observations)),
-                        size = 2) +
+
+  p <- ggplot2::ggplot(
+    as.data.frame(x, stringsAsFactors = FALSE),
+    ggplot2::aes(x = year, y = value)
+  ) +
+    ggplot2::geom_point(
+      data = subset(x, !is.na(observations)),
+      size = 2
+    ) +
     scale_y_percent(limits = c(0, 1)) +
-    ggplot2::labs(title = main,
-                  y = paste0("Percentage (", ylab, ")"),
-                  x = "Year",
-                  caption = paste0("(n = ", sum(x$observations, na.rm = TRUE),
-                                   ", model: ", attributes(x)$model_title, ")"))
-  
+    ggplot2::labs(
+      title = main,
+      y = paste0("Percentage (", ylab, ")"),
+      x = "Year",
+      caption = paste0(
+        "(n = ", sum(x$observations, na.rm = TRUE),
+        ", model: ", attributes(x)$model_title, ")"
+      )
+    )
+
   if (ribbon == TRUE) {
     p <- p + ggplot2::geom_ribbon(ggplot2::aes(ymin = se_min, ymax = se_max), alpha = 0.25)
   } else {
@@ -389,9 +392,11 @@ ggplot_rsi_predict <- function(x,
   }
   p <- p +
     # overlay grey points for prediction
-    ggplot2::geom_point(data = subset(x, is.na(observations)),
-                        size = 2,
-                        colour = "grey40")
+    ggplot2::geom_point(
+      data = subset(x, is.na(observations)),
+      size = 2,
+      colour = "grey40"
+    )
   p
 }
 

R/rsi_calc.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -24,7 +24,7 @@
 # ==================================================================== #
 
 dots2vars <- function(...) {
-  # this function is to give more informative output about 
+  # this function is to give more informative output about
   # variable names in count_* and proportion_* functions
   dots <- substitute(list(...))
   as.character(dots)[2:length(dots)]
@@ -41,26 +41,30 @@ rsi_calc <- function(...,
   meet_criteria(as_percent, allow_class = "logical", has_length = 1, .call_depth = 1)
   meet_criteria(only_all_tested, allow_class = "logical", has_length = 1, .call_depth = 1)
   meet_criteria(only_count, allow_class = "logical", has_length = 1, .call_depth = 1)
-  
+
   data_vars <- dots2vars(...)
-  
-  dots_df <- switch(1, ...)
+
+  dots_df <- switch(1,
+    ...
+  )
   if (is.data.frame(dots_df)) {
     # make sure to remove all other classes like tibbles, data.tables, etc
     dots_df <- as.data.frame(dots_df, stringsAsFactors = FALSE)
   }
-  
+
   dots <- eval(substitute(alist(...)))
   stop_if(length(dots) == 0, "no variables selected", call = -2)
-  
+
   stop_if("also_single_tested" %in% names(dots),
-          "`also_single_tested` was replaced by `only_all_tested`.\n",
-          "Please read Details in the help page (`?proportion`) as this may have a considerable impact on your analysis.", call = -2)
+    "`also_single_tested` was replaced by `only_all_tested`.\n",
+    "Please read Details in the help page (`?proportion`) as this may have a considerable impact on your analysis.",
+    call = -2
+  )
   ndots <- length(dots)
-  
+
   if (is.data.frame(dots_df)) {
     # data.frame passed with other columns, like: example_isolates %pm>% proportion_S(AMC, GEN)
-    
+
     dots <- as.character(dots)
     # remove first element, it's the data.frame
     if (length(dots) == 1) {
@@ -69,14 +73,16 @@ rsi_calc <- function(...,
       dots <- dots[2:length(dots)]
     }
     if (length(dots) == 0 | all(dots == "df")) {
-     # for complete data.frames, like example_isolates %pm>% select(AMC, GEN) %pm>% proportion_S()
+      # for complete data.frames, like example_isolates %pm>% select(AMC, GEN) %pm>% proportion_S()
       # and the old rsi function, which has "df" as name of the first argument
       x <- dots_df
     } else {
       # get dots that are in column names already, and the ones that will be once evaluated using dots_df or global env
       # this is to support susceptibility(example_isolates, AMC, any_of(some_vector_with_AB_names))
-      dots <- c(dots[dots %in% colnames(dots_df)],
-                eval(parse(text = dots[!dots %in% colnames(dots_df)]), envir = dots_df, enclos = globalenv()))
+      dots <- c(
+        dots[dots %in% colnames(dots_df)],
+        eval(parse(text = dots[!dots %in% colnames(dots_df)]), envir = dots_df, enclos = globalenv())
+      )
       dots_not_exist <- dots[!dots %in% colnames(dots_df)]
       stop_if(length(dots_not_exist) > 0, "column(s) not found: ", vector_and(dots_not_exist, quotes = TRUE), call = -2)
       x <- dots_df[, dots, drop = FALSE]
@@ -89,11 +95,11 @@ rsi_calc <- function(...,
     x <- NULL
     try(x <- as.data.frame(dots, stringsAsFactors = FALSE), silent = TRUE)
     if (is.null(x)) {
-      # support for example_isolates %pm>% group_by(hospital_id) %pm>% summarise(amox = susceptibility(GEN, AMX))
+      # support for example_isolates %pm>% group_by(ward) %pm>% summarise(amox = susceptibility(GEN, AMX))
       x <- as.data.frame(list(...), stringsAsFactors = FALSE)
     }
   }
-  
+
   if (is.null(x)) {
     warning_("argument is NULL (check if columns exist): returning NA")
     if (as_percent == TRUE) {
@@ -102,11 +108,11 @@ rsi_calc <- function(...,
       return(NA_real_)
     }
   }
-  
+
   print_warning <- FALSE
-  
+
   ab_result <- as.rsi(ab_result)
-  
+
   if (is.data.frame(x)) {
     rsi_integrity_check <- character(0)
     for (i in seq_len(ncol(x))) {
@@ -121,13 +127,15 @@ rsi_calc <- function(...,
       # this will give a warning for invalid results, of all input columns (so only 1 warning)
       rsi_integrity_check <- as.rsi(rsi_integrity_check)
     }
-    
+
     x_transposed <- as.list(as.data.frame(t(x), stringsAsFactors = FALSE))
     if (only_all_tested == TRUE) {
       # no NAs in any column
-      y <- apply(X = as.data.frame(lapply(x, as.integer), stringsAsFactors = FALSE),
-                 MARGIN = 1,
-                 FUN = min)
+      y <- apply(
+        X = as.data.frame(lapply(x, as.integer), stringsAsFactors = FALSE),
+        MARGIN = 1,
+        FUN = min
+      )
       numerator <- sum(as.integer(y) %in% as.integer(ab_result), na.rm = TRUE)
       denominator <- sum(vapply(FUN.VALUE = logical(1), x_transposed, function(y) !(any(is.na(y)))))
     } else {
@@ -145,20 +153,21 @@ rsi_calc <- function(...,
     numerator <- sum(x %in% ab_result, na.rm = TRUE)
     denominator <- sum(x %in% levels(ab_result), na.rm = TRUE)
   }
-  
+
   if (print_warning == TRUE) {
     if (message_not_thrown_before("rsi_calc")) {
       warning_("Increase speed by transforming to class <rsi> on beforehand:\n",
-               "  your_data %>% mutate_if(is.rsi.eligible, as.rsi)\n",
-               "  your_data %>% mutate(across(where(is.rsi.eligible), as.rsi))",
-               call = FALSE)
+        "  your_data %>% mutate_if(is.rsi.eligible, as.rsi)\n",
+        "  your_data %>% mutate(across(where(is.rsi.eligible), as.rsi))",
+        call = FALSE
+      )
     }
   }
-  
+
   if (only_count == TRUE) {
     return(numerator)
   }
-  
+
   if (denominator < minimum) {
     if (data_vars != "") {
       data_vars <- paste(" for", data_vars)
@@ -182,16 +191,18 @@ rsi_calc <- function(...,
       }
     }
     warning_("Introducing NA: ",
-             ifelse(denominator == 0, "no", paste("only", denominator)),
-             " results available",
-             data_vars,
-             " (`minimum` = ", minimum, ").", call = FALSE)
+      ifelse(denominator == 0, "no", paste("only", denominator)),
+      " results available",
+      data_vars,
+      " (`minimum` = ", minimum, ").",
+      call = FALSE
+    )
     fraction <- NA_real_
   } else {
     fraction <- numerator / denominator
     fraction[is.nan(fraction)] <- NA_real_
   }
-  
+
   if (as_percent == TRUE) {
     percentage(fraction, digits = 1)
   } else {
@@ -216,16 +227,17 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both"
   meet_criteria(as_percent, allow_class = "logical", has_length = 1, .call_depth = 1)
   meet_criteria(combine_SI, allow_class = "logical", has_length = 1, .call_depth = 1)
   meet_criteria(combine_SI_missing, allow_class = "logical", has_length = 1, .call_depth = 1)
-  
+
   check_dataset_integrity()
-  
+
   if (isTRUE(combine_IR) & isTRUE(combine_SI_missing)) {
     combine_SI <- FALSE
   }
   stop_if(isTRUE(combine_SI) & isTRUE(combine_IR), "either `combine_SI` or `combine_IR` can be TRUE, not both", call = -2)
-  
+
   translate_ab <- get_translate_ab(translate_ab)
-  
+
+  data.bak <- data
   # select only groups and antibiotics
   if (is_null_or_grouped_tbl(data)) {
     data_has_groups <- TRUE
@@ -235,7 +247,7 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both"
     data_has_groups <- FALSE
     data <- data[, colnames(data)[vapply(FUN.VALUE = logical(1), data, is.rsi)], drop = FALSE]
   }
-  
+
   data <- as.data.frame(data, stringsAsFactors = FALSE)
   if (isTRUE(combine_SI) | isTRUE(combine_IR)) {
     for (i in seq_len(ncol(data))) {
@@ -249,13 +261,15 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both"
       }
     }
   }
-  
+
   sum_it <- function(.data) {
-    out <- data.frame(antibiotic = character(0),
-                      interpretation = character(0),
-                      value = double(0),
-                      isolates = integer(0),
-                      stringsAsFactors = FALSE)
+    out <- data.frame(
+      antibiotic = character(0),
+      interpretation = character(0),
+      value = double(0),
+      isolates = integer(0),
+      stringsAsFactors = FALSE
+    )
     if (data_has_groups) {
       group_values <- unique(.data[, which(colnames(.data) %in% groups), drop = FALSE])
       rownames(group_values) <- NULL
@@ -279,18 +293,22 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both"
         } else {
           col_results$value <- rep(NA_real_, NROW(col_results))
         }
-        out_new <- data.frame(antibiotic = ifelse(isFALSE(translate_ab),
-                                                  colnames(.data)[i],
-                                                  ab_property(colnames(.data)[i], property = translate_ab, language = language)),
-                              interpretation = col_results$interpretation,
-                              value = col_results$value,
-                              isolates = col_results$isolates,
-                              stringsAsFactors = FALSE)
+        out_new <- data.frame(
+          antibiotic = ifelse(isFALSE(translate_ab),
+            colnames(.data)[i],
+            ab_property(colnames(.data)[i], property = translate_ab, language = language)
+          ),
+          interpretation = col_results$interpretation,
+          value = col_results$value,
+          isolates = col_results$isolates,
+          stringsAsFactors = FALSE
+        )
         if (data_has_groups) {
           if (nrow(group_values) < nrow(out_new)) {
             # repeat group_values for the number of rows in out_new
             repeated <- rep(seq_len(nrow(group_values)),
-                            each = nrow(out_new) / nrow(group_values))
+              each = nrow(out_new) / nrow(group_values)
+            )
             group_values <- group_values[repeated, , drop = FALSE]
           }
           out_new <- cbind(group_values, out_new)
@@ -300,7 +318,7 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both"
     }
     out
   }
-  
+
   # based on pm_apply_grouped_function
   apply_group <- function(.data, fn, groups, drop = FALSE, ...) {
     grouped <- pm_split_into_groups(.data, groups, drop)
@@ -311,13 +329,13 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both"
     }
     res
   }
-  
+
   if (data_has_groups) {
     out <- apply_group(data, "sum_it", groups)
   } else {
     out <- sum_it(data)
   }
-  
+
   # apply factors for right sorting in interpretation
   if (isTRUE(combine_SI)) {
     out$interpretation <- factor(out$interpretation, levels = c("SI", "R"), ordered = TRUE)
@@ -328,24 +346,24 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both"
     # the same data structure as output, regardless of input
     out$interpretation <- factor(out$interpretation, levels = c("S", "I", "R"), ordered = TRUE)
   }
-  
+
   if (data_has_groups) {
     # ordering by the groups and two more: "antibiotic" and "interpretation"
-   out <-  pm_ungroup(out[do.call("order", out[, seq_len(length(groups) + 2)]), ])
+    out <- pm_ungroup(out[do.call("order", out[, seq_len(length(groups) + 2), drop = FALSE]), , drop = FALSE])
   } else {
-    out <- out[order(out$antibiotic, out$interpretation), ]
+    out <- out[order(out$antibiotic, out$interpretation), , drop = FALSE]
   }
-  
+
   if (type == "proportion") {
     out <- subset(out, select = -c(isolates))
   } else if (type == "count") {
     out$value <- out$isolates
     out <- subset(out, select = -c(isolates))
-  } 
-  
+  }
+
   rownames(out) <- NULL
-  class(out) <- c("rsi_df", class(out))
-  out
+  out <- as_original_data_class(out, class(data.bak))
+  structure(out, class = c("rsi_df", class(out)))
 }
 
 get_translate_ab <- function(translate_ab) {
@@ -357,9 +375,10 @@ get_translate_ab <- function(translate_ab) {
   } else {
     translate_ab <- tolower(translate_ab)
     stop_ifnot(translate_ab %in% colnames(AMR::antibiotics),
-               "invalid value for 'translate_ab', this must be a column name of the antibiotics data set\n",
-               "or TRUE (equals 'name') or FALSE to not translate at all.",
-               call = FALSE)
+      "invalid value for 'translate_ab', this must be a column name of the antibiotics data set\n",
+      "or TRUE (equals 'name') or FALSE to not translate at all.",
+      call = FALSE
+    )
     translate_ab
   }
 }

R/rsi_df.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -23,7 +23,7 @@
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #
 
-#' @rdname proportion 
+#' @rdname proportion
 #' @export
 rsi_df <- function(data,
                    translate_ab = "name",
@@ -32,14 +32,15 @@ rsi_df <- function(data,
                    as_percent = FALSE,
                    combine_SI = TRUE,
                    combine_IR = FALSE) {
-  rsi_calc_df(type = "both",
-              data = data,
-              translate_ab = translate_ab,
-              language = language,
-              minimum = minimum,
-              as_percent = as_percent,
-              combine_SI = combine_SI,
-              combine_IR = combine_IR,
-              combine_SI_missing = missing(combine_SI))
-  
+  rsi_calc_df(
+    type = "both",
+    data = data,
+    translate_ab = translate_ab,
+    language = language,
+    minimum = minimum,
+    as_percent = as_percent,
+    combine_SI = combine_SI,
+    combine_IR = combine_IR,
+    combine_SI_missing = missing(combine_SI)
+  )
 }

R/skewness.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -28,13 +28,13 @@
 #' @description Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.
 #'
 #' When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0.
-#' @inheritSection lifecycle Stable Lifecycle
 #' @param x a vector of values, a [matrix] or a [data.frame]
 #' @param na.rm a [logical] value indicating whether `NA` values should be stripped before the computation proceeds
 #' @seealso [kurtosis()]
 #' @rdname skewness
-#' @inheritSection AMR Read more on Our Website!
 #' @export
+#' @examples
+#' skewness(runif(1000))
 skewness <- function(x, na.rm = FALSE) {
   meet_criteria(na.rm, allow_class = "logical", has_length = 1)
   UseMethod("skewness")
@@ -50,7 +50,7 @@ skewness.default <- function(x, na.rm = FALSE) {
     x <- x[!is.na(x)]
   }
   n <- length(x)
-  (sum((x - mean(x))^3) / n) / (sum((x - mean(x)) ^ 2) / n) ^ (3 / 2)
+  (sum((x - mean(x))^3) / n) / (sum((x - mean(x))^2) / n)^(3 / 2)
 }
 
 #' @method skewness matrix

R/translate.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -23,154 +23,161 @@
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #
 
-#' Translate Strings from AMR Package
+#' Translate Strings from the AMR Package
 #'
 #' For language-dependent output of AMR functions, like [mo_name()], [mo_gramstain()], [mo_type()] and [ab_name()].
-#' @inheritSection lifecycle Stable Lifecycle
-#' @details Strings will be translated to foreign languages if they are defined in a local translation file. Additions to this file can be suggested at our repository. The file can be found here: <https://github.com/msberends/AMR/blob/main/data-raw/translations.tsv>. This file will be read by all functions where a translated output can be desired, like all [`mo_*`][mo_property()] functions (such as [mo_name()], [mo_gramstain()], [mo_type()], etc.) and [`ab_*`][ab_property()] functions (such as [ab_name()], [ab_group()], etc.). 
+#' @param x text to translate
+#' @param language language to choose. Use one of these supported language names or ISO-639-1 codes: `r paste0('"', sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), '" ("' , LANGUAGES_SUPPORTED, '")', collapse = ", ")`.
+#' @details The currently `r length(LANGUAGES_SUPPORTED)` supported languages are `r vector_and(sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), quotes = FALSE, sort = FALSE)`. All these languages have translations available for all antimicrobial agents and colloquial microorganism names.
 #'
-#' Currently supported languages are: `r vector_and(names(LANGUAGES_SUPPORTED), quotes = FALSE)`. All these languages have translations available for all antimicrobial agents and colloquial microorganism names.
-#'
-#' Please suggest your own translations [by creating a new issue on our repository](https://github.com/msberends/AMR/issues/new?title=Translations).
+#' Please read about adding or updating a language in [our Wiki](https://github.com/msberends/AMR/wiki/).
 #'
 #' ## Changing the Default Language
-#' The system language will be used at default (as returned by `Sys.getenv("LANG")` or, if `LANG` is not set, [Sys.getlocale()]), if that language is supported. But the language to be used can be overwritten in two ways and will be checked in this order:
-#' 
-#'   1. Setting the R option `AMR_locale`, e.g. by running `options(AMR_locale = "de")`
-#'   2. Setting the system variable `LANGUAGE` or `LANG`, e.g. by adding `LANGUAGE="de_DE.utf8"` to your `.Renviron` file in your home directory
-#' 
+#' The system language will be used at default (as returned by `Sys.getenv("LANG")` or, if `LANG` is not set, [`Sys.getlocale("LC_COLLATE")`][Sys.getlocale()]), if that language is supported. But the language to be used can be overwritten in two ways and will be checked in this order:
+#'
+#'   1. Setting the R option `AMR_locale`, either by using `set_AMR_locale()` or by running e.g. `options(AMR_locale = "de")`.
+#'
+#'      Note that setting an \R option only works in the same session. Save the command `options(AMR_locale = "(your language)")` to your `.Rprofile` file to apply it for every session.
+#'   2. Setting the system variable `LANGUAGE` or `LANG`, e.g. by adding `LANGUAGE="de_DE.utf8"` to your `.Renviron` file in your home directory.
+#'
 #' Thus, if the R option `AMR_locale` is set, the system variables `LANGUAGE` and `LANG` will be ignored.
-#' @inheritSection AMR Read more on Our Website!
 #' @rdname translate
 #' @name translate
 #' @export
 #' @examples
-#' # The 'language' argument of below functions
-#' # will be set automatically to your system language
-#' # with get_AMR_locale()
+#' # Current settings (based on system language)
+#' ab_name("Ciprofloxacin")
+#' mo_name("Coagulase-negative Staphylococcus")
 #'
-#' # English
-#' mo_name("CoNS", language = "en")
-#' #> "Coagulase-negative Staphylococcus (CoNS)"
+#' # setting another language
+#' set_AMR_locale("Greek")
+#' ab_name("Ciprofloxacin")
+#' mo_name("Coagulase-negative Staphylococcus")
 #'
-#' # Danish
-#' mo_name("CoNS", language = "da")
-#' #> "Koagulase-negative stafylokokker (KNS)"
-#' 
-#' # Dutch
-#' mo_name("CoNS", language = "nl")
-#' #> "Coagulase-negatieve Staphylococcus (CNS)"
+#' set_AMR_locale("Spanish")
+#' ab_name("Ciprofloxacin")
+#' mo_name("Coagulase-negative Staphylococcus")
 #'
-#' # German
-#' mo_name("CoNS", language = "de")
-#' #> "Koagulase-negative Staphylococcus (KNS)"
+#' # set_AMR_locale() understands endonyms, English exonyms, and ISO-639-1:
+#' set_AMR_locale("Deutsch")
+#' set_AMR_locale("German")
+#' set_AMR_locale("de")
 #'
-#' # Italian
-#' mo_name("CoNS", language = "it")
-#' #> "Staphylococcus negativo coagulasi (CoNS)"
-#'
-#' # Portuguese
-#' mo_name("CoNS", language = "pt")
-#' #> "Staphylococcus coagulase negativo (CoNS)"
-#'
-#' # Spanish
-#' mo_name("CoNS", language = "es")
-#' #> "Staphylococcus coagulasa negativo (SCN)"
+#' # reset to system default
+#' reset_AMR_locale()
 get_AMR_locale <- function() {
-  # AMR versions 1.3.0 and prior used the environmental variable:
-  if (!identical("", Sys.getenv("AMR_locale"))) {
-    options(AMR_locale = Sys.getenv("AMR_locale"))
-  }
-  
   if (!is.null(getOption("AMR_locale", default = NULL))) {
-    lang <- getOption("AMR_locale")
-    if (lang %in% LANGUAGES_SUPPORTED) {
-      return(lang)
-    } else {
-      stop_("unsupported language set as option 'AMR_locale': \"", lang, "\" - use either ",
-            vector_or(paste0('"', LANGUAGES_SUPPORTED, '" (', names(LANGUAGES_SUPPORTED), ")"), quotes = FALSE))
-    }
-  } else {
-    # now check the LANGUAGE system variable - return it if set
-    if (!identical("", Sys.getenv("LANGUAGE"))) {
-      return(coerce_language_setting(Sys.getenv("LANGUAGE")))
-    }
-    if (!identical("", Sys.getenv("LANG"))) {
-      return(coerce_language_setting(Sys.getenv("LANG")))
-    }
+    return(validate_language(getOption("AMR_locale"), extra_txt = "set with `options(AMR_locale = ...)`"))
   }
-  
-  # fallback - automatic determination based on LC_COLLATE
-  if (interactive() && message_not_thrown_before("get_AMR_locale", entire_session = TRUE)) {
-    lang <- coerce_language_setting(Sys.getlocale("LC_COLLATE"))
-    if (lang != "en") {
-      message_("Assuming the ", names(LANGUAGES_SUPPORTED)[LANGUAGES_SUPPORTED == lang], 
-               " language for the AMR package. Change this with `options(AMR_locale = \"...\")` or see `?get_AMR_locale()`. ",
-               "Supported languages are ", vector_and(names(LANGUAGES_SUPPORTED), quotes = FALSE),
-               ". This note will be shown once per session.")
-    }
-    return(lang)
+
+  lang <- ""
+  # now check the LANGUAGE system variable - return it if set
+  if (!identical("", Sys.getenv("LANGUAGE"))) {
+    lang <- Sys.getenv("LANGUAGE")
   }
-  coerce_language_setting(Sys.getlocale("LC_COLLATE"))
+  if (!identical("", Sys.getenv("LANG"))) {
+    lang <- Sys.getenv("LANG")
+  }
+  if (lang == "") {
+    lang <- Sys.getlocale("LC_COLLATE")
+  }
+
+  lang <- find_language(lang)
+  if (lang != "en" && interactive() && message_not_thrown_before("get_AMR_locale", entire_session = TRUE)) {
+    message_(
+      "Assuming the ", LANGUAGES_SUPPORTED_NAMES[[lang]]$exonym, " language (",
+      LANGUAGES_SUPPORTED_NAMES[[lang]]$endonym, ") for the AMR package. Change this with `set_AMR_locale()`. ",
+      "This note will be shown once per session."
+    )
+  }
+  lang
 }
 
-coerce_language_setting <- function(lang) {
-  # grepl() with ignore.case = FALSE is 8x faster than %like_case%
-  if (grepl("^(English|en_|EN_)", lang, ignore.case = FALSE, perl = TRUE)) {
-    # as first option to optimise speed
-    "en"
-  } else if (grepl("^(German|Deutsch|de_|DE_)", lang, ignore.case = FALSE, perl = TRUE)) {
-    "de"
-  } else if (grepl("^(Dutch|Nederlands|nl_|NL_)", lang, ignore.case = FALSE, perl = TRUE)) {
-    "nl"
-  } else if (grepl("^(Danish|Dansk|da_|DA_)", lang, ignore.case = FALSE, perl = TRUE)) {
-    "da"
-  } else if (grepl("^(Spanish|Espa.+ol|es_|ES_)", lang, ignore.case = FALSE, perl = TRUE)) {
-    "es"
-  } else if (grepl("^(Italian|Italiano|it_|IT_)", lang, ignore.case = FALSE, perl = TRUE)) {
-    "it"
-  } else if (grepl("^(French|Fran.+ais|fr_|FR_)", lang, ignore.case = FALSE, perl = TRUE)) {
-    "fr"
-  } else if (grepl("^(Portuguese|Portugu.+s|pt_|PT_)", lang, ignore.case = FALSE, perl = TRUE)) {
-    "pt"
-  } else if (grepl("^(Russian|pycc|ru_|RU_)", lang, ignore.case = FALSE, perl = TRUE)) {
-    "ru"
-  } else if (grepl("^(Swedish|Svenskt|sv_|SV_)", lang, ignore.case = FALSE, perl = TRUE)) {
-    "sv"
-  } else {
-    # other language -> set to English
-    "en"
+#' @rdname translate
+#' @export
+set_AMR_locale <- function(language) {
+  language <- validate_language(language)
+  options(AMR_locale = language)
+  message_("Using the ", LANGUAGES_SUPPORTED_NAMES[[language]]$exonym, " language (", LANGUAGES_SUPPORTED_NAMES[[language]]$endonym, ") for the AMR package for this session.")
+}
+
+#' @rdname translate
+#' @export
+reset_AMR_locale <- function() {
+  options(AMR_locale = NULL)
+}
+
+#' @rdname translate
+#' @export
+translate_AMR <- function(x, language = get_AMR_locale()) {
+  translate_into_language(x, language = language)
+}
+
+
+validate_language <- function(language, extra_txt = character(0)) {
+  if (trimws(tolower(language)) %in% c("en", "english", "", "false", NA)) {
+    return("en")
   }
+  lang <- find_language(language, fallback = FALSE)
+  stop_ifnot(length(lang) > 0 && lang %in% LANGUAGES_SUPPORTED,
+    "unsupported language for AMR package", extra_txt, ": \"", language, "\". Use one of these language names or ISO-639-1 codes: ",
+    paste0('"', vapply(FUN.VALUE = character(1), LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]),
+      '" ("', LANGUAGES_SUPPORTED, '")',
+      collapse = ", "
+    ),
+    call = FALSE
+  )
+  lang
+}
+
+find_language <- function(language, fallback = TRUE) {
+  language <- Map(function(l, n, check = language) {
+    grepl(paste0(
+      "^(", l[1], "|", l[2], "|",
+      n, "(_|$)|", toupper(n), "(_|$))"
+    ),
+    check,
+    ignore.case = FALSE,
+    perl = TRUE,
+    useBytes = FALSE
+    )
+  },
+  LANGUAGES_SUPPORTED_NAMES,
+  LANGUAGES_SUPPORTED,
+  USE.NAMES = TRUE
+  )
+  language <- names(which(language == TRUE))
+  if (isTRUE(fallback) && length(language) == 0) {
+    # other language -> set to English
+    language <- "en"
+  }
+  language
 }
 
 # translate strings based on inst/translations.tsv
-translate_AMR <- function(from,
-                          language = get_AMR_locale(), 
-                          only_unknown = FALSE,
-                          only_affect_ab_names = FALSE,
-                          only_affect_mo_names = FALSE) {
-  
+translate_into_language <- function(from,
+                                    language = get_AMR_locale(),
+                                    only_unknown = FALSE,
+                                    only_affect_ab_names = FALSE,
+                                    only_affect_mo_names = FALSE) {
   if (is.null(language)) {
     return(from)
   }
   if (language %in% c("en", "", NA)) {
     return(from)
   }
-  
+
   df_trans <- TRANSLATIONS # internal data file
   from.bak <- from
   from_unique <- unique(from)
   from_unique_translated <- from_unique
-  
-  stop_ifnot(language %in% LANGUAGES_SUPPORTED,
-             "unsupported language: \"", language, "\" - use either ",
-             vector_or(LANGUAGES_SUPPORTED, quotes = TRUE),
-             call = FALSE)
-  
+
+  # get ISO-639-1 of language
+  lang <- validate_language(language)
   # only keep lines where translation is available for this language
-  df_trans <- df_trans[which(!is.na(df_trans[, language, drop = TRUE])), , drop = FALSE]
+  df_trans <- df_trans[which(!is.na(df_trans[, lang, drop = TRUE])), , drop = FALSE]
   # and where the original string is not equal to the string in the target language
-  df_trans <- df_trans[which(df_trans[, "pattern", drop = TRUE] != df_trans[, language, drop = TRUE]), , drop = FALSE]
+  df_trans <- df_trans[which(df_trans[, "pattern", drop = TRUE] != df_trans[, lang, drop = TRUE]), , drop = FALSE]
   if (only_unknown == TRUE) {
     df_trans <- subset(df_trans, pattern %like% "unknown")
   }
@@ -183,32 +190,39 @@ translate_AMR <- function(from,
   if (NROW(df_trans) == 0) {
     return(from)
   }
-  
+
   # default: case sensitive if value if 'case_sensitive' is missing:
   df_trans$case_sensitive[is.na(df_trans$case_sensitive)] <- TRUE
   # default: not using regular expressions if 'regular_expr' is missing:
   df_trans$regular_expr[is.na(df_trans$regular_expr)] <- FALSE
-  
+
   # check if text to look for is in one of the patterns
   any_form_in_patterns <- tryCatch(
     any(from_unique %like% paste0("(", paste(gsub(" +\\(.*", "", df_trans$pattern), collapse = "|"), ")")),
     error = function(e) {
       warning_("Translation not possible. Please open an issue on GitHub (https://github.com/msberends/AMR/issues).")
       return(FALSE)
-    })
-  
+    }
+  )
+
   if (NROW(df_trans) == 0 | !any_form_in_patterns) {
     return(from)
   }
-  
-  lapply(seq_len(nrow(df_trans)), 
-         function(i) from_unique_translated <<- gsub(pattern = df_trans$pattern[i],
-                                                     replacement = df_trans[i, language, drop = TRUE],
-                                                     x = from_unique_translated,
-                                                     ignore.case = !df_trans$case_sensitive[i] & df_trans$regular_expr[i], 
-                                                     fixed = !df_trans$regular_expr[i],
-                                                     perl = df_trans$regular_expr[i]))
-  
+
+  lapply(
+    seq_len(nrow(df_trans)),
+    function(i) {
+      from_unique_translated <<- gsub(
+        pattern = df_trans$pattern[i],
+        replacement = df_trans[i, lang, drop = TRUE],
+        x = from_unique_translated,
+        ignore.case = !df_trans$case_sensitive[i] & df_trans$regular_expr[i],
+        fixed = !df_trans$regular_expr[i],
+        perl = df_trans$regular_expr[i]
+      )
+    }
+  )
+
   # force UTF-8 for diacritics
   from_unique_translated <- enc2utf8(from_unique_translated)
 

R/vctrs.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -23,13 +23,14 @@
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #
 
-# These are all S3 implementations for the vctrs package, 
+# These are all S3 implementations for the vctrs package,
 # that is used internally by tidyverse packages such as dplyr.
 # They are to convert AMR-specific classes to bare characters and integers.
 # All of them will be exported using s3_register() in R/zzz.R when loading the package.
 
-# S3: ab_selector
 # see https://github.com/tidyverse/dplyr/issues/5955 why this is required
+
+# S3: ab_selector
 vec_ptype2.character.ab_selector <- function(x, y, ...) {
   x
 }
@@ -40,6 +41,17 @@ vec_cast.character.ab_selector <- function(x, to, ...) {
   unclass(x)
 }
 
+# S3: ab_selector_any_all
+vec_ptype2.logical.ab_selector_any_all <- function(x, y, ...) {
+  x
+}
+vec_ptype2.ab_selector_any_all.logical <- function(x, y, ...) {
+  y
+}
+vec_cast.logical.ab_selector_any_all <- function(x, to, ...) {
+  unclass(x)
+}
+
 # S3: ab
 vec_ptype2.character.ab <- function(x, y, ...) {
   x

R/whocc.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -28,14 +28,14 @@
 #' All antimicrobial drugs and their official names, ATC codes, ATC groups and defined daily dose (DDD) are included in this package, using the WHO Collaborating Centre for Drug Statistics Methodology.
 #' @section WHOCC:
 #' \if{html}{\figure{logo_who.png}{options: height="60" style=margin-bottom:"5"} \cr}
-#' This package contains **all ~550 antibiotic, antimycotic and antiviral drugs** and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <https://www.whocc.no>) and the Pharmaceuticals Community Register of the European Commission (<https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm>). 
+#' This package contains **all ~550 antibiotic, antimycotic and antiviral drugs** and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <https://www.whocc.no>) and the Pharmaceuticals Community Register of the European Commission (<https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm>).
 #'
 #' These have become the gold standard for international drug utilisation monitoring and research.
 #'
 #' The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.
-#' 
+#'
 #' **NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.** See <https://www.whocc.no/copyright_disclaimer/.>
-#' @inheritSection AMR Read more on Our Website!
+
 #' @name WHOCC
 #' @rdname WHOCC
 #' @examples

R/zzz.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -26,16 +26,19 @@
 # set up package environment, used by numerous AMR functions
 pkg_env <- new.env(hash = FALSE)
 pkg_env$mo_failed <- character(0)
-pkg_env$mo_field_abbreviations <- c("AIEC", "ATEC", "BORSA", "CRSM", "DAEC", "EAEC",
-                                    "EHEC", "EIEC", "EPEC", "ETEC", "GISA", "MRPA",
-                                    "MRSA", "MRSE", "MSSA", "MSSE", "NMEC", "PISP",
-                                    "PRSP", "STEC", "UPEC", "VISA", "VISP", "VRE",
-                                    "VRSA", "VRSP")
+pkg_env$mo_field_abbreviations <- c(
+  "AIEC", "ATEC", "BORSA", "CRSM", "DAEC", "EAEC",
+  "EHEC", "EIEC", "EPEC", "ETEC", "GISA", "MRPA",
+  "MRSA", "MRSE", "MSSA", "MSSE", "NMEC", "PISP",
+  "PRSP", "STEC", "UPEC", "VISA", "VISP", "VRE",
+  "VRSA", "VRSP"
+)
 
 # determine info icon for messages
 utf8_supported <- isTRUE(base::l10n_info()$`UTF-8`)
 is_latex <- tryCatch(import_fn("is_latex_output", "knitr", error_on_fail = FALSE)(),
-                     error = function(e) FALSE)
+  error = function(e) FALSE
+)
 if (utf8_supported && !is_latex) {
   # \u2139 is a symbol officially named 'information source'
   pkg_env$info_icon <- "\u2139"
@@ -45,8 +48,8 @@ if (utf8_supported && !is_latex) {
 
 .onLoad <- function(...) {
   # Support for tibble headers (type_sum) and tibble columns content (pillar_shaft)
-  # without the need to depend on other packages. This was suggested by the 
-  # developers of the vctrs package: 
+  # without the need to depend on other packages. This was suggested by the
+  # developers of the vctrs package:
   # https://github.com/r-lib/vctrs/blob/05968ce8e669f73213e3e894b5f4424af4f46316/R/register-s3.R
   s3_register("pillar::pillar_shaft", "ab")
   s3_register("pillar::pillar_shaft", "mo")
@@ -87,30 +90,35 @@ if (utf8_supported && !is_latex) {
   s3_register("vctrs::vec_ptype2", "ab_selector.character")
   s3_register("vctrs::vec_ptype2", "character.ab_selector")
   s3_register("vctrs::vec_cast", "character.ab_selector")
+  s3_register("vctrs::vec_ptype2", "ab_selector_any_all.logical")
+  s3_register("vctrs::vec_ptype2", "logical.ab_selector_any_all")
+  s3_register("vctrs::vec_cast", "logical.ab_selector_any_all")
   s3_register("vctrs::vec_ptype2", "disk.integer")
   s3_register("vctrs::vec_ptype2", "integer.disk")
   s3_register("vctrs::vec_cast", "integer.disk")
-  
+
   # if mo source exists, fire it up (see mo_source())
-  try({
-    if (file.exists(getOption("AMR_mo_source", "~/mo_source.rds"))) {
-      invisible(get_mo_source())
-    }
-  }, silent = TRUE)
-  
-  
+  try(
+    {
+      if (file.exists(getOption("AMR_mo_source", "~/mo_source.rds"))) {
+        invisible(get_mo_source())
+      }
+    },
+    silent = TRUE
+  )
+
+  # be sure to print tibbles as tibbles
+  if (pkg_is_available("tibble", also_load = FALSE)) {
+    loadNamespace("tibble")
+  }
+
   # reference data - they have additional columns compared to `antibiotics` and `microorganisms` to improve speed
-  # they cannott be part of R/sysdata.rda since CRAN thinks it would make the package too large (+3 MB)
+  # they cannot be part of R/sysdata.rda since CRAN thinks it would make the package too large (+3 MB)
   assign(x = "AB_lookup", value = create_AB_lookup(), envir = asNamespace("AMR"))
   assign(x = "MO_lookup", value = create_MO_lookup(), envir = asNamespace("AMR"))
   assign(x = "MO.old_lookup", value = create_MO.old_lookup(), envir = asNamespace("AMR"))
   # for mo_is_intrinsic_resistant() - saves a lot of time when executed on this vector
   assign(x = "INTRINSIC_R", value = create_intr_resistance(), envir = asNamespace("AMR"))
-  
-  # for building the website, only print first 5 rows of a data set
-  # if (Sys.getenv("IN_PKGDOWN") != "" && !interactive()) {
-  #   ...
-  # }
 }
 
 # Helper functions --------------------------------------------------------
@@ -121,7 +129,7 @@ create_AB_lookup <- function() {
 
 create_MO_lookup <- function() {
   MO_lookup <- AMR::microorganisms
-  
+
   MO_lookup$kingdom_index <- NA_real_
   MO_lookup[which(MO_lookup$kingdom == "Bacteria" | MO_lookup$mo == "UNKNOWN"), "kingdom_index"] <- 1
   MO_lookup[which(MO_lookup$kingdom == "Fungi"), "kingdom_index"] <- 2
@@ -129,26 +137,31 @@ create_MO_lookup <- function() {
   MO_lookup[which(MO_lookup$kingdom == "Archaea"), "kingdom_index"] <- 4
   # all the rest
   MO_lookup[which(is.na(MO_lookup$kingdom_index)), "kingdom_index"] <- 5
-  
+
   # use this paste instead of `fullname` to work with Viridans Group Streptococci, etc.
-  MO_lookup$fullname_lower <- MO_FULLNAME_LOWER
-  
+  if (length(MO_FULLNAME_LOWER) == nrow(MO_lookup)) {
+    MO_lookup$fullname_lower <- MO_FULLNAME_LOWER
+  } else {
+    MO_lookup$fullname_lower <- ""
+    warning("MO table updated - Run: source(\"data-raw/_pre_commit_hook.R\")", call. = FALSE)
+  }
+
   # add a column with only "e coli" like combinations
   MO_lookup$g_species <- gsub("^([a-z])[a-z]+ ([a-z]+) ?.*", "\\1 \\2", MO_lookup$fullname_lower, perl = TRUE)
-  
+
   # so arrange data on prevalence first, then kingdom, then full name
-  MO_lookup[order(MO_lookup$prevalence, MO_lookup$kingdom_index, MO_lookup$fullname_lower), ]
+  MO_lookup[order(MO_lookup$prevalence, MO_lookup$kingdom_index, MO_lookup$fullname_lower), , drop = FALSE]
 }
 
 create_MO.old_lookup <- function() {
   MO.old_lookup <- AMR::microorganisms.old
   MO.old_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", tolower(trimws(MO.old_lookup$fullname))))
-  
+
   # add a column with only "e coli"-like combinations
   MO.old_lookup$g_species <- trimws(gsub("^([a-z])[a-z]+ ([a-z]+) ?.*", "\\1 \\2", MO.old_lookup$fullname_lower))
-  
+
   # so arrange data on prevalence first, then full name
-  MO.old_lookup[order(MO.old_lookup$prevalence, MO.old_lookup$fullname_lower), ]
+  MO.old_lookup[order(MO.old_lookup$prevalence, MO.old_lookup$fullname_lower), , drop = FALSE]
 }
 
 create_intr_resistance <- function() {

README.md

@@ -8,9 +8,7 @@
 
 <img src="https://msberends.github.io/AMR/AMR_intro.svg" align="center" height="300px" />
 
-The latest built **source package** (`AMR_latest.tar.gz`) can be found in folder [/data-raw/](https://github.com/msberends/AMR/tree/main/data-raw).
-
-`AMR` is a free, open-source and independent R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. It is currently being used in over 150 countries.
+`AMR` is a free, open-source and independent R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. It is currently being used in over 175 countries.
  
 After installing this package, R knows ~71,000 distinct microbial species and all ~570 antibiotic, antimycotic, and antiviral drugs by name and code (including ATC, WHONET/EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. Antimicrobial names and group names are available in Danish, Dutch, English, French, German, Italian, Portuguese and Spanish.
 

_pkgdown.yml

@@ -26,14 +26,40 @@
 title: "AMR (for R)"
 url: "https://msberends.github.io/AMR/"
 
-development:
-  mode: "release" # improves indexing by search engines
-  version_tooltip: "Latest development version"
+template:
+  bootstrap: 5
+  bootswatch: "flatly"
+  assets: "pkgdown/logos" # use logos in this folder
+  bslib:
+    code_font: {google: "Fira Code"}
+    # body-text-align: "justify"
+    line-height-base: 1.75
+    # the green "success" colour of this bootstrap theme should be the same as the green in our logo
+    success: "#128f76"
+    link-color: "#128f76"
+    navbar-padding-y: "0.5rem"
+  opengraph:
+    twitter:
+      creator: "@msberends"
+      site: "@univgroningen"
+      card: summary_large_image
 
 news:
   one_page: true
   cran_dates: true
 
+footer:
+  structure:
+    left: [devtext]
+    right: [logo]
+  components:
+    devtext: '<code>AMR</code> (for R). Developed at the <a target="_blank" href="https://www.rug.nl">University of Groningen</a> in collaboration with non-profit organisations<br><a target="_blank" href="https://www.certe.nl">Certe Medical Diagnostics and Advice Foundation</a> and <a target="_blank" href="https://www.umcg.nl">University Medical Center Groningen</a>.'
+    logo: '<a target="_blank" href="https://www.rug.nl"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/logos/logo_rug.svg" style="max-width: 200px;"></a>'
+
+home:
+  sidebar:
+    structure: [toc, links, authors, citation]
+
 navbar:
   title: "AMR (for R)"
   left:
@@ -73,9 +99,9 @@ navbar:
       - text: "Get properties of an antibiotic"
         icon: "fa-capsules"
         href: "reference/ab_property.html" # reference instead of an article
-      - text: "Other: benchmarks"
-        icon: "fa-shipping-fast"
-        href: "articles/benchmarks.html"
+      # - text: "Other: benchmarks"
+      #   icon: "fa-shipping-fast"
+      #   href: "articles/benchmarks.html"
     - text: "Manual"
       icon: "fa-book-open"
       href: "reference/index.html"
@@ -102,7 +128,7 @@ reference:
     - "`as.mo`"
     - "`mo_property`"
     - "`mo_source`"
-    
+
   - title: "Preparing data: antibiotics"
     desc: >
       Use these functions to get valid properties of antibiotics from any input or to clean your input.
@@ -112,7 +138,7 @@ reference:
     - "`ab_property`"
     - "`ab_from_text`"
     - "`atc_online_property`"
-    
+
   - title: "Preparing data: antimicrobial resistance"
     desc: >
       With `as.mic()` and `as.disk()` you can transform your raw input to valid MIC or disk diffusion values.
@@ -124,7 +150,7 @@ reference:
     - "`as.disk`"
     - "`eucast_rules`"
     - "`custom_eucast_rules`"
-    
+
   - title: "Analysing data: antimicrobial resistance"
     desc: >
       Use these function for the analysis part. You can use `susceptibility()` or `resistance()` on any antibiotic column.
@@ -161,11 +187,10 @@ reference:
     - "`catalogue_of_life`"
     - "`catalogue_of_life_version`"
     - "`WHOCC`"
-    - "`lifecycle`"
     - "`example_isolates_unclean`"
     - "`rsi_translation`"
     - "`WHONET`"
-    
+
   - title: "Other: miscellaneous functions"
     desc: >
       These functions are mostly for internal use, but some of
@@ -183,7 +208,7 @@ reference:
     - "`mo_matching_score`"
     - "`pca`"
     - "`random`"
-  
+
   - title: "Other: statistical tests"
     desc: >
       Some statistical tests or methods are not part of base R and were added to this package for convenience.
@@ -199,15 +224,3 @@ reference:
       in a future version.
     contents:
     - "`AMR-deprecated`"
-
-template:
-  bootstrap: 3
-  opengraph:
-    twitter:
-      creator: "@msberends"
-      site: "@univgroningen"
-      card: summary_large_image
-  assets: "pkgdown/logos" # use logos in this folder
-  params:
-    noindex: false
-    bootswatch: "flatly"

data-raw/Loinc.csv

@@ -71673,7 +71673,7 @@
 "7553-1","Origanum vulgare Ab.IgG","ACnc","Pt","Ser","Qn","","ALLERGY","2.27","MIN","","ACTIVE","","1","","","","","","Y","","ABS; Aby; Allergen; Allergens; ALLERGY TESTING; Antby; Anti; Antibodies; Antibody; Arbitrary concentration; Autoantibodies; Autoantibody; f283; Immune globulin G; Immunoglobulin G; Oregano; Oreganum; Point in time; QNT; Quan; Quant; Quantitative; Random; Rf283; Serum; SR","Oregano IgG Qn","Both","","","","","Oregano IgG Ab [Units/volume] in Serum","","","","","","","0","0","0","","","","","","1.0h(2)","","Oregano IgG Qn (S)"
 "75531-4","Enrollment basis","Type","Pt","^Patient","Nom","","SURVEY.PCORNET","2.50","MIN","","ACTIVE","","4","","","","","","","","Nominal; Point in time; Random; Survey; SURVEY.PCORNET; Typ","Enrollment basis","Observation","","","","","Enrollment basis","","","","","","","0","0","0","","","","","","2.50","",""
 "75532-2","Applicable accrediting agency for unit","Type","Pt","{Nursing unit}","Nom","NMMDS","SURVEY.NMMDS","2.50","MIN","Types of accreditation that are appropriate or applicable to a unit or service.  The unit may or may not have received the accreditation.","ACTIVE","","4","","","","","","","","Nominal; Nursing Management Minimum Data Set; Point in time; Random; Survey; SURVEY.NMMDS; Typ","","Observation","","","Copyright © 2006 Diane Huber and Connie Delaney. Used with permission.","","Applicable accrediting agency for unit [NMMDS]","","","","","","","0","0","0","","NMMDS","","","","2.50","",""
-"75533-0","Accreditation, certification, & licensure panel","-","Pt","{Nursing unit}","-","NMMDS","PANEL.SURVEY.NMMDS","2.52","MIN","The set of terms in this panel are used to indicate quality assurance organizations of the nursing delivery unit/service by 3 different quality measure categories: accreditation, certification and licensure. Accreditation is a seal of approval given by private, nationally recognized groups that check on the quality of care at health care facilities and organizations. Health care organizations must meet certain quality standards in order to be accredited. Certification is the formal recognition of the knowledge, skills, and experience demonstrated by the achievement of standards that are identified by the profession² (ANA, 2009). Licensure is the granting of authority to practice² (ANA, 2009). State agencies determine the requirements for licensure and examine the competency necessary to meet quality standards.","ACTIVE","","4","","","","","","","","Nursing Management Minimum Data Set; Pan; PANEL.SURVEY.NMMDS; Panl; Pnl; Point in time; Random; Survey; SURVEY.NMMDS","","","","","Copyright © 2006 Diane Huber and Connie Delaney. Used with permission.","","NMMDS accreditation, certification, and licensure panel [NMMDS]","","","","","","","0","0","0","","NMMDS","Panel","","","2.50","",""
+"75533-0","Accreditation, certification, & licensure panel","-","Pt","{Nursing unit}","-","NMMDS","PANEL.SURVEY.NMMDS","2.52","MIN","The set of terms in this panel are used to indicate quality assurance organizations of the nursing delivery unit/service by 3 different quality measure categories: accreditation, certification and licensure. Accreditation is a seal of approval given by private, nationally recognized groups that check on the quality of care at health care facilities and organizations. Health care organizations must meet certain quality standards in order to be accredited. Certification is the formal recognition of the knowledge, skills, and experience demonstrated by the achievement of standards that are identified by the profession² (ANA, 2009). Licensure is the granting of authority to practise² (ANA, 2009). State agencies determine the requirements for licensure and examine the competency necessary to meet quality standards.","ACTIVE","","4","","","","","","","","Nursing Management Minimum Data Set; Pan; PANEL.SURVEY.NMMDS; Panl; Pnl; Point in time; Random; Survey; SURVEY.NMMDS","","","","","Copyright © 2006 Diane Huber and Connie Delaney. Used with permission.","","NMMDS accreditation, certification, and licensure panel [NMMDS]","","","","","","","0","0","0","","NMMDS","Panel","","","2.50","",""
 "75534-8","Accreditation received","Type","Pt","{Nursing unit}","Nom","NMMDS","SURVEY.NMMDS","2.50","MIN","Types of accreditation obtained by a unit to demonstrate quality of care. Accreditation is a seal of approval given by private, nationally recognized groups that check on the quality of care at health care facilities and organizations. Health care organizations must meet certain quality standards in order to be accredited.","ACTIVE","","4","","","","","","","","Nominal; Nursing Management Minimum Data Set; Point in time; Random; Survey; SURVEY.NMMDS; Typ","","Observation","","","Copyright © 2006 Diane Huber and Connie Delaney. Used with permission.","","Accreditation received [NMMDS]","","","","","","","0","0","0","","NMMDS","","","","2.50","",""
 "75535-5","Certification received","Type","Pt","{Nursing unit}","Nom","NMMDS","SURVEY.NMMDS","2.50","MIN","Types of certification obtained by a unit to demonstrate quality care.","ACTIVE","","4","","","","","","","","Nominal; Nursing Management Minimum Data Set; Point in time; Random; Survey; SURVEY.NMMDS; Typ","","Observation","","","Copyright © 2006 Diane Huber and Connie Delaney. Used with permission.","","Certification received [NMMDS]","","","","","","","0","0","0","","NMMDS","","","","2.50","",""
 "75536-3","Applicable certification agency for unit","Type","Pt","{Nursing unit}","Nom","NMMDS","SURVEY.NMMDS","2.50","MIN","Types of certification that are appropriate or applicable to a unit or service.  The unit may or may not have received the certification.","ACTIVE","","4","","","","","","","","Nominal; Nursing Management Minimum Data Set; Point in time; Random; Survey; SURVEY.NMMDS; Typ","","Observation","","","Copyright © 2006 Diane Huber and Connie Delaney. Used with permission.","","Applicable certification agency for unit [NMMDS]","","","","","","","0","0","0","","NMMDS","","","","2.50","",""

data-raw/_install_deps.R

@@ -9,7 +9,7 @@
 # (c) 2018-2022 Berends MS, Luz CF et al.                              #
 # Developed at the University of Groningen, the Netherlands, in        #
 # collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
+# Diagnostics & Advice, and University Medical Center Groningen.       #
 #                                                                      #
 # This R package is free software; you can freely use and distribute   #
 # it for both personal and commercial purposes under the terms of the  #
@@ -25,12 +25,16 @@
 
 # some old R instances have trouble installing tinytest, so we ship it too
 install.packages("data-raw/tinytest_1.3.1.tar.gz", dependencies = c("Depends", "Imports", "LinkingTo"))
-install.packages("data-raw/AMR_latest.tar.gz", dependencies = FALSE)
+install.packages(getwd(), repos = NULL, type = "source")
 
-pkg_suggests <- gsub("[^a-zA-Z0-9]+", "",
-                     unlist(strsplit(unlist(packageDescription("AMR",
-                                                               fields = c("Suggests", "Enhances", "LinkingTo"))),
-                                     split = ", ?")))
+pkg_suggests <- gsub(
+  "[^a-zA-Z0-9]+", "",
+  unlist(strsplit(unlist(packageDescription("AMR",
+    fields = c("Suggests", "Enhances", "LinkingTo")
+  )),
+  split = ", ?"
+  ))
+)
 pkg_suggests <- unname(pkg_suggests[!is.na(pkg_suggests)])
 cat("################################################\n")
 cat("Packages listed in Suggests/Enhances:", paste(pkg_suggests, collapse = ", "), "\n")
@@ -48,22 +52,26 @@ if (length(to_install) == 0) {
 for (i in seq_len(length(to_install))) {
   cat("Installing package", to_install[i], "\n")
   tryCatch(install.packages(to_install[i],
-                            type = "source",
-                            repos = "https://cran.rstudio.com/",
-                            dependencies = c("Depends", "Imports", "LinkingTo"),
-                            quiet = FALSE),
-           # message = function(m) invisible(),
-           warning = function(w) message(w$message),
-           error = function(e) message(e$message))
+    type = "source",
+    repos = "https://cran.rstudio.com/",
+    dependencies = c("Depends", "Imports", "LinkingTo"),
+    quiet = FALSE
+  ),
+  # message = function(m) invisible(),
+  warning = function(w) message(w$message),
+  error = function(e) message(e$message)
+  )
   if (.Platform$OS.type != "unix" && !to_install[i] %in% rownames(utils::installed.packages())) {
     tryCatch(install.packages(to_install[i],
-                              type = "binary",
-                              repos = "https://cran.rstudio.com/",
-                              dependencies = c("Depends", "Imports", "LinkingTo"),
-                              quiet = FALSE),
-             # message = function(m) invisible(),
-             warning = function(w) message(w$message),
-             error = function(e) message(e$message))
+      type = "binary",
+      repos = "https://cran.rstudio.com/",
+      dependencies = c("Depends", "Imports", "LinkingTo"),
+      quiet = FALSE
+    ),
+    # message = function(m) invisible(),
+    warning = function(w) message(w$message),
+    error = function(e) message(e$message)
+    )
   }
 }
 
@@ -75,8 +83,9 @@ if (length(to_update) == 0) {
 for (i in seq_len(length(to_update))) {
   cat("Updating package '", to_update[i], "' v", as.character(packageVersion(to_update[i])), "\n", sep = "")
   tryCatch(update.packages(to_update[i], repos = "https://cran.rstudio.com/", ask = FALSE),
-           # message = function(m) invisible(),
-           warning = function(w) message(w$message),
-           error = function(e) message(e$message))
+    # message = function(m) invisible(),
+    warning = function(w) message(w$message),
+    error = function(e) message(e$message)
+  )
   cat("Updated to '", to_update[i], "' v", as.character(packageVersion(to_update[i])), "\n", sep = "")
 }

data-raw/_internals.R

@@ -1,343 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Data Analysis for R                   #
-#                                                                      #
-# SOURCE                                                               #
-# https://github.com/msberends/AMR                                     #
-#                                                                      #
-# LICENCE                                                              #
-# (c) 2018-2022 Berends MS, Luz CF et al.                              #
-# Developed at the University of Groningen, the Netherlands, in        #
-# collaboration with non-profit organisations Certe Medical            #
-# Diagnostics & Advice, and University Medical Center Groningen.       # 
-#                                                                      #
-# This R package is free software; you can freely use and distribute   #
-# it for both personal and commercial purposes under the terms of the  #
-# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
-# the Free Software Foundation.                                        #
-# We created this package for both routine data analysis and academic  #
-# research and it was publicly released in the hope that it will be    #
-# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
-#                                                                      #
-# Visit our website for the full manual and a complete tutorial about  #
-# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
-# ==================================================================== #
-
-# Run this file to update the package using:
-# source("data-raw/_internals.R")
-
-library(dplyr, warn.conflicts = FALSE)
-devtools::load_all(quiet = TRUE)
-
-old_globalenv <- ls(envir = globalenv())
-
-# Save internal data to R/sysdata.rda -------------------------------------
-
-# See 'data-raw/eucast_rules.tsv' for the EUCAST reference file
-EUCAST_RULES_DF <- utils::read.delim(file = "data-raw/eucast_rules.tsv",
-                                       skip = 10,
-                                       sep = "\t",
-                                       stringsAsFactors = FALSE,
-                                       header = TRUE,
-                                       strip.white = TRUE,
-                                       na = c(NA, "", NULL)) %>% 
-  # take the order of the reference.rule_group column in the original data file
-  mutate(reference.rule_group = factor(reference.rule_group,
-                                       levels = unique(reference.rule_group),
-                                       ordered = TRUE),
-         sorting_rule = ifelse(grepl("^Table", reference.rule, ignore.case = TRUE), 1, 2)) %>% 
-  arrange(reference.rule_group,
-          reference.version,
-          sorting_rule,
-          reference.rule) %>% 
-  mutate(reference.rule_group = as.character(reference.rule_group)) %>% 
-  select(-sorting_rule)
-
-# Translations
-TRANSLATIONS <- utils::read.delim(file = "data-raw/translations.tsv",
-                                       sep = "\t",
-                                       stringsAsFactors = FALSE,
-                                       header = TRUE,
-                                       blank.lines.skip = TRUE,
-                                       fill = TRUE,
-                                       strip.white = TRUE,
-                                       encoding = "UTF-8",
-                                       fileEncoding = "UTF-8",
-                                       na.strings = c(NA, "", NULL),
-                                       allowEscapes = TRUE, # else "\\1" will be imported as "\\\\1"
-                                       quote = "")
-
-# for checking input in `language` argument in e.g. mo_*() and ab_*() functions
-LANGUAGES_SUPPORTED <- c(Danish = "da",
-                         German = "de",
-                         English = "en",
-                         Spanish = "es",
-                         French = "fr",
-                         Italian = "it",
-                         Dutch = "nl",
-                         Portuguese = "pt",
-                         Russian = "ru",
-                         Swedish = "sv")
-
-# EXAMPLE_ISOLATES <- readRDS("data-raw/example_isolates.rds")
-
-# vectors of CoNS and CoPS, improves speed in as.mo()
-create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
-  # Determination of which staphylococcal species are CoNS/CoPS according to:
-  # - Becker et al. 2014, PMID 25278577
-  # - Becker et al. 2019, PMID 30872103
-  # - Becker et al. 2020, PMID 32056452
-  # this function returns class <mo>
-  MO_staph <- AMR::microorganisms
-  MO_staph <- MO_staph[which(MO_staph$genus == "Staphylococcus"), , drop = FALSE]
-  if (type == "CoNS") {
-    MO_staph[which(MO_staph$species %in% c("coagulase-negative", "argensis", "arlettae",
-                                           "auricularis", "borealis", "caeli", "capitis", "caprae", 
-                                           "carnosus", "casei", "chromogenes", "cohnii", "condimenti",
-                                           "croceilyticus",
-                                           "debuckii", "devriesei", "edaphicus", "epidermidis",
-                                           "equorum", "felis", "fleurettii", "gallinarum",
-                                           "haemolyticus", "hominis", "jettensis", "kloosii",
-                                           "lentus", "lugdunensis", "massiliensis", "microti",
-                                           "muscae", "nepalensis", "pasteuri", "petrasii",
-                                           "pettenkoferi", "piscifermentans", "pragensis", "pseudoxylosus",
-                                           "pulvereri", "rostri", "saccharolyticus", "saprophyticus",
-                                           "sciuri", "simulans", "stepanovicii", "succinus",
-                                           "ureilyticus",
-                                           "vitulinus", "vitulus", "warneri", "xylosus",
-                                           "caledonicus", "canis",
-                                           "durrellii", "lloydii")
-                   | (MO_staph$species == "schleiferi" & MO_staph$subspecies %in% c("schleiferi", ""))),
-             "mo", drop = TRUE]
-  } else if (type == "CoPS") {
-    MO_staph[which(MO_staph$species %in% c("coagulase-positive", "coagulans",
-                                           "agnetis", "argenteus",
-                                           "cornubiensis",
-                                           "delphini", "lutrae",
-                                           "hyicus", "intermedius",
-                                           "pseudintermedius", "pseudointermedius",
-                                           "schweitzeri", "simiae",
-                                           "roterodami")
-                   | (MO_staph$species == "schleiferi" & MO_staph$subspecies == "coagulans")),
-             "mo", drop = TRUE]
-  }
-}
-create_MO_fullname_lower <- function() {
-  MO_lookup <- AMR::microorganisms
-  # use this paste instead of `fullname` to work with Viridans Group Streptococci, etc.
-  MO_lookup$fullname_lower <- tolower(trimws(paste(MO_lookup$genus, 
-                                                   MO_lookup$species,
-                                                   MO_lookup$subspecies)))
-  ind <- MO_lookup$genus == "" | grepl("^[(]unknown ", MO_lookup$fullname, perl = TRUE)
-  MO_lookup[ind, "fullname_lower"] <- tolower(MO_lookup[ind, "fullname"])
-  MO_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", MO_lookup$fullname_lower, perl = TRUE))
-  MO_lookup$fullname_lower
-}
-MO_CONS <- create_species_cons_cops("CoNS")
-MO_COPS <- create_species_cons_cops("CoPS")
-MO_STREP_ABCG <- as.mo(MO_lookup[which(MO_lookup$genus == "Streptococcus"), "mo", drop = TRUE], Lancefield = TRUE) %in% c("B_STRPT_GRPA", "B_STRPT_GRPB", "B_STRPT_GRPC", "B_STRPT_GRPG")
-MO_FULLNAME_LOWER <- create_MO_fullname_lower()
-
-# antibiotic groups
-# (these will also be used for eucast_rules() and understanding data-raw/eucast_rules.tsv)
-globalenv_before_ab <- c(ls(envir = globalenv()), "globalenv_before_ab")
-AB_AMINOGLYCOSIDES <- antibiotics %>% filter(group %like% "aminoglycoside") %>% pull(ab)
-AB_AMINOPENICILLINS <- as.ab(c("AMP", "AMX"))
-AB_ANTIFUNGALS <- AB_lookup %>% filter(group %like% "antifungal") %>% pull(ab)
-AB_ANTIMYCOBACTERIALS <- AB_lookup %>% filter(group %like% "antimycobacterial") %>% pull(ab)
-AB_CARBAPENEMS <- antibiotics %>% filter(group %like% "carbapenem") %>% pull(ab)
-AB_CEPHALOSPORINS <- antibiotics %>% filter(group %like% "cephalosporin") %>% pull(ab)
-AB_CEPHALOSPORINS_1ST <- antibiotics %>% filter(group %like% "cephalosporin.*1") %>% pull(ab)
-AB_CEPHALOSPORINS_2ND <- antibiotics %>% filter(group %like% "cephalosporin.*2") %>% pull(ab)
-AB_CEPHALOSPORINS_3RD <- antibiotics %>% filter(group %like% "cephalosporin.*3") %>% pull(ab)
-AB_CEPHALOSPORINS_4TH <- antibiotics %>% filter(group %like% "cephalosporin.*4") %>% pull(ab)
-AB_CEPHALOSPORINS_5TH <- antibiotics %>% filter(group %like% "cephalosporin.*5") %>% pull(ab)
-AB_CEPHALOSPORINS_EXCEPT_CAZ <- AB_CEPHALOSPORINS[AB_CEPHALOSPORINS != "CAZ"]
-AB_FLUOROQUINOLONES <- antibiotics %>% filter(atc_group2 %like% "fluoroquinolone" | (group %like% "quinolone" & is.na(atc_group2))) %>% pull(ab)
-AB_GLYCOPEPTIDES <- antibiotics %>% filter(group %like% "glycopeptide") %>% pull(ab)
-AB_LIPOGLYCOPEPTIDES <- as.ab(c("DAL", "ORI", "TLV")) # dalba/orita/tela
-AB_GLYCOPEPTIDES_EXCEPT_LIPO <- AB_GLYCOPEPTIDES[!AB_GLYCOPEPTIDES %in% AB_LIPOGLYCOPEPTIDES]
-AB_LINCOSAMIDES <- antibiotics %>% filter(atc_group2 %like% "lincosamide" | (group %like% "lincosamide" & is.na(atc_group2))) %>% pull(ab)
-AB_MACROLIDES <- antibiotics %>% filter(atc_group2 %like% "macrolide" | (group %like% "macrolide" & is.na(atc_group2))) %>% pull(ab)
-AB_OXAZOLIDINONES <- antibiotics %>% filter(group %like% "oxazolidinone") %>% pull(ab)
-AB_PENICILLINS <- antibiotics %>% filter(group %like% "penicillin") %>% pull(ab)
-AB_POLYMYXINS <- antibiotics %>% filter(group %like% "polymyxin") %>% pull(ab)
-AB_QUINOLONES <- antibiotics %>% filter(group %like% "quinolone") %>% pull(ab)
-AB_STREPTOGRAMINS <- antibiotics %>% filter(atc_group2 %like% "streptogramin") %>% pull(ab)
-AB_TETRACYCLINES <- antibiotics %>% filter(group %like% "tetracycline") %>% pull(ab)
-AB_TETRACYCLINES_EXCEPT_TGC <- AB_TETRACYCLINES[AB_TETRACYCLINES != "TGC"]
-AB_TRIMETHOPRIMS <- antibiotics %>% filter(group %like% "trimethoprim") %>% pull(ab)
-AB_UREIDOPENICILLINS <- as.ab(c("PIP", "TZP", "AZL", "MEZ"))
-AB_BETALACTAMS <- c(AB_PENICILLINS, AB_CEPHALOSPORINS, AB_CARBAPENEMS)
-# this will be used for documentation:
-DEFINED_AB_GROUPS <- ls(envir = globalenv())
-DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab]
-create_AB_lookup <- function() {
-  AB_lookup <- AMR::antibiotics
-  AB_lookup$generalised_name <- generalise_antibiotic_name(AB_lookup$name)
-  AB_lookup$generalised_synonyms <- lapply(AB_lookup$synonyms, generalise_antibiotic_name)
-  AB_lookup$generalised_abbreviations <- lapply(AB_lookup$abbreviations, generalise_antibiotic_name)
-  AB_lookup$generalised_loinc <- lapply(AB_lookup$loinc, generalise_antibiotic_name)
-  AB_lookup$generalised_all <- unname(lapply(as.list(as.data.frame(t(AB_lookup[, 
-                                                                               c("ab", "atc", "cid", "name",
-                                                                                 colnames(AB_lookup)[colnames(AB_lookup) %like% "generalised"]),
-                                                                               drop = FALSE]),
-                                                                   stringsAsFactors = FALSE)),
-                                             function(x) {
-                                               x <- generalise_antibiotic_name(unname(unlist(x)))
-                                               x[x != ""]
-                                             }))
-  AB_lookup[, colnames(AB_lookup)[colnames(AB_lookup) %like% "^generalised"]]
-}
-AB_LOOKUP <- create_AB_lookup()
-
-# Export to package as internal data ----
-usethis::use_data(EUCAST_RULES_DF, 
-                  TRANSLATIONS,
-                  LANGUAGES_SUPPORTED,
-                  # EXAMPLE_ISOLATES,
-                  MO_CONS,
-                  MO_COPS,
-                  MO_STREP_ABCG,
-                  MO_FULLNAME_LOWER,
-                  AB_LOOKUP,
-                  AB_AMINOGLYCOSIDES,
-                  AB_AMINOPENICILLINS,
-                  AB_ANTIFUNGALS,
-                  AB_ANTIMYCOBACTERIALS,
-                  AB_CARBAPENEMS,
-                  AB_CEPHALOSPORINS,
-                  AB_CEPHALOSPORINS_1ST,
-                  AB_CEPHALOSPORINS_2ND,
-                  AB_CEPHALOSPORINS_3RD,
-                  AB_CEPHALOSPORINS_4TH,
-                  AB_CEPHALOSPORINS_5TH,
-                  AB_CEPHALOSPORINS_EXCEPT_CAZ,
-                  AB_FLUOROQUINOLONES,
-                  AB_LIPOGLYCOPEPTIDES,
-                  AB_GLYCOPEPTIDES,
-                  AB_GLYCOPEPTIDES_EXCEPT_LIPO,
-                  AB_LINCOSAMIDES,
-                  AB_MACROLIDES,
-                  AB_OXAZOLIDINONES,
-                  AB_PENICILLINS,
-                  AB_POLYMYXINS,
-                  AB_QUINOLONES,
-                  AB_STREPTOGRAMINS,
-                  AB_TETRACYCLINES,
-                  AB_TETRACYCLINES_EXCEPT_TGC,
-                  AB_TRIMETHOPRIMS,
-                  AB_UREIDOPENICILLINS,
-                  AB_BETALACTAMS,
-                  DEFINED_AB_GROUPS,
-                  internal = TRUE,
-                  overwrite = TRUE,
-                  version = 2,
-                  compress = "xz")
-
-# Export data sets to the repository in different formats -----------------
-
-write_md5 <- function(object) {
-  conn <- file(paste0("data-raw/", deparse(substitute(object)), ".md5"))
-  writeLines(digest::digest(object, "md5"), conn)
-  close(conn)
-}
-changed_md5 <- function(object) {
-  tryCatch({
-    conn <- file(paste0("data-raw/", deparse(substitute(object)), ".md5"))
-    compared <- digest::digest(object, "md5") != readLines(con = conn)
-    close(conn)
-    compared
-  }, error = function(e) TRUE)
-}
-
-# give official names to ABs and MOs
-rsi <- dplyr::mutate(rsi_translation, ab = ab_name(ab), mo = mo_name(mo))
-if (changed_md5(rsi)) {
-  usethis::ui_info(paste0("Saving {usethis::ui_value('rsi_translation')} to {usethis::ui_value('/data-raw/')}"))
-  write_md5(rsi)
-  try(saveRDS(rsi, "data-raw/rsi_translation.rds", version = 2, compress = "xz"), silent = TRUE)
-  try(write.table(rsi, "data-raw/rsi_translation.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
-  try(haven::write_sas(rsi, "data-raw/rsi_translation.sas"), silent = TRUE)
-  try(haven::write_sav(rsi, "data-raw/rsi_translation.sav"), silent = TRUE)
-  try(haven::write_dta(rsi, "data-raw/rsi_translation.dta"), silent = TRUE)
-  try(openxlsx::write.xlsx(rsi, "data-raw/rsi_translation.xlsx"), silent = TRUE)
-}
-
-mo <- dplyr::mutate_if(microorganisms, ~!is.numeric(.), as.character)
-if (changed_md5(mo)) {
-  usethis::ui_info(paste0("Saving {usethis::ui_value('microorganisms')} to {usethis::ui_value('/data-raw/')}"))
-  write_md5(mo)
-  try(saveRDS(mo, "data-raw/microorganisms.rds", version = 2, compress = "xz"), silent = TRUE)
-  try(write.table(mo, "data-raw/microorganisms.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
-  try(haven::write_sas(dplyr::select(mo, -snomed), "data-raw/microorganisms.sas"), silent = TRUE)
-  try(haven::write_sav(dplyr::select(mo, -snomed), "data-raw/microorganisms.sav"), silent = TRUE)
-  try(haven::write_dta(dplyr::select(mo, -snomed), "data-raw/microorganisms.dta"), silent = TRUE)
-  try(openxlsx::write.xlsx(mo, "data-raw/microorganisms.xlsx"), silent = TRUE)
-}
-
-if (changed_md5(microorganisms.old)) {
-  usethis::ui_info(paste0("Saving {usethis::ui_value('microorganisms.old')} to {usethis::ui_value('/data-raw/')}"))
-  write_md5(microorganisms.old)
-  try(saveRDS(microorganisms.old, "data-raw/microorganisms.old.rds", version = 2, compress = "xz"), silent = TRUE)
-  try(write.table(microorganisms.old, "data-raw/microorganisms.old.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
-  try(haven::write_sas(microorganisms.old, "data-raw/microorganisms.old.sas"), silent = TRUE)
-  try(haven::write_sav(microorganisms.old, "data-raw/microorganisms.old.sav"), silent = TRUE)
-  try(haven::write_dta(microorganisms.old, "data-raw/microorganisms.old.dta"), silent = TRUE)
-  try(openxlsx::write.xlsx(microorganisms.old, "data-raw/microorganisms.old.xlsx"), silent = TRUE)
-}
-
-ab <- dplyr::mutate_if(antibiotics, ~!is.numeric(.), as.character)
-if (changed_md5(ab)) {
-  usethis::ui_info(paste0("Saving {usethis::ui_value('antibiotics')} to {usethis::ui_value('/data-raw/')}"))
-  write_md5(ab)
-  try(saveRDS(ab, "data-raw/antibiotics.rds", version = 2, compress = "xz"), silent = TRUE)
-  try(write.table(ab, "data-raw/antibiotics.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
-  try(haven::write_sas(ab, "data-raw/antibiotics.sas"), silent = TRUE)
-  try(haven::write_sav(ab, "data-raw/antibiotics.sav"), silent = TRUE)
-  try(haven::write_dta(ab, "data-raw/antibiotics.dta"), silent = TRUE)
-  try(openxlsx::write.xlsx(ab, "data-raw/antibiotics.xlsx"), silent = TRUE)
-}
-
-av <- dplyr::mutate_if(antivirals, ~!is.numeric(.), as.character)
-if (changed_md5(av)) {
-  usethis::ui_info(paste0("Saving {usethis::ui_value('antivirals')} to {usethis::ui_value('/data-raw/')}"))
-  write_md5(av)
-  try(saveRDS(av, "data-raw/antivirals.rds", version = 2, compress = "xz"), silent = TRUE)
-  try(write.table(av, "data-raw/antivirals.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
-  try(haven::write_sas(av, "data-raw/antivirals.sas"), silent = TRUE)
-  try(haven::write_sav(av, "data-raw/antivirals.sav"), silent = TRUE)
-  try(haven::write_dta(av, "data-raw/antivirals.dta"), silent = TRUE)
-  try(openxlsx::write.xlsx(av, "data-raw/antivirals.xlsx"), silent = TRUE)
-}
-
-# give official names to ABs and MOs
-intrinsicR <- data.frame(microorganism = mo_name(intrinsic_resistant$mo),
-                         antibiotic = ab_name(intrinsic_resistant$ab),
-                         stringsAsFactors = FALSE)
-if (changed_md5(intrinsicR)) {
-  usethis::ui_info(paste0("Saving {usethis::ui_value('intrinsic_resistant')} to {usethis::ui_value('/data-raw/')}"))
-  write_md5(intrinsicR)
-  try(saveRDS(intrinsicR, "data-raw/intrinsic_resistant.rds", version = 2, compress = "xz"), silent = TRUE)
-  try(write.table(intrinsicR, "data-raw/intrinsic_resistant.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
-  try(haven::write_sas(intrinsicR, "data-raw/intrinsic_resistant.sas"), silent = TRUE)
-  try(haven::write_sav(intrinsicR, "data-raw/intrinsic_resistant.sav"), silent = TRUE)
-  try(haven::write_dta(intrinsicR, "data-raw/intrinsic_resistant.dta"), silent = TRUE)
-  try(openxlsx::write.xlsx(intrinsicR, "data-raw/intrinsic_resistant.xlsx"), silent = TRUE)
-}
-
-if (changed_md5(dosage)) {
-  usethis::ui_info(paste0("Saving {usethis::ui_value('dosage')} to {usethis::ui_value('/data-raw/')}"))
-  write_md5(dosage)
-  try(saveRDS(dosage, "data-raw/dosage.rds", version = 2, compress = "xz"), silent = TRUE)
-  try(write.table(dosage, "data-raw/dosage.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
-  try(haven::write_sas(dosage, "data-raw/dosage.sas"), silent = TRUE)
-  try(haven::write_sav(dosage, "data-raw/dosage.sav"), silent = TRUE)
-  try(haven::write_dta(dosage, "data-raw/dosage.dta"), silent = TRUE)
-  try(openxlsx::write.xlsx(dosage, "data-raw/dosage.xlsx"), silent = TRUE)
-}
-
-# remove leftovers from global env
-current_globalenv <- ls(envir = globalenv())
-rm(list = current_globalenv[!current_globalenv %in% old_globalenv])
-rm(current_globalenv)

data-raw/_language_update.R

@@ -0,0 +1,91 @@
+# ==================================================================== #
+# TITLE                                                                #
+# Antimicrobial Resistance (AMR) Data Analysis for R                   #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# LICENCE                                                              #
+# (c) 2018-2022 Berends MS, Luz CF et al.                              #
+# Developed at the University of Groningen, the Netherlands, in        #
+# collaboration with non-profit organisations Certe Medical            #
+# Diagnostics & Advice, and University Medical Center Groningen.       #
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+# Run this file to update the languages used in the packages:
+# source("data-raw/_language_update.R")
+
+if (!file.exists("DESCRIPTION") || !"Package: AMR" %in% readLines("DESCRIPTION")) {
+  stop("Be sure to run this script in the root location of the AMR package folder.\n",
+    "Working directory expected to contain the DESCRIPTION file of the AMR package.\n",
+    "Current working directory: ", getwd(),
+    call. = FALSE
+  )
+}
+
+# save old global env to restore later
+lang_env <- new.env(hash = FALSE)
+
+# load current internal data into new env
+load("R/sysdata.rda", envir = lang_env)
+
+# replace language objects with updates
+message("Reading translation file...")
+lang_env$TRANSLATIONS <- utils::read.delim(
+  file = "data-raw/translations.tsv",
+  sep = "\t",
+  stringsAsFactors = FALSE,
+  header = TRUE,
+  blank.lines.skip = TRUE,
+  fill = TRUE,
+  strip.white = TRUE,
+  encoding = "UTF-8",
+  fileEncoding = "UTF-8",
+  na.strings = c(NA, "", NULL),
+  allowEscapes = TRUE, # else "\\1" will be imported as "\\\\1"
+  quote = ""
+)
+
+lang_env$LANGUAGES_SUPPORTED_NAMES <- c(
+  list(en = list(exonym = "English", endonym = "English")),
+  lapply(
+    lang_env$TRANSLATIONS[, which(nchar(colnames(lang_env$TRANSLATIONS)) == 2), drop = FALSE],
+    function(x) list(exonym = x[1], endonym = x[2])
+  )
+)
+
+lang_env$LANGUAGES_SUPPORTED <- names(lang_env$LANGUAGES_SUPPORTED_NAMES)
+
+# save env to internal package data
+# usethis::use_data() does not allow to save a list :(
+message("Saving to internal data...")
+save(
+  list = names(lang_env),
+  file = "R/sysdata.rda",
+  ascii = FALSE,
+  version = 2,
+  compress = "xz",
+  envir = lang_env
+)
+
+rm(lang_env)
+
+if ("roxygen2" %in% utils::installed.packages()) {
+  message("Updating package documentation...")
+  suppressMessages(roxygen2::roxygenise(package.dir = "."))
+} else {
+  message("NOTE: please install the roxygen2 package to update package documentation, and run this script again.")
+}
+
+message("Done!")

data-raw/_pre_commit_hook.R

@@ -0,0 +1,503 @@
+# ==================================================================== #
+# TITLE                                                                #
+# Antimicrobial Resistance (AMR) Data Analysis for R                   #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# LICENCE                                                              #
+# (c) 2018-2022 Berends MS, Luz CF et al.                              #
+# Developed at the University of Groningen, the Netherlands, in        #
+# collaboration with non-profit organisations Certe Medical            #
+# Diagnostics & Advice, and University Medical Center Groningen.       #
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+# Run this file to update the package using:
+# source("data-raw/_pre_commit_hook.R")
+
+library(dplyr, warn.conflicts = FALSE)
+devtools::load_all(quiet = TRUE)
+
+suppressMessages(set_AMR_locale("English"))
+
+old_globalenv <- ls(envir = globalenv())
+
+# Save internal data to R/sysdata.rda -------------------------------------
+
+# See 'data-raw/eucast_rules.tsv' for the EUCAST reference file
+EUCAST_RULES_DF <- utils::read.delim(
+  file = "data-raw/eucast_rules.tsv",
+  skip = 10,
+  sep = "\t",
+  stringsAsFactors = FALSE,
+  header = TRUE,
+  strip.white = TRUE,
+  na = c(NA, "", NULL)
+) %>%
+  # take the order of the reference.rule_group column in the original data file
+  mutate(
+    reference.rule_group = factor(reference.rule_group,
+      levels = unique(reference.rule_group),
+      ordered = TRUE
+    ),
+    sorting_rule = ifelse(grepl("^Table", reference.rule, ignore.case = TRUE), 1, 2)
+  ) %>%
+  arrange(
+    reference.rule_group,
+    reference.version,
+    sorting_rule,
+    reference.rule
+  ) %>%
+  mutate(reference.rule_group = as.character(reference.rule_group)) %>%
+  select(-sorting_rule)
+
+TRANSLATIONS <- utils::read.delim(
+  file = "data-raw/translations.tsv",
+  sep = "\t",
+  stringsAsFactors = FALSE,
+  header = TRUE,
+  blank.lines.skip = TRUE,
+  fill = TRUE,
+  strip.white = TRUE,
+  encoding = "UTF-8",
+  fileEncoding = "UTF-8",
+  na.strings = c(NA, "", NULL),
+  allowEscapes = TRUE, # else "\\1" will be imported as "\\\\1"
+  quote = ""
+)
+
+LANGUAGES_SUPPORTED_NAMES <- c(
+  list(en = list(exonym = "English", endonym = "English")),
+  lapply(
+    TRANSLATIONS[, which(nchar(colnames(TRANSLATIONS)) == 2), drop = FALSE],
+    function(x) list(exonym = x[1], endonym = x[2])
+  )
+)
+
+LANGUAGES_SUPPORTED <- names(LANGUAGES_SUPPORTED_NAMES)
+
+# vectors of CoNS and CoPS, improves speed in as.mo()
+create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
+  # Determination of which staphylococcal species are CoNS/CoPS according to:
+  # - Becker et al. 2014, PMID 25278577
+  # - Becker et al. 2019, PMID 30872103
+  # - Becker et al. 2020, PMID 32056452
+  # this function returns class <mo>
+  MO_staph <- AMR::microorganisms
+  MO_staph <- MO_staph[which(MO_staph$genus == "Staphylococcus"), , drop = FALSE]
+  if (type == "CoNS") {
+    MO_staph[which(MO_staph$species %in% c(
+      "coagulase-negative", "argensis", "arlettae",
+      "auricularis", "borealis", "caeli", "capitis", "caprae",
+      "carnosus", "casei", "chromogenes", "cohnii", "condimenti",
+      "croceilyticus",
+      "debuckii", "devriesei", "edaphicus", "epidermidis",
+      "equorum", "felis", "fleurettii", "gallinarum",
+      "haemolyticus", "hominis", "jettensis", "kloosii",
+      "lentus", "lugdunensis", "massiliensis", "microti",
+      "muscae", "nepalensis", "pasteuri", "petrasii",
+      "pettenkoferi", "piscifermentans", "pragensis", "pseudoxylosus",
+      "pulvereri", "rostri", "saccharolyticus", "saprophyticus",
+      "sciuri", "simulans", "stepanovicii", "succinus",
+      "ureilyticus",
+      "vitulinus", "vitulus", "warneri", "xylosus",
+      "caledonicus", "canis",
+      "durrellii", "lloydii"
+    ) |
+      (MO_staph$species == "schleiferi" & MO_staph$subspecies %in% c("schleiferi", ""))),
+    "mo",
+    drop = TRUE
+    ]
+  } else if (type == "CoPS") {
+    MO_staph[which(MO_staph$species %in% c(
+      "coagulase-positive", "coagulans",
+      "agnetis", "argenteus",
+      "cornubiensis",
+      "delphini", "lutrae",
+      "hyicus", "intermedius",
+      "pseudintermedius", "pseudointermedius",
+      "schweitzeri", "simiae",
+      "roterodami"
+    ) |
+      (MO_staph$species == "schleiferi" & MO_staph$subspecies == "coagulans")),
+    "mo",
+    drop = TRUE
+    ]
+  }
+}
+create_MO_fullname_lower <- function() {
+  MO_lookup <- AMR::microorganisms
+  # use this paste instead of `fullname` to work with Viridans Group Streptococci, etc.
+  MO_lookup$fullname_lower <- tolower(trimws(paste(
+    MO_lookup$genus,
+    MO_lookup$species,
+    MO_lookup$subspecies
+  )))
+  ind <- MO_lookup$genus == "" | grepl("^[(]unknown ", MO_lookup$fullname, perl = TRUE)
+  MO_lookup[ind, "fullname_lower"] <- tolower(MO_lookup[ind, "fullname", drop = TRUE])
+  MO_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", MO_lookup$fullname_lower, perl = TRUE))
+  MO_lookup$fullname_lower
+}
+MO_CONS <- create_species_cons_cops("CoNS")
+MO_COPS <- create_species_cons_cops("CoPS")
+MO_STREP_ABCG <- as.mo(MO_lookup[which(MO_lookup$genus == "Streptococcus"), "mo", drop = TRUE], Lancefield = TRUE) %in% c("B_STRPT_GRPA", "B_STRPT_GRPB", "B_STRPT_GRPC", "B_STRPT_GRPG")
+MO_FULLNAME_LOWER <- create_MO_fullname_lower()
+MO_PREVALENT_GENERA <- c(
+  "Absidia", "Acholeplasma", "Acremonium", "Actinotignum", "Aedes", "Alistipes", "Alloprevotella",
+  "Alternaria", "Anaerosalibacter", "Ancylostoma", "Angiostrongylus", "Anisakis", "Anopheles",
+  "Apophysomyces", "Arachnia", "Aspergillus", "Aureobasidium", "Bacteroides", "Basidiobolus",
+  "Beauveria", "Bergeyella", "Blastocystis", "Blastomyces", "Borrelia", "Brachyspira", "Branhamella",
+  "Butyricimonas", "Candida", "Capillaria", "Capnocytophaga", "Catabacter", "Cetobacterium", "Chaetomium",
+  "Chlamydia", "Chlamydophila", "Chryseobacterium", "Chrysonilia", "Cladophialophora", "Cladosporium",
+  "Conidiobolus", "Contracaecum", "Cordylobia", "Cryptococcus", "Curvularia", "Deinococcus", "Demodex",
+  "Dermatobia", "Diphyllobothrium", "Dirofilaria", "Dysgonomonas", "Echinostoma", "Elizabethkingia",
+  "Empedobacter", "Enterobius", "Exophiala", "Exserohilum", "Fasciola", "Flavobacterium", "Fonsecaea",
+  "Fusarium", "Fusobacterium", "Giardia", "Haloarcula", "Halobacterium", "Halococcus", "Hendersonula",
+  "Heterophyes", "Histoplasma", "Hymenolepis", "Hypomyces", "Hysterothylacium", "Lelliottia",
+  "Leptosphaeria", "Leptotrichia", "Lucilia", "Lumbricus", "Malassezia", "Malbranchea", "Metagonimus",
+  "Microsporum", "Mortierella", "Mucor", "Mycocentrospora", "Mycoplasma", "Myroides", "Necator",
+  "Nectria", "Ochroconis", "Odoribacter", "Oesophagostomum", "Oidiodendron", "Opisthorchis",
+  "Ornithobacterium", "Parabacteroides", "Pediculus", "Pedobacter", "Phlebotomus", "Phocaeicola",
+  "Phocanema", "Phoma", "Piedraia", "Pithomyces", "Pityrosporum", "Porphyromonas", "Prevotella",
+  "Pseudallescheria", "Pseudoterranova", "Pulex", "Rhizomucor", "Rhizopus", "Rhodotorula", "Riemerella",
+  "Saccharomyces", "Sarcoptes", "Scolecobasidium", "Scopulariopsis", "Scytalidium", "Sphingobacterium",
+  "Spirometra", "Spiroplasma", "Sporobolomyces", "Stachybotrys", "Streptobacillus", "Strongyloides",
+  "Syngamus", "Taenia", "Tannerella", "Tenacibaculum", "Terrimonas", "Toxocara", "Treponema", "Trichinella",
+  "Trichobilharzia", "Trichoderma", "Trichomonas", "Trichophyton", "Trichosporon", "Trichostrongylus",
+  "Trichuris", "Tritirachium", "Trombicula", "Tunga", "Ureaplasma", "Victivallis", "Wautersiella",
+  "Weeksella", "Wuchereria"
+)
+
+# antibiotic groups
+# (these will also be used for eucast_rules() and understanding data-raw/eucast_rules.tsv)
+globalenv_before_ab <- c(ls(envir = globalenv()), "globalenv_before_ab")
+AB_AMINOGLYCOSIDES <- antibiotics %>%
+  filter(group %like% "aminoglycoside") %>%
+  pull(ab)
+AB_AMINOPENICILLINS <- as.ab(c("AMP", "AMX"))
+AB_ANTIFUNGALS <- AB_lookup %>%
+  filter(group %like% "antifungal") %>%
+  pull(ab)
+AB_ANTIMYCOBACTERIALS <- AB_lookup %>%
+  filter(group %like% "antimycobacterial") %>%
+  pull(ab)
+AB_CARBAPENEMS <- antibiotics %>%
+  filter(group %like% "carbapenem") %>%
+  pull(ab)
+AB_CEPHALOSPORINS <- antibiotics %>%
+  filter(group %like% "cephalosporin") %>%
+  pull(ab)
+AB_CEPHALOSPORINS_1ST <- antibiotics %>%
+  filter(group %like% "cephalosporin.*1") %>%
+  pull(ab)
+AB_CEPHALOSPORINS_2ND <- antibiotics %>%
+  filter(group %like% "cephalosporin.*2") %>%
+  pull(ab)
+AB_CEPHALOSPORINS_3RD <- antibiotics %>%
+  filter(group %like% "cephalosporin.*3") %>%
+  pull(ab)
+AB_CEPHALOSPORINS_4TH <- antibiotics %>%
+  filter(group %like% "cephalosporin.*4") %>%
+  pull(ab)
+AB_CEPHALOSPORINS_5TH <- antibiotics %>%
+  filter(group %like% "cephalosporin.*5") %>%
+  pull(ab)
+AB_CEPHALOSPORINS_EXCEPT_CAZ <- AB_CEPHALOSPORINS[AB_CEPHALOSPORINS != "CAZ"]
+AB_FLUOROQUINOLONES <- antibiotics %>%
+  filter(atc_group2 %like% "fluoroquinolone" | (group %like% "quinolone" & is.na(atc_group2))) %>%
+  pull(ab)
+AB_GLYCOPEPTIDES <- antibiotics %>%
+  filter(group %like% "glycopeptide") %>%
+  pull(ab)
+AB_LIPOGLYCOPEPTIDES <- as.ab(c("DAL", "ORI", "TLV")) # dalba/orita/tela
+AB_GLYCOPEPTIDES_EXCEPT_LIPO <- AB_GLYCOPEPTIDES[!AB_GLYCOPEPTIDES %in% AB_LIPOGLYCOPEPTIDES]
+AB_LINCOSAMIDES <- antibiotics %>%
+  filter(atc_group2 %like% "lincosamide" | (group %like% "lincosamide" & is.na(atc_group2))) %>%
+  pull(ab)
+AB_MACROLIDES <- antibiotics %>%
+  filter(atc_group2 %like% "macrolide" | (group %like% "macrolide" & is.na(atc_group2))) %>%
+  pull(ab)
+AB_OXAZOLIDINONES <- antibiotics %>%
+  filter(group %like% "oxazolidinone") %>%
+  pull(ab)
+AB_PENICILLINS <- antibiotics %>%
+  filter(group %like% "penicillin") %>%
+  pull(ab)
+AB_POLYMYXINS <- antibiotics %>%
+  filter(group %like% "polymyxin") %>%
+  pull(ab)
+AB_QUINOLONES <- antibiotics %>%
+  filter(group %like% "quinolone") %>%
+  pull(ab)
+AB_STREPTOGRAMINS <- antibiotics %>%
+  filter(atc_group2 %like% "streptogramin") %>%
+  pull(ab)
+AB_TETRACYCLINES <- antibiotics %>%
+  filter(group %like% "tetracycline") %>%
+  pull(ab)
+AB_TETRACYCLINES_EXCEPT_TGC <- AB_TETRACYCLINES[AB_TETRACYCLINES != "TGC"]
+AB_TRIMETHOPRIMS <- antibiotics %>%
+  filter(group %like% "trimethoprim") %>%
+  pull(ab)
+AB_UREIDOPENICILLINS <- as.ab(c("PIP", "TZP", "AZL", "MEZ"))
+AB_BETALACTAMS <- c(AB_PENICILLINS, AB_CEPHALOSPORINS, AB_CARBAPENEMS)
+# this will be used for documentation:
+DEFINED_AB_GROUPS <- ls(envir = globalenv())
+DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab]
+create_AB_lookup <- function() {
+  AB_lookup <- AMR::antibiotics
+  AB_lookup$generalised_name <- generalise_antibiotic_name(AB_lookup$name)
+  AB_lookup$generalised_synonyms <- lapply(AB_lookup$synonyms, generalise_antibiotic_name)
+  AB_lookup$generalised_abbreviations <- lapply(AB_lookup$abbreviations, generalise_antibiotic_name)
+  AB_lookup$generalised_loinc <- lapply(AB_lookup$loinc, generalise_antibiotic_name)
+  AB_lookup$generalised_all <- unname(lapply(
+    as.list(as.data.frame(t(AB_lookup[,
+      c(
+        "ab", "atc", "cid", "name",
+        colnames(AB_lookup)[colnames(AB_lookup) %like% "generalised"]
+      ),
+      drop = FALSE
+    ]),
+    stringsAsFactors = FALSE
+    )),
+    function(x) {
+      x <- generalise_antibiotic_name(unname(unlist(x)))
+      x[x != ""]
+    }
+  ))
+  AB_lookup[, colnames(AB_lookup)[colnames(AB_lookup) %like% "^generalised"]]
+}
+AB_LOOKUP <- create_AB_lookup()
+
+# Export to package as internal data ----
+usethis::ui_info(paste0("Saving {usethis::ui_value('sysdata.rda')} to {usethis::ui_value('R/')}"))
+suppressMessages(usethis::use_data(EUCAST_RULES_DF,
+  TRANSLATIONS,
+  LANGUAGES_SUPPORTED_NAMES,
+  LANGUAGES_SUPPORTED,
+  MO_CONS,
+  MO_COPS,
+  MO_STREP_ABCG,
+  MO_FULLNAME_LOWER,
+  MO_PREVALENT_GENERA,
+  AB_LOOKUP,
+  AB_AMINOGLYCOSIDES,
+  AB_AMINOPENICILLINS,
+  AB_ANTIFUNGALS,
+  AB_ANTIMYCOBACTERIALS,
+  AB_CARBAPENEMS,
+  AB_CEPHALOSPORINS,
+  AB_CEPHALOSPORINS_1ST,
+  AB_CEPHALOSPORINS_2ND,
+  AB_CEPHALOSPORINS_3RD,
+  AB_CEPHALOSPORINS_4TH,
+  AB_CEPHALOSPORINS_5TH,
+  AB_CEPHALOSPORINS_EXCEPT_CAZ,
+  AB_FLUOROQUINOLONES,
+  AB_LIPOGLYCOPEPTIDES,
+  AB_GLYCOPEPTIDES,
+  AB_GLYCOPEPTIDES_EXCEPT_LIPO,
+  AB_LINCOSAMIDES,
+  AB_MACROLIDES,
+  AB_OXAZOLIDINONES,
+  AB_PENICILLINS,
+  AB_POLYMYXINS,
+  AB_QUINOLONES,
+  AB_STREPTOGRAMINS,
+  AB_TETRACYCLINES,
+  AB_TETRACYCLINES_EXCEPT_TGC,
+  AB_TRIMETHOPRIMS,
+  AB_UREIDOPENICILLINS,
+  AB_BETALACTAMS,
+  DEFINED_AB_GROUPS,
+  internal = TRUE,
+  overwrite = TRUE,
+  version = 2,
+  compress = "xz"
+))
+
+# Export data sets to the repository in different formats -----------------
+
+for (pkg in c("haven", "openxlsx", "arrow")) {
+  if (!pkg %in% rownames(utils::installed.packages())) {
+    message("NOTE: package '", pkg, "' not installed! Ignoring export where this package is required.")
+  }
+}
+if ("digest" %in% rownames(utils::installed.packages())) {
+  md5 <- function(object) digest::digest(object, "md5")
+} else {
+  # will write all files anyway, since MD5 hash cannot be determined
+  md5 <- function(object) "unknown-md5-hash"
+}
+
+write_md5 <- function(object) {
+  conn <- file(paste0("data-raw/", deparse(substitute(object)), ".md5"))
+  writeLines(md5(object), conn)
+  close(conn)
+}
+changed_md5 <- function(object) {
+  tryCatch(
+    {
+      conn <- file(paste0("data-raw/", deparse(substitute(object)), ".md5"))
+      compared <- md5(object) != readLines(con = conn)
+      close(conn)
+      compared
+    },
+    error = function(e) TRUE
+  )
+}
+
+# give official names to ABs and MOs
+rsi <- rsi_translation %>%
+  mutate(mo_name = mo_name(mo, language = NULL), .after = mo) %>%
+  mutate(ab_name = ab_name(ab, language = NULL), .after = ab)
+if (changed_md5(rsi)) {
+  usethis::ui_info(paste0("Saving {usethis::ui_value('rsi_translation')} to {usethis::ui_value('data-raw/')}"))
+  write_md5(rsi)
+  try(saveRDS(rsi, "data-raw/rsi_translation.rds", version = 2, compress = "xz"), silent = TRUE)
+  try(write.table(rsi, "data-raw/rsi_translation.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
+  try(haven::write_sas(rsi, "data-raw/rsi_translation.sas"), silent = TRUE)
+  try(haven::write_sav(rsi, "data-raw/rsi_translation.sav"), silent = TRUE)
+  try(haven::write_dta(rsi, "data-raw/rsi_translation.dta"), silent = TRUE)
+  try(openxlsx::write.xlsx(rsi, "data-raw/rsi_translation.xlsx"), silent = TRUE)
+  try(arrow::write_feather(rsi, "data-raw/rsi_translation.feather"), silent = TRUE)
+  try(arrow::write_parquet(rsi, "data-raw/rsi_translation.parquet"), silent = TRUE)
+}
+
+if (changed_md5(microorganisms)) {
+  usethis::ui_info(paste0("Saving {usethis::ui_value('microorganisms')} to {usethis::ui_value('data-raw/')}"))
+  write_md5(microorganisms)
+  try(saveRDS(microorganisms, "data-raw/microorganisms.rds", version = 2, compress = "xz"), silent = TRUE)
+  try(write.table(mo, "data-raw/microorganisms.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
+  max_50_snomed <- sapply(microorganisms$snomed, function(x) paste(x[seq_len(min(50, length(x), na.rm = TRUE))], collapse = " "))
+  mo <- microorganisms
+  mo$snomed <- max_50_snomed
+  mo <- dplyr::mutate_if(mo, ~ !is.numeric(.), as.character)
+  try(haven::write_sas(mo, "data-raw/microorganisms.sas"), silent = TRUE)
+  try(haven::write_sav(mo, "data-raw/microorganisms.sav"), silent = TRUE)
+  try(haven::write_dta(mo, "data-raw/microorganisms.dta"), silent = TRUE)
+  try(openxlsx::write.xlsx(mo, "data-raw/microorganisms.xlsx"), silent = TRUE)
+  try(arrow::write_feather(microorganisms, "data-raw/microorganisms.feather"), silent = TRUE)
+  try(arrow::write_parquet(microorganisms, "data-raw/microorganisms.parquet"), silent = TRUE)
+}
+
+if (changed_md5(microorganisms.old)) {
+  usethis::ui_info(paste0("Saving {usethis::ui_value('microorganisms.old')} to {usethis::ui_value('data-raw/')}"))
+  write_md5(microorganisms.old)
+  try(saveRDS(microorganisms.old, "data-raw/microorganisms.old.rds", version = 2, compress = "xz"), silent = TRUE)
+  try(write.table(microorganisms.old, "data-raw/microorganisms.old.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
+  try(haven::write_sas(microorganisms.old, "data-raw/microorganisms.old.sas"), silent = TRUE)
+  try(haven::write_sav(microorganisms.old, "data-raw/microorganisms.old.sav"), silent = TRUE)
+  try(haven::write_dta(microorganisms.old, "data-raw/microorganisms.old.dta"), silent = TRUE)
+  try(openxlsx::write.xlsx(microorganisms.old, "data-raw/microorganisms.old.xlsx"), silent = TRUE)
+  try(arrow::write_feather(microorganisms.old, "data-raw/microorganisms.old.feather"), silent = TRUE)
+  try(arrow::write_parquet(microorganisms.old, "data-raw/microorganisms.old.parquet"), silent = TRUE)
+}
+
+ab <- dplyr::mutate_if(antibiotics, ~ !is.numeric(.), as.character)
+if (changed_md5(ab)) {
+  usethis::ui_info(paste0("Saving {usethis::ui_value('antibiotics')} to {usethis::ui_value('data-raw/')}"))
+  write_md5(ab)
+  try(saveRDS(antibiotics, "data-raw/antibiotics.rds", version = 2, compress = "xz"), silent = TRUE)
+  try(write.table(antibiotics, "data-raw/antibiotics.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
+  try(haven::write_sas(ab, "data-raw/antibiotics.sas"), silent = TRUE)
+  try(haven::write_sav(ab, "data-raw/antibiotics.sav"), silent = TRUE)
+  try(haven::write_dta(ab, "data-raw/antibiotics.dta"), silent = TRUE)
+  try(openxlsx::write.xlsx(ab, "data-raw/antibiotics.xlsx"), silent = TRUE)
+  try(arrow::write_feather(antibiotics, "data-raw/antibiotics.feather"), silent = TRUE)
+  try(arrow::write_parquet(antibiotics, "data-raw/antibiotics.parquet"), silent = TRUE)
+}
+
+av <- dplyr::mutate_if(antivirals, ~ !is.numeric(.), as.character)
+if (changed_md5(av)) {
+  usethis::ui_info(paste0("Saving {usethis::ui_value('antivirals')} to {usethis::ui_value('data-raw/')}"))
+  write_md5(av)
+  try(saveRDS(antivirals, "data-raw/antivirals.rds", version = 2, compress = "xz"), silent = TRUE)
+  try(write.table(av, "data-raw/antivirals.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
+  try(haven::write_sas(av, "data-raw/antivirals.sas"), silent = TRUE)
+  try(haven::write_sav(av, "data-raw/antivirals.sav"), silent = TRUE)
+  try(haven::write_dta(av, "data-raw/antivirals.dta"), silent = TRUE)
+  try(openxlsx::write.xlsx(av, "data-raw/antivirals.xlsx"), silent = TRUE)
+  try(arrow::write_feather(antivirals, "data-raw/antivirals.feather"), silent = TRUE)
+  try(arrow::write_parquet(antivirals, "data-raw/antivirals.parquet"), silent = TRUE)
+}
+
+# give official names to ABs and MOs
+intrinsicR <- data.frame(
+  microorganism = mo_name(intrinsic_resistant$mo, language = NULL),
+  antibiotic = ab_name(intrinsic_resistant$ab, language = NULL),
+  stringsAsFactors = FALSE
+)
+if (changed_md5(intrinsicR)) {
+  usethis::ui_info(paste0("Saving {usethis::ui_value('intrinsic_resistant')} to {usethis::ui_value('data-raw/')}"))
+  write_md5(intrinsicR)
+  try(saveRDS(intrinsicR, "data-raw/intrinsic_resistant.rds", version = 2, compress = "xz"), silent = TRUE)
+  try(write.table(intrinsicR, "data-raw/intrinsic_resistant.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
+  try(haven::write_sas(intrinsicR, "data-raw/intrinsic_resistant.sas"), silent = TRUE)
+  try(haven::write_sav(intrinsicR, "data-raw/intrinsic_resistant.sav"), silent = TRUE)
+  try(haven::write_dta(intrinsicR, "data-raw/intrinsic_resistant.dta"), silent = TRUE)
+  try(openxlsx::write.xlsx(intrinsicR, "data-raw/intrinsic_resistant.xlsx"), silent = TRUE)
+  try(arrow::write_feather(intrinsicR, "data-raw/intrinsic_resistant.feather"), silent = TRUE)
+  try(arrow::write_parquet(intrinsicR, "data-raw/intrinsic_resistant.parquet"), silent = TRUE)
+}
+
+if (changed_md5(dosage)) {
+  usethis::ui_info(paste0("Saving {usethis::ui_value('dosage')} to {usethis::ui_value('data-raw/')}"))
+  write_md5(dosage)
+  try(saveRDS(dosage, "data-raw/dosage.rds", version = 2, compress = "xz"), silent = TRUE)
+  try(write.table(dosage, "data-raw/dosage.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE)
+  try(haven::write_sas(dosage, "data-raw/dosage.sas"), silent = TRUE)
+  try(haven::write_sav(dosage, "data-raw/dosage.sav"), silent = TRUE)
+  try(haven::write_dta(dosage, "data-raw/dosage.dta"), silent = TRUE)
+  try(openxlsx::write.xlsx(dosage, "data-raw/dosage.xlsx"), silent = TRUE)
+  try(arrow::write_feather(dosage, "data-raw/dosage.feather"), silent = TRUE)
+  try(arrow::write_parquet(dosage, "data-raw/dosage.parquet"), silent = TRUE)
+}
+
+suppressMessages(reset_AMR_locale())
+
+# remove leftovers from global env
+current_globalenv <- ls(envir = globalenv())
+rm(list = current_globalenv[!current_globalenv %in% old_globalenv])
+rm(current_globalenv)
+
+devtools::load_all(quiet = TRUE)
+suppressMessages(set_AMR_locale("English"))
+
+# Update URLs -------------------------------------------------------------
+usethis::ui_info("Checking URLs for redirects")
+invisible(capture.output(urlchecker::url_update()))
+
+
+# Document pkg ------------------------------------------------------------
+usethis::ui_info("Documenting package")
+suppressMessages(devtools::document(quiet = TRUE))
+
+
+# Style pkg ---------------------------------------------------------------
+usethis::ui_info("Styling package")
+invisible(capture.output(styler::style_pkg(
+  style = styler::tidyverse_style,
+  filetype = c("R", "Rmd")
+)))
+invisible(capture.output(styler::style_dir(
+  path = "inst", # unit tests
+  style = styler::tidyverse_style,
+  filetype = c("R", "Rmd")
+)))
+
+
+# Finished ----------------------------------------------------------------
+usethis::ui_done("All done")
+suppressMessages(reset_AMR_locale())

data-raw/ab.md5

@@ -1 +1 @@
-4f082a7952a37133305f64d6f711e81e
+79ed9c5d9ddd2c270a5bbb579a920992

data-raw/antibiotics.txt

@@ -1,519 +1,2 @@
 "ab"	"cid"	"name"	"group"	"atc"	"atc_group1"	"atc_group2"	"abbreviations"	"synonyms"	"oral_ddd"	"oral_units"	"iv_ddd"	"iv_units"	"loinc"
-"AMA"	4649	"4-aminosalicylic acid"	"Antimycobacterials"	"J04AA01"	"Drugs for treatment of tuberculosis"	"Aminosalicylic acid and derivatives"	""	"c(\"aminopar\", \"aminosalicylic\", \"aminosalicylic acid\", \"aminosalyl\", \"aminox\", \"apacil\", \"deapasil\", \"entepas\", \"ferrosan\", \"gabbropas\", \"helipidyl\", \"hellipidyl\", \"neopasalate\", \"osacyl\", \"pamacyl\", \"pamisyl\", \"paramycin\", \"parasal\", \"parasalicil\", \"parasalindon\", \"pasalon\", \"pasara\", \"pascorbic\", \"pasdium\", \"paser granules\", \"paskalium\", \"pasmed\", \"pasnodia\", \"pasolac\", \"propasa\", \"rezipas\", \"teebacin\", \"wln: zr cq dvq\")"	12	"g"			"character(0)"
-"FCT"	3366	"5-fluorocytosine"	"Antifungals/antimycotics"	"D01AE21"	"Antifungals for topical use"	"Other antifungals for topical use"	"c(\"5flc\", \"fcu\", \"fluo\", \"fluy\")"	"c(\"alcobon\", \"ancobon\", \"ancotil\", \"ancotyl\", \"flucitosina\", \"flucystine\", \"flucytosin\", \"flucytosine\", \"flucytosinum\", \"flucytosone\", \"fluocytosine\", \"fluorcytosine\")"					"c(\"10974-4\", \"23805-5\", \"25142-1\", \"25143-9\", \"3639-2\", \"46218-4\")"
-"ACM"	6450012	"Acetylmidecamycin"	"Macrolides/lincosamides"				""	""					""
-"ASP"	49787020	"Acetylspiramycin"	"Macrolides/lincosamides"				""	"c(\"acetylspiramycin\", \"foromacidin b\", \"spiramycin ii\")"					"character(0)"
-"ALS"	8954	"Aldesulfone sodium"	"Other antibacterials"	"J04BA03"	"Drugs for treatment of lepra"	"Drugs for treatment of lepra"	""	"c(\"adesulfone sodium\", \"aldapsone\", \"aldesulfona sodica\", \"aldesulfone\", \"aldesulfone sodique\", \"aldesulfone sodium\", \"diamidin\", \"diasone\", \"diasone sodium\", \"diazon\", \"novotrone\", \"sodium aldesulphone\", \"sodium sulfoxone\", \"sulfoxone sodium\")"	0.33	"g"			"character(0)"
-"AMK"	37768	"Amikacin"	"Aminoglycosides"	"c(\"D06AX12\", \"J01GB06\", \"S01AA21\")"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	"c(\"ak\", \"ami\", \"amik\", \"amk\", \"an\")"	"c(\"amicacin\", \"amikacillin\", \"amikacin\", \"amikacin base\", \"amikacin dihydrate\", \"amikacin sulfate\", \"amikacina\", \"amikacine\", \"amikacinum\", \"amikavet\", \"amikin\", \"amiklin\", \"amikozit\", \"amukin\", \"arikace\", \"briclin\", \"lukadin\", \"mikavir\", \"pierami\", \"potentox\")"			1	"g"	"c(\"13546-7\", \"15098-7\", \"17798-0\", \"31097-9\", \"31098-7\", \"31099-5\", \"3319-1\", \"3320-9\", \"3321-7\", \"35669-1\", \"50802-8\", \"50803-6\", \"56628-1\", \"59378-0\", \"80972-3\")"
-"AKF"		"Amikacin/fosfomycin"	"Aminoglycosides"				""	""					""
-"AMX"	33613	"Amoxicillin"	"Beta-lactams/penicillins"	"J01CA04"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"c(\"ac\", \"amox\", \"amx\")"	"c(\"actimoxi\", \"amoclen\", \"amolin\", \"amopen\", \"amopenixin\", \"amoxibiotic\", \"amoxicaps\", \"amoxicilina\", \"amoxicillin\", \"amoxicilline\", \"amoxicillinum\", \"amoxiden\", \"amoxil\", \"amoxivet\", \"amoxy\", \"amoxycillin\", \"anemolin\", \"aspenil\", \"biomox\", \"bristamox\", \"cemoxin\", \"clamoxyl\", \"delacillin\", \"dispermox\", \"efpenix\", \"flemoxin\", \"hiconcil\", \"histocillin\", \"hydroxyampicillin\", \"ibiamox\", \"imacillin\", \"lamoxy\", \"metafarma capsules\", \"metifarma capsules\", \"moxacin\", \"moxatag\", \"ospamox\", \"pamoxicillin\", 
-\"piramox\", \"robamox\", \"sawamox pm\", \"tolodina\", \"unicillin\", \"utimox\", \"vetramox\")"	1.5	"g"	3	"g"	"c(\"16365-9\", \"25274-2\", \"3344-9\", \"80133-2\")"
-"AMC"	23665637	"Amoxicillin/clavulanic acid"	"Beta-lactams/penicillins"	"J01CR02"	"Beta-lactam antibacterials, penicillins"	"Combinations of penicillins, incl. beta-lactamase inhibitors"	"c(\"a/c\", \"amcl\", \"aml\", \"aug\", \"xl\")"	"c(\"amocla\", \"amoclan\", \"amoclav\", \"amoxsiklav\", \"augmentan\", \"augmentin\", \"augmentin xr\", \"augmentine\", \"auspilic\", \"clamentin\", \"clamobit\", \"clavamox\", \"clavinex\", \"clavoxilin plus\", \"clavulin\", \"clavumox\", \"coamoxiclav\", \"eumetinex\", \"kmoxilin\", \"spectramox\", \"spektramox\", \"viaclav\", \"xiclav\")"	1.5	"g"	3	"g"	"character(0)"
-"AXS"	465441	"Amoxicillin/sulbactam"	"Beta-lactams/penicillins"				""	""					""
-"AMB"	5280965	"Amphotericin B"	"Antifungals/antimycotics"	"c(\"A01AB04\", \"A07AA07\", \"G01AA03\", \"J02AA01\")"	"Antimycotics for systemic use"	"Antibiotics"	"c(\"amf\", \"amfb\", \"amph\")"	"c(\"abelcet\", \"abelecet\", \"ambisome\", \"amfotericina b\", \"amphocin\", \"amphomoronal\", \"amphortericin b\", \"amphotec\", \"amphotericin\", \"amphotericin b\", \"amphotericine b\", \"amphotericinum b\", \"amphozone\", \"anfotericine b\", \"fungilin\", \"fungisome\", \"fungisone\", \"fungizone\", \"halizon\")"	40	"mg"	35	"mg"	"c(\"16370-9\", \"3353-0\", \"3354-8\", \"40707-2\", \"40757-7\", \"49859-2\")"
-"AMH"		"Amphotericin B-high"	"Aminoglycosides"				"c(\"amfo b high\", \"amhl\", \"ampho b high\", \"amphotericin high\")"	""					""
-"AMP"	6249	"Ampicillin"	"Beta-lactams/penicillins"	"c(\"J01CA01\", \"S01AA19\")"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"c(\"am\", \"amp\", \"ampi\")"	"c(\"acillin\", \"adobacillin\", \"amblosin\", \"amcill\", \"amfipen\", \"amfipen v\", \"amipenix s\", \"ampichel\", \"ampicil\", \"ampicilina\", \"ampicillin\", \"ampicillin a\", \"ampicillin acid\", \"ampicillin anhydrate\", \"ampicillin anhydrous\", \"ampicillin base\", \"ampicillin sodium\", \"ampicillina\", \"ampicilline\", \"ampicillinum\", \"ampicin\", \"ampifarm\", \"ampikel\", \"ampimed\", \"ampipenin\", \"ampiscel\", \"ampisyn\", \"ampivax\", \"ampivet\", \"amplacilina\", \"amplin\", \"amplipenyl\", \"amplisom\", \"amplital\", \"anhydrous ampicillin\", \"austrapen\", 
-\"binotal\", \"bonapicillin\", \"britacil\", \"campicillin\", \"copharcilin\", \"delcillin\", \"deripen\", \"divercillin\", \"doktacillin\", \"duphacillin\", \"grampenil\", \"guicitrina\", \"guicitrine\", \"lifeampil\", \"marcillin\", \"morepen\", \"norobrittin\", \"nuvapen\", \"olin kid\", \"omnipen\", \"orbicilina\", \"pen a oral\", \"pen ampil\", \"penbristol\", \"penbritin\", \"penbritin paediatric\", \"penbritin syrup\", \"penbrock\", \"penicline\", \"penimic\", \"pensyn\", \"pentrex\", \"pentrexl\", \"pentrexyl\", \"pentritin\", \"pfizerpen a\", \"polycillin\", \"polyflex\", 
-\"ponecil\", \"princillin\", \"principen\", \"qidamp\", \"racenacillin\", \"rosampline\", \"roscillin\", \"semicillin\", \"semicillin r\", \"servicillin\", \"sumipanto\", \"synpenin\", \"texcillin\", \"tokiocillin\", \"tolomol\", \"totacillin\", \"totalciclina\", \"totapen\", \"trifacilina\", \"ukapen\", \"ultrabion\", \"ultrabron\", \"vampen\", \"viccillin\", \"viccillin s\", \"vidocillin\", \"wypicil\")"	2	"g"	6	"g"	"c(\"21066-6\", \"3355-5\", \"33562-0\", \"33919-2\", \"43883-8\", \"43884-6\", \"87604-5\")"
-"SAM"	119561	"Ampicillin/sulbactam"	"Beta-lactams/penicillins"	"J01CR01"	"Beta-lactam antibacterials, penicillins"	"Combinations of penicillins, incl. beta-lactamase inhibitors"	"c(\"a/s\", \"ab\", \"ams\", \"amsu\", \"apsu\", \"sam\")"	""			6	"g"	""
-"AMR"	73341	"Amprolium"	"Other antibacterials"				""	"c(\"amprocidum\", \"amprolio\", \"amprolium\", \"amprovine\")"					"character(0)"
-"ANI"	166548	"Anidulafungin"	"Antifungals/antimycotics"	"J02AX06"	"Antimycotics for systemic use"	"Other antimycotics for systemic use"	"anid"	"c(\"anidulafungin\", \"anidulafungina\", \"anidulafungine\", \"anidulafunginum\", \"ecalta\", \"eraxis\")"			0.1	"g"	"58420-1"
-"APL"	6602341	"Apalcillin"	"Beta-lactams/penicillins"				""	"c(\"apalcilina\", \"apalcillin\", \"apalcilline\", \"apalcillinum\")"					"character(0)"
-"APR"	3081545	"Apramycin"	"Aminoglycosides"				""	"c(\"ambylan\", \"apralan\", \"apramicina\", \"apramycin\", \"apramycine\", \"apramycinum\", \"nebramycin ii\")"					"character(0)"
-"ARB"	68682	"Arbekacin"	"Aminoglycosides"	"J01GB12"			""	"c(\"arbekacin\", \"arbekacina\", \"arbekacine\", \"arbekacini sulfas\", \"arbekacinum\", \"habekacin\", \"haberacin\")"			0.2	"g"	"character(0)"
-"APX"	71961	"Aspoxicillin"	"Beta-lactams/penicillins"	"J01CA19"			""	"c(\"aspoxicilina\", \"aspoxicillan\", \"aspoxicillin\", \"aspoxicilline\", \"aspoxicillinum\")"			4	"g"	"character(0)"
-"AST"	5284517	"Astromicin"	"Aminoglycosides"				""	"c(\"astromicin\", \"astromicin a\", \"astromicina\", \"astromicine\", \"astromicinum\", \"fortimicin a\")"					"character(0)"
-"AVB"	9835049	"Avibactam"	"Beta-lactams/penicillins"				""	"c(\"avibactam\", \"avibactam free acid\")"					"character(0)"
-"AVI"	71674	"Avilamycin"	"Other antibacterials"				""	"c(\"avilamycin\", \"avilamycina\", \"avilamycine\", \"avilamycinum\", \"surmax\")"					"character(0)"
-"AVO"	16131159	"Avoparcin"	"Glycopeptides"				""	""					""
-"AZD"	15574941	"Azidocillin"	"Beta-lactams/penicillins"	"J01CE04"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase sensitive penicillins"	""	"c(\"azidocilina\", \"azidocillin\", \"azidocillina\", \"azidocilline\", \"azidocillinum\")"	1.5	"g"			"character(0)"
-"AZM"	447043	"Azithromycin"	"Macrolides/lincosamides"	"c(\"J01FA10\", \"S01AA26\")"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	"c(\"az\", \"azi\", \"azit\", \"azm\")"	"c(\"aritromicina\", \"azasite\", \"azenil\", \"azifast\", \"azigram\", \"azimakrol\", \"azithramycine\", \"azithromycin\", \"azithromycine\", \"azithromycinum\", \"azitrocin\", \"azitromax\", \"azitromicina\", \"azitromicine\", \"azitromin\", \"aziwok\", \"aztrin\", \"azyter\", \"azythromycin\", \"hemomycin\", \"misultina\", \"mixoterin\", \"setron\", \"sumamed\", \"tromix\", \"trulimax\", \"zentavion\", \"zithrax\", \"zithromac\", \"zithromax\", \"zithromax iv\", \"zithromycin\", \"zitrim\", \"zitromax\", \"zitrotek\", \"zmax sr\")"	0.3	"g"	0.5	"g"	"c(\"16420-2\", \"25233-8\")"
-"AZL"	6479523	"Azlocillin"	"Beta-lactams/penicillins"	"J01CA09"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"c(\"az\", \"azl\", \"azlo\")"	""			12	"g"	""
-"ATM"	5742832	"Aztreonam"	"Beta-lactams/penicillins"	"J01DF01"	"Other beta-lactam antibacterials"	"Monobactams"	"c(\"at\", \"atm\", \"azm\", \"azt\", \"aztr\")"	"c(\"azactam\", \"azetreonam\", \"azthreonam\", \"aztreonam\", \"primbactam\")"			4	"g"	"c(\"16423-6\", \"25234-6\", \"3369-6\")"
-"AZA"		"Aztreonam/avibactam"	"Beta-lactams/penicillins"				""	""					""
-"ANC"		"Aztreonam/nacubactam"	"Beta-lactams/penicillins"				""	""					""
-"BAM"	441397	"Bacampicillin"	"Beta-lactams/penicillins"	"J01CA06"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	""	"c(\"bacampicilina\", \"bacampicillin\", \"bacampicilline\", \"bacampicillinum\", \"penglobe\")"	1.2	"g"			"character(0)"
-"BAC"	78358334	"Bacitracin zinc"	"Other antibacterials"	"R02AB04"			"baci"	""					""
-"BDQ"	5388906	"Bedaquiline"	"Other antibacterials"	"J04AK05"			""	"c(\"bedaquiline\", \"sirturo\")"	86	"mg"			"80637-2"
-"BEK"	439318	"Bekanamycin"	"Aminoglycosides"	"J01GB13"			""	"c(\"aminodeoxykanamycin\", \"becanamicina\", \"bekanamycin\", \"bekanamycine\", \"bekanamycinum\", \"nebramycin v\")"			0.6	"g"	"character(0)"
-"BNB"		"Benzathine benzylpenicillin"	"Beta-lactams/penicillins"	"J01CE08"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase sensitive penicillins"	""	""			3.6	"g"	""
-"BNP"	64725	"Benzathine phenoxymethylpenicillin"	"Beta-lactams/penicillins"	"J01CE10"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase sensitive penicillins"	""	"c(\"bicillin v\", \"biphecillin\")"	2	"g"			"character(0)"
-"PEN"	5904	"Benzylpenicillin"	"Beta-lactams/penicillins"	"c(\"J01CE01\", \"S01AA14\")"	"Combinations of antibacterials"	"Combinations of antibacterials"	"c(\"bepe\", \"pen\", \"peni\", \"peni g\", \"penicillin\", \"penicillin g\", \"pg\")"	"c(\"abbocillin\", \"ayercillin\", \"bencilpenicilina\", \"benzopenicillin\", \"benzyl penicillin\", \"benzylpenicillin\", \"benzylpenicillin g\", \"benzylpenicilline\", \"benzylpenicillinum\", \"bicillin\", \"cillora\", \"cilloral\", \"cilopen\", \"compocillin g\", \"cosmopen\", \"dropcillin\", \"free penicillin g\", \"free penicillin ii\", \"galofak\", \"gelacillin\", \"liquacillin\", \"megacillin\", \"pencillin g\", \"penicillin\", \"penicilling\", \"pentids\", \"permapen\", \"pfizerpen\", \"pfizerpen g\", \"pharmacillin\", \"pradupen\", \"specilline g\", \"ursopen\"
-)"			3.6	"g"	"3913-1"
-"BES"	10178705	"Besifloxacin"	"Quinolones"	"S01AE08"			""	"besifloxacin"					"character(0)"
-"BIA"	71339	"Biapenem"	"Carbapenems"	"J01DH05"			""	"c(\"biapenem\", \"biapenern\", \"bipenem\", \"omegacin\")"			1.2	"g"	"character(0)"
-"BCZ"	65807	"Bicyclomycin"	"Other antibacterials"				"c(\"\", \"bicozamycin\")"	"c(\"aizumycin\", \"bacfeed\", \"bacteron\", \"bicozamicina\", \"bicozamycin\", \"bicozamycine\", \"bicozamycinum\")"					"character(0)"
-"BDP"	68760	"Brodimoprim"	"Trimethoprims"	"J01EA02"	"Sulfonamides and trimethoprim"	"Trimethoprim and derivatives"	""	"c(\"brodimoprim\", \"brodimoprima\", \"brodimoprime\", \"brodimoprimum\", \"bromdimoprim\", \"hyprim\", \"unitrim\")"	0.2	"g"			"character(0)"
-"BUT"	47472	"Butoconazole"	"Antifungals/antimycotics"	"G01AF15"			""	"c(\"butaconazole\", \"butoconazol\", \"butoconazole\", \"butoconazolum\", \"compositenstarke\", \"dahlin\", \"femstat\", \"gynofort\", \"polyfructosanum\")"					"character(0)"
-"CDZ"	44242317	"Cadazolid"	"Oxazolidinones"				""	"cadazolid"					"character(0)"
-"CLA"		"Calcium aminosalicylate"	"Antimycobacterials"	"J04AA03"	"Drugs for treatment of tuberculosis"	"Aminosalicylic acid and derivatives"	""	""	15	"g"			""
-"CAP"	135565060	"Capreomycin"	"Antimycobacterials"	"J04AB30"	"Drugs for treatment of tuberculosis"	"Antibiotics"	"c(\"\", \"capr\")"	""			1	"g"	""
-"CRB"	20824	"Carbenicillin"	"Beta-lactams/penicillins"	"J01CA03"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"c(\"bar\", \"carb\", \"cb\")"	"c(\"anabactyl\", \"carbenicilina\", \"carbenicillin\", \"carbenicillina\", \"carbenicilline\", \"carbenicillinum\", \"geopen\", \"pyopen\")"			12	"g"	"3434-8"
-"CRN"	93184	"Carindacillin"	"Beta-lactams/penicillins"	"J01CA05"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	""	"c(\"carindacilina\", \"carindacillin\", \"carindacilline\", \"carindacillinum\")"	4	"g"			"character(0)"
-"CAR"	6540466	"Carumonam"	"Other antibacterials"	"J01DF02"			""	"c(\"carumonam\", \"carumonamum\")"			2	"g"	"character(0)"
-"CAS"	2826718	"Caspofungin"	"Antifungals/antimycotics"	"J02AX04"	"Antimycotics for systemic use"	"Other antimycotics for systemic use"	"casp"	"c(\"cancidas\", \"capsofungin\", \"caspofungin\")"			50	"mg"	"58419-3"
-"CAC"	91562	"Cefacetrile"	"Cephalosporins (1st gen.)"	"J01DB10"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	""	"c(\"cefacetril\", \"cefacetrile\", \"cefacetrilo\", \"cefacetrilum\", \"celospor\", \"celtol\", \"cephacetrile\", \"cristacef\", \"vetrimast\")"					"character(0)"
-"CEC"	51039	"Cefaclor"	"Cephalosporins (2nd gen.)"	"J01DC04"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	"c(\"ccl\", \"cec\", \"cf\", \"cfac\", \"cfc\", \"cfcl\", \"cfr\", \"fac\")"	"c(\"alenfral\", \"alfacet\", \"ceclor\", \"ceclor cd\", \"cefaclor\", \"cefaclor anhydrous\", \"cefaclor monohydrate\", \"cefacloro\", \"cefaclorum\", \"cefeaclor\", \"cephaclor\", \"dystaclor mr\", \"keflor\", \"kefral\", \"raniclor\")"	1	"g"			"c(\"16564-7\", \"21149-0\")"
-"CFR"	47965	"Cefadroxil"	"Cephalosporins (1st gen.)"	"J01DB05"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	"c(\"cfdx\", \"cfr\", \"fad\")"	"c(\"cefadrops\", \"cefadroxil\", \"cefadroxil anhydrous\", \"cefadroxilo\", \"cefadroxilum\", \"cefradroxil\", \"cephadroxil\", \"duricef\", \"sumacef\", \"ultracef\")"	2	"g"			"16565-4"
-"RID"	5773	"Cefaloridine"	"Cephalosporins (1st gen.)"	"J01DB02"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	"cefa"	"c(\"aliporina\", \"ampligram\", \"cefaloridin\", \"cefaloridina\", \"cefaloridine\", \"cefaloridinum\", \"cefalorizin\", \"ceflorin\", \"cepaloridin\", \"cepalorin\", \"cephalomycine\", \"cephaloridin\", \"cephaloridine\", \"cephaloridinum\", \"ceporan\", \"ceporin\", \"ceporine\", \"cilifor\", \"deflorin\", \"faredina\", \"floridin\", \"glaxoridin\", \"intrasporin\", \"keflodin\", \"keflordin\", \"kefloridin\", \"kefspor\", \"lloncefal\", \"loridine\", \"sasperin\", \"sefacin\", \"verolgin\", \"vioviantine\")"			3	"g"	"character(0)"
-"MAN"	456255	"Cefamandole"	"Cephalosporins (2nd gen.)"	"J01DC03"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	"c(\"cfam\", \"cfmn\")"	"c(\"cefadole\", \"cefamandol\", \"cefamandole\", \"cefamandolum\", \"cephadole\", \"cephamandole\", \"kefamandol\", \"kefdole\", \"mancef\")"			6	"g"	"3441-3"
-"CTZ"	6410758	"Cefatrizine"	"Cephalosporins (1st gen.)"	"J01DB07"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	""	"c(\"bricef\", \"cefatrix\", \"cefatrizine\", \"cefatrizino\", \"cefatrizinum\", \"cepticol\", \"cetrazil\", \"latocef\", \"orosporina\", \"trizina\")"	1	"g"			"character(0)"
-"CZD"	71736	"Cefazedone"	"Cephalosporins (1st gen.)"	"J01DB06"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	""	"c(\"cefazedon\", \"cefazedona\", \"cefazedone\", \"cefazedone acid\", \"cefazedonum\", \"refosporen\", \"refosporene\", \"refosporin\")"			3	"g"	"character(0)"
-"CZO"	33255	"Cefazolin"	"Cephalosporins (1st gen.)"	"J01DB04"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	"c(\"cfz\", \"cfzl\", \"cz\", \"czol\", \"faz\", \"kz\")"	"c(\"atirin\", \"cefamezin\", \"cefamezine\", \"cefazina\", \"cefazolin\", \"cefazolin acid\", \"cefazolina\", \"cefazoline\", \"cefazolinum\", \"cephamezine\", \"cephazolidin\", \"cephazolin\", \"cephazoline\", \"elzogram\", \"firmacef\", \"kefzol\", \"liviclina\", \"totacef\")"			3	"g"	"c(\"16566-2\", \"25235-3\", \"3442-1\", \"3443-9\", \"80962-4\")"
-"CFB"	127527	"Cefbuperazone"	"Other antibacterials"	"J01DC13"			""	"c(\"cefbuperazona\", \"cefbuperazone\", \"cefbuperazonum\", \"cefbuperzaone\", \"cerbuperazone\", \"tomiporan\")"			2	"g"	"character(0)"
-"CCP"	6436055	"Cefcapene"	"Cephalosporins (3rd gen.)"	"J01DD17"			""	"c(\"cefcamate\", \"cefcapene\")"	0.45	"g"			"character(0)"
-"CCX"	5282438	"Cefcapene pivoxil"	"Cephalosporins (3rd gen.)"				""	"c(\"cefcamate pivoxil\", \"cefcapene piroxil\")"					"character(0)"
-"CDR"	6915944	"Cefdinir"	"Cephalosporins (3rd gen.)"	"J01DD15"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"cd\", \"cdn\", \"cdr\", \"cfd\", \"din\")"	"c(\"cefdinir\", \"cefdinirum\", \"cefdinyl\", \"cefdirnir\", \"ceftinex\", \"cefzon\", \"omnicef\")"	0.6	"g"			"character(0)"
-"DIT"	9870843	"Cefditoren"	"Cephalosporins (3rd gen.)"	"J01DD16"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"cdn"	"cefditoren"	0.4	"g"			"character(0)"
-"DIX"	6437877	"Cefditoren pivoxil"	"Cephalosporins (3rd gen.)"				""	"c(\"cefditoren\", \"cefditoren pi voxil\", \"cefditoren pivoxil\", \"cefditorin\", \"cefditorin pivoxil\", \"meiact\", \"spectracef\")"					"character(0)"
-"FEP"	5479537	"Cefepime"	"Cephalosporins (4th gen.)"	"J01DE01"	"Other beta-lactam antibacterials"	"Fourth-generation cephalosporins"	"c(\"cfep\", \"cfpi\", \"cpe\", \"cpm\", \"fep\", \"pm\", \"xpm\")"	"c(\"axepim\", \"cefepima\", \"cefepime\", \"cefepimum\", \"cepimax\", \"cepimex\", \"maxcef\", \"maxipime\")"			4	"g"	"38363-8"
-"CPC"	9567559	"Cefepime/clavulanic acid"	"Cephalosporins (4th gen.)"				"c(\"cicl\", \"xpml\")"	""					""
-"FNC"		"Cefepime/nacubactam"	"Beta-lactams/penicillins"				""	""					""
-"FPT"	9567558	"Cefepime/tazobactam"	"Cephalosporins (4th gen.)"				""	""					""
-"FPZ"		"Cefepime/zidebactam"	"Other antibacterials"				""	""					""
-"CAT"	5487888	"Cefetamet"	"Cephalosporins (3rd gen.)"	"J01DD10"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	""	"c(\"cefetamet\", \"cefetametum\", \"cepime o\", \"deacetoxycefotaxime\")"	1	"g"			"character(0)"
-"CPI"	5486182	"Cefetamet pivoxil"	"Cephalosporins (3rd gen.)"				""	"c(\"cefetamet pivoxyl\", \"globocef\")"					"character(0)"
-"CCL"	71719688	"Cefetecol"	"Cephalosporins (4th gen.)"				"c(\"\", \"cefcatacol\")"	""					""
-"CZL"	193956	"Cefetrizole"	"Cephalosporins (unclassified gen.)"				""	"c(\"cefetrizole\", \"cefetrizolum\")"					"character(0)"
-"FDC"	77843966	"Cefiderocol"	"Other antibacterials"	"J01DI04"			""	"cefiderocol"					"character(0)"
-"CFM"	5362065	"Cefixime"	"Cephalosporins (3rd gen.)"	"J01DD08"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"cfe\", \"cfix\", \"cfxm\", \"dcfm\", \"fix\", \"ix\")"	"c(\"cefixim\", \"cefixima\", \"cefixime\", \"cefixime anhydrous\", \"cefiximum\", \"cefixoral\", \"cefspan\", \"cephoral\", \"denvar\", \"necopen\", \"suprax\", \"tricef\", \"unixime\")"	0.4	"g"			"c(\"16567-0\", \"25236-1\")"
-"CMX"	9570757	"Cefmenoxime"	"Cephalosporins (3rd gen.)"	"J01DD05"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	""	"c(\"bestron\", \"cefmax\", \"cefmenoxima\", \"cefmenoxime\", \"cefmenoximum\")"			2	"g"	"character(0)"
-"CMZ"	42008	"Cefmetazole"	"Cephalosporins (2nd gen.)"	"J01DC09"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	""	"c(\"cefmetazole\", \"cefmetazolo\", \"cefmetazolum\")"			4	"g"	"character(0)"
-"CNX"	71141	"Cefminox"	"Other antibacterials"	"J01DC12"			""	"c(\"cefminox\", \"cefminoxum\")"			4	"g"	"character(0)"
-"DIZ"	5361871	"Cefodizime"	"Cephalosporins (3rd gen.)"	"J01DD09"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	""	"c(\"cefodizima\", \"cefodizime\", \"cefodizime acid\", \"cefodizimum\", \"cefodizme\", \"diezime\", \"modivid\", \"neucef\", \"timecef\")"			2	"g"	"character(0)"
-"CID"	43594	"Cefonicid"	"Cephalosporins (2nd gen.)"	"J01DC06"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	""	"c(\"cefonicid\", \"cefonicido\", \"cefonicidum\", \"monocef\")"			1	"g"	"c(\"25237-9\", \"3444-7\")"
-"CFP"	44187	"Cefoperazone"	"Cephalosporins (3rd gen.)"	"J01DD12"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"cfp\", \"cfpz\", \"cp\", \"cpz\", \"fop\", \"per\")"	"c(\"bioperazone\", \"cefobid\", \"cefoperazine\", \"cefoperazon\", \"cefoperazone\", \"cefoperazone acid\", \"cefoperazono\", \"cefoperazonum\", \"cefozon\", \"medocef\", \"myticef\", \"pathozone\", \"peracef\")"			4	"g"	"3445-4"
-"CSL"		"Cefoperazone/sulbactam"	"Cephalosporins (3rd gen.)"	"J01DD62"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	""	""			4	"g"	""
-"CND"	43507	"Ceforanide"	"Cephalosporins (2nd gen.)"	"J01DC11"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	""	"c(\"ceforanide\", \"ceforanido\", \"ceforanidum\", \"precef\", \"radacef\")"			4	"g"	"character(0)"
-"CSE"	9830519	"Cefoselis"	"Cephalosporins (4th gen.)"				""	"c(\"cefoselis\", \"cefoselis sulfate\", \"winsef\")"					"character(0)"
-"CTX"	5742673	"Cefotaxime"	"Cephalosporins (3rd gen.)"	"J01DD01"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"cfot\", \"cft\", \"cftx\", \"ct\", \"ctx\", \"fot\", \"tax\", \"xct\")"	"c(\"cefotaxim\", \"cefotaxim hikma\", \"cefotaxima\", \"cefotaxime\", \"cefotaxime acid\", \"cefotaximum\", \"cephotaxime\", \"claforan\", \"omnatax\")"			4	"g"	"c(\"25238-7\", \"3446-2\", \"80961-6\")"
-"CTC"	9575353	"Cefotaxime/clavulanic acid"	"Cephalosporins (3rd gen.)"				"c(\"cxcl\", \"xctl\")"	""					""
-"CTS"	9574753	"Cefotaxime/sulbactam"	"Cephalosporins (3rd gen.)"				""	""					""
-"CTT"	53025	"Cefotetan"	"Cephalosporins (2nd gen.)"	"J01DC05"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	"c(\"cftt\", \"cn\", \"cte\", \"ctn\", \"ctt\", \"tans\")"	"c(\"apacef\", \"cefotetan\", \"cefotetan free acid\", \"cefotetanum\")"			4	"g"	"c(\"25239-5\", \"3447-0\")"
-"CTF"	43708	"Cefotiam"	"Cephalosporins (2nd gen.)"	"J01DC07"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	""	"c(\"cefotiam\", \"cefotiam?\", \"cefotiamum\", \"ceradolan\", \"ceradon\", \"haloapor\")"	1.2	"g"	4	"g"	"character(0)"
-"CHE"	125846	"Cefotiam hexetil"	"Cephalosporins (3rd gen.)"				""	"c(\"cefotiam cilexetil\", \"pansporin t\")"					"character(0)"
-"FOV"	9578573	"Cefovecin"	"Cephalosporins (3rd gen.)"				""	""					""
-"FOX"	441199	"Cefoxitin"	"Cephalosporins (2nd gen.)"	"J01DC01"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	"c(\"cfox\", \"cfx\", \"cfxt\", \"cx\", \"fox\", \"fx\")"	"c(\"cefoxitin\", \"cefoxitina\", \"cefoxitine\", \"cefoxitinum\", \"cefoxotin\", \"cephoxitin\", \"mefoxin\", \"mefoxitin\", \"rephoxitin\")"			6	"g"	"c(\"25240-3\", \"3448-8\")"
-"FOX1"		"Cefoxitin screening"	"Cephalosporins (2nd gen.)"				"cfsc"	""					""
-"ZOP"	9571080	"Cefozopran"	"Cephalosporins (4th gen.)"	"J01DE03"			""	"cefozopran"			4	"g"	"character(0)"
-"CFZ"	68597	"Cefpimizole"	"Cephalosporins (3rd gen.)"				""	"c(\"cefpimizol\", \"cefpimizole\", \"cefpimizole sodium\", \"cefpimizolum\")"					"character(0)"
-"CPM"	636405	"Cefpiramide"	"Cephalosporins (3rd gen.)"	"J01DD11"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	""	"c(\"cefpiramide\", \"cefpiramide acid\", \"cefpiramido\", \"cefpiramidum\")"			2	"g"	"character(0)"
-"CPO"	5479539	"Cefpirome"	"Cephalosporins (4th gen.)"	"J01DE02"	"Other beta-lactam antibacterials"	"Fourth-generation cephalosporins"	"c(\"\", \"cfpr\")"	"c(\"broact\", \"cefpiroma\", \"cefpirome\", \"cefpiromum\", \"cefrom\", \"cerfpirome\", \"keiten\")"			4	"g"	"character(0)"
-"CPD"	6335986	"Cefpodoxime"	"Cephalosporins (3rd gen.)"	"J01DD13"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"cfpd\", \"cfpo\", \"cpd\", \"pod\", \"px\")"	"c(\"cefpodoxim acid\", \"cefpodoxima\", \"cefpodoxime\", \"cefpodoxime acid\", \"cefpodoximum\", \"epoxim\")"	0.4	"g"			"25241-1"
-"CPX"	6526396	"Cefpodoxime proxetil"	"Cephalosporins (3rd gen.)"				""	"c(\"cefodox\", \"cefoprox\", \"cefpodoxime proxetil\", \"cepodem\", \"orelox\", \"otreon\", \"podomexef\", \"simplicef\", \"vantin\")"					"character(0)"
-"CDC"		"Cefpodoxime/clavulanic acid"	"Cephalosporins (3rd gen.)"				"c(\"\", \"cecl\")"	""					""
-"CPR"	5281006	"Cefprozil"	"Cephalosporins (2nd gen.)"	"J01DC10"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	"c(\"cpr\", \"cpz\", \"fp\")"	"c(\"arzimol\", \"brisoral\", \"cefprozil\", \"cefprozil anhydrous\", \"cefprozil hydrate\", \"cefprozilo\", \"cefprozilum\", \"cefzil\", \"cronocef\", \"procef\", \"serozil\")"	1	"g"			"character(0)"
-"CEQ"	5464355	"Cefquinome"	"Cephalosporins (4th gen.)"				""	"c(\"cefquinoma\", \"cefquinome\", \"cefquinomum\", \"cobactan\")"					"character(0)"
-"CRD"	5284529	"Cefroxadine"	"Cephalosporins (1st gen.)"	"J01DB11"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	""	"c(\"cefroxadine\", \"cefroxadino\", \"cefroxadinum\")"	2.1	"g"			"character(0)"
-"CFS"	656575	"Cefsulodin"	"Cephalosporins (3rd gen.)"	"J01DD03"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"cfsl\", \"cfsu\")"	"c(\"cefsulodin\", \"cefsulodine\", \"cefsulodino\", \"cefsulodinum\")"			4	"g"	"c(\"131-3\", \"25242-9\")"
-"CSU"	68718	"Cefsumide"	"Cephalosporins (unclassified gen.)"				""	"c(\"cefsumide\", \"cefsumido\", \"cefsumidum\")"					"character(0)"
-"CPT"	56841980	"Ceftaroline"	"Cephalosporins (5th gen.)"	"J01DI02"			"c(\"\", \"cfro\")"	"c(\"teflaro\", \"zinforo\")"			1.2	"g"	"character(0)"
-"CPA"		"Ceftaroline/avibactam"	"Cephalosporins (5th gen.)"				""	""					""
-"CAZ"	5481173	"Ceftazidime"	"Cephalosporins (3rd gen.)"	"J01DD02"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"caz\", \"cefta\", \"cfta\", \"cftz\", \"taz\", \"tz\", \"xtz\")"	"c(\"ceftazidim\", \"ceftazidima\", \"ceftazidime\", \"ceftazidimum\", \"ceptaz\", \"fortaz\", \"fortum\", \"pentacef\", \"tazicef\", \"tazidime\")"			4	"g"	"c(\"21151-6\", \"3449-6\", \"80960-8\")"
-"CZA"	90643431	"Ceftazidime/avibactam"	"Cephalosporins (3rd gen.)"				"c(\"\", \"cfav\")"	"c(\"avycaz\", \"zavicefta\")"					""
-"CCV"	9575352	"Ceftazidime/clavulanic acid"	"Cephalosporins (3rd gen.)"	"J01DD52"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"czcl\", \"xtzl\")"	""			6	"g"	""
-"CEM"	6537431	"Cefteram"	"Cephalosporins (3rd gen.)"	"J01DD18"			""	"c(\"cefteram\", \"cefterame\", \"cefteramum\", \"ceftetrame\")"	0.4	"g"			"character(0)"
-"CPL"	5362114	"Cefteram pivoxil"	"Cephalosporins (3rd gen.)"				""	"c(\"cefteram pivoxil\", \"tomiron\")"					"character(0)"
-"CTL"	65755	"Ceftezole"	"Cephalosporins (1st gen.)"	"J01DB12"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	""	"c(\"ceftezol\", \"ceftezole\", \"ceftezolo\", \"ceftezolum\", \"demethylcefazolin\")"			3	"g"	"character(0)"
-"CTB"	5282242	"Ceftibuten"	"Cephalosporins (3rd gen.)"	"J01DD14"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"cb\", \"cfbu\", \"ctb\", \"tib\")"	"c(\"ceftem\", \"ceftibuten\", \"ceftibuten hydrate\", \"ceftibutene\", \"ceftibuteno\", \"ceftibutenum\", \"cephem\", \"ceprifran\", \"isocef\", \"keimax\")"	0.4	"g"			"character(0)"
-"TIO"	6328657	"Ceftiofur"	"Cephalosporins (3rd gen.)"				""	"c(\"ceftiofur\", \"ceftiofurum\", \"excede\", \"excenel\", \"naxcel\")"					"character(0)"
-"CZX"	6533629	"Ceftizoxime"	"Cephalosporins (3rd gen.)"	"J01DD07"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"cfzx\", \"ctz\", \"cz\", \"czx\", \"tiz\", \"zox\")"	"c(\"cefizox\", \"ceftisomin\", \"ceftix\", \"ceftizoxima\", \"ceftizoxime\", \"ceftizoximum\", \"epocelin\", \"eposerin\")"			4	"g"	"c(\"25243-7\", \"3450-4\")"
-"CZP"	9578661	"Ceftizoxime alapivoxil"	"Cephalosporins (3rd gen.)"				""	""					""
-"BPR"	135413542	"Ceftobiprole"	"Cephalosporins (5th gen.)"				""	"ceftobiprole"					"character(0)"
-"CFM1"	135413544	"Ceftobiprole medocaril"	"Cephalosporins (5th gen.)"	"J01DI01"	"Other beta-lactam antibacterials"	"Other cephalosporins and penems"	""	""			1.5	"g"	""
-"CEI"		"Ceftolozane/enzyme inhibitor"	"Cephalosporins (5th gen.)"	"J01DI54"	"Other beta-lactam antibacterials"	"Other cephalosporins and penems"	""	""			3	"g"	""
-"CZT"		"Ceftolozane/tazobactam"	"Cephalosporins (5th gen.)"				""	""					""
-"CRO"	5479530	"Ceftriaxone"	"Cephalosporins (3rd gen.)"	"J01DD04"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"axo\", \"cax\", \"cftr\", \"cro\", \"ctr\", \"frx\", \"tx\")"	"c(\"biotrakson\", \"cefatriaxone\", \"cefatriaxone hydrate\", \"ceftriaxon\", \"ceftriaxona\", \"ceftriaxone\", \"ceftriaxone sodium\", \"ceftriaxonum\", \"ceftriazone\", \"cephtriaxone\", \"longacef\", \"rocefin\", \"rocephalin\", \"rocephin\", \"rocephine\", \"rophex\")"			2	"g"	"c(\"25244-5\", \"3451-2\", \"80957-4\")"
-"CXM"	5479529	"Cefuroxime"	"Cephalosporins (2nd gen.)"	"c(\"J01DC02\", \"S01AA27\")"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	"c(\"cfrx\", \"cfur\", \"cfx\", \"crm\", \"cxm\", \"fur\", \"rox\", \"xm\")"	"c(\"biofuroksym\", \"cefuril\", \"cefuroxim\", \"cefuroxime\", \"cefuroximine\", \"cefuroximo\", \"cefuroximum\", \"cephuroxime\", \"kefurox\", \"sharox\", \"zinacef\", \"zinacef danmark\")"	0.5	"g"	3	"g"	"c(\"25245-2\", \"3452-0\", \"80608-3\", \"80617-4\")"
-"CXA"	6321416	"Cefuroxime axetil"	"Cephalosporins (2nd gen.)"				"c(\"\", \"cfax\")"	"c(\"altacef\", \"bioracef\", \"cefaks\", \"cefazine\", \"ceftin\", \"cefuroximaxetil\", \"cefuroxime axetil\", \"celocid\", \"cepazine\", \"cethixim\", \"cetoxil\", \"coliofossim\", \"elobact\", \"forcef\", \"furoxime\", \"kalcef\", \"maxitil\", \"medoxm\", \"nivador\", \"zinnat\")"					"character(0)"
-"CFM2"		"Cefuroxime/metronidazole"	"Other antibacterials"	"J01RA03"	"Combinations of antibacterials"	"Combinations of antibacterials"	""	""					""
-"ZON"	6336505	"Cefuzonam"	"Other antibacterials"				""	"c(\"cefuzonam\", \"cefuzonam sodium\", \"cefuzoname\", \"cefuzonamum\")"					"character(0)"
-"LEX"	27447	"Cephalexin"	"Cephalosporins (1st gen.)"	"J01DB01"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	"c(\"\", \"cflx\")"	"c(\"alcephin\", \"alexin\", \"alsporin\", \"anhydrous cefalexin\", \"anhydrous cephalexin\", \"biocef\", \"carnosporin\", \"cefablan\", \"cefadal\", \"cefadin\", \"cefadina\", \"cefaleksin\", \"cefalessina\", \"cefalexin\", \"cefalexin anhydrous\", \"cefalexina\", \"cefalexine\", \"cefalexinum\", \"cefalin\", \"cefaloto\", \"cefaseptin\", \"ceflax\", \"ceforal\", \"cefovit\", \"celexin\", \"cepastar\", \"cepexin\", \"cephacillin\", \"cephalexin\", \"cephalexin anhydrous\", \"cephalexine\", \"cephalexinum\", \"cephanasten\", \"cephaxin\", \"cephin\", \"ceporex\", \"ceporex forte\", 
-\"ceporexin\", \"ceporexine\", \"cerexin\", \"cerexins\", \"cophalexin\", \"durantel\", \"durantel ds\", \"erocetin\", \"factagard\", \"felexin\", \"ibilex\", \"ibrexin\", \"inphalex\", \"kefalospes\", \"keflet\", \"keflex\", \"kefolan\", \"keforal\", \"keftab\", \"kekrinal\", \"kidolex\", \"lafarine\", \"larixin\", \"lenocef\", \"lexibiotico\", \"lonflex\", \"lopilexin\", \"madlexin\", \"mamalexin\", \"mamlexin\", \"medoxine\", \"neokef\", \"neolexina\", \"novolexin\", \"optocef\", \"oracef\", \"oriphex\", \"oroxin\", \"ortisporina\", \"ospexin\", \"palitrex\", \"panixine disperdose\", 
-\"pectril\", \"pyassan\", \"roceph\", \"roceph distab\", \"sanaxin\", \"sartosona\", \"sencephalin\", \"sepexin\", \"servispor\", \"sialexin\", \"sinthecillin\", \"sporicef\", \"sporidex\", \"syncle\", \"synecl\", \"tepaxin\", \"tokiolexin\", \"uphalexin\", \"voxxim\", \"winlex\", \"zozarine\")"	2	"g"			"c(\"21175-5\", \"3453-8\")"
-"CEP"	6024	"Cephalothin"	"Cephalosporins (1st gen.)"	"J01DB03"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	"c(\"cfal\", \"cflt\")"	"c(\"cefalothin\", \"cefalotin\", \"cefalotina\", \"cefalotina fabra\", \"cefalotine\", \"cefalotinum\", \"cemastin\", \"cephalothinum\", \"cephalotin\", \"coaxin\", \"keflin\", \"seffin\")"			4	"g"	"c(\"25246-0\", \"3454-6\")"
-"HAP"	30699	"Cephapirin"	"Cephalosporins (1st gen.)"	"J01DB08"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	""	"c(\"ambrocef\", \"cefadyl\", \"cefapilin\", \"cefapirin\", \"cefapirina\", \"cefapirine\", \"cefapirinum\", \"cefaprin\", \"cefaprin sodium\", \"cefatrex\", \"cefatrexyl\", \"cephapirine\", \"metricure\")"			4	"g"	"10980-1"
-"CED"	38103	"Cephradine"	"Cephalosporins (1st gen.)"	"J01DB09"	"Other beta-lactam antibacterials"	"First-generation cephalosporins"	"c(\"cfra\", \"cfrd\")"	"c(\"anspor\", \"cefradin\", \"cefradina\", \"cefradine\", \"cefradinum\", \"cekodin\", \"cephradin\", \"cephradine\", \"eskacef\", \"infexin\", \"megace f\", \"megacef\", \"sefril\", \"velocef\", \"velosef\")"	2	"g"	2	"g"	"character(0)"
-"CTO"	71402	"Cetocycline"	"Tetracyclines"				""	"c(\"cetocycline\", \"cetocyline\", \"cetotetrine\")"					"character(0)"
-"CHL"	5959	"Chloramphenicol"	"Amphenicols"	"c(\"D06AX02\", \"D10AF03\", \"G01AA05\", \"J01BA01\", \"S01AA01\", \"S02AA01\", \"S03AA08\")"	"Amphenicols"	"Amphenicols"	"c(\"c\", \"chl\", \"chlo\", \"cl\")"	"c(\"alficetyn\", \"ambofen\", \"amphenicol\", \"amphicol\", \"amseclor\", \"anacetin\", \"aquamycetin\", \"austracil\", \"austracol\", \"biocetin\", \"biophenicol\", \"catilan\", \"ch loramex\", \"chemiceticol\", \"chemicetin\", \"chemicetina\", \"chlomin\", \"chlomycol\", \"chloramex\", \"chloramfenikol\", \"chloramficin\", \"chloramfilin\", \"chloramphenicol\", \"chloramphenicole\", \"chloramphenicolum\", \"chloramsaar\", \"chlorasol\", \"chlorbiotic\", \"chloricol\", \"chlormycetin r\", \"chlornitromycin\", \"chloroamphenicol\", \"chlorocaps\", \"chlorocid\", 
-\"chlorocid s\", \"chlorocide\", \"chlorocidin c\", \"chlorocidin c tetran\", \"chlorocin\", \"chlorocol\", \"chlorofair\", \"chloroject l\", \"chloromax\", \"chloromycetin\", \"chloromycetny\", \"chloromyxin\", \"chloronitrin\", \"chloroptic\", \"chloroptic s.o.p\", \"chloroptic s.o.p.\", \"chlorovules\", \"chlorsig\", \"cidocetine\", \"ciplamycetin\", \"cloramfen\", \"cloramfenicol\", \"cloramfenicolo\", \"cloramficin\", \"cloramical\", \"cloramicol\", \"cloramidina\", \"cloranfenicol\", \"cloroamfenicolo\", \"clorocyn\", \"cloromisan\", \"cloromissan\", \"clorosintex\", 
-\"comycetin\", \"cylphenicol\", \"desphen\", \"detreomycin\", \"detreomycine\", \"dextromycetin\", \"doctamicina\", \"duphenicol\", \"econochlor\", \"embacetin\", \"emetren\", \"enicol\", \"enteromycetin\", \"erbaplast\", \"ertilen\", \"f armicetina\", \"farmicetina\", \"fenicol\", \"globenicol\", \"glorous\", \"halomycetin\", \"hortfenicol\", \"interomycetine\", \"intramycetin\", \"intramyctin\", \"isicetin\", \"ismicetina\", \"isophenicol\", \"isopto fenicol\", \"juvamycetin\", \"kamaver\", \"kemicetina\", \"kemicetine\", \"kloramfenikol\", \"klorita\", \"klorocid s\", 
-\"laevomycetinum\", \"leukamycin\", \"leukomyan\", \"leukomycin\", \"levocin\", \"levomicetina\", \"levomitsetin\", \"levomycetin\", \"levoplast\", \"levosin\", \"levovetin\", \"loromicetina\", \"loromisan\", \"loromisin\", \"mastiphen\", \"mediamycetine\", \"medichol\", \"micloretin\", \"micochlorine\", \"micoclorina\", \"microcetina\", \"mychel\", \"mycinol\", \"myclocin\", \"mycochlorin\", \"myscel\", \"normimycin v\", \"novochlorocap\", \"novomycetin\", \"novophenicol\", \"ocuphenicol\", \"oftalent\", \"oleomycetin\", \"opclor\", \"opelor\", \"ophthochlor\", \"ophthocort\", 
-\"ophtochlor\", \"optomycin\", \"otachron\", \"otophen\", \"pantovernil\", \"paraxin\", \"pentamycetin\", \"quemicetina\", \"rivomycin\", \"romphenil\", \"ronfenil\", \"ronphenil\", \"septicol\", \"sificetina\", \"sintomicetina\", \"sintomicetine r\", \"sno phenicol\", \"soluthor\", \"stanomycetin\", \"synthomycetin\", \"synthomycetine\", \"synthomycine\", \"syntomycin\", \"tevcocin\", \"tevcosin\", \"tifomycin\", \"tifomycine\", \"tiromycetin\", \"treomicetina\", \"unimycetin\", \"veticol\", \"vice ton\", \"viceton\")"	3	"g"	3	"g"	"c(\"15101-9\", \"16603-3\", \"16604-1\", \"25247-8\", \"29214-4\", \"29346-4\", \"29347-2\", \"3455-3\")"
-"CTE"	54675777	"Chlortetracycline"	"Tetracyclines"	"c(\"A01AB21\", \"D06AA02\", \"J01AA03\", \"S01AA02\")"	"Tetracyclines"	"Tetracyclines"	""	"c(\"acronize\", \"aueromycin\", \"aureocina\", \"aureomycin\", \"aureomykoin\", \"biomitsin\", \"biomycin\", \"biomycin a\", \"chlormax\", \"chlorotetracycline\", \"chlortetracycline\", \"chlortetracyclinum\", \"chrysomykine\", \"clortetraciclina\", \"duomycin\", \"flamycin\", \"uromycin\")"	1	"g"			"87600-3"
-"CIC"	19003	"Ciclacillin"	"Beta-lactams/penicillins"				""	"c(\"bastcillin\", \"calthor\", \"ciclacilina\", \"ciclacillin\", \"ciclacilline\", \"ciclacillinum\", \"ciclacillum\", \"citosarin\", \"cyclacillin\", \"cyclapen\", \"noblicil\", \"orfilina\", \"peamezin\", \"syngacillin\", \"ultracillin\", \"vastcillin\", \"vipicil\", \"wyvital\")"					"character(0)"
-"CIX"	47472	"Ciclopirox"	"Antifungals/antimycotics"	"c(\"D01AE14\", \"G01AX12\")"	"Antifungals for topical use"	"Other antifungals for topical use"	"cipx"	"c(\"butaconazole\", \"butoconazol\", \"butoconazole\", \"butoconazolum\", \"compositenstarke\", \"dahlin\", \"femstat\", \"gynofort\", \"polyfructosanum\")"					"character(0)"
-"CIN"	2762	"Cinoxacin"	"Quinolones"	"J01MB06"	"Quinolone antibacterials"	"Other quinolones"	"c(\"cino\", \"cnox\")"	"c(\"azolinic acid\", \"cinobac\", \"cinobactin\", \"cinoxacin\", \"cinoxacine\", \"cinoxacino\", \"cinoxacinum\", \"clinoxacin\", \"noxigram\", \"uronorm\")"	1	"g"			"character(0)"
-"CIP"	2764	"Ciprofloxacin"	"Quinolones"	"c(\"J01MA02\", \"S01AE03\", \"S02AA15\", \"S03AA07\")"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"ci\", \"cip\", \"cipr\", \"cp\")"	"c(\"alcon cilox\", \"auripro\", \"bacquinor\", \"baflox\", \"baycip\", \"bernoflox\", \"cetraxal\", \"ciflox\", \"cifloxin\", \"ciloxan\", \"ciplus\", \"ciprecu\", \"ciprine\", \"ciprinol\", \"cipro i.v.\", \"cipro iv\", \"cipro xl\", \"cipro xr\", \"ciprobay\", \"ciprobay uro\", \"ciprocinol\", \"ciprodar\", \"ciproflox\", \"ciprofloxacin\", \"ciprofloxacina\", \"ciprofloxacine\", \"ciprofloxacino\", \"ciprofloxacinum\", \"ciprogis\", \"ciprolin\", \"ciprolon\", \"cipromycin\", \"ciproquinol\", \"ciprowin\", \"ciproxan\", \"ciproxin\", \"ciproxina\", \"ciproxine\", \"ciriax\", 
-\"citopcin\", \"corsacin\", \"cyprobay\", \"fimoflox\", \"flociprin\", \"ipiflox\", \"italnik\", \"linhaliq\", \"otiprio\", \"probiox\", \"proflaxin\", \"quinolid\", \"quintor\", \"rancif\", \"roxytal\", \"septicide\", \"sophixin ofteno\", \"spitacin\", \"superocin\", \"velmonit\", \"velomonit\", \"zumaflox\")"	1	"g"	0.8	"g"	"c(\"14031-9\", \"14032-7\", \"14058-2\", \"14059-0\", \"25248-6\", \"34636-1\", \"3484-3\")"
-"CLR"	84029	"Clarithromycin"	"Macrolides/lincosamides"	"J01FA09"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	"c(\"ch\", \"cla\", \"clar\", \"clm\", \"clr\")"	"c(\"abbotic\", \"astromen\", \"biaxin\", \"biaxin filmtab\", \"biaxin hp\", \"biaxin xl\", \"biaxin xl filmtab\", \"bicrolid\", \"clacee\", \"clacid\", \"clacine\", \"clambiotic\", \"clarem\", \"claribid\", \"claricide\", \"claridar\", \"claripen\", \"clarith\", \"clarithromycin\", \"clarithromycine\", \"clarithromycinum\", \"claritromicina\", \"clathromycin\", \"crixan\", \"cyllid\", \"cyllind\", \"fromilid\", \"heliclar\", \"klabax\", \"klacid\", \"klaciped\", \"klaricid\", \"klaricid h.p\", \"klaricid h.p.\", \"klaricid pediatric\", \"klaricid xl\", \"klarid\", \"klarin\", 
-\"kofron\", \"mabicrol\", \"macladin\", \"maclar\", \"veclam\", \"vikrol\", \"zeclar\")"	0.5	"g"	1	"g"	"c(\"16619-9\", \"25253-6\", \"34638-7\", \"80559-8\")"
-"CLA1"	5280980	"Clavulanic acid"	"Other antibacterials"				""	"c(\"acide clavulanique\", \"acido clavulanico\", \"acidum clavulanicum\", \"clavulanate\", \"clavulanate acid\", \"clavulanate lithium\", \"clavulanic acid\", \"clavulansaeure\", \"clavulansaure\", \"clavulinic acid\", \"clavulox\", \"sodium clavulanate\")"					"character(0)"
-"CLX"	60063	"Clinafloxacin"	"Quinolones"				""	"clinafloxacin"					"character(0)"
-"CLI"	446598	"Clindamycin"	"Macrolides/lincosamides"	"c(\"D10AF01\", \"G01AA10\", \"J01FF01\")"	"Macrolides, lincosamides and streptogramins"	"Lincosamides"	"c(\"cc\", \"cd\", \"cli\", \"clin\", \"cm\", \"da\")"	"c(\"antirobe\", \"chlolincocin\", \"clindaderm\", \"clindamicina\", \"clindamycin\", \"clindamycine\", \"clindamycinum\", \"clinimycin\", \"dalacin c\", \"dalacine\", \"klimicin\", \"sobelin\")"	1.2	"g"	1.8	"g"	"c(\"16621-5\", \"16622-3\", \"25249-4\", \"3486-8\")"
-"CLF"	2794	"Clofazimine"	"Antimycobacterials"	"J04BA01"	"Drugs for treatment of lepra"	"Drugs for treatment of lepra"	"clof"	"c(\"chlofazimine\", \"clofazimin\", \"clofazimina\", \"clofazimine\", \"clofaziminum\", \"lampren\", \"lamprene\", \"riminophenazine\")"	0.1	"g"			"character(0)"
-"CLF1"	2799	"Clofoctol"	"Other antibacterials"	"J01XX03"	"Other antibacterials"	"Other antibacterials"	""	"c(\"clofoctol\", \"clofoctolo\", \"clofoctolum\", \"gramplus\", \"octofene\")"					"character(0)"
-"CLM"	71807	"Clometocillin"	"Beta-lactams/penicillins"	"J01CE07"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase sensitive penicillins"	""	"c(\"chlomethocillin\", \"clometacillin\", \"clometocilina\", \"clometocillin\", \"clometocilline\", \"clometocillinum\", \"rixapen\")"	1	"g"			"character(0)"
-"CLM1"	54680675	"Clomocycline"	"Tetracyclines"	"J01AA11"	"Tetracyclines"	"Tetracyclines"	""	"c(\"chlormethylencycline\", \"clomociclina\", \"clomocyclin\", \"clomocycline\", \"clomocyclinum\", \"megaclor\")"	1	"g"			"character(0)"
-"CTR"	2812	"Clotrimazole"	"Antifungals/antimycotics"	"c(\"A01AB18\", \"D01AC01\", \"G01AF02\")"			"clot"	"c(\"canesten\", \"canesten cream\", \"canesten solution\", \"canestene\", \"canestine\", \"canifug\", \"chlotrimazole\", \"cimitidine\", \"clomatin\", \"clotrimaderm\", \"clotrimaderm cream\", \"clotrimazol\", \"clotrimazole\", \"clotrimazolum\", \"cutistad\", \"desamix f\", \"diphenylmethane\", \"empecid\", \"esparol\", \"fem care\", \"femcare\", \"gyne lotrimin\", \"jidesheng\", \"kanesten\", \"klotrimazole\", \"lotrimax\", \"lotrimin\", \"lotrimin af\", \"lotrimin af cream\", \"lotrimin af lotion\", \"lotrimin af solution\", \"lotrimin cream\", \"lotrimin lotion\", 
-\"lotrimin solution\", \"monobaycuten\", \"mycelax\", \"mycelex\", \"mycelex cream\", \"mycelex g\", \"mycelex otc\", \"mycelex solution\", \"mycelex troches\", \"mycelex twin pack\", \"myclo cream\", \"myclo solution\", \"myclo spray solution\", \"mycofug\", \"mycosporin\", \"mykosporin\", \"nalbix\", \"otomax\", \"pedisafe\", \"rimazole\", \"stiemazol\", \"tibatin\", \"trimysten\", \"veltrim\")"					"character(0)"
-"CLO"	6098	"Cloxacillin"	"Beta-lactams/penicillins"	"J01CF02"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase resistant penicillins"	"c(\"\", \"clox\")"	"c(\"chloroxacillin\", \"clossacillina\", \"cloxacilina\", \"cloxacillin\", \"cloxacillin sodium\", \"cloxacilline\", \"cloxacillinna\", \"cloxacillinum\", \"cloxapen\", \"methocillin s\", \"orbenin\", \"syntarpen\", \"tegopen\")"	2	"g"	2	"g"	"c(\"16628-0\", \"25250-2\")"
-"COL"	5311054	"Colistin"	"Polymyxins"	"c(\"A07AA10\", \"J01XB01\")"	"Other antibacterials"	"Polymyxins"	"c(\"cl\", \"coli\", \"cs\", \"cst\", \"ct\")"	"c(\"belcomycine\", \"colimycin\", \"colimycin sulphate\", \"colisticin\", \"colistimethate\", \"colistimethate sodium\", \"colistin sulfate\", \"colistin sulphate\", \"colomycin\", \"coly-mycin\", \"polymyxin e\", \"polymyxin e. sulfate\", \"promixin\", \"totazina\")"	9	"MU"	9	"MU"	"c(\"16645-4\", \"29493-4\")"
-"COP"		"Colistin/polysorbate"	"Other antibacterials"				""	""					""
-"CYC"	6234	"Cycloserine"	"Oxazolidinones"	"J04AB01"	"Drugs for treatment of tuberculosis"	"Antibiotics"	"cycl"	"c(\"cicloserina\", \"closerin\", \"closina\", \"cyclorin\", \"cycloserin\", \"cycloserine\", \"cycloserinum\", \"farmiserina\", \"micoserina\", \"miroserina\", \"miroseryn\", \"novoserin\", \"oxamicina\", \"oxamycin\", \"seromycin\", \"tebemicina\", \"tisomycin\", \"wasserina\")"	0.75	"g"			"c(\"16702-3\", \"25251-0\", \"3519-6\")"
-"DAL"	23724878	"Dalbavancin"	"Glycopeptides"	"J01XA04"	"Other antibacterials"	"Glycopeptide antibacterials"	"dalb"	"c(\"dalbavancin\", \"dalvance\")"			1.5	"g"	"character(0)"
-"DAN"	71335	"Danofloxacin"	"Quinolones"				""	"c(\"advocin\", \"danofloxacin\", \"danofloxacine\", \"danofloxacino\", \"danofloxacinum\")"					"character(0)"
-"DPS"	2955	"Dapsone"	"Other antibacterials"	"c(\"D10AX05\", \"J04BA02\")"	"Drugs for treatment of lepra"	"Drugs for treatment of lepra"	""	"c(\"aczone\", \"araldite ht\", \"atrisone\", \"avlosulfon\", \"avlosulfone\", \"avlosulphone\", \"avsulfor\", \"bis sulfone\", \"bissulfone\", \"bissulphone\", \"croysulfone\", \"croysulphone\", \"dapson\", \"dapsona\", \"dapsone\", \"dapsonum\", \"di sulfone\", \"diaphenyl sulfone\", \"diaphenylsulfon\", \"diaphenylsulfone\", \"diaphenylsulphon\", \"diaphenylsulphone\", \"dimitone\", \"diphenasone\", \"diphone\", \"disulfone\", \"disulone\", \"disulphone\", \"dubronax\", \"dubronaz\", \"dumitone\", \"eporal\", \"metabolite c\", \"novophone\", \"protogen\", \"servidapson\", 
-\"slphadione\", \"sulfadione\", \"sulfona\", \"sulfone ucb\", \"sulfonyldianiline\", \"sulphadione\", \"sulphonyldianiline\", \"sumicure s\", \"tarimyl\", \"udolac\", \"wln: zr dswr dz\")"	50	"mg"			"9747-7"
-"DAP"	16134395	"Daptomycin"	"Other antibacterials"	"J01XX09"	"Other antibacterials"	"Other antibacterials"	"c(\"dap\", \"dapt\")"	"c(\"cidecin\", \"cubicin\", \"dapcin\", \"daptomicina\", \"daptomycine\", \"daptomycinum\")"			0.28	"g"	"character(0)"
-"DFX"	487101	"Delafloxacin"	"Quinolones"	"J01MA23"			""	"c(\"baxdela\", \"delafloxacin\", \"delafloxacinum\")"	0.9	"g"	0.6	"g"	"character(0)"
-"DLM"	6480466	"Delamanid"	"Antimycobacterials"	"J04AK06"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	"dela"	"c(\"delamanid\", \"deltyba\")"	0.2	"g"			"character(0)"
-"DEM"	54680690	"Demeclocycline"	"Tetracyclines"	"c(\"D06AA01\", \"J01AA01\")"	"Tetracyclines"	"Tetracyclines"	""	"c(\"bioterciclin\", \"clortetrin\", \"deganol\", \"demeclociclina\", \"demeclocycline\", \"demeclocyclinum\", \"demeclor\", \"demetraclin\", \"diuciclin\", \"elkamicina\", \"ledermycin\", \"mexocine\", \"novotriclina\", \"perciclina\", \"sumaclina\")"	0.6	"g"			"c(\"10982-7\", \"29494-2\")"
-"DKB"	470999	"Dibekacin"	"Aminoglycosides"	"J01GB09"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	""	"c(\"debecacin\", \"dibekacin\", \"dibekacin sulfate\", \"dibekacina\", \"dibekacine\", \"dibekacinum\", \"dideoxykanamycin b\", \"kappati\", \"orbicin\", \"panamicin\")"			0.14	"g"	"character(0)"
-"DIC"	18381	"Dicloxacillin"	"Beta-lactams/penicillins"	"J01CF01"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase resistant penicillins"	"c(\"\", \"dicl\")"	"c(\"dichloroxacillin\", \"diclossacillina\", \"dicloxaciclin\", \"dicloxacilin\", \"dicloxacilina\", \"dicloxacillin\", \"dicloxacillin sodium\", \"dicloxacillina\", \"dicloxacilline\", \"dicloxacillinum\", \"dicloxacycline\", \"dycill\", \"dynapen\", \"maclicine\", \"nm|| dicloxacillin\", \"pathocil\")"	2	"g"	2	"g"	"c(\"10984-3\", \"16769-2\", \"25252-8\")"
-"DIF"	56206	"Difloxacin"	"Quinolones"				""	"difloxacin"					"character(0)"
-"DIR"	6473883	"Dirithromycin"	"Macrolides/lincosamides"	"J01FA13"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	""	"c(\"dirithromycin\", \"dirithromycine\", \"dirithromycinum\", \"diritromicina\", \"divitross\", \"dynabac\", \"noriclan\", \"valodin\")"	0.5	"g"			"character(0)"
-"DOR"	73303	"Doripenem"	"Carbapenems"	"J01DH04"	"Other beta-lactam antibacterials"	"Carbapenems"	"dori"	"c(\"doribax\", \"doripenem\", \"doripenem hydrate\", \"finibax\")"			1.5	"g"	"character(0)"
-"DOX"	54671203	"Doxycycline"	"Tetracyclines"	"c(\"A01AB22\", \"J01AA02\")"	"Tetracyclines"	"Tetracyclines"	"c(\"dox\", \"doxy\")"	"c(\"atridox\", \"azudoxat\", \"deoxymykoin\", \"dossiciclina\", \"doxcycline anhydrous\", \"doxiciclina\", \"doxitard\", \"doxivetin\", \"doxycen\", \"doxychel\", \"doxycin\", \"doxycyclin\", \"doxycycline\", \"doxycycline calcium\", \"doxycycline hyclate\", \"doxycyclinum\", \"doxylin\", \"doxysol\", \"doxytec\", \"doxytetracycline\", \"hydramycin\", \"investin\", \"jenacyclin\", \"liviatin\", \"monodox\", \"oracea\", \"periostat\", \"ronaxan\", \"spanor\", \"supracyclin\", \"vibramycin\", \"vibramycin novum\", \"vibramycine\", \"vibravenos\", \"zenavod\")"	0.1	"g"	0.1	"g"	"c(\"10986-8\", \"21250-6\", \"26902-7\")"
-"ECO"	3198	"Econazole"	"Antifungals/antimycotics"	"c(\"D01AC03\", \"G01AF05\")"	"Antifungals for topical use"	"Imidazole and triazole derivatives"	"econ"	"c(\"econazol\", \"econazole\", \"econazolum\", \"ecostatin\", \"ecostatin cream\", \"palavale\", \"pevaryl\", \"spectazole\", \"spectazole cream\")"					"character(0)"
-"ENX"	3229	"Enoxacin"	"Quinolones"	"J01MA04"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"\", \"enox\")"	"c(\"almitil\", \"bactidan\", \"bactidron\", \"comprecin\", \"enofloxacine\", \"enoksetin\", \"enoram\", \"enoxacin\", \"enoxacina\", \"enoxacine\", \"enoxacino\", \"enoxacinum\", \"enoxen\", \"enoxin\", \"enoxor\", \"flumark\", \"penetrex\")"	0.8	"g"			"c(\"16816-1\", \"3590-7\")"
-"ENR"	71188	"Enrofloxacin"	"Quinolones"				""	"c(\"baytril\", \"enrofloxacin\", \"enrofloxacine\", \"enrofloxacino\", \"enrofloxacinum\")"					"character(0)"
-"ENV"	135565326	"Enviomycin"	"Antimycobacterials"				"c(\"\", \"tuberactinomycin\")"	"c(\"enviomicina\", \"enviomycin\", \"enviomycina\", \"enviomycinum\")"					"character(0)"
-"EPE"		"Eperozolid"	"Other antibacterials"				""	""					""
-"EPC"	71392	"Epicillin"	"Beta-lactams/penicillins"	"J01CA07"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	""	"c(\"dexacillin\", \"dihydroampicillin\", \"epicilina\", \"epicillin\", \"epicilline\", \"epicillinum\")"	2	"g"	2	"g"	"character(0)"
-"EPP"	68916	"Epiroprim"	"Other antibacterials"				""	"c(\"epiroprim\", \"epiroprima\", \"epiroprime\", \"epiroprimum\")"					"character(0)"
-"ERV"	54726192	"Eravacycline"	"Tetracyclines"	"J01AA13"	"Tetracyclines"	"Tetracyclines"	"erav"	"eravacycline"					"character(0)"
-"ETP"	150610	"Ertapenem"	"Carbapenems"	"J01DH03"	"Other beta-lactam antibacterials"	"Carbapenems"	"c(\"erta\", \"etp\")"	"c(\"ertapenem\", \"invanz\")"			1	"g"	"character(0)"
-"ERY"	12560	"Erythromycin"	"Macrolides/lincosamides"	"c(\"D10AF02\", \"J01FA01\", \"S01AA17\")"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	"c(\"e\", \"em\", \"ery\", \"eryt\")"	"c(\"abboticin\", \"abomacetin\", \"acneryne\", \"acnesol\", \"akne cordes losung\", \"aknederm ery gel\", \"aknemycin\", \"austrias\", \"benzamycin\", \"derimer\", \"deripil\", \"dotycin\", \"dumotrycin\", \"emuvin\", \"emycin\", \"endoeritrin\", \"erecin\", \"erisone\", \"eritomicina\", \"eritrocina\", \"eritromicina\", \"ermycin\", \"eryacne\", \"eryacnen\", \"eryc sprinkles\", \"erycen\", \"erycette\", \"erycin\", \"erycinum\", \"eryderm\", \"erydermer\", \"erygel\", \"eryhexal\", \"erymax\", \"erymed\", \"erysafe\", \"erytab\", \"erythrocin\", \"erythrocin stearate\", 
-\"erythroderm\", \"erythrogran\", \"erythroguent\", \"erythromid\", \"erythromycin\", \"erythromycin a\", \"erythromycin base\", \"erythromycin lactate\", \"erythromycine\", \"erythromycines\", \"erythromycinum\", \"erytop\", \"erytrociclin\", \"ilocaps\", \"ilosone\", \"iloticina\", \"ilotycin\", \"ilotycin gluceptate\", \"ilotycin t.s.\", \"inderm\", \"inderm gel\", \"indermretcin\", \"latotryd\", \"lederpax\", \"mephamycin\", \"mercina\", \"oftamolets\", \"paediathrocin\", \"pantoderm\", \"pantodrin\", \"pantomicina\", \"pce dispertab\", \"pharyngocin\", \"primacine\", 
-\"propiocine\", \"proterytrin\", \"retcin\", \"robimycin\", \"romycin\", \"sansac\", \"skid gel e\", \"staticin\", \"stiemicyn\", \"stiemycin\", \"theramycin z\", \"tiloryth\", \"tiprocin\", \"torlamicina\", \"udima ery gel\", \"wyamycin s\")"	2	"g"	1	"g"	"c(\"12298-6\", \"16829-4\", \"25275-9\", \"3597-2\")"
-"ETH"	14052	"Ethambutol"	"Antimycobacterials"	"J04AK02"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	"etha"	"c(\"aethambutolum\", \"ebutol\", \"etambutol\", \"etambutolo\", \"etapiam\", \"ethambutol\", \"ethambutolum\", \"myambutol\", \"mycobutol\", \"purderal\", \"servambutol\")"	1.2	"g"	1.2	"g"	"c(\"25404-5\", \"3607-9\")"
-"ETI"	456476	"Ethambutol/isoniazid"	"Antimycobacterials"	"J04AM03"	"Drugs for treatment of tuberculosis"	"Combinations of drugs for treatment of tuberculosis"	""	""					""
-"ETI1"	2761171	"Ethionamide"	"Antimycobacterials"	"J04AD03"	"Drugs for treatment of tuberculosis"	"Thiocarbamide derivatives"	"ethi"	"c(\"aethionamidum\", \"aetina\", \"aetiva\", \"amidazin\", \"amidazine\", \"ethatyl\", \"ethimide\", \"ethina\", \"ethinamide\", \"ethionamide\", \"ethionamidum\", \"ethioniamide\", \"ethylisothiamide\", \"ethyonomide\", \"etimid\", \"etiocidan\", \"etionamid\", \"etionamida\", \"etionamide\", \"etioniamid\", \"etionid\", \"etionizin\", \"etionizina\", \"etionizine\", \"fatoliamid\", \"iridocin\", \"iridocin bayer\", \"iridozin\", \"isothin\", \"isotiamida\", \"itiocide\", \"nicotion\", \"nisotin\", \"nizotin\", \"rigenicid\", \"sertinon\", \"teberus\", \"thianid\", \"thianide\", 
-\"thioamide\", \"thiodine\", \"thiomid\", \"thioniden\", \"tianid\", \"tiomid\", \"trecator\", \"trecator sc\", \"trekator\", \"trescatyl\", \"trescazide\", \"tubenamide\", \"tubermin\", \"tuberoid\", \"tuberoson\")"	0.75	"g"			"16845-0"
-"ETO"	6034	"Ethopabate"	"Other antibacterials"				""	"c(\"amprol plus\", \"ethopabat\", \"ethopabate\", \"ethyl pabate\")"					"character(0)"
-"EXE"		"Exebacase"					""	""					""
-"FAR"	65894	"Faropenem"	"Other antibacterials"	"J01DI03"	"Other beta-lactam antibacterials"	"Other cephalosporins and penems"	""	"c(\"faropenem\", \"faropenem sodium\", \"fropenem\", \"fropenum sodium\")"	0.75	"g"			"character(0)"
-"FDX"	10034073	"Fidaxomicin"	"Other antibacterials"	"A07AA12"			""	"c(\"dificid\", \"dificlir\", \"difimicin\", \"fidaxomicin\", \"lipiarmycin\", \"tiacumicin b\")"	0.4	"g"			"character(0)"
-"FIN"	11567473	"Finafloxacin"	"Quinolones"				""	"finafloxacin"					"character(0)"
-"FLA"	46783781	"Flavomycin"	"Other antibacterials"				""	"moenomycin complex"					"character(0)"
-"FLE"	3357	"Fleroxacin"	"Quinolones"	"J01MA08"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"\", \"fler\")"	"c(\"fleroxacin\", \"fleroxacine\", \"fleroxacino\", \"fleroxacinum\", \"fleroxicin\", \"megalocin\", \"megalone\", \"megalosin\", \"quinodis\")"	0.4	"g"	0.4	"g"	"character(0)"
-"FLO"	65864	"Flomoxef"	"Other antibacterials"	"J01DC14"			""	"c(\"flomoxef\", \"flomoxefo\", \"flomoxefum\")"			2	"g"	"character(0)"
-"FLR"	114811	"Florfenicol"	"Other antibacterials"				""	"c(\"aquafen\", \"florfenicol\", \"nuflor\", \"nuflor gold\")"					"87599-7"
-"FLC"	21319	"Flucloxacillin"	"Beta-lactams/penicillins"	"J01CF05"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase resistant penicillins"	"c(\"clox\", \"flux\")"	"c(\"floxacillin\", \"floxapen\", \"floxapen sodium salt\", \"fluclox\", \"flucloxacilina\", \"flucloxacillin\", \"flucloxacilline\", \"flucloxacillinum\", \"fluorochloroxacillin\")"	2	"g"	2	"g"	"character(0)"
-"FLU"	3365	"Fluconazole"	"Antifungals/antimycotics"	"c(\"D01AC15\", \"J02AC01\")"	"Antimycotics for systemic use"	"Triazole derivatives"	"c(\"fluc\", \"fluz\", \"flz\")"	"c(\"alflucoz\", \"alfumet\", \"biocanol\", \"biozole\", \"biozolene\", \"canzol\", \"cryptal\", \"diflazon\", \"diflucan\", \"dimycon\", \"elazor\", \"flucazol\", \"fluconazol\", \"fluconazole\", \"fluconazole capsules\", \"fluconazolum\", \"flucostat\", \"flukezol\", \"flunazol\", \"flunizol\", \"flusol\", \"fluzon\", \"fluzone\", \"forcan\", \"fuconal\", \"fungata\", \"loitin\", \"oxifugol\", \"pritenzol\", \"syscan\", \"trican\", \"triconal\", \"triflucan\", \"zoltec\")"	0.2	"g"	0.2	"g"	"c(\"10987-6\", \"16870-8\", \"25255-1\", \"80530-9\")"
-"FLM"	3374	"Flumequine"	"Quinolones"	"J01MB07"	"Quinolone antibacterials"	"Other quinolones"	""	"c(\"apurone\", \"fantacin\", \"flumequine\", \"flumequino\", \"flumequinum\", \"flumigal\", \"flumiquil\", \"flumisol\", \"flumix\", \"imequyl\")"	1.2	"g"			"character(0)"
-"FLR1"	71260	"Flurithromycin"	"Macrolides/lincosamides"	"J01FA14"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	""	"c(\"flurithromicina\", \"flurithromycime\", \"flurithromycin\", \"flurithromycine\", \"flurithromycinum\", \"fluritromicina\", \"fluritromycinum\", \"flurizic\")"	0.75	"g"			"character(0)"
-"FFL"	214356	"Fosfluconazole"	"Antifungals/antimycotics"				""	"c(\"fosfluconazole\", \"phosfluconazole\", \"procif\", \"prodif\")"					"character(0)"
-"FOS"	446987	"Fosfomycin"	"Other antibacterials"	"J01XX01"	"Other antibacterials"	"Other antibacterials"	"c(\"ff\", \"fm\", \"fo\", \"fof\", \"fos\", \"fosf\")"	"c(\"fosfocina\", \"fosfomicina\", \"fosfomycin\", \"fosfomycin sodium\", \"fosfomycine\", \"fosfomycinum\", \"fosfonomycin\", \"monuril\", \"monurol\", \"phosphonemycin\", \"phosphonomycin\", \"veramina\")"	3	"g"	8	"g"	"character(0)"
-"FMD"	572	"Fosmidomycin"	"Other antibacterials"				""	"c(\"fosmidomycin\", \"fosmidomycina\", \"fosmidomycine\", \"fosmidomycinum\")"					"character(0)"
-"FRM"	8378	"Framycetin"	"Aminoglycosides"	"c(\"D09AA01\", \"R01AX08\", \"S01AA07\")"			"c(\"\", \"fram\")"	"c(\"actilin\", \"actiline\", \"antibiotique\", \"bycomycin\", \"endomixin\", \"enterfram\", \"fradiomycin\", \"fradiomycin b\", \"fradiomycinum\", \"framicetina\", \"framycetin\", \"framycetin sulfate\", \"framycetine\", \"framycetinum\", \"framygen\", \"fraquinol\", \"jernadex\", \"myacine\", \"myacyne\", \"mycerin\", \"mycifradin\", \"neobrettin\", \"neolate\", \"neomas\", \"neomcin\", \"neomicina\", \"neomin\", \"neomycin\", \"neomycin b\", \"neomycin b sulfate\", \"neomycin solution\", \"neomycin sulfate\", \"neomycin sulphate\", \"neomycinb\", \"neomycine\", \"neomycinum\", 
-\"nivemycin\", \"pimavecort\", \"soframycin\", \"soframycine\", \"tuttomycin\", \"vonamycin\", \"vonamycin powder v\")"					"character(0)"
-"FRZ"	5323714	"Furazolidone"	"Other antibacterials"	"G01AX06"			""	"c(\"bifuron\", \"corizium\", \"coryzium\", \"diafuron\", \"enterotoxon\", \"furall\", \"furaxon\", \"furaxone\", \"furazol\", \"furazolidine\", \"furazolidon\", \"furazolidona\", \"furazolidone\", \"furazolidonum\", \"furazolum\", \"furazon\", \"furidon\", \"furovag\", \"furox aerosol powder\", \"furoxal\", \"furoxane\", \"furoxon\", \"furoxone\", \"furoxone liquid\", \"furoxone swine mix\", \"furozolidine\", \"giardil\", \"giarlam\", \"medaron\", \"neftin\", \"nicolen\", \"nifulidone\", \"nifuran\", \"nifurazolidone\", \"nifurazolidonum\", \"nitrofurazolidone\", \"nitrofurazolidonum\", 
-\"nitrofuroxon\", \"optazol\", \"ortazol\", \"puradin\", \"roptazol\", \"sclaventerol\", \"tikofuran\", \"topazone\", \"trichofuron\", \"tricofuron\", \"tricoron\", \"trifurox\", \"viofuragyn\")"					"character(0)"
-"FUS"	3000226	"Fusidic acid"	"Other antibacterials"	"c(\"D06AX01\", \"D09AA02\", \"J01XC01\", \"S01AA13\")"	"Other antibacterials"	"Steroid antibacterials"	"c(\"fa\", \"fusi\")"	"c(\"acide fusidique\", \"acido fusidico\", \"acidum fusidicum\", \"flucidin\", \"fucidate\", \"fucidate sodium\", \"fucidic acid\", \"fucidin\", \"fucidin acid\", \"fucithalmic\", \"fusidate\", \"fusidate acid\", \"fusidic acid\", \"fusidine\", \"fusidinic acid\", \"ramycin\")"	1.5	"g"	1.5	"g"	"character(0)"
-"GAM"	59364992	"Gamithromycin"	"Macrolides/lincosamides"				""	"gamithromycin"					"character(0)"
-"GRN"	124093	"Garenoxacin"	"Quinolones"	"J01MA19"			""	"c(\"ganefloxacin\", \"garenfloxacin\", \"garenoxacin\")"	0.4	"g"			"character(0)"
-"GAT"	5379	"Gatifloxacin"	"Quinolones"	"c(\"J01MA16\", \"S01AE06\")"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"\", \"gati\")"	"c(\"gatiflo\", \"gatifloxacin\", \"gatifloxacine\", \"gatifloxcin\", \"gatilox\", \"gatiquin\", \"gatispan\", \"tequin\", \"tequin and zymar\", \"zymaxid\")"	0.4	"g"	0.4	"g"	"character(0)"
-"GEM"	9571107	"Gemifloxacin"	"Quinolones"	"J01MA15"	"Quinolone antibacterials"	"Fluoroquinolones"	""	"c(\"factiv\", \"factive\", \"gemifioxacin\", \"gemifloxacin\", \"gemifloxacine\", \"gemifloxacino\", \"gemifloxacinum\")"	0.32	"g"			"character(0)"
-"GEN"	3467	"Gentamicin"	"Aminoglycosides"	"c(\"D06AX07\", \"J01GB03\", \"S01AA11\", \"S02AA14\", \"S03AA06\")"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	"c(\"cn\", \"gen\", \"gent\", \"gm\")"	"c(\"apogen\", \"centicin\", \"cidomycin\", \"garasol\", \"genoptic liquifilm\", \"genoptic s.o.p.\", \"gentacycol\", \"gentafair\", \"gentak\", \"gentamar\", \"gentamcin sulfate\", \"gentamicin\", \"gentamicina\", \"gentamicine\", \"gentamicins\", \"gentamicinum\", \"gentamycin\", \"gentamycins\", \"gentamycinum\", \"gentavet\", \"gentocin\", \"jenamicin\", \"lyramycin\", \"oksitselanim\", \"refobacin\", \"refobacin tm\", \"septigen\", \"uromycine\")"			0.24	"g"	"c(\"13561-6\", \"13562-4\", \"15106-8\", \"22746-2\", \"22747-0\", \"31091-2\", \"31092-0\", \"31093-8\", \"35668-3\", \"3663-2\", \"3664-0\", \"3665-7\", \"39082-3\", \"47109-4\", \"59379-8\", \"80971-5\", \"88111-0\")"
-"GEH"		"Gentamicin-high"	"Aminoglycosides"				"c(\"gehi\", \"gehl\", \"genta high\", \"gentamicin high\")"	""					""
-"GEP"	25101874	"Gepotidacin"	"Other antibacterials"				""	"gepotidacin"					"character(0)"
-"GRX"	72474	"Grepafloxacin"	"Quinolones"	"J01MA11"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"\", \"grep\")"	"grepafloxacin"	0.4	"g"			"character(0)"
-"GRI"	441140	"Griseofulvin"	"Antifungals/antimycotics"	"c(\"D01AA08\", \"D01BA01\")"			""	"c(\"amudane\", \"curling factor\", \"delmofulvina\", \"fulcin\", \"fulcine\", \"fulvican grisactin\", \"fulvicin\", \"fulvicin bolus\", \"fulvidex\", \"fulvina\", \"fulvinil\", \"fulvistatin\", \"fungivin\", \"greosin\", \"gresfeed\", \"gricin\", \"grifulin\", \"grifulvin\", \"grifulvin v\", \"grisactin\", \"grisactin ultra\", \"grisactin v\", \"griscofulvin\", \"grise ostatin\", \"grisefuline\", \"griseo\", \"griseofulvin\", \"griseofulvin forte\", \"griseofulvina\", \"griseofulvine\", \"griseofulvinum\", \"griseomix\", \"griseostatin\", \"grisetin\", \"grisofulvin\", 
-\"grisovin\", \"grisovin fp\", \"grizeofulvin\", \"grysio\", \"guservin\", \"lamoryl\", \"likuden\", \"likunden\", \"murfulvin\", \"poncyl\", \"spirofulvin\", \"sporostatin xan\", \"xuanjing\")"	0.5	"g"			"12402-4"
-"HAB"	175989	"Habekacin"	"Aminoglycosides"				""	"c(\"arbekacin sulfate\", \"habekacin\", \"habekacin sulfate\", \"habekacin xsulfate\")"					"character(0)"
-"HCH"	11979956	"Hachimycin"	"Antifungals/antimycotics"	"c(\"D01AA03\", \"G01AA06\", \"J02AA02\")"	"Antimycotics for systemic use"	"Antibiotics"	""	"c(\"cabimicina\", \"hachimicina\", \"hachimycin\", \"hachimycine\", \"hachimycinum\", \"trichomycinum\", \"trichonat\")"					"character(0)"
-"HET"	443387	"Hetacillin"	"Beta-lactams/penicillins"	"J01CA18"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	""	"c(\"etacillina\", \"hetacilina\", \"hetacillin\", \"hetacilline\", \"hetacillinum\", \"phenazacillin\", \"versapen\")"	2	"g"			"character(0)"
-"HYG"	56928061	"Hygromycin"	"Aminoglycosides"				""	"c(\"antihelmycin\", \"hydromycin b\", \"hygrovetine\")"					"character(0)"
-"IBX"		"Ibrexafungerp"	"Antifungals"				""	""					""
-"ICL"	213043	"Iclaprim"	"Other antibacterials"	"J01EA03"			""	"c(\"iclaprim\", \"mersarex\")"					"character(0)"
-"IPM"	104838	"Imipenem"	"Carbapenems"	"J01DH51"	"Other beta-lactam antibacterials"	"Carbapenems"	"c(\"imci\", \"imi\", \"imip\", \"imp\")"	"c(\"imipemide\", \"imipenem\", \"imipenem anhydrous\", \"imipenem/cilastatin\", \"imipenemum\", \"imipenen\", \"primaxin\", \"tienamycin\")"			2	"g"	"c(\"17010-0\", \"25257-7\", \"27331-8\", \"3688-9\")"
-"IPE"		"Imipenem/EDTA"	"Carbapenems"				""	""					""
-"IMR"		"Imipenem/relebactam"	"Carbapenems"				""	""					""
-"ISV"	6918485	"Isavuconazole"	"Antifungals/antimycotics"	"J02AC05"			"c(\"\", \"isav\")"	"isavuconazole"	0.2	"g"	0.2	"g"	"character(0)"
-"ISE"	3037209	"Isepamicin"	"Aminoglycosides"	"J01GB11"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	""	"c(\"isepacin\", \"isepalline\", \"isepamicin\", \"isepamicina\", \"isepamicine\", \"isepamicinum\")"			0.4	"g"	"character(0)"
-"ISO"	3760	"Isoconazole"	"Antifungals/antimycotics"	"c(\"D01AC05\", \"G01AF07\")"	"Antimycotics for topic use"	"Triazole derivatives"	""	"c(\"isoconazol\", \"isoconazole\", \"isoconazolum\", \"travogen\")"					"character(0)"
-"INH"	3767	"Isoniazid"	"Antimycobacterials"	"J04AC01"	"Drugs for treatment of tuberculosis"	"Hydrazides"	"inh"	"c(\"abdizide\", \"andrazide\", \"anidrasona\", \"antimicina\", \"antituberkulosum\", \"armacide\", \"armazid\", \"armazide\", \"atcotibine\", \"azt + isoniazid\", \"azuren\", \"bacillin\", \"cemidon\", \"chemiazid\", \"chemidon\", \"continazine\", \"cortinazine\", \"cotinazin\", \"cotinizin\", \"defonin\", \"dibutin\", \"diforin\", \"dinacrin\", \"ditubin\", \"ebidene\", \"eralon\", \"ertuban\", \"eutizon\", \"evalon\", \"fetefu\", \"fimalene\", \"hid rasonil\", \"hidranizil\", \"hidrasonil\", \"hidrulta\", \"hidrun\", \"hycozid\", \"hydrazid\", \"hydrazide\", \"hyozid\", \"i.a.i.\", 
-\"idrazil\", \"inizid\", \"iscotin\", \"isidrina\", \"ismazide\", \"isobicina\", \"isocid\", \"isocidene\", \"isocotin\", \"isohydrazide\", \"isokin\", \"isolyn\", \"isonerit\", \"isonex\", \"isoniacid\", \"isoniazid\", \"isoniazid sa\", \"isoniazida\", \"isoniazide\", \"isoniazidum\", \"isonicazide\", \"isonicid\", \"isonico\", \"isonicotan\", \"isonicotil\", \"isonicotinhydrazid\", \"isonicotinohydrazide\", \"isonide\", \"isonidrin\", \"isonikazid\", \"isonilex\", \"isonin\", \"isonindon\", \"isonirit\", \"isoniton\", \"isonizida\", \"isonizide\", \"isotamine\", \"isotebe\", 
-\"isotebezid\", \"isotinyl\", \"isozid\", \"isozide\", \"isozyd\", \"laniazid\", \"laniozid\", \"lanizid\", \"mayambutol\", \"mybasan\", \"neoteben\", \"neoxin\", \"neumandin\", \"niadrin\", \"nicazide\", \"nicetal\", \"nicizina\", \"niconyl\", \"nicotibina\", \"nicotibine\", \"nicotisan\", \"nicozide\", \"nidaton\", \"nidrazid\", \"nikozid\", \"niplen\", \"nitadon\", \"niteban\", \"nydrazid\", \"nyscozid\", \"pelazid\", \"percin\", \"phthisen\", \"pycazide\", \"pyreazid\", \"pyricidin\", \"pyridicin\", \"pyrizidin\", \"raumanon\", \"razide\", \"retozide\", \"rifater\", \"rimicid\", 
-\"rimifon\", \"rimiphone\", \"rimitsid\", \"robiselin\", \"robisellin\", \"roxifen\", \"sanohidrazina\", \"sauterazid\", \"sauterzid\", \"stanozide\", \"tebecid\", \"tebenic\", \"tebexin\", \"tebilon\", \"teebaconin\", \"tekazin\", \"tibazide\", \"tibemid\", \"tibiazide\", \"tibinide\", \"tibison\", \"tibivis\", \"tibizide\", \"tibusan\", \"tisiodrazida\", \"tizide\", \"tubazid\", \"tubazide\", \"tubeco\", \"tubecotubercid\", \"tuberian\", \"tubicon\", \"tubilysin\", \"tubizid\", \"tubomel\", \"unicocyde\", \"unicozyde\", \"vazadrine\", \"vederon\", \"zidafimia\", \"zinadon\", 
-\"zonazide\")"	0.3	"g"	0.3	"g"	"c(\"25451-6\", \"26756-7\", \"3697-0\", \"40371-7\")"
-"ITR"	3793	"Itraconazole"	"Antifungals/antimycotics"	"J02AC02"	"Antimycotics for systemic use"	"Triazole derivatives"	"itra"	"c(\"itraconazol\", \"itraconazole\", \"itraconazolum\", \"itraconzaole\", \"itrazole\", \"oriconazole\", \"sporanox\")"	0.2	"g"	0.2	"g"	"c(\"10989-2\", \"12392-7\", \"25258-5\", \"27081-9\", \"32184-4\", \"32185-1\", \"80531-7\")"
-"JOS"	5282165	"Josamycin"	"Macrolides/lincosamides"	"J01FA07"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	""	"c(\"josacine\", \"josamicina\", \"josamycin\", \"josamycine\", \"josamycinum\")"	2	"g"			"character(0)"
-"KAN"	6032	"Kanamycin"	"Aminoglycosides"	"c(\"A07AA08\", \"J01GB04\", \"S01AA24\")"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	"c(\"hlk\", \"k\", \"kan\", \"kana\", \"km\")"	"c(\"kanamicina\", \"kanamycin\", \"kanamycin a\", \"kanamycin base\", \"kanamycine\", \"kanamycinum\", \"kantrex\", \"kenamycin a\", \"klebcil\", \"liposomal kanamycin\")"	3	"g"	1	"g"	"c(\"23889-9\", \"3698-8\", \"3699-6\", \"3700-2\", \"47395-9\")"
-"KAH"		"Kanamycin-high"	"Aminoglycosides"				"c(\"\", \"k_h\", \"kahl\")"	""					""
-"KAC"		"Kanamycin/cephalexin"	"Aminoglycosides"				""	""					""
-"KET"	456201	"Ketoconazole"	"Antifungals/antimycotics"	"c(\"D01AC08\", \"G01AF11\", \"H02CA03\", \"J02AB02\")"	"Antimycotics for systemic use"	"Imidazole derivatives"	"c(\"keto\", \"ktc\")"	"c(\"extina\", \"fungarest\", \"fungoral\", \"ketocanazole\", \"ketoconazol\", \"ketoconazole\", \"ketoconazolum\", \"ketoderm\", \"nizoral\", \"xolegel\")"	0.2	"g"			"c(\"10990-0\", \"12393-5\", \"25259-3\", \"60091-6\", \"60092-4\")"
-"KIT"		"Kitasamycin"	"Macrolides/lincosamides"				"c(\"\", \"leucomycin\")"	""					""
-"LAS"	5360807	"Lasalocid"	"Other antibacterials"				""	"c(\"avatec\", \"lasalocid\", \"lasalocid a\", \"lasalocide\", \"lasalocide a\", \"lasalocido\", \"lasalocidum\")"					"87598-9"
-"LTM"	47499	"Latamoxef"	"Cephalosporins (3rd gen.)"	"J01DD06"	"Other beta-lactam antibacterials"	"Third-generation cephalosporins"	"c(\"mox\", \"moxa\", \"moxalactam\")"	"c(\"disodium moxalactam\", \"festamoxin\", \"lamoxactam\", \"latamoxef\", \"latamoxefum\", \"shiomarin\")"			4	"g"	"character(0)"
-"LMU"	25185057	"Lefamulin"	"Other antibacterials"	"J01XX12"			""	"lefamulin"					"character(0)"
-"LEN"	65646	"Lenampicillin"	"Beta-lactams/penicillins"				""	"c(\"lenampicilina\", \"lenampicillin\", \"lenampicillin hcl\", \"lenampicilline\", \"lenampicillinum\")"					"character(0)"
-"LVX"	149096	"Levofloxacin"	"Quinolones"	"c(\"J01MA12\", \"S01AE05\")"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"le\", \"lev\", \"levo\", \"lvx\")"	"c(\"aeroquin\", \"cravit\", \"cravit hydrate\", \"cravit iv\", \"cravit ophthalmic\", \"elequine\", \"floxacin\", \"floxel\", \"iquix hydrate\", \"leroxacin\", \"lesacin\", \"levaquin\", \"levaquin hydrate\", \"levo floxacin\", \"levofiexacin\", \"levofloxacin\", \"levofloxacin hydrate\", \"levofloxacine\", \"levofloxacino\", \"levofloxacinum\", \"levokacin\", \"levoxacin\", \"mosardal\", \"nofaxin\", \"oftaquix\", \"quixin\", \"reskuin\", \"tavanic\", \"unibiotic\", \"venaxan\", \"volequin\")"	0.5	"g"	0.5	"g"	"c(\"21368-6\", \"30532-6\", \"30533-4\")"
-"LND"	9850038	"Levonadifloxacin"	"Quinolones"	"J01MA24"			""	"levonadifloxacin"					"character(0)"
-"LSP"		"Linco-spectin"	"Other antibacterials"				"c(\"\", \"lincomycin/spectinomycin\")"	""					""
-"LIN"	3000540	"Lincomycin"	"Macrolides/lincosamides"	"J01FF02"	"Macrolides, lincosamides and streptogramins"	"Lincosamides"	"linc"	"c(\"cillimycin\", \"jiemycin\", \"lincolcina\", \"lincolnensin\", \"lincomicina\", \"lincomycin\", \"lincomycin a\", \"lincomycine\", \"lincomycinum\")"	1.8	"g"	1.8	"g"	"87597-1"
-"LNZ"	441401	"Linezolid"	"Oxazolidinones"	"J01XX08"	"Other antibacterials"	"Other antibacterials"	"c(\"line\", \"lnz\", \"lz\", \"lzd\")"	"c(\"linezlid\", \"linezoid\", \"linezolid\", \"linezolide\", \"linezolidum\", \"zivoxid\", \"zyvoxa\", \"zyvoxam\", \"zyvoxid\")"	1.2	"g"	1.2	"g"	"c(\"34202-2\", \"80609-1\")"
-"LFE"		"Linoprist-flopristin"	"Other antibacterials"				""	""					""
-"LOM"	3948	"Lomefloxacin"	"Quinolones"	"c(\"J01MA07\", \"S01AE04\")"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"lmf\", \"lom\", \"lome\")"	"c(\"lomefloxacin\", \"lomefloxacine\", \"lomefloxacino\", \"lomefloxacinum\", \"maxaquin\")"	0.4	"g"			"character(0)"
-"LOR"	5284585	"Loracarbef"	"Cephalosporins (2nd gen.)"	"J01DC08"	"Other beta-lactam antibacterials"	"Second-generation cephalosporins"	"c(\"\", \"lora\")"	"c(\"anhydrous loracarbef\", \"lorabid\", \"loracarbef\", \"loracarbefum\", \"lorbef\", \"loribid\")"	0.6	"g"			"character(0)"
-"LYM"	54707177	"Lymecycline"	"Tetracyclines"	"J01AA04"	"Tetracyclines"	"Tetracyclines"	""	"c(\"biovetin\", \"chlortetracyclin\", \"ciclisin\", \"ciclolysal\", \"infaciclina\", \"limeciclina\", \"lisinbiotic\", \"lymecyclin\", \"lymecycline\", \"lymecyclinum\", \"mucomycin\", \"ntetracycline\", \"tetralisal\", \"tetralysal\", \"vebicyclysal\")"	0.6	"g"	0.6	"g"	"character(0)"
-"MNA"	1292	"Mandelic acid"	"Other antibacterials"	"c(\"B05CA06\", \"J01XX06\")"	"Other antibacterials"	"Other antibacterials"	""	"c(\"acido mandelico\", \"almond acid\", \"amygdalic acid\", \"benzoglycolic acid\", \"hydroxyacetic acid\", \"kyselina mandlova\", \"mandelic acid\", \"paramandelic acid\", \"phenylglycolic acid\", \"uromaline\")"	12	"g"			"character(0)"
-"MGX"		"Manogepix"	"Antifungals"				""	""					""
-"MAR"	60651	"Marbofloxacin"	"Quinolones"				""	"c(\"marbocyl\", \"marbofloxacin\", \"marbofloxacine\", \"marbofloxacino\", \"marbofloxacinum\", \"zeniquin\")"					"character(0)"
-"MEC"	36273	"Mecillinam"	"Beta-lactams/penicillins"	"J01CA11"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"c(\"\", \"amdinocillin\")"	"c(\"amdinocillin\", \"coactin\", \"hexacillin\", \"mecilinamo\", \"mecillinam\", \"mecillinamum\", \"micillinam\", \"penicillin hx\", \"selexidin\")"			1.2	"g"	"character(0)"
-"MEL"	71306732	"Meleumycin"	"Macrolides/lincosamides"				""	""					""
-"MEM"	441130	"Meropenem"	"Carbapenems"	"J01DH02"	"Other beta-lactam antibacterials"	"Carbapenems"	"c(\"mem\", \"mer\", \"mero\", \"mp\", \"mrp\")"	"c(\"meronem\", \"meropen\", \"meropenem\", \"meropenem anhydrous\", \"meropenem hydrate\", \"meropenem trihydrate\", \"meropenemum\", \"merrem\", \"merrem i.v.\", \"merrem iv\")"			3	"g"	"41406-0"
-"MNC"		"Meropenem/nacubactam"	"Carbapenems"				""	""					""
-"MEV"		"Meropenem/vaborbactam"	"Carbapenems"	"J01DH52"	"Other beta-lactam antibacterials"	"Carbapenems"	""	""			3	"g"	""
-"MES"	176886	"Mesulfamide"	"Other antibacterials"				""	"c(\"mesulfamide\", \"mesulfamido\", \"mesulfamidum\")"					"character(0)"
-"MTC"	54675785	"Metacycline"	"Tetracyclines"	"J01AA05"	"Tetracyclines"	"Tetracyclines"	""	"c(\"bialatan\", \"metaciclina\", \"metacycline\", \"metacyclinum\", \"methacycline\", \"methacycline base\", \"methacyclinum\", \"methylenecycline\", \"physiomycine\", \"rondomycin\")"	0.6	"g"			"character(0)"
-"MTM"	6713928	"Metampicillin"	"Beta-lactams/penicillins"	"J01CA14"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	""	"c(\"blomopen\", \"bonopen\", \"celinmicina\", \"elatocilline\", \"fedacilina kapseln\", \"filorex\", \"italcina kapseln\", \"magnipen\", \"metabacter ampullen\", \"metambac\", \"metampicilina\", \"metampicillin\", \"metampicillin sodium\", \"metampicillina\", \"metampicilline\", \"metampicillinum\", \"methampicillin\", \"metiskia ampullen\", \"micinovo\", \"micinovo ampullen\", \"pangocilin\", \"probiotic\", \"rastomycin k\", \"relyothenate\", \"ruticina\", \"rutizina\", \"rutizina ampullen\", \"sedomycin\", \"suvipen\", \"suvipen ampullen\", \"tampilen ampullen\", 
-\"teonicon trofen\", \"viderpen\", \"viderpin\", \"vioplex\")"	1.5	"g"	1.5	"g"	"character(0)"
-"MTH"	4101	"Methenamine"	"Other antibacterials"	"J01XX05"	"Other antibacterials"	"Other antibacterials"	""	"c(\"aceto hmt\", \"aminoform\", \"aminoformaldehyde\", \"ammoform\", \"ammonioformaldehyde\", \"antihydral\", \"cystamin\", \"cystex\", \"cystogen\", \"duirexol\", \"ekagom h\", \"esametilentetramina\", \"formamine\", \"formin\", \"h.m.t.\", \"heksa k\", \"herax uts\", \"heterin\", \"hexa b\", \"hexaform\", \"hexaloids\", \"hexamethylamine\", \"hexamethylenamine\", \"hexamethyleneamine\", \"hexamethylentetramin\", \"hexamine\", \"hexamine silver\", \"hexamine superfine\", \"hexaminum\", \"hexasan\", \"hexilmethylenamine\", \"metenamina\", \"metenamine\", \"methamin\", 
-\"methenamin\", \"methenamine\", \"methenamine silver\", \"methenaminum\", \"metramine\", \"naphthamine\", \"nocceler h\", \"preparation af\", \"resotropin\", \"sanceler h\", \"sanceler ht\", \"silver methenamine\", \"uramin\", \"uratrine\", \"urisol\", \"uritone\", \"urodeine\", \"urotropin\", \"urotropine\", \"vesaloin\", \"vesalvine\", \"xametrin\")"	3	"g"			"character(0)"
-"MET"	6087	"Methicillin"	"Beta-lactams/penicillins"	"J01CF03"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase resistant penicillins"	"meti"	"c(\"dimocillin\", \"metacillin\", \"methcilline\", \"methicillin\", \"methicillinum\", \"methycillin\", \"meticilina\", \"meticillin\", \"meticillina\", \"meticilline\", \"meticillinum\", \"staphcillin\")"			4	"g"	"c(\"29492-6\", \"3788-7\")"
-"MTP"	68590	"Metioprim"	"Other antibacterials"				""	"c(\"methioprim\", \"metioprim\", \"metioprima\", \"metioprime\", \"metioprimum\")"					"character(0)"
-"MXT"	3047729	"Metioxate"	"Quinolones"				""	"c(\"metioxate\", \"metioxato\", \"metioxatum\")"					"character(0)"
-"MTR"	4173	"Metronidazole"	"Other antibacterials"	"c(\"A01AB17\", \"D06BX01\", \"G01AF01\", \"J01XD01\", \"P01AB01\")"	"Other antibacterials"	"Imidazole derivatives"	"c(\"metr\", \"mnz\")"	"c(\"acromona\", \"anagiardil\", \"arilin\", \"atrivyl\", \"danizol\", \"deflamon\", \"efloran\", \"elyzol\", \"entizol\", \"flagemona\", \"flagesol\", \"flagil\", \"flagyl\", \"flagyl er\", \"flagyl i.v.\", \"flagyl i.v. rtu\", \"flazol\", \"flegyl\", \"florazole\", \"fossyol\", \"giatricol\", \"ginefla vir\", \"gineflavir\", \"helidac\", \"mepagyl\", \"meronidal\", \"methronidazole\", \"metric\", \"metro cream\", \"metro gel\", \"metro i.v\", \"metro i.v.\", \"metro iv\", \"metrocream\", \"metrodzhil\", \"metrogel\", \"metrogyl\", \"metrolag\", \"metrolotion\", \"metrolyl\", 
-\"metromidol\", \"metronidaz\", \"metronidazol\", \"metronidazole\", \"metronidazole usp\", \"metronidazolo\", \"metronidazolum\", \"metrotop\", \"metrozine\", \"metryl\", \"mexibol\", \"mexibol 'silanes'\", \"monagyl\", \"monasin\", \"nidagel\", \"nidagyl\", \"noritate\", \"novonidazol\", \"orvagil\", \"polibiotic\", \"protostat\", \"rathimed\", \"rosased\", \"sanatrichom\", \"satric\", \"takimetol\", \"trichazol\", \"trichex\", \"tricho cordes\", \"trichobrol\", \"trichocide\", \"trichomol\", \"trichopal\", \"trichopol\", \"tricocet\", \"tricom\", \"tricowas b\", \"trikacide\", 
-\"trikamon\", \"trikhopol\", \"trikojol\", \"trikozol\", \"trimeks\", \"trivazol\", \"vagilen\", \"vagimid\", \"vandazole\", \"vertisal\", \"wagitran\", \"zadstat\", \"zidoval\")"	2	"g"	1.5	"g"	"10991-8"
-"MEZ"	656511	"Mezlocillin"	"Beta-lactams/penicillins"	"J01CA10"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"c(\"mez\", \"mezl\", \"mz\")"	"c(\"mezlin\", \"mezlocilina\", \"mezlocillin\", \"mezlocillin acid\", \"mezlocillin sodium\", \"mezlocilline\", \"mezlocillinum\", \"multocillin\")"			6	"g"	"3820-8"
-"MSU"		"Mezlocillin/sulbactam"	"Beta-lactams/penicillins"				""	""					""
-"MIF"	477468	"Micafungin"	"Antifungals/antimycotics"	"J02AX05"	"Antimycotics for systemic use"	"Other antimycotics for systemic use"	"c(\"\", \"mica\")"	"c(\"micafungin\", \"mycamine\")"			0.1	"g"	"58418-5"
-"MCZ"	4189	"Miconazole"	"Antifungals/antimycotics"	"c(\"A01AB09\", \"A07AC01\", \"D01AC02\", \"G01AF04\", \"J02AB01\", \"S02AA13\")"	"Antimycotics for systemic use"	"Imidazole derivatives"	"mico"	"c(\"aflorix\", \"albistat\", \"andergin\", \"brentan\", \"conofite\", \"dactarin\", \"daktarin\", \"daktarin iv\", \"florid\", \"lotrimin af\", \"micantin\", \"miconasil nitrate\", \"miconazol\", \"miconazole\", \"miconazole base\", \"miconazolo\", \"miconazolum\", \"micozole\", \"minostate\", \"monista\", \"monistat\", \"monistat iv\", \"oravig\", \"vusion\", \"zimybase\", \"zimycan\")"	0.2	"g"	1	"g"	"17278-3"
-"MCR"	3037206	"Micronomicin"	"Aminoglycosides"	"S01AA22"			""	"c(\"gentamicin c\", \"micromycin\", \"micronomicin\", \"micronomicina\", \"micronomicine\", \"micronomicinum\", \"sagamicin\", \"santemycin\")"					"character(0)"
-"MID"	5282169	"Midecamycin"	"Macrolides/lincosamides"	"J01FA03"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	""	"c(\"aboren\", \"espinomycin a\", \"macropen\", \"madecacine\", \"medemycin\", \"midecamicina\", \"midecamycin\", \"midecamycin a\", \"midecamycine\", \"midecamycinum\", \"midecin\", \"momicine\", \"mydecamycin\", \"myoxam\", \"normicina\", \"rubimycin\", \"turimycin p\")"	1.2	"g"	1	"g"	"character(0)"
-"MIL"	37614	"Miloxacin"	"Quinolones"				""	"c(\"miloxacin\", \"miloxacine\", \"miloxacino\", \"miloxacinum\")"					"character(0)"
-"MNO"	54675783	"Minocycline"	"Tetracyclines"	"c(\"A01AB23\", \"D10AF07\", \"J01AA08\")"	"Tetracyclines"	"Tetracyclines"	"c(\"mc\", \"mh\", \"mi\", \"min\", \"mino\", \"mn\", \"mno\")"	"c(\"akamin\", \"aknemin\", \"borymycin\", \"dynacin\", \"klinomycin\", \"minociclina\", \"minocin\", \"minocline\", \"minocyclin\", \"minocycline\", \"minocyclinum\", \"minocyn\", \"minoderm\", \"minomycin\", \"sebomin\", \"solodyn\", \"vectrin\")"	1	"mg"	0.2	"g"	"c(\"34606-4\", \"3822-4\", \"49757-8\")"
-"MCM"	5282188	"Miocamycin"	"Macrolides/lincosamides"	"J01FA11"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	""	"c(\"acecamycin\", \"macroral\", \"midecamycin acetate\", \"miocamen\", \"miocamycine\", \"miokamycin\", \"myocamicin\", \"ponsinomycin\")"	1.2	"g"			"character(0)"
-"MON"	23667299	"Monensin sodium"	"Other antibacterials"				""	"c(\"monensin sodium\", \"sodium monensin\")"					"character(0)"
-"MRN"	70374	"Morinamide"	"Antimycobacterials"	"J04AK04"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	""	"c(\"morfazinamide\", \"morfazinammide\", \"morfgazinamide\", \"morinamida\", \"morinamide\", \"morinamidum\", \"morphazinamid\", \"morphazinamide\", \"piazofolina\", \"piazolin\", \"piazolina\")"					"character(0)"
-"MFX"	152946	"Moxifloxacin"	"Quinolones"	"c(\"J01MA14\", \"S01AE07\")"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"mox\", \"moxi\", \"mxf\")"	"c(\"actira\", \"avelox\", \"avelox i.v.\", \"avelox iv\", \"avolex\", \"izilox\", \"moxeza\", \"moxifloxacin\", \"moxifloxacine\", \"vigamox\")"	0.4	"g"	0.4	"g"	"c(\"43751-7\", \"45223-5\", \"80540-8\")"
-"MUP"	446596	"Mupirocin"	"Other antibacterials"	"c(\"D06AX09\", \"R01AX06\")"			"c(\"mup\", \"mupi\")"	"c(\"bactoderm\", \"bactroban\", \"bactroban nasal\", \"bactroban ointment\", \"centany\", \"mupirocin\", \"mupirocina\", \"mupirocine\", \"mupirocinum\", \"plasimine\", \"pseudomonic acid\", \"pseudomonic acid a\", \"turixin\")"					"character(0)"
-"NAC"	73386748	"Nacubactam"	"Beta-lactams/penicillins"				""	"nacubactam"					"character(0)"
-"NAD"	4410	"Nadifloxacin"	"Quinolones"	"D10AF05"			""	"c(\"acuatim\", \"nadifloxacin\", \"nadifloxacine\", \"nadifloxacino\", \"nadifloxacinum\", \"nadixa\", \"nadoxin\")"					"character(0)"
-"NAF"	8982	"Nafcillin"	"Beta-lactams/penicillins"	"J01CF06"			""	"c(\"nafcilina\", \"nafcillin\", \"nafcillin sodium\", \"nafcilline\", \"nafcillinum\", \"nallpen\", \"naphcillin\", \"unipen\")"			3	"g"	"c(\"10993-4\", \"25232-0\")"
-"ZWK"	117587595	"Nafithromycin"	"Macrolides/lincosamides"				""	"nafithromycin"					"character(0)"
-"NAL"	4421	"Nalidixic acid"	"Quinolones"	"J01MB02"	"Quinolone antibacterials"	"Other quinolones"	"c(\"na\", \"nal\", \"nali\")"	"c(\"acide nalidixico\", \"acide nalidixique\", \"acido nalidissico\", \"acido nalidixico\", \"acidum nalidixicum\", \"betaxina\", \"dixiben\", \"dixinal\", \"eucisten\", \"eucistin\", \"innoxalomn\", \"innoxalon\", \"jicsron\", \"kusnarin\", \"naldixic acid\", \"nalidic acid\", \"nalidicron\", \"nalidixan\", \"nalidixane\", \"nalidixate\", \"nalidixate sodium\", \"nalidixic\", \"nalidixic acid\", \"nalidixin\", \"nalidixinic acid\", \"nalidixinsaure\", \"nalitucsan\", \"nalurin\", \"narigix\", \"naxuril\", \"neggram\", \"negram\", \"nevigramon\", \"nicelate\", \"nogram\", 
-\"poleon\", \"sicmylon\", \"specifen\", \"specifin\", \"unaserus\", \"uralgin\", \"uriben\", \"uriclar\", \"urisal\", \"urodixin\", \"uroman\", \"uroneg\", \"uronidix\", \"uropan\", \"wintomylon\", \"wintron\")"	4	"g"			"character(0)"
-"NAR"	65452	"Narasin"	"Other antibacterials"				""	"c(\"monteban\", \"narasin\", \"narasin a\", \"narasine\", \"narasino\", \"narasinum\", \"narasul\")"					"87570-8"
-"NEO"	8378	"Neomycin"	"Aminoglycosides"	"c(\"A01AB08\", \"A07AA01\", \"B05CA09\", \"D06AX04\", \"J01GB05\", \"R02AB01\", \"S01AA03\", \"S02AA07\", \"S03AA01\")"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	"neom"	"c(\"actilin\", \"actiline\", \"antibiotique\", \"bycomycin\", \"endomixin\", \"enterfram\", \"fradiomycin\", \"fradiomycin b\", \"fradiomycinum\", \"framicetina\", \"framycetin\", \"framycetin sulfate\", \"framycetine\", \"framycetinum\", \"framygen\", \"fraquinol\", \"jernadex\", \"myacine\", \"myacyne\", \"mycerin\", \"mycifradin\", \"neobrettin\", \"neolate\", \"neomas\", \"neomcin\", \"neomicina\", \"neomin\", \"neomycin\", \"neomycin b\", \"neomycin b sulfate\", \"neomycin solution\", \"neomycin sulfate\", \"neomycin sulphate\", \"neomycinb\", \"neomycine\", \"neomycinum\", 
-\"nivemycin\", \"pimavecort\", \"soframycin\", \"soframycine\", \"tuttomycin\", \"vonamycin\", \"vonamycin powder v\")"	5	"g"			"c(\"10995-9\", \"25262-7\")"
-"NET"	441306	"Netilmicin"	"Aminoglycosides"	"c(\"J01GB07\", \"S01AA23\")"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	"neti"	"c(\"netillin\", \"netilmicin\", \"netilmicin sulfate\", \"netilmicina\", \"netilmicine\", \"netilmicinum\", \"netilyn\", \"netira\", \"vectacin\")"	0.35	"g"	0.35	"g"	"c(\"25263-5\", \"3848-9\", \"3849-7\", \"3850-5\", \"47385-0\", \"59565-2\", \"59566-0\", \"59567-8\")"
-"NIC"	9507	"Nicarbazin"	"Other antibacterials"				""	"c(\"nicarb\", \"nicarbasin\", \"nicarbazin\", \"nicarbazine\", \"nicoxin\", \"nicrazin\", \"nicrazine\", \"nirazin\")"					"character(0)"
-"NIF"	71946	"Nifuroquine"	"Quinolones"				""	"c(\"nifuroquina\", \"nifuroquine\", \"nifuroquinum\", \"quinaldofur\")"					"character(0)"
-"NFR"	9571062	"Nifurtoinol"	"Other antibacterials"	"J01XE02"	"Other antibacterials"	"Nitrofuran derivatives"	""	"c(\"levantin\", \"nifurtoinol\", \"nifurtoinolo\", \"nifurtoinolum\", \"urfadin\", \"urfadine\", \"urfadyn\")"	0.16	"g"			"character(0)"
-"NTZ"	41684	"Nitazoxanide"	"Other antibacterials"	"P01AX11"			""	"c(\"adrovet\", \"alinia\", \"azt + nitazoxanide\", \"colufase\", \"cryptaz\", \"dexidex\", \"heliton\", \"kidonax\", \"nitaxozanid\", \"nitaxozanide\", \"nitazox\", \"nitazoxamide\", \"nitazoxanid\", \"nitazoxanida\", \"nitazoxanide\", \"nitazoxanidum\", \"omniparax\", \"pacovanton\", \"paramix\", \"taenitaz\")"	1	"g"			"character(0)"
-"NIT"	6604200	"Nitrofurantoin"	"Other antibacterials"	"J01XE01"	"Other antibacterials"	"Nitrofuran derivatives"	"c(\"f\", \"f/m\", \"fd\", \"ft\", \"ni\", \"nit\", \"nitr\")"	"c(\"alfuran\", \"benkfuran\", \"berkfuran\", \"berkfurin\", \"ceduran\", \"chemiofuran\", \"cistofuran\", \"cyantin\", \"cystit\", \"dantafur\", \"fua med\", \"fuamed\", \"furabid\", \"furachel\", \"furadantin\", \"furadantin retard\", \"furadantina mc\", \"furadantine\", \"furadantine mc\", \"furadantoin\", \"furadoin\", \"furadoine\", \"furadonin\", \"furadonine\", \"furadoninum\", \"furadontin\", \"furadoxyl\", \"furalan\", \"furaloid\", \"furantoin\", \"furantoina\", \"furatoin\", \"furedan\", \"furina\", \"furobactina\", \"furodantin\", \"furophen t\", \"gerofuran\", 
-\"io>>uss>>a<<ixoo\", \"ituran\", \"ivadantin\", \"macpac\", \"macrobid\", \"macrodantin\", \"macrodantina\", \"macrofuran\", \"macrofurin\", \"nierofu\", \"nifurantin\", \"nifuretten\", \"nitoin\", \"nitrex\", \"nitrofuradantin\", \"nitrofurantion\", \"nitrofurantoin\", \"nitrofurantoin macro\", \"nitrofurantoina\", \"nitrofurantoine\", \"nitrofurantoinum\", \"novofuran\", \"orafuran\", \"parfuran\", \"phenurin\", \"piyeloseptyl\", \"siraliden\", \"trantoin\", \"uerineks\", \"urantoin\", \"urizept\", \"urodin\", \"urofuran\", \"urofurin\", \"urolisa\", \"urolong\", 
-\"uvamin\", \"welfurin\", \"zoofurin\")"	0.2	"g"			"3860-4"
-"NIZ"	5447130	"Nitrofurazone"	"Other antibacterials"				""	"c(\"acutol\", \"aldomycin\", \"alfucin\", \"amifur\", \"babrocid\", \"becafurazone\", \"biofuracina\", \"biofurea\", \"chemofuran\", \"chixin\", \"cocafurin\", \"coxistat\", \"dermofural\", \"dymazone\", \"dynazone\", \"eldezol\", \"fedacin\", \"flavazone\", \"fracine\", \"furacilin\", \"furacilinum\", \"furacillin\", \"furacin\", \"furacine\", \"furacinetten\", \"furacoccid\", \"furacort\", \"furacycline\", \"furaderm\", \"furagent\", \"furalcyn\", \"furaldon\", \"furalone\", \"furametral\", \"furaplast\", \"furaseptyl\", \"furaskin\", \"furatsilin\", \"furaziline\", \"furazin\", 
-\"furazina\", \"furazol w\", \"furazone\", \"furazyme\", \"furesol\", \"furfurin\", \"furosem\", \"fuvacillin\", \"hemofuran\", \"ibiofural\", \"mammex\", \"mastofuran\", \"monafuracin\", \"monafuracis\", \"monofuracin\", \"nfz mix\", \"nifucin\", \"nifurid\", \"nifuzon\", \"nitrofural\", \"nitrofuralum\", \"nitrofuran\", \"nitrofurane\", \"nitrofurazan\", \"nitrofurazone\", \"nitrofurazonum\", \"nitrofurol\", \"nitrozone\", \"otofural\", \"otofuran\", \"rivafurazon\", \"sanfuran\", \"vabrocid\", \"vadrocid\", \"yatrocin\")"					"character(0)"
-"NTR"	19910	"Nitroxoline"	"Quinolones"	"J01XX07"	"Other antibacterials"	"Other antibacterials"	""	"c(\"galinok\", \"isinok\", \"nibiol\", \"nicene forte\", \"nitroxolin\", \"nitroxolina\", \"nitroxoline\", \"nitroxolinum\", \"notroxoline\", \"noxibiol\")"	1	"g"			"character(0)"
-"NOR"	4539	"Norfloxacin"	"Quinolones"	"c(\"J01MA06\", \"S01AE02\")"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"nor\", \"norf\", \"nx\", \"nxn\")"	"c(\"baccidal\", \"barazan\", \"chibroxin\", \"chibroxine\", \"chibroxol\", \"fulgram\", \"gonorcin\", \"lexinor\", \"nolicin\", \"noracin\", \"noraxin\", \"norflo\", \"norfloxacin\", \"norfloxacine\", \"norfloxacino\", \"norfloxacinum\", \"norocin\", \"noroxin\", \"noroxine\", \"norxacin\", \"sebercim\", \"uroxacin\", \"utinor\", \"zoroxin\")"	0.8	"g"			"3867-9"
-"NVA"	10419027	"Norvancomycin"	"Glycopeptides"				""	"norvancomycin"					"character(0)"
-"NOV"	54675769	"Novobiocin"	"Other antibacterials"				"novo"	"c(\"albamix\", \"albamycin\", \"cardelmycin\", \"cathocin\", \"cathomycin\", \"crystallinic acid\", \"inamycin\", \"novobiocin\", \"novobiocina\", \"novobiocine\", \"novobiocinum\", \"robiocina\", \"sirbiocina\", \"spheromycin\", \"stilbiocina\", \"streptonivicin\")"					"17378-1"
-"NYS"	6433272	"Nystatin"	"Antifungals/antimycotics"	"c(\"A07AA02\", \"D01AA01\", \"G01AA01\")"			"nyst"	"c(\"biofanal\", \"candex lotion\", \"comycin\", \"diastatin\", \"herniocid\", \"moronal\", \"myconystatin\", \"mycostatin\", \"mycostatin pastilles\", \"mykinac\", \"mykostatyna\", \"nilstat\", \"nistatin\", \"nistatina\", \"nyamyc\", \"nyotran\", \"nyotrantrade mark\", \"nystaform\", \"nystan\", \"nystatin\", \"nystatin a\", \"nystatin g\", \"nystatin lf\", \"nystatine\", \"nystatinum\", \"nystatyna\", \"nystavescent\", \"nystex\", \"nystop\", \"stamycin\", \"terrastatin\", \"zydin e\")"	1.5	"MU"			"character(0)"
-"OFX"	4583	"Ofloxacin"	"Quinolones"	"c(\"J01MA01\", \"S01AE01\", \"S02AA16\")"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"of\", \"ofl\", \"oflo\", \"ofx\")"	"c(\"bactocin\", \"danoflox\", \"effexin\", \"exocin\", \"exocine\", \"flobacin\", \"flodemex\", \"flotavid\", \"flovid\", \"floxal\", \"floxil\", \"floxin\", \"floxin otic\", \"floxstat\", \"fugacin\", \"inoflox\", \"kinflocin\", \"kinoxacin\", \"levofloxacin hcl\", \"liflox\", \"loxinter\", \"marfloxacin\", \"medofloxine\", \"mergexin\", \"monoflocet\", \"novecin\", \"nufafloqo\", \"occidal\", \"ocuflox\", \"oflocee\", \"oflocet\", \"oflocin\", \"oflodal\", \"oflodex\", \"oflodura\", \"ofloxacin\", \"ofloxacin otic\", \"ofloxacina\", \"ofloxacine\", \"ofloxacino\", \"ofloxacinum\", 
-\"ofloxin\", \"onexacin\", \"operan\", \"orocin\", \"otonil\", \"oxaldin\", \"pharflox\", \"praxin\", \"puiritol\", \"qinolon\", \"quinolon\", \"quotavil\", \"sinflo\", \"tabrin\", \"taravid\", \"tariflox\", \"tarivid\", \"telbit\", \"tructum\", \"uro tarivid\", \"viotisone\", \"visiren\", \"zanocin\")"	0.4	"g"	0.4	"g"	"c(\"25264-3\", \"3877-8\")"
-"OLE"	72493	"Oleandomycin"	"Macrolides/lincosamides"	"J01FA05"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	""	"c(\"amimycin\", \"landomycin\", \"matromycin\", \"oleandomycin a\", \"romicil\")"	1	"g"			"character(0)"
-"OMC"	54697325	"Omadacycline"	"Tetracyclines"	"J01AA15"			""	"c(\"amadacycline\", \"omadacycline\")"	0.3	"g"	0.1	"g"	"character(0)"
-"OPT"	87880	"Optochin"	"Other antibacterials"				""	"c(\"numoquin\", \"optochin\", \"optoquine\")"					"character(0)"
-"ORB"	60605	"Orbifloxacin"	"Quinolones"				""	"orbifloxacin"					"character(0)"
-"ORI"	16136912	"Oritavancin"	"Glycopeptides"	"J01XA05"	"Other antibacterials"	"Glycopeptide antibacterials"	"orit"	"oritavancin"					"character(0)"
-"ORS"		"Ormetroprim/sulfamethoxazole"	"Other antibacterials"				""	""					""
-"ORN"	28061	"Ornidazole"	"Other antibacterials"	"c(\"G01AF06\", \"J01XD03\", \"P01AB03\")"	"Other antibacterials"	"Imidazole derivatives"	""	"c(\"madelen\", \"ornidal\", \"ornidazol\", \"ornidazole\", \"ornidazolum\", \"tiberal\")"	1.5	"g"	1	"g"	"character(0)"
-"OXA"	6196	"Oxacillin"	"Beta-lactams/penicillins"	"J01CF04"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase resistant penicillins"	"c(\"ox\", \"oxa\", \"oxac\", \"oxal\", \"oxs\")"	"c(\"bactocill\", \"ossacillina\", \"oxacilina\", \"oxacillin\", \"oxacillin sodium\", \"oxacilline\", \"oxacillinum\", \"oxazocillin\", \"oxazocilline\", \"prostaphlin\", \"prostaphlyn\", \"sodium oxacillin\")"	2	"g"	2	"g"	"c(\"25265-0\", \"3882-8\")"
-"OXO"	4628	"Oxolinic acid"	"Quinolones"	"J01MB05"	"Quinolone antibacterials"	"Other quinolones"	""	"c(\"acide oxolinique\", \"acido ossolico\", \"acido oxolinico\", \"acidum oxolinicum\", \"aqualinic\", \"cistopax\", \"dioxacin\", \"emyrenil\", \"gramurin\", \"inoxyl\", \"nidantin\", \"oksaren\", \"orthurine\", \"ossian\", \"oxoboi\", \"oxolinic\", \"oxolinic acid\", \"pietil\", \"prodoxal\", \"prodoxol\", \"starner\", \"tiurasin\", \"ultibid\", \"urinox\", \"uritrate\", \"urotrate\", \"uroxol\", \"utibid\")"	1	"g"			"character(0)"
-"OXY"	54675779	"Oxytetracycline"	"Tetracyclines"	"c(\"D06AA03\", \"G01AA07\", \"J01AA06\", \"S01AA04\")"	"Tetracyclines"	"Tetracyclines"	""	"c(\"adamycin\", \"berkmycen\", \"biostat\", \"biostat pa\", \"dabicycline\", \"dalimycin\", \"embryostat\", \"fanterrin\", \"galsenomycin\", \"geomycin\", \"geotilin\", \"hydroxytetracyclinum\", \"imperacin\", \"lenocycline\", \"macocyn\", \"medamycin\", \"mepatar\", \"oksisyklin\", \"ossitetraciclina\", \"oxacycline\", \"oxitetraciclina\", \"oxitetracyclin\", \"oxitetracycline\", \"oxitetracyclinum\", \"oxydon\", \"oxymycin\", \"oxymykoin\", \"oxypam\", \"oxysteclin\", \"oxyterracin\", \"oxyterracine\", \"oxyterracyne\", \"oxytetracid\", \"oxytetracyclin\", \"oxytetracycline\", 
-\"oxytetracycline base\", \"oxytetracyclinum\", \"proteroxyna\", \"riomitsin\", \"ryomycin\", \"solkaciclina\", \"stecsolin\", \"stevacin\", \"tarocyn\", \"tarosin\", \"teravit\", \"terrafungine\", \"terramitsin\", \"terramycin\", \"terramycin im\", \"tetran\", \"unimycin\", \"ursocyclin\", \"ursocycline\", \"vendarcin\")"	1	"g"	1	"g"	"c(\"17396-3\", \"25266-8\", \"87595-5\")"
-"OZN"		"Ozenoxacin"					""	""					""
-"PAS"	4649	"P-aminosalicylic acid"	"Antimycobacterials"				""	"c(\"aminopar\", \"aminosalicylic\", \"aminosalicylic acid\", \"aminosalyl\", \"aminox\", \"apacil\", \"deapasil\", \"entepas\", \"ferrosan\", \"gabbropas\", \"helipidyl\", \"hellipidyl\", \"neopasalate\", \"osacyl\", \"pamacyl\", \"pamisyl\", \"paramycin\", \"parasal\", \"parasalicil\", \"parasalindon\", \"pasalon\", \"pasara\", \"pascorbic\", \"pasdium\", \"paser granules\", \"paskalium\", \"pasmed\", \"pasnodia\", \"pasolac\", \"propasa\", \"rezipas\", \"teebacin\", \"wln: zr cq dvq\")"					"character(0)"
-"PAN"	72015	"Panipenem"	"Carbapenems"				""	"c(\"panipenem\", \"panipenemum\", \"penipanem\")"					"character(0)"
-"PAR"	165580	"Paromomycin"	"Other antibacterials"	"A07AA06"			""	"c(\"aminosidin\", \"aminosidine\", \"aminosidine i\", \"aminosidine sulfate\", \"amminosidin\", \"crestomycin\", \"estomycin\", \"gabbromicina\", \"gabbromycin\", \"gabromycin\", \"humatin\", \"humycin\", \"hydroxymycin\", \"hydroxymycin sulfate\", \"monomycin\", \"monomycin a\", \"neomycin e\", \"paramomycin\", \"paramomycin sulfate\", \"paromomicina\", \"paromomycin\", \"paromomycin i\", \"paromomycine\", \"paromomycinum\", \"paucimycin\", \"paucimycinum\", \"quintomycin c\")"	3	"g"			"character(0)"
-"PAZ"	65957	"Pazufloxacin"	"Quinolones"	"J01MA18"	"Quinolone antibacterials"	"Fluoroquinolones"	""	"c(\"pazufloxacin\", \"pazufloxacine\", \"pazufloxacino\", \"pazufloxacinum\")"			1	"g"	"character(0)"
-"PEF"	51081	"Pefloxacin"	"Quinolones"	"J01MA03"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"\", \"pefl\")"	"c(\"abactal\", \"labocton\", \"pefloxacin\", \"pefloxacine\", \"pefloxacino\", \"pefloxacinum\", \"perfloxacin\", \"silver pefloxacin\")"	0.8	"g"	0.8	"g"	"3906-5"
-"PNM"	10250769	"Penamecillin"	"Beta-lactams/penicillins"	"J01CE06"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase sensitive penicillins"	""	"c(\"hydroxymethyl\", \"penamecilina\", \"penamecillin\", \"penamecillina\", \"penamecilline\", \"penamecillinum\")"	1.05	"g"			"character(0)"
-"PNO"		"Penicillin/novobiocin"	"Beta-lactams/penicillins"				""	""					""
-"PSU"		"Penicillin/sulbactam"	"Beta-lactams/penicillins"				""	""					""
-"PNM1"	54686187	"Penimepicycline"	"Tetracyclines"	"J01AA10"	"Tetracyclines"	"Tetracyclines"	""	"c(\"duamine\", \"hydrocycline\", \"penetracyne\", \"penimepiciclina\", \"penimepicycline\", \"penimepicyclinum\")"					"character(0)"
-"PIM"	65453	"Pentisomicin"	"Aminoglycosides"				""	"c(\"pentisomicin\", \"pentisomicina\", \"pentisomicine\", \"pentisomicinum\")"					"character(0)"
-"PTZ"	55250256	"Pentizidone"	"Other antibacterials"				""	""					""
-"PEX"	16132253	"Pexiganan"	"Other antibacterials"				""	"pexiganan"					"character(0)"
-"PHE"	272833	"Phenethicillin"	"Beta-lactams/penicillins"	"J01CE05"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase sensitive penicillins"	"c(\"\", \"fene\")"	"c(\"feneticilina\", \"feneticillina\", \"feneticilline\", \"k phenethicillin\", \"phenethicilin\", \"phenethicillinum\", \"pheneticillin\", \"pheneticilline\", \"pheneticillinum\", \"phenoxy pc\", \"potassium penicillin\")"	1	"g"			"41471-4"
-"PHN"	6869	"Phenoxymethylpenicillin"	"Beta-lactams/penicillins"	"J01CE02"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase sensitive penicillins"	"c(\"fepe\", \"peni v\", \"penicillin v\", \"pnv\", \"pv\")"	"c(\"acipen v\", \"apocillin\", \"apopen\", \"beromycin\", \"calcipen\", \"compocillin v\", \"crystapen v\", \"distaquaine v\", \"eskacillian v\", \"eskacillin v\", \"fenacilin\", \"fenospen\", \"meropenin\", \"oracillin\", \"oratren\", \"penicillin v\", \"phenocillin\", \"phenomycilline\", \"phenopenicillin\", \"robicillin\", \"rocilin\", \"stabicillin\", \"vebecillin\", \"veetids\", \"vegacillin\")"	2	"g"			"character(0)"
-"PMR"	5284447	"Pimaricin"	"Antifungals/antimycotics"				"c(\"\", \"natamycin\")"	"c(\"delvocid\", \"mycophyt\", \"myprozine\", \"natacyn\", \"natamicina\", \"natamycin\", \"natamycine\", \"natamycinum\", \"pimafucin\", \"pimaracin\", \"pimarizin\", \"synogil\", \"tennecetin\")"					"character(0)"
-"PPA"	4831	"Pipemidic acid"	"Quinolones"	"J01MB04"	"Quinolone antibacterials"	"Other quinolones"	"c(\"pipz\", \"pizu\")"	"c(\"acide pipemidique\", \"acido pipemidico\", \"acidum pipemidicum\", \"deblaston\", \"dolcol\", \"pipedac\", \"pipemid\", \"pipemidic\", \"pipemidic acid\", \"pipemidicacid\", \"pipram\", \"uromidin\")"	0.8	"g"			"character(0)"
-"PIP"	43672	"Piperacillin"	"Beta-lactams/penicillins"	"J01CA12"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"c(\"pi\", \"pip\", \"pipc\", \"pipe\", \"pp\")"	"c(\"isipen\", \"pentcillin\", \"peperacillin\", \"peracin\", \"piperacilina\", \"piperacillin\", \"piperacillin na\", \"piperacillin sodium\", \"piperacilline\", \"piperacillinum\", \"pipercillin\", \"pipracil\", \"pipril\")"			14	"g"	"c(\"25268-4\", \"3972-7\")"
-"PIS"		"Piperacillin/sulbactam"	"Beta-lactams/penicillins"				""	""					""
-"TZP"	461573	"Piperacillin/tazobactam"	"Beta-lactams/penicillins"	"J01CR05"	"Beta-lactam antibacterials, penicillins"	"Combinations of penicillins, incl. beta-lactamase inhibitors"	"c(\"p/t\", \"piptaz\", \"piptazo\", \"pit\", \"pita\", \"pt\", \"ptc\", \"ptz\", \"tzp\")"	"c(\"\", \"tazocel\", \"tazocillin\", \"tazocin\", \"zosyn\")"			14	"g"	"character(0)"
-"PRC"	71978	"Piridicillin"	"Beta-lactams/penicillins"				""	"piridicillin"					"character(0)"
-"PRL"	157385	"Pirlimycin"	"Macrolides/lincosamides"				""	"c(\"pirlimycin\", \"pirlimycina\", \"pirlimycine\", \"pirlimycinum\", \"pirsue\")"					"character(0)"
-"PIR"	4855	"Piromidic acid"	"Quinolones"	"J01MB03"	"Quinolone antibacterials"	"Other quinolones"	""	"c(\"acide piromidique\", \"acido piromidico\", \"acidum piromidicum\", \"actrun c\", \"bactramyl\", \"enterol\", \"gastrurol\", \"panacid\", \"pirodal\", \"piromidic acid\", \"pyrido\", \"reelon\", \"septural\", \"urisept\", \"uropir\", \"zaomeal\")"	2	"g"			"character(0)"
-"PVM"	33478	"Pivampicillin"	"Beta-lactams/penicillins"	"J01CA02"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	""	"c(\"berocillin\", \"pivaloylampicillin\", \"pivampicilina\", \"pivampicillin\", \"pivampicilline\", \"pivampicillinum\", \"pondocillin\")"	1.05	"g"			"character(0)"
-"PME"	115163	"Pivmecillinam"	"Beta-lactams/penicillins"	"J01CA08"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	""	"c(\"amdinocillin pivoxil\", \"coactabs\", \"hydroxymethyl\", \"pivmecilinamo\", \"pivmecillinam\", \"pivmecillinam hcl\", \"pivmecillinamum\")"	0.6	"g"			"character(0)"
-"PLZ"	42613186	"Plazomicin"	"Aminoglycosides"	"J01GB14"			""	"plazomicin"					"92024-9"
-"PLB"	49800004	"Polymyxin B"	"Polymyxins"	"c(\"A07AA05\", \"J01XB02\", \"S01AA18\", \"S02AA11\", \"S03AA03\")"	"Other antibacterials"	"Polymyxins"	"c(\"pb\", \"pol\", \"polb\", \"poly\", \"poly b\", \"polymixin\", \"polymixin b\")"	"c(\"polimixina b\", \"polumyxin b\", \"polymixin b\", \"polymyxine b\")"	3	"MU"	0.15	"g"	"c(\"17473-0\", \"25269-2\")"
-"POP"		"Polymyxin B/polysorbate 80"	"Polymyxins"				""	""					""
-"POS"	468595	"Posaconazole"	"Antifungals/antimycotics"	"J02AC04"	"Antimycotics for systemic use"	"Triazole derivatives"	"posa"	"c(\"noxafil\", \"posaconazole\", \"posaconazole sp\", \"posconazole\")"	0.3	"g"	0.3	"g"	"c(\"53731-6\", \"80545-7\")"
-"PRA"	9802884	"Pradofloxacin"	"Quinolones"				""	"pradofloxacin"					"character(0)"
-"PRX"	71455	"Premafloxacin"	"Quinolones"				""	"premafloxacin"					"character(0)"
-"PMD"	456199	"Pretomanid"	"Antimycobacterials"	"J04AK08"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	""	""					""
-"PRM"	6446787	"Primycin"	"Macrolides/lincosamides"				""	""					""
-"PRI"	11979535	"Pristinamycin"	"Macrolides/lincosamides"	"J01FG01"	"Macrolides, lincosamides and streptogramins"	"Streptogramins"	"c(\"\", \"pris\")"	"c(\"eskalin v\", \"mikamycin\", \"mikamycine\", \"mikamycinum\", \"ostreogrycinum\", \"pristinamycine\", \"pristinamycinum\", \"stafac\", \"stafytracine\", \"staphylomycin\", \"starfac\", \"streptogramin\", \"vernamycin\", \"virgimycin\", \"virgimycine\", \"virginiamycina\", \"virginiamycine\", \"virginiamycinum\")"	2	"g"			"character(0)"
-"PRB"	5903	"Procaine benzylpenicillin"	"Beta-lactams/penicillins"	"J01CE09"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase sensitive penicillins"	""	"c(\"depocillin\", \"duphapen\", \"hostacillin\", \"hydracillin\", \"jenacillin o\", \"nopcaine\", \"penicillin procaine\", \"retardillin\", \"vetspen\", \"vitablend\")"			0.6	"g"	"character(0)"
-"PRP"	92879	"Propicillin"	"Beta-lactams/penicillins"	"J01CE03"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase sensitive penicillins"	""	"c(\"propicilina\", \"propicillin\", \"propicilline\", \"propicillinum\")"	0.9	"g"			"character(0)"
-"PKA"	9872451	"Propikacin"	"Aminoglycosides"				""	"c(\"propikacin\", \"propikacina\", \"propikacine\", \"propikacinum\")"					"character(0)"
-"PTH"	666418	"Prothionamide"	"Antimycobacterials"	"J04AD01"	"Drugs for treatment of tuberculosis"	"Thiocarbamide derivatives"	"prot"	"c(\"ektebin\", \"peteha\", \"prothionamide\", \"prothionamidum\", \"protion\", \"protionamid\", \"protionamida\", \"protionamide\", \"protionamidum\", \"protionizina\", \"tebeform\", \"trevintix\", \"tuberex\")"	0.75	"g"			"character(0)"
-"PRU"	65947	"Prulifloxacin"	"Quinolones"	"J01MA17"	"Quinolone antibacterials"	"Fluoroquinolones"	""	"c(\"prulifloxacin\", \"pruvel\", \"pufloxacin dioxolil\", \"quisnon\")"	0.6	"g"			"character(0)"
-"PZA"	1046	"Pyrazinamide"	"Antimycobacterials"	"J04AK01"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	"pyra"	"c(\"aldinamid\", \"aldinamide\", \"braccopiral\", \"corsazinmid\", \"dipimide\", \"eprazin\", \"farmizina\", \"isopas\", \"lynamide\", \"novamid\", \"p ezetamid\", \"pezetamid\", \"pharozinamide\", \"piraldina\", \"pirazimida\", \"pirazinamid\", \"pirazinamida\", \"pirazinamide\", \"prazina\", \"pyrafat\", \"pyramide\", \"pyrazide\", \"pyrazinamdie\", \"pyrazinamid\", \"pyrazinamide\", \"pyrazinamidum\", \"pyrazine carboxamide\", \"pyrazineamide\", \"pyrizinamide\", \"rifafour\", \"rozide\", \"tebrazid\", \"tebrazio\", \"tisamid\", \"unipyranamide\", \"zinamide\", \"zinastat\"
-)"	1.5	"g"			"c(\"11001-5\", \"25270-0\")"
-"QDA"	11979418	"Quinupristin/dalfopristin"	"Macrolides/lincosamides"	"J01FG02"	"Macrolides, lincosamides and streptogramins"	"Streptogramins"	"c(\"q/d\", \"qda\", \"qida\", \"quda\", \"rp\", \"syn\")"	""			1.5	"g"	""
-"RAC"	56052	"Ractopamine"	"Other antibacterials"				""	"c(\"ractopamina\", \"ractopamine\", \"ractopaminum\")"					"character(0)"
-"RAM"	16132338	"Ramoplanin"	"Glycopeptides"				""	"ramoplanin"					"character(0)"
-"RZM"	10993211	"Razupenem"	"Carbapenems"				""	"razupenem"					"character(0)"
-"RTP"	6918462	"Retapamulin"	"Other antibacterials"	"D06AX13"	"Antibiotics for topical use"	"Other antibiotics for topical use"	"c(\"\", \"ret\")"	"c(\"altabax\", \"altargo\", \"retapamulin\")"					"character(0)"
-"RZF"		"Rezafungin"	"Antifungals"				""	""					""
-"RBC"	44631912	"Ribociclib"	"Antifungals/antimycotics"	"L01EF02"	"Antimycotics for systemic use"	"Triazole derivatives"	"ribo"	"c(\"kisqali\", \"ribociclib\")"					"character(0)"
-"RST"	33042	"Ribostamycin"	"Aminoglycosides"	"J01GB10"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	""	"c(\"dekamycin iv\", \"hetangmycin\", \"ribastamin\", \"ribostamicina\", \"ribostamycin\", \"ribostamycine\", \"ribostamycinum\", \"vistamycin\", \"xylostatin\")"			1	"g"	"character(0)"
-"RID1"	16659285	"Ridinilazole"	"Other antibacterials"				""	"ridinilazole"					"character(0)"
-"RIB"	135398743	"Rifabutin"	"Antimycobacterials"	"J04AB04"	"Drugs for treatment of tuberculosis"	"Antibiotics"	"rifb"	"c(\"alfacid\", \"ansamicin\", \"ansamycin\", \"ansatipin\", \"ansatipine\", \"mycobutin\", \"rifabutin\", \"rifabutina\", \"rifabutine\", \"rifabutinum\")"	0.15	"g"			"24032-5"
-"RIF"	135398735	"Rifampicin"	"Antimycobacterials"	"J04AB02"	"Drugs for treatment of tuberculosis"	"Antibiotics"	"rifa"	"c(\"abrifam\", \"archidyn\", \"arficin\", \"arzide\", \"azt + rifampin\", \"benemicin\", \"benemycin\", \"dipicin\", \"doloresum\", \"eremfat\", \"famcin\", \"fenampicin\", \"rifadin\", \"rifadin i.v\", \"rifadin i.v.\", \"rifadine\", \"rifagen\", \"rifaldazin\", \"rifaldazine\", \"rifaldin\", \"rifamate\", \"rifamicin amp\", \"rifamor\", \"rifampicin\", \"rifampicin sv\", \"rifampicina\", \"rifampicine\", \"rifampicinum\", \"rifampin\", \"rifamsolin\", \"rifamycin amp\", \"rifaprodin\", \"rifcin\", \"rifobac\", \"rifoldin\", \"rifoldine\", \"riforal\", \"rimactan\", \"rimactane\", 
-\"rimactizid\", \"rimazid\", \"rimycin\", \"sinerdol\", \"tubocin\")"	0.6	"g"	0.6	"g"	"character(0)"
-"RFI"		"Rifampicin/isoniazid"	"Antimycobacterials"	"J04AM02"	"Drugs for treatment of tuberculosis"	"Combinations of drugs for treatment of tuberculosis"	""	"c(\"rifinah\", \"rimactazid\")"					"character(0)"
-"RPEI"		"Rifampicin/pyrazinamide/ethambutol/isoniazid"	"Antimycobacterials"	"J04AM06"	"Drugs for treatment of tuberculosis"	"Combinations of drugs for treatment of tuberculosis"	""	""					""
-"RPI"		"Rifampicin/pyrazinamide/isoniazid"	"Antimycobacterials"	"J04AM05"	"Drugs for treatment of tuberculosis"	"Combinations of drugs for treatment of tuberculosis"	""	""					""
-"RFM"	6324616	"Rifamycin"	"Antimycobacterials"	"c(\"A07AA13\", \"D06AX15\", \"J04AB03\", \"S01AA16\", \"S02AA12\")"	"Drugs for treatment of tuberculosis"	"Antibiotics"	""	"c(\"aemcolo\", \"rifacin\", \"rifamicina\", \"rifamicine sv\", \"rifamycin\", \"rifamycine\", \"rifamycinum\", \"rifocin\", \"rifocyn\", \"rifomycin\", \"rifomycin sv\", \"tuborin\")"			0.6	"g"	"character(0)"
-"RFP"	135403821	"Rifapentine"	"Antimycobacterials"	"J04AB05"	"Drugs for treatment of tuberculosis"	"Antibiotics"	"c(\"rifp\", \"rpt\")"	"c(\"cyclopentyl rifampin\", \"priftin\", \"rifapentin\", \"rifapentina\", \"rifapentine\", \"rifapentinum\")"	0.11	"g"			"character(0)"
-"RFX"	6436173	"Rifaximin"	"Other antibacterials"	"c(\"A07AA11\", \"D06AX11\")"	"Intestinal antiinfectives"	"Antibiotics"	""	"c(\"fatroximin\", \"flonorm\", \"lormyx\", \"lumenax\", \"normix\", \"redactiv\", \"rifacol\", \"rifamixin\", \"rifaxidin\", \"rifaximin\", \"rifaximina\", \"rifaximine\", \"rifaximinum\", \"rifaxin\", \"ritacol\", \"spiraxin\", \"xifaxan\", \"xifaxsan\")"	0.6	"g"			"character(0)"
-"RIT"	65633	"Ritipenem"	"Carbapenems"				""	"ritipenem"					"character(0)"
-"RIA"	163692	"Ritipenem acoxil"	"Carbapenems"				""	"ritipenem acoxil"					"character(0)"
-"ROK"	5282211	"Rokitamycin"	"Macrolides/lincosamides"	"J01FA12"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	""	"c(\"propionylleucomycin\", \"ricamycin\", \"rokicid\", \"rokital\", \"rokitamicina\", \"rokitamycin\", \"rokitamycine\", \"rokitamycinum\")"	0.8	"g"			"character(0)"
-"RLT"	54682938	"Rolitetracycline"	"Tetracyclines"	"J01AA09"	"Tetracyclines"	"Tetracyclines"	""	"c(\"bristacin\", \"kinteto\", \"reverin\", \"rolitetraciclina\", \"rolitetracycline\", \"rolitetracyclinum\", \"solvocillin\", \"superciclin\", \"synotodecin\", \"synterin\", \"syntetrex\", \"syntetrin\", \"velacicline\", \"velacycline\")"			0.35	"g"	"character(0)"
-"ROS"	287180	"Rosoxacin"	"Quinolones"	"J01MB01"	"Quinolone antibacterials"	"Other quinolones"	""	"c(\"acrosoxacin\", \"eracine\", \"eradacil\", \"eradacin\", \"rosoxacin\", \"rosoxacine\", \"rosoxacino\", \"rosoxacinum\", \"roxadyl\", \"winuron\")"	0.3	"g"			"character(0)"
-"RXT"		"Roxithromycin"	"Macrolides/lincosamides"	"J01FA06"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	"roxi"	""	0.3	"g"			""
-"RFL"	58258	"Rufloxacin"	"Quinolones"	"J01MA10"	"Quinolone antibacterials"	"Fluoroquinolones"	""	"c(\"rufloxacin\", \"rufloxacin hcl\", \"rufloxacine\", \"rufloxacino\", \"rufloxacinum\")"	0.2	"g"			"character(0)"
-"SAL"	3085092	"Salinomycin"	"Other antibacterials"				""	"c(\"coxistac\", \"procoxacin\", \"salinomicina\", \"salinomycin\", \"salinomycine\", \"salinomycinum\")"					"87593-0"
-"SAR"	56208	"Sarafloxacin"	"Quinolones"				""	"c(\"difloxacine\", \"difloxacino\", \"difloxacinum\", \"saraflox\", \"sarafloxacin\", \"sarafloxacine\", \"sarafloxacino\", \"sarafloxacinum\")"					"character(0)"
-"SRX"	9933415	"Sarmoxicillin"	"Beta-lactams/penicillins"				""	"sarmoxicillin"					"character(0)"
-"SEC"	71815	"Secnidazole"	"Other antibacterials"	"P01AB07"			""	"c(\"flagentyl\", \"secnidal\", \"secnidazol\", \"secnidazole\", \"secnidazolum\", \"secnil\", \"sindose\", \"solosec\")"	2	"g"			"character(0)"
-"SMF"		"Simvastatin/fenofibrate"	"Antimycobacterials"	"C10BA04"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	"simv"	""					""
-"SIS"	36119	"Sisomicin"	"Aminoglycosides"	"J01GB08"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	"siso"	"c(\"rickamicin\", \"salvamina\", \"siseptin sulfate\", \"sisomicin\", \"sisomicin sulfate\", \"sisomicina\", \"sisomicine\", \"sisomicinum\", \"sisomin\", \"sisomycin\", \"sissomicin\", \"sizomycin\")"			0.24	"g"	"character(0)"
-"SIT"	461399	"Sitafloxacin"	"Quinolones"	"J01MA21"			""	"c(\"gracevit\", \"sitafloxacinisomer\")"	0.1	"g"			"character(0)"
-"SDA"	2724368	"Sodium aminosalicylate"	"Antimycobacterials"	"J04AA02"	"Drugs for treatment of tuberculosis"	"Aminosalicylic acid and derivatives"	""	"c(\"bactylan\", \"decapasil\", \"lepasen\", \"monopas\", \"nippas\", \"p.a.s. sodium\", \"pamisyl sodium\", \"parasal sodium\", \"pas sodium\", \"pasade\", \"pasnal\", \"passodico\", \"salvis\", \"sanipirol\", \"sodiopas\", \"sodium p.a.s\", \"sodium pas\", \"teebacin\", \"tubersan\")"	14	"g"	14	"g"	"character(0)"
-"SOL"	25242512	"Solithromycin"	"Macrolides/lincosamides"	"J01FA16"			""	""					""
-"SPX"	60464	"Sparfloxacin"	"Quinolones"	"J01MA09"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"\", \"spa\", \"spar\")"	"c(\"esparfloxacino\", \"sparfloxacin\", \"sparfloxacine\", \"sparfloxacinum\")"	0.2	"g"			"character(0)"
-"SPT"	15541	"Spectinomycin"	"Other antibacterials"	"J01XX04"	"Other antibacterials"	"Other antibacterials"	"c(\"sc\", \"spe\", \"spec\", \"spt\")"	"c(\"actinospectacina\", \"adspec\", \"espectinomicina\", \"prospec\", \"specitinomycin\", \"spectam\", \"spectinomicina\", \"spectinomycin\", \"spectinomycin di hcl\", \"spectinomycine\", \"spectinomycinum\", \"stanilo\", \"togamycin\", \"trobicin\")"			3	"g"	"character(0)"
-"SPI"	6419898	"Spiramycin"	"Macrolides/lincosamides"	"J01FA02"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	"c(\"\", \"spir\")"	"c(\"espiramicin\", \"provamycin\", \"rovamycin\", \"rovamycine\", \"sequamycin\", \"spiramycine\", \"spiramycinum\")"	3	"g"			"character(0)"
-"SPM"		"Spiramycin/metronidazole"	"Other antibacterials"	"J01RA04"	"Combinations of antibacterials"	"Combinations of antibacterials"	""	""					""
-"STR"		"Streptoduocin"	"Aminoglycosides"	"J01GA02"	"Aminoglycoside antibacterials"	"Streptomycins"	""	""			1	"g"	""
-"STR1"	19649	"Streptomycin"	"Aminoglycosides"	"c(\"A07AA04\", \"J01GA01\")"	"Aminoglycoside antibacterials"	"Streptomycins"	"c(\"s\", \"stm\", \"str\", \"stre\")"	"c(\"agrept\", \"agrimycin\", \"chemform\", \"estreptomicina\", \"neodiestreptopab\", \"strepcen\", \"streptomicina\", \"streptomycin\", \"streptomycin a\", \"streptomycin spx\", \"streptomycin sulfate\", \"streptomycine\", \"streptomyzin\", \"vetstrep\")"			1	"g"	"4039-4"
-"STH"		"Streptomycin-high"	"Aminoglycosides"				"c(\"sthi\", \"sthl\", \"strepto high\", \"streptomycin high\")"	""					""
-"STI"		"Streptomycin/isoniazid"	"Antimycobacterials"	"J04AM01"	"Drugs for treatment of tuberculosis"	"Combinations of drugs for treatment of tuberculosis"	""	""					""
-"SUL"	130313	"Sulbactam"	"Beta-lactams/penicillins"	"J01CG01"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase inhibitors"	""	"c(\"betamaze\", \"sulbactam\", \"sulbactam acid\", \"sulbactam free acid\", \"sulbactamum\")"			1	"g"	"character(0)"
-"SBC"	20055036	"Sulbenicillin"	"Beta-lactams/penicillins"	"J01CA16"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	""	"c(\"kedacillina\", \"sulbenicilina\", \"sulbenicilline\", \"sulbenicillinum\")"			15	"g"	"character(0)"
-"SUC"	5318	"Sulconazole"	"Antifungals/antimycotics"	"D01AC09"			""	"c(\"sulconazol\", \"sulconazole\", \"sulconazolum\")"					"character(0)"
-"SUP"	6634	"Sulfachlorpyridazine"	"Other antibacterials"				""	"c(\"cluricol\", \"cosulid\", \"cosumix\", \"durasulf\", \"nefrosul\", \"nsulfanilamide\", \"prinzone vet\", \"prinzone vet.\", \"solfaclorpiridazina\", \"sonilyn\", \"sulfachlorpyridazine\", \"sulfacloropiridazina\", \"vetisulid\")"					"character(0)"
-"SDI"	5215	"Sulfadiazine"	"Trimethoprims"	"J01EC02"	"Sulfonamides and trimethoprim"	"Intermediate-acting sulfonamides"	""	"c(\"adiazin\", \"adiazine\", \"cocodiazine\", \"codiazine\", \"cremodiazine\", \"cremotres\", \"debenal\", \"deltazina\", \"diazin\", \"diazolone\", \"diazovit\", \"diazyl\", \"eskadiazine\", \"honey diazine\", \"liquadiazine\", \"microsulfon\", \"neazine\", \"neotrizine\", \"nsulfanilamide\", \"palatrize\", \"piridisir\", \"pirimal\", \"pyrimal\", \"quadetts\", \"quadramoid\", \"sanodiazine\", \"sildaflo\", \"silvadene\", \"solfadiazina\", \"spofadrizine\", \"sterazine\", \"sulfacombin\", \"sulfadiazene\", \"sulfadiazin\", \"sulfadiazina\", \"sulfadiazine\", \"sulfadiazinum\", 
-\"sulfapirimidin\", \"sulfapyrimidin\", \"sulfapyrimidine\", \"sulfatryl\", \"sulfazine\", \"sulfolex\", \"sulfonamides duplex\", \"sulfonsol\", \"sulfose\", \"sulphadiazine\", \"sulphadiazine e\", \"terfonyl\", \"theradiazine\", \"thermazene\", \"trifonamide\", \"triple sulfa\", \"triple sulfas\", \"trisem\", \"truozine\", \"zinc sulfadiazine\")"	0.6	"g"			"c(\"27216-1\", \"59742-7\", \"6907-0\")"
-"SLT"	122284	"Sulfadiazine/tetroxoprim"	"Trimethoprims"	"J01EE06"	"Sulfonamides and trimethoprim"	"Combinations of sulfonamides and trimethoprim, incl. derivatives"	""	""					""
-"SLT1"	64932	"Sulfadiazine/trimethoprim"	"Trimethoprims"	"J01EE02"	"Sulfonamides and trimethoprim"	"Combinations of sulfonamides and trimethoprim, incl. derivatives"	""	"c(\"antastmon\", \"cotrimazine\", \"diaziprim forte\", \"ditrim\", \"ditrivet\", \"sultrisan\", \"triglobe\", \"trimin\", \"tucoprim\", \"uniprim\")"					"character(0)"
-"SUD"	5323	"Sulfadimethoxine"	"Trimethoprims"	"J01ED01"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"c(\"agribon\", \"arnosulfan\", \"bactrovet\", \"deposul\", \"diasulfa\", \"diasulfyl\", \"dimetazina\", \"dinosol\", \"dorisul\", \"lasibon\", \"madribon\", \"madrigid\", \"madriqid\", \"madroxin\", \"madroxine\", \"maxulvet\", \"mecozine\", \"memcozine\", \"metoxidon\", \"neostrepal\", \"neostreptal\", \"nsulfanilamide\", \"omnibon\", \"persulfen\", \"primor\", \"radonin\", \"redifal\", \"rofenaid\", \"roscosulf\", \"scandisil\", \"solfadimetossina\", \"sudine\", \"suldixine\", \"sulfabon\", \"sulfadimethoxin\", \"sulfadimethoxine\", \"sulfadimethoxinum\", \"sulfadimetossina\", 
-\"sulfadimetoxin\", \"sulfadimetoxina\", \"sulfadimetoxine\", \"sulfastop\", \"sulfdimethoxine\", \"sulfoplan\", \"sulphadimethoxine\", \"sulxin\", \"sumbio\", \"symbio\", \"theracanzan\", \"ultrasulfon\")"	0.5	"g"			"character(0)"
-"SDM"	5327	"Sulfadimidine"	"Trimethoprims"	"J01EB03"	"Sulfonamides and trimethoprim"	"Short-acting sulfonamides"	""	"c(\"azolmetazin\", \"benzene sulfonamide\", \"calfspan\", \"calfspan tablets\", \"cremomethazine\", \"diazil\", \"diazilsulfadine\", \"dimezathine\", \"intradine\", \"kelametazine\", \"mermeth\", \"metazin\", \"neasina\", \"neazina\", \"nsulfanilamide\", \"panazin\", \"pirmazin\", \"primazin\", \"sa iii\", \"solfadimidina\", \"spanbolet\", \"sulfadimerazine\", \"sulfadimesin\", \"sulfadimesine\", \"sulfadimethyldiazine\", \"sulfadimezin\", \"sulfadimezine\", \"sulfadimezinum\", \"sulfadimidin\", \"sulfadimidina\", \"sulfadimidine\", \"sulfadimidinum\", \"sulfadine\", 
-\"sulfametazina\", \"sulfametazyny\", \"sulfamethazine\", \"sulfamethiazine\", \"sulfamezathine\", \"sulfamidine\", \"sulfasure sr bolus\", \"sulfodimesin\", \"sulfodimezine\", \"sulka k boluses\", \"sulka s boluses\", \"sulmet\", \"sulphadimidine\", \"sulphamethasine\", \"sulphamethazine\", \"sulphamezathine\", \"sulphamidine\", \"sulphodimezine\", \"superseptil\", \"superseptyl\", \"vertolan\")"	4	"g"			"character(0)"
-"SLT2"		"Sulfadimidine/trimethoprim"	"Trimethoprims"	"J01EE05"	"Sulfonamides and trimethoprim"	"Combinations of sulfonamides and trimethoprim, incl. derivatives"	""	""					""
-"SLF"	5344	"Sulfafurazole"	"Trimethoprims"	"c(\"J01EB05\", \"S01AB02\")"	"Sulfonamides and trimethoprim"	"Short-acting sulfonamides"	"c(\"\", \"sfsz\")"	"c(\"accuzole\", \"alphazole\", \"amidoxal\", \"astrazolo\", \"azo gantrisin\", \"azosulfizin\", \"bactesulf\", \"barazae\", \"chemouag\", \"cosoxazole\", \"dorsulfan\", \"dorsulfan warthausen\", \"entusil\", \"entusul\", \"eryzole\", \"gantrisin\", \"gantrisine\", \"gantrisona\", \"gantrizin\", \"gantrosan\", \"isoxamin\", \"neazolin\", \"neoxazoi\", \"neoxazol\", \"novazolo\", \"novosaxazole\", \"nsulfanilamide\", \"nsulphanilamide\", \"pancid\", \"pediazole\", \"renosulfan\", \"resoxol\", \"roxosul\", \"roxosul tablets\", \"roxoxol\", \"saxosozine\", \"sodizole\", \"solfafurazolo\", 
-\"soxamide\", \"soxazole\", \"soxisol\", \"soxitabs\", \"soxomide\", \"stansin\", \"sulbio\", \"sulfafuraz ole\", \"sulfafurazol\", \"sulfafurazole\", \"sulfafurazolum\", \"sulfagan\", \"sulfagen\", \"sulfaisoxazole\", \"sulfalar\", \"sulfapolar\", \"sulfasol\", \"sulfasoxazole\", \"sulfasoxizole\", \"sulfazin\", \"sulfisin\", \"sulfisonazole\", \"sulfisoxasole\", \"sulfisoxazol\", \"sulfisoxazole\", \"sulfisoxazolum\", \"sulfizin\", \"sulfizol\", \"sulfizole\", \"sulfofurazole\", \"sulfoxol\", \"suloxsol\", \"sulphafuraz\", \"sulphafurazol\", \"sulphafurazole\", \"sulphafurazolum\", 
-\"sulphaisoxazole\", \"sulphisoxazol\", \"sulphisoxazole\", \"sulphofurazole\", \"sulsoxin\", \"thiasin\", \"unisulf\", \"urisoxin\", \"uritrisin\", \"urogan\", \"vagilia\")"	4	"g"	4	"g"	"character(0)"
-"SLF1"	5343	"Sulfaisodimidine"	"Trimethoprims"	"J01EB01"	"Sulfonamides and trimethoprim"	"Short-acting sulfonamides"	""	"c(\"aristamid\", \"aristamide\", \"aristogyn\", \"domain\", \"domian\", \"elcosin\", \"elcosine\", \"elkosil\", \"elkosin\", \"elkosine\", \"erycon\", \"isosulf\", \"mefenal\", \"nsulfanilamide\", \"solfisomidina\", \"sulfadimetine\", \"sulfaisodimerazine\", \"sulfaisodimidine\", \"sulfaisodimidinum\", \"sulfaisomidine\", \"sulfamethin\", \"sulfasomidine\", \"sulfisomidina\", \"sulfisomidine\", \"sulfisomidine sodium\", \"sulfisomidinum\", \"sulphasomidine\")"	4	"g"	4	"g"	"character(0)"
-"SLF2"	9047	"Sulfalene"	"Trimethoprims"	"J01ED02"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"c(\"dalysep\", \"kelfizin\", \"kelfizina\", \"kelfizine\", \"kelfizine w\", \"longum\", \"nsulfanilamide\", \"policydal\", \"polycidal\", \"solfametopirazina\", \"sulfalen\", \"sulfalene\", \"sulfaleno\", \"sulfalenum\", \"sulfamethopyrazine\", \"sulfamethoxypyrazine\", \"sulfametopyrazine\", \"sulfametoxypyridazin\", \"sulphalene\", \"sulphametopyrazine\", \"vetkelfizina\")"	0.1	"g"			"character(0)"
-"SZO"	187764	"Sulfamazone"	"Trimethoprims"	"J01ED09"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"c(\"sulfamazon\", \"sulfamazona\", \"sulfamazone\", \"sulfamazonum\")"	1.5	"g"			"character(0)"
-"SLF3"	5325	"Sulfamerazine"	"Trimethoprims"	"c(\"D06BA06\", \"J01ED07\")"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"c(\"cremomerazine\", \"kelamerazine\", \"mebacid\", \"mesulfa\", \"methylpyrimal\", \"methylsulfazin\", \"methylsulfazine\", \"metilsulfadiazin\", \"metilsulfazin\", \"nsulfanilamide\", \"percoccide\", \"pyralcid\", \"pyrimal m\", \"romezin\", \"septacil\", \"septosyl\", \"solfamerazina\", \"solumedin\", \"sulfameradine\", \"sulfamerazin\", \"sulfamerazina\", \"sulfamerazine\", \"sulfamerazinum\", \"sulfamethyldiazine\", \"sulphamerazine\", \"sumedine\", \"susfamerazine\")"	3	"g"			"character(0)"
-"SLT3"		"Sulfamerazine/trimethoprim"	"Trimethoprims"	"J01EE07"	"Sulfonamides and trimethoprim"	"Combinations of sulfonamides and trimethoprim, incl. derivatives"	""	""					""
-"SUM"	5327	"Sulfamethazine"	"Other antibacterials"				""	"c(\"azolmetazin\", \"benzene sulfonamide\", \"calfspan\", \"calfspan tablets\", \"cremomethazine\", \"diazil\", \"diazilsulfadine\", \"dimezathine\", \"intradine\", \"kelametazine\", \"mermeth\", \"metazin\", \"neasina\", \"neazina\", \"nsulfanilamide\", \"panazin\", \"pirmazin\", \"primazin\", \"sa iii\", \"solfadimidina\", \"spanbolet\", \"sulfadimerazine\", \"sulfadimesin\", \"sulfadimesine\", \"sulfadimethyldiazine\", \"sulfadimezin\", \"sulfadimezine\", \"sulfadimezinum\", \"sulfadimidin\", \"sulfadimidina\", \"sulfadimidine\", \"sulfadimidinum\", \"sulfadine\", 
-\"sulfametazina\", \"sulfametazyny\", \"sulfamethazine\", \"sulfamethiazine\", \"sulfamezathine\", \"sulfamidine\", \"sulfasure sr bolus\", \"sulfodimesin\", \"sulfodimezine\", \"sulka k boluses\", \"sulka s boluses\", \"sulmet\", \"sulphadimidine\", \"sulphamethasine\", \"sulphamethazine\", \"sulphamezathine\", \"sulphamidine\", \"sulphodimezine\", \"superseptil\", \"superseptyl\", \"vertolan\")"					"87592-2"
-"SLF4"	5328	"Sulfamethizole"	"Trimethoprims"	"c(\"B05CA04\", \"D06BA04\", \"J01EB02\", \"S01AB01\")"	"Sulfonamides and trimethoprim"	"Short-acting sulfonamides"	"c(\"\", \"sfmz\")"	"c(\"ayerlucil\", \"lucosil\", \"methazol\", \"microsul\", \"nsulfanilamide\", \"proklar\", \"renasul\", \"salimol\", \"solfametizolo\", \"sulamethizole\", \"sulfa gram\", \"sulfamethizol\", \"sulfamethizole\", \"sulfamethizolum\", \"sulfametizol\", \"sulfapyelon\", \"sulfstat\", \"sulfurine\", \"sulphamethizole\", \"tetracid\", \"thidicur\", \"thiosulfil\", \"thiosulfil forte\", \"ultrasul\", \"urocydal\", \"urodiaton\", \"urolucosil\", \"urosulfin\")"	4	"g"			"c(\"60175-7\", \"60176-5\", \"60177-3\")"
-"SMX"	5329	"Sulfamethoxazole"	"Trimethoprims"	"J01EC01"	"Sulfonamides and trimethoprim"	"Intermediate-acting sulfonamides"	"c(\"sfmx\", \"sulf\")"	"c(\"azo gantanol\", \"eusaprim\", \"gamazole\", \"gantanol\", \"gantanol ds\", \"metoxal\", \"nsulfanilamide\", \"nsulphanilamide\", \"radonil\", \"septran\", \"septrin\", \"simsinomin\", \"sinomin\", \"solfametossazolo\", \"sulfamethalazole\", \"sulfamethoxazol\", \"sulfamethoxazole\", \"sulfamethoxazolum\", \"sulfamethoxizole\", \"sulfamethylisoxazole\", \"sulfametoxazol\", \"sulfisomezole\", \"sulphamethalazole\", \"sulphamethoxazol\", \"sulphamethoxazole\", \"sulphisomezole\", \"urobak\")"	2	"g"			"c(\"10342-4\", \"25271-8\", \"39772-9\", \"59971-2\", \"59972-0\", \"60333-2\", \"72674-5\", \"80549-9\", \"80974-9\")"
-"SLF5"	5330	"Sulfamethoxypyridazine"	"Trimethoprims"	"J01ED05"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"c(\"altezol\", \"davosin\", \"depovernil\", \"kineks\", \"lederkyn\", \"lentac\", \"lisulfen\", \"longin\", \"medicel\", \"midicel\", \"midikel\", \"myasul\", \"nsulfanilamide\", \"opinsul\", \"paramid\", \"paramid supra\", \"petrisul\", \"piridolo\", \"quinoseptyl\", \"retamid\", \"retasulfin\", \"retasulphine\", \"slosul\", \"spofadazine\", \"sulfalex\", \"sulfapyridazine\", \"sulfdurazin\", \"sulfozona\", \"sultirene\", \"vinces\")"	0.5	"g"			"character(0)"
-"SLF6"	19596	"Sulfametomidine"	"Trimethoprims"	"J01ED03"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"c(\"duroprocin\", \"methofadin\", \"methofazine\", \"nsulfanilamide\", \"solfametomidina\", \"sulfamethomidine\", \"sulfametomidin\", \"sulfametomidina\", \"sulfametomidine\", \"sulfametomidinum\")"					"character(0)"
-"SLF7"	5326	"Sulfametoxydiazine"	"Trimethoprims"	"J01ED04"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"c(\"bayrena\", \"berlicid\", \"dairena\", \"durenat\", \"juvoxin\", \"kinecid\", \"kirocid\", \"longasulf\", \"methoxypyrimal\", \"nsulfanilamide\", \"solfametossidiazina\", \"sulfameter\", \"sulfamethorine\", \"sulfamethoxine\", \"sulfamethoxydiazin\", \"sulfamethoxydiazine\", \"sulfamethoxydin\", \"sulfamethoxydine\", \"sulfametin\", \"sulfametinum\", \"sulfametorin\", \"sulfametorine\", \"sulfametorinum\", \"sulfametoxidiazina\", \"sulfametoxidine\", \"sulfametoxydiazine\", \"sulfametoxydiazinum\", \"sulphameter\", \"sulphamethoxydiazine\", \"supramid\", 
-\"ultrax\")"	0.5	"g"			"character(0)"
-"SLT4"		"Sulfametrole/trimethoprim"	"Trimethoprims"	"J01EE03"	"Sulfonamides and trimethoprim"	"Combinations of sulfonamides and trimethoprim, incl. derivatives"	"c(\"\", \"trsm\")"	""					""
-"SLF8"	12894	"Sulfamoxole"	"Trimethoprims"	"J01EC03"	"Sulfonamides and trimethoprim"	"Intermediate-acting sulfonamides"	""	"c(\"justamil\", \"nsulfanilamide\", \"oxasulfa\", \"solfamossolo\", \"sulfadimethyloxazole\", \"sulfamoxol\", \"sulfamoxole\", \"sulfamoxolum\", \"sulfano\", \"sulfavigor\", \"sulfmidil\", \"sulfono\", \"sulfune\", \"sulfuno\", \"sulphamoxole\", \"tardamid\", \"tardamide\")"	1	"g"	1	"g"	"character(0)"
-"SLT5"		"Sulfamoxole/trimethoprim"	"Trimethoprims"	"J01EE04"	"Sulfonamides and trimethoprim"	"Combinations of sulfonamides and trimethoprim, incl. derivatives"	""	""					""
-"SLF9"	5333	"Sulfanilamide"	"Trimethoprims"	"c(\"D06BA05\", \"J01EB06\")"	"Sulfonamides and trimethoprim"	"Short-acting sulfonamides"	""	"c(\"albexan\", \"albosal\", \"ambeside\", \"antistrept\", \"astreptine\", \"astrocid\", \"bacteramid\", \"bactesid\", \"collomide\", \"colsulanyde\", \"copticide\", \"deseptyl\", \"desseptyl\", \"dipron\", \"ergaseptine\", \"erysipan\", \"estreptocida\", \"exoseptoplix\", \"gerison\", \"gombardol\", \"infepan\", \"lysococcine\", \"neococcyl\", \"orgaseptine\", \"prontalbin\", \"prontosil album\", \"prontosil i\", \"prontosil white\", \"prontylin\", \"pronzin album\", \"proseptal\", \"proseptine\", \"proseptol\", \"pysococcine\", \"rubiazol a\", \"sanamid\", \"septamide album\", 
-\"septanilam\", \"septinal\", \"septolix\", \"septoplex\", \"septoplix\", \"solfanilamide\", \"stopton album\", \"stramid\", \"strepamide\", \"strepsan\", \"streptagol\", \"streptamid\", \"streptamin\", \"streptasol\", \"streptocid\", \"streptocid album\", \"streptocide\", \"streptocide white\", \"streptocidum\", \"streptoclase\", \"streptocom\", \"streptol\", \"strepton\", \"streptopan\", \"streptosil\", \"streptozol\", \"streptozone\", \"streptrocide\", \"sulfamidyl\", \"sulfamine\", \"sulfana\", \"sulfanalone\", \"sulfanidyl\", \"sulfanil\", \"sulfanilamida\", \"sulfanilamide\", 
-\"sulfanilamidum\", \"sulfanilimidic acid\", \"sulfanimide\", \"sulfocidin\", \"sulfocidine\", \"sulfonamide\", \"sulfonamide p\", \"sulfonylamide\", \"sulphanilamide\", \"sulphanilamide gr\", \"sulphonamide\", \"therapol\", \"tolder\", \"white streptocide\", \"wln: zswr dz\")"					"character(0)"
-"SLF10"	68933	"Sulfaperin"	"Trimethoprims"	"J01ED06"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"c(\"anastaf\", \"archisulfa\", \"avissul\", \"chemiopen\", \"demosulfan\", \"durisan saft\", \"ipersulfidin sirup\", \"isosulfamerazine\", \"methylsulfadiazin\", \"novosul\", \"nsulfanilamide\", \"orosulfan\", \"pallidin\", \"retardon\", \"risulfasens\", \"sulfaperin\", \"sulfaperina\", \"sulfaperine\", \"sulfaperinum\", \"sulfatreis\", \"sulfopirimidine\", \"sulpenta\", \"ultrasulfon sirup\")"	0.5	"g"			"character(0)"
-"SLF11"	5335	"Sulfaphenazole"	"Trimethoprims"	"J01ED08"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"c(\"depocid\", \"depotsulfonamide\", \"eftolon\", \"firmazolo\", \"inamil\", \"isarol\", \"isarol v\", \"merian\", \"microtan pirazolo\", \"nsulfanilamide\", \"orisul\", \"orisulf\", \"paidazolo\", \"phenylsulfapyrazole\", \"plisulfan\", \"raziosulfa\", \"solfafenazolo\", \"sulfabid\", \"sulfafenazol\", \"sulfafenazolo\", \"sulfaphenazol\", \"sulfaphenazole\", \"sulfaphenazolum\", \"sulfaphenazon\", \"sulfaphenylpipazol\", \"sulfaphenylpyrazol\", \"sulfaphenylpyrazole\", \"sulfonylpyrazol\", \"sulphaphenazole\", \"sulphenazole\")"	1	"g"			"character(0)"
-"SLF12"	5336	"Sulfapyridine"	"Trimethoprims"	"J01EB04"	"Sulfonamides and trimethoprim"	"Short-acting sulfonamides"	""	"c(\"adiplon\", \"coccoclase\", \"dagenan\", \"eubasin\", \"eubasinum\", \"haptocil\", \"piridazol\", \"plurazol\", \"pyriamid\", \"pyridazol\", \"relbapiridina\", \"septipulmon\", \"solfapiridina\", \"streptosilpyridine\", \"sulfapiridina\", \"sulfapyridin\", \"sulfapyridine\", \"sulfapyridinum\", \"sulfidin\", \"sulfidine\", \"sulphapyridin\", \"sulphapyridine\", \"thioseptal\", \"trianon\")"	1	"g"			"c(\"14075-6\", \"55580-5\")"
-"SNA"	60582	"Sulfasuccinamide"	"Other antibacterials"				""	"c(\"ambesid\", \"derganil\", \"sulfasuccinamid\", \"sulfasuccinamida\", \"sulfasuccinamide\", \"sulfasuccinamidum\")"					"character(0)"
-"SUT"	5340	"Sulfathiazole"	"Trimethoprims"	"c(\"D06BA02\", \"J01EB07\")"	"Sulfonamides and trimethoprim"	"Short-acting sulfonamides"	""	"c(\"azoquimiol\", \"azoseptale\", \"cerazol\", \"cerazole\", \"chemosept\", \"cibazol\", \"duatok\", \"dulana\", \"eleudron\", \"enterobiocine\", \"estafilol\", \"formosulfathiazole\", \"neostrepsan\", \"norsulfasol\", \"norsulfazol\", \"norsulfazole\", \"norsulfazolum\", \"nsulfanilamide\", \"planomide\", \"poliseptil\", \"sanotiazol\", \"septozol\", \"solfatiazolo\", \"streptosilthiazole\", \"sulfamul\", \"sulfathiazol\", \"sulfathiazole\", \"sulfathiazolum\", \"sulfatiazol\", \"sulfavitina\", \"sulfocerol\", \"sulphathiazole\", \"sulzol\", \"thiacoccine\", \"thiasulfol\", 
-\"thiazamide\", \"thiozamide\", \"wintrazole\")"					"87591-4"
-"SLF13"	3000579	"Sulfathiourea"	"Trimethoprims"	"J01EB08"	"Sulfonamides and trimethoprim"	"Short-acting sulfonamides"	""	"c(\"badional\", \"baldinol\", \"fontamide\", \"salvoseptyl\", \"solfatiourea\", \"solufontamide\", \"sulfanilthiourea\", \"sulfathiocarbamid\", \"sulfathiocarbamide\", \"sulfathiocarbamidum\", \"sulfathiourea\", \"sulfathiouree\", \"sulfatiourea\", \"sulphathiourea\")"	6	"g"			"character(0)"
-"SOX"	5344	"Sulfisoxazole"	"Other antibacterials"				""	"c(\"accuzole\", \"alphazole\", \"amidoxal\", \"astrazolo\", \"azo gantrisin\", \"azosulfizin\", \"bactesulf\", \"barazae\", \"chemouag\", \"cosoxazole\", \"dorsulfan\", \"dorsulfan warthausen\", \"entusil\", \"entusul\", \"eryzole\", \"gantrisin\", \"gantrisine\", \"gantrisona\", \"gantrizin\", \"gantrosan\", \"isoxamin\", \"neazolin\", \"neoxazoi\", \"neoxazol\", \"novazolo\", \"novosaxazole\", \"nsulfanilamide\", \"nsulphanilamide\", \"pancid\", \"pediazole\", \"renosulfan\", \"resoxol\", \"roxosul\", \"roxosul tablets\", \"roxoxol\", \"saxosozine\", \"sodizole\", \"solfafurazolo\", 
-\"soxamide\", \"soxazole\", \"soxisol\", \"soxitabs\", \"soxomide\", \"stansin\", \"sulbio\", \"sulfafuraz ole\", \"sulfafurazol\", \"sulfafurazole\", \"sulfafurazolum\", \"sulfagan\", \"sulfagen\", \"sulfaisoxazole\", \"sulfalar\", \"sulfapolar\", \"sulfasol\", \"sulfasoxazole\", \"sulfasoxizole\", \"sulfazin\", \"sulfisin\", \"sulfisonazole\", \"sulfisoxasole\", \"sulfisoxazol\", \"sulfisoxazole\", \"sulfisoxazolum\", \"sulfizin\", \"sulfizol\", \"sulfizole\", \"sulfofurazole\", \"sulfoxol\", \"suloxsol\", \"sulphafuraz\", \"sulphafurazol\", \"sulphafurazole\", \"sulphafurazolum\", 
-\"sulphaisoxazole\", \"sulphisoxazol\", \"sulphisoxazole\", \"sulphofurazole\", \"sulsoxin\", \"thiasin\", \"unisulf\", \"urisoxin\", \"uritrisin\", \"urogan\", \"vagilia\")"					"9701-4"
-"SSS"	86225	"Sulfonamide"	"Other antibacterials"				"c(\"\", \"sfna\")"	""					""
-"SLP"	9950244	"Sulopenem"	"Other antibacterials"				""	"sulopenem"					"character(0)"
-"SLT6"	444022	"Sultamicillin"	"Beta-lactams/penicillins"	"J01CR04"	"Beta-lactam antibacterials, penicillins"	"Combinations of penicillins, incl. beta-lactamase inhibitors"	""	"c(\"sultamicilina\", \"sultamicillin\", \"sultamicillinum\")"	1.5	"g"			"character(0)"
-"SUR"	46700778	"Surotomycin"	"Other antibacterials"				""	"surotomycin"					"character(0)"
-"TAL"	71447	"Talampicillin"	"Beta-lactams/penicillins"	"J01CA15"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	""	"c(\"talampicilina\", \"talampicillin\", \"talampicilline\", \"talampicillinum\")"	2	"g"			"character(0)"
-"TLP"	163307	"Talmetoprim"	"Other antibacterials"				""	"talmetoprim"					"character(0)"
-"TAZ"	123630	"Tazobactam"	"Beta-lactams/penicillins"	"J01CG02"	"Beta-lactam antibacterials, penicillins"	"Beta-lactamase inhibitors"	"tazo"	"c(\"tazobactam\", \"tazobactam acid\", \"tazobactamum\", \"tazobactum\")"					"character(0)"
-"TBP"	9800194	"Tebipenem"	"Carbapenems"				""	""					""
-"TZD"	11234049	"Tedizolid"	"Oxazolidinones"	"J01XX11"	"Other antibacterials"	"Other antibacterials"	"tedi"	"c(\"tedizolid\", \"torezolid\")"	0.2	"g"	0.2	"g"	"character(0)"
-"TEC"	16131923	"Teicoplanin"	"Glycopeptides"	"J01XA02"	"Other antibacterials"	"Glycopeptide antibacterials"	"c(\"tec\", \"tei\", \"teic\", \"tp\", \"tpl\", \"tpn\")"	"c(\"targocid\", \"tecoplanina\", \"tecoplanine\", \"tecoplaninum\", \"teichomycin\", \"teicoplanina\", \"teicoplanine\", \"teicoplaninum\")"			0.4	"g"	"c(\"25534-9\", \"25535-6\", \"34378-0\", \"34379-8\", \"4043-6\", \"80968-1\")"
-"TCM"		"Teicoplanin-macromethod"	"Glycopeptides"				""	""					""
-"TLV"	3081362	"Telavancin"	"Glycopeptides"	"J01XA03"	"Other antibacterials"	"Glycopeptide antibacterials"	"tela"	"c(\"telavancin\", \"vibativ\")"					"character(0)"
-"TLT"	3002190	"Telithromycin"	"Macrolides/lincosamides"	"J01FA15"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	"c(\"\", \"teli\")"	"levviax"	0.8	"g"			"character(0)"
-"TMX"	60021	"Temafloxacin"	"Quinolones"	"J01MA05"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"\", \"tema\")"	"c(\"omniflox\", \"temafloxacin\", \"temafloxacina\", \"temafloxacine\", \"temafloxacinum\")"	0.8	"g"			"character(0)"
-"TEM"	171758	"Temocillin"	"Beta-lactams/penicillins"	"J01CA17"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"c(\"\", \"temo\")"	"c(\"temocilina\", \"temocillin\", \"temocillina\", \"temocilline\", \"temocillinum\")"			4	"g"	"character(0)"
-"TRB"	1549008	"Terbinafine"	"Antifungals/antimycotics"	"c(\"D01AE15\", \"D01BA02\")"	"Antifungals for systemic use"	"Antifungals for systemic use"	"c(\"\", \"terb\")"	"c(\"corbinal\", \"lamasil\", \"lamisil\", \"lamisil at\", \"lamisil tablet\", \"terbinafina\", \"terbinafine\", \"terbinafinum\", \"terbinex\")"	0.25	"g"			"character(0)"
-"TRC"	441383	"Terconazole"	"Antifungals/antimycotics"	"G01AG02"			""	"c(\"fungistat\", \"panlomyc\", \"terazol\", \"terconazol\", \"terconazole\", \"terconazolum\", \"tercospor\", \"triaconazole\", \"zazole\")"					"character(0)"
-"TRZ"	65720	"Terizidone"	"Antimycobacterials"	"J04AK03"	"Drugs for treatment of tuberculosis"	"Other drugs for treatment of tuberculosis"	""	"c(\"terivalidin\", \"terizidon\", \"terizidona\", \"terizidone\", \"terizidonum\")"					"character(0)"
-"TCY"	54675776	"Tetracycline"	"Tetracyclines"	"c(\"A01AB13\", \"D06AA04\", \"J01AA07\", \"S01AA09\", \"S02AA08\", \"S03AA02\")"	"Tetracyclines"	"Tetracyclines"	"c(\"tc\", \"te\", \"tet\", \"tetr\")"	"c(\"abramycin\", \"abricycline\", \"achromycin\", \"achromycin v\", \"actisite\", \"agromicina\", \"ambramicina\", \"ambramycin\", \"amycin\", \"biocycline\", \"bristaciclin\", \"bristaciclina\", \"bristacycline\", \"cefracycline\", \"centet\", \"ciclibion\", \"copharlan\", \"criseociclina\", \"cyclomycin\", \"cyclopar\", \"cytome\", \"democracin\", \"deschlorobiomycin\", \"dumocyclin\", \"enterocycline\", \"hostacyclin\", \"lexacycline\", \"limecycline\", \"liquamycin\", \"medocycline\", \"mericycline\", \"micycline\", \"neocycline\", \"oletetrin\", \"omegamycin\", 
-\"orlycycline\", \"panmycin\", \"piracaps\", \"polycycline\", \"polyotic\", \"purocyclina\", \"resteclin\", \"robitet\", \"roviciclina\", \"sigmamycin\", \"solvocin\", \"sumycin\", \"sumycin syrup\", \"tetrabon\", \"tetrachel\", \"tetraciclina\", \"tetracycl\", \"tetracyclin\", \"tetracycline\", \"tetracycline base\", \"tetracycline i\", \"tetracycline ii\", \"tetracyclinum\", \"tetracyn\", \"tetradecin\", \"tetrafil\", \"tetramed\", \"tetrasure\", \"tetraverine\", \"tetrazyklin\", \"tetrex\", \"topicycline\", \"tsiklomistsin\", \"tsiklomitsin\", \"veracin\", \"vetacyclinum\"
-)"	1	"g"	1	"g"	"c(\"25272-6\", \"4045-1\", \"87590-6\")"
-"TET"	65450	"Tetroxoprim"	"Other antibacterials"				""	"c(\"tetroxoprim\", \"tetroxoprima\", \"tetroxoprime\", \"tetroxoprimum\")"					"character(0)"
-"THA"	9568512	"Thiacetazone"	"Oxazolidinones"				""	"c(\"aktivan\", \"ambathizon\", \"amithiozone\", \"amithizone\", \"amitiozon\", \"benthiozone\", \"benzothiozane\", \"benzothiozon\", \"berculon a\", \"berkazon\", \"citazone\", \"conteben\", \"diasan\", \"diazan\", \"domakol\", \"ilbion\", \"livazone\", \"mirizone neustab\", \"mivizon\", \"myvizone\", \"neotibil\", \"neustab\", \"novakol\", \"nuclon argentinian\", \"panrone\", \"parazone\", \"seroden\", \"siocarbazone\", \"tebalon\", \"tebecure\", \"tebemar\", \"tebesone i\", \"tebethion\", \"tebethione\", \"tebezon\", \"thiacetazone\", \"thiacetone\", \"thiacetozone\", 
-\"thibon\", \"thibone\", \"thioacetazon\", \"thioacetazone\", \"thioacetazonum\", \"thioazetazone\", \"thiocarbazil\", \"thiomicid\", \"thionicid\", \"thioparamizon\", \"thioparamizone\", \"thiosemicarbarzone\", \"thiosemicarbazone\", \"thiotebesin\", \"thiotebezin\", \"thiotebicina\", \"thizone\", \"tiacetazon\", \"tibicur\", \"tibion\", \"tibione\", \"tibizan\", \"tibone\", \"tioacetazon\", \"tioacetazona\", \"tioatsetazon\", \"tiobicina\", \"tiocarone\", \"tiosecolo\", \"tubercazon\", \"tubigal\")"					"character(0)"
-"THI"	27200	"Thiamphenicol"	"Amphenicols"	"J01BA02"	"Amphenicols"	"Amphenicols"	""	"c(\"descocin\", \"dexawin\", \"dextrosulfenidol\", \"dextrosulphenidol\", \"efnicol\", \"hyrazin\", \"igralin\", \"macphenicol\", \"masatirin\", \"neomyson\", \"racefenicol\", \"racefenicolo\", \"racefenicolum\", \"raceophenidol\", \"racephenicol\", \"rincrol\", \"thiamcol\", \"thiamphenicol\", \"thiamphenicolum\", \"thiocymetin\", \"thiomycetin\", \"thiophenicol\", \"tiamfenicol\", \"tiamfenicolo\", \"urfamicina\", \"urfamycine\", \"vicemycetin\")"	1.5	"g"	1.5	"g"	"character(0)"
-"THI1"		"Thioacetazone/isoniazid"	"Antimycobacterials"	"J04AM04"	"Drugs for treatment of tuberculosis"	"Combinations of drugs for treatment of tuberculosis"	""	""					""
-"TIA"	656958	"Tiamulin"	"Other antibacterials"				""	"c(\"denagard\", \"tiamulin\", \"tiamulin pamoate\", \"tiamulina\", \"tiamuline\", \"tiamulinum\")"					"87589-8"
-"TIC"	36921	"Ticarcillin"	"Beta-lactams/penicillins"	"J01CA13"	"Beta-lactam antibacterials, penicillins"	"Penicillins with extended spectrum"	"c(\"tc\", \"ti\", \"tic\", \"tica\")"	"c(\"ticarcilina\", \"ticarcillin\", \"ticarcilline\", \"ticarcillinum\", \"ticillin\")"			15	"g"	"c(\"25254-4\", \"4054-3\", \"4055-0\")"
-"TCC"	6437075	"Ticarcillin/clavulanic acid"	"Beta-lactams/penicillins"	"J01CR03"	"Beta-lactam antibacterials, penicillins"	"Combinations of penicillins, incl. beta-lactamase inhibitors"	"c(\"t/c\", \"tcc\", \"ticl\", \"tim\", \"tlc\")"	"timentin"			15	"g"	"character(0)"
-"TGC"	54686904	"Tigecycline"	"Tetracyclines"	"J01AA12"	"Tetracyclines"	"Tetracyclines"	"c(\"tgc\", \"tig\", \"tige\")"	"c(\"haizheng li xing\", \"tigeciclina\", \"tigecyclin\", \"tigecycline\", \"tigecycline hydrate\", \"tigecyclinum\", \"tigilcycline\", \"tygacil\")"			0.1	"g"	"character(0)"
-"TBQ"	65592	"Tilbroquinol"	"Quinolones"	"P01AA05"			""	"c(\"tilbroquinol\", \"tilbroquinolum\")"					"character(0)"
-"TIP"	24860548	"Tildipirosin"	"Macrolides/lincosamides"				""	"c(\"tildipirosin\", \"zuprevo\")"					"character(0)"
-"TIL"	5282521	"Tilmicosin"	"Macrolides/lincosamides"				""	"c(\"micotil\", \"pulmotil\", \"tilmicosin\", \"tilmicosina\", \"tilmicosine\", \"tilmicosinum\")"					"87588-0"
-"TIN"	5479	"Tinidazole"	"Other antibacterials"	"c(\"J01XD02\", \"P01AB02\")"	"Other antibacterials"	"Imidazole derivatives"	"c(\"\", \"tini\")"	"c(\"amtiba\", \"bioshik\", \"ethyl sulfone\", \"fasigin\", \"fasigyn\", \"fasigyntrade mark\", \"fasygin\", \"glongyn\", \"haisigyn\", \"pletil\", \"simplotan\", \"simplotantrade mark\", \"sorquetan\", \"tindamax\", \"tindamaxtrade mark\", \"tinidazol\", \"tinidazole\", \"tinidazolum\", \"tricolam\", \"trimonase\")"	2	"g"	1.5	"g"	"character(0)"
-"TCR"	3001386	"Tiocarlide"	"Antimycobacterials"	"J04AD02"	"Drugs for treatment of tuberculosis"	"Thiocarbamide derivatives"	""	"c(\"amixyl\", \"datanil\", \"disocarban\", \"disoxyl\", \"thiocarlide\", \"tiocarlid\", \"tiocarlida\", \"tiocarlide\", \"tiocarlidum\")"	7	"g"			"character(0)"
-"TDC"	10247721	"Tiodonium chloride"	"Other antibacterials"				""	"c(\"cloruro de tiodonio\", \"tiodonii chloridum\", \"tiodonium chloride\")"					"character(0)"
-"TXC"	65788	"Tioxacin"	"Quinolones"				""	"c(\"tioxacin\", \"tioxacine\", \"tioxacino\", \"tioxacinum\", \"tioxic acid\")"					"character(0)"
-"TIZ"	394397	"Tizoxanide"	"Other antibacterials"				""	"ntzdes"					"character(0)"
-"TOB"	36294	"Tobramycin"	"Aminoglycosides"	"c(\"J01GB01\", \"S01AA12\")"	"Aminoglycoside antibacterials"	"Other aminoglycosides"	"c(\"nn\", \"tm\", \"to\", \"tob\", \"tobr\")"	"c(\"bethkis\", \"brulamycin\", \"deoxykanamycin b\", \"distobram\", \"gernebcin\", \"gotabiotic\", \"kitabis pak\", \"nebcin\", \"nebicin\", \"nebramycin\", \"nebramycin vi\", \"obramycin\", \"sybryx\", \"tenebrimycin\", \"tenemycin\", \"tobacin\", \"tobi podhaler\", \"tobracin\", \"tobradex\", \"tobradistin\", \"tobralex\", \"tobramaxin\", \"tobramicin\", \"tobramicina\", \"tobramitsetin\", \"tobramycetin\", \"tobramycin\", \"tobramycin base\", \"tobramycin sulfate\", \"tobramycine\", \"tobramycinum\", \"tobrased\", \"tobrasone\", \"tobrex\")"			0.24	"g"	"c(\"13584-8\", \"17808-7\", \"22750-4\", \"22751-2\", \"22752-0\", \"31094-6\", \"31095-3\", \"31096-1\", \"35239-3\", \"35670-9\", \"4057-6\", \"4058-4\", \"4059-2\", \"50927-3\", \"52962-8\", \"59380-6\", \"80966-5\")"
-"TOH"		"Tobramycin-high"	"Aminoglycosides"				"c(\"tobra high\", \"tobramycin high\", \"tohl\")"	""					""
-"TFX"	5517	"Tosufloxacin"	"Quinolones"	"J01MA22"			""	"tosufloxacin"	0.45	"g"			"character(0)"
-"TMP"	5578	"Trimethoprim"	"Trimethoprims"	"J01EA01"	"Sulfonamides and trimethoprim"	"Trimethoprim and derivatives"	"c(\"t\", \"tmp\", \"tr\", \"tri\", \"trim\", \"w\")"	"c(\"abaprim\", \"alprim\", \"anitrim\", \"antrima\", \"antrimox\", \"bacdan\", \"bacidal\", \"bacide\", \"bacterial\", \"bacticel\", \"bactifor\", \"bactin\", \"bactoprim\", \"bactramin\", \"bactrim\", \"bencole\", \"bethaprim\", \"biosulten\", \"briscotrim\", \"chemotrin\", \"colizole\", \"colizole ds\", \"conprim\", \"cotrimel\", \"cotrimoxizole\", \"deprim\", \"dosulfin\", \"duocide\", \"esbesul\", \"espectrin\", \"euctrim\", \"exbesul\", \"fermagex\", \"fortrim\", \"idotrim\", \"ikaprim\", \"instalac\", \"kombinax\", \"lagatrim\", \"lagatrim forte\", \"lastrim\", \"lescot\", 
-\"methoprim\", \"metoprim\", \"monoprim\", \"monotrim\", \"monotrimin\", \"novotrimel\", \"omstat\", \"oraprim\", \"pancidim\", \"polytrim\", \"priloprim\", \"primosept\", \"primsol\", \"proloprim\", \"protrin\", \"purbal\", \"resprim\", \"resprim forte\", \"roubac\", \"roubal\", \"salvatrim\", \"septrin ds\", \"septrin forte\", \"septrin s\", \"setprin\", \"sinotrim\", \"stopan\", \"streptoplus\", \"sugaprim\", \"sulfamar\", \"sulfamethoprim\", \"sulfoxaprim\", \"sulthrim\", \"sultrex\", \"syraprim\", \"tiempe\", \"tmp smx\", \"toprim\", \"trimanyl\", \"trimethioprim\", \"trimethopim\", 
-\"trimethoprim\", \"trimethoprime\", \"trimethoprimum\", \"trimethopriom\", \"trimetoprim\", \"trimetoprima\", \"trimexazole\", \"trimexol\", \"trimezol\", \"trimogal\", \"trimono\", \"trimopan\", \"trimpex\", \"triprim\", \"trisul\", \"trisulcom\", \"trisulfam\", \"trisural\", \"uretrim\", \"urobactrim\", \"utetrin\", \"velaten\", \"wellcoprim\", \"wellcoprin\", \"xeroprim\", \"zamboprim\")"	0.4	"g"	0.4	"g"	"c(\"11005-6\", \"17747-7\", \"25273-4\", \"32342-8\", \"4079-0\", \"4080-8\", \"4081-6\", \"55584-7\", \"80552-3\", \"80973-1\")"
-"SXT"	358641	"Trimethoprim/sulfamethoxazole"	"Trimethoprims"	"J01EE01"	"Sulfonamides and trimethoprim"	"Combinations of sulfonamides and trimethoprim, incl. derivatives"	"c(\"cot\", \"cotrim\", \"sxt\", \"t/s\", \"trsu\", \"trsx\", \"ts\")"	"c(\"bactrim\", \"bactrimel\", \"belcomycine\", \"colimycin\", \"colimycin sulphate\", \"colisticin\", \"colistimethate\", \"colistimethate sodium\", \"colistin sulfate\", \"colistin sulphate\", \"colomycin\", \"coly-mycin\", \"cotrimazole\", \"cotrimoxazole\", \"polymyxin e\", \"polymyxin e. sulfate\", \"promixin\", \"septra\", \"totazina\")"					"character(0)"
-"TRL"	202225	"Troleandomycin"	"Macrolides/lincosamides"	"J01FA08"	"Macrolides, lincosamides and streptogramins"	"Macrolides"	""	"c(\"acetyloleandomycin\", \"aovine\", \"cyclamycin\", \"evramicina\", \"matromicina\", \"matromycin t\", \"oleandocetine\", \"t.a.o.\", \"treolmicina\", \"tribiocillina\", \"triocetin\", \"triolan\", \"troleandomicina\", \"troleandomycin\", \"troleandomycine\", \"troleandomycinum\", \"viamicina\", \"wytrion\")"	1	"g"			"character(0)"
-"TRO"	55886	"Trospectomycin"	"Other antibacterials"				""	"c(\"trospectinomycin\", \"trospectomicina\", \"trospectomycin\", \"trospectomycine\", \"trospectomycinum\")"					"character(0)"
-"TVA"	62959	"Trovafloxacin"	"Quinolones"	"J01MA13"	"Quinolone antibacterials"	"Fluoroquinolones"	"c(\"\", \"trov\")"	"c(\"trovafloxacin\", \"trovan\")"	0.2	"g"	0.2	"g"	"character(0)"
-"TUL"	9832301	"Tulathromycin"	"Macrolides/lincosamides"				""	"c(\"draxxin\", \"tulathrmycin a\", \"tulathromycin\", \"tulathromycin a\")"					"character(0)"
-"TYL"	5280440	"Tylosin"	"Macrolides/lincosamides"				""	"c(\"fradizine\", \"tilosina\", \"tylocine\", \"tylosin\", \"tylosin a\", \"tylosine\", \"tylosinum\")"					"87587-2"
-"TYL1"	6441094	"Tylvalosin"	"Macrolides/lincosamides"				"c(\"\", \"tvn\")"	""					""
-"PRU1"	124225	"Ulifloxacin (Prulifloxacin)"	"Other antibacterials"				""	"ulifloxacin"					"character(0)"
-"VAN"	14969	"Vancomycin"	"Glycopeptides"	"c(\"A07AA09\", \"J01XA01\", \"S01AA28\")"	"Other antibacterials"	"Glycopeptide antibacterials"	"c(\"va\", \"van\", \"vanc\")"	"c(\"vancocin\", \"vancocin hcl\", \"vancoled\", \"vancomicina\", \"vancomycin\", \"vancomycin hcl\", \"vancomycine\", \"vancomycinum\", \"vancor\", \"viomycin derivative\")"	2	"g"	2	"g"	"c(\"13586-3\", \"13587-1\", \"20578-1\", \"31012-8\", \"39092-2\", \"39796-8\", \"39797-6\", \"4089-9\", \"4090-7\", \"4091-5\", \"4092-3\", \"50938-0\", \"59381-4\")"
-"VAM"		"Vancomycin-macromethod"	"Glycopeptides"				""	""					""
-"VIO"	135398671	"Viomycin"	"Antimycobacterials"				""	"c(\"celiomycin\", \"florimycin\", \"floromycin\", \"viomicina\", \"viomycin\", \"viomycine\", \"viomycinum\")"					"character(0)"
-"VIR"	11979535	"Virginiamycine"	"Other antibacterials"				""	"c(\"eskalin v\", \"mikamycin\", \"mikamycine\", \"mikamycinum\", \"ostreogrycinum\", \"pristinamycine\", \"pristinamycinum\", \"stafac\", \"stafytracine\", \"staphylomycin\", \"starfac\", \"streptogramin\", \"vernamycin\", \"virgimycin\", \"virgimycine\", \"virginiamycina\", \"virginiamycine\", \"virginiamycinum\")"					"character(0)"
-"VOR"	71616	"Voriconazole"	"Antifungals/antimycotics"	"J02AC03"	"Antimycotics for systemic use"	"Triazole derivatives"	"c(\"vori\", \"vrc\")"	"c(\"pfizer\", \"vfend i.v.\", \"voriconazol\", \"voriconazole\", \"voriconazolum\", \"vorikonazole\")"	0.4	"g"	0.4	"g"	"c(\"38370-3\", \"53902-3\", \"73676-9\", \"80553-1\", \"80651-3\")"
-"XBR"	72144	"Xibornol"	"Other antibacterials"	"J01XX02"	"Other antibacterials"	"Other antibacterials"	""	"c(\"bactacine\", \"bracen\", \"nanbacine\", \"xibornol\", \"xibornolo\", \"xibornolum\")"					"character(0)"
-"ZID"	77846445	"Zidebactam"	"Other antibacterials"				""	"zidebactam"					"character(0)"
-"ZFD"		"Zoliflodacin"					""	""					""
+"AMA"	4649	"4-aminosalicylic acid"	"Antimycobacterials"	

data-raw/av.md5

@@ -1 +1 @@
-7b6649442069d3d121f61ca3ff01843a
+246da79545e045edac7c3ec445b3a04e

data-raw/dosage.md5

@@ -1 +1 @@
-58d6a0589aea598420e37045fb04a5ae
+21f4808065fcad26bdf869a693b074d2