(v2.1.1.9131) implement testthat

2026-10-01 04:13:33 +02:00 · 2025-01-27 21:43:10 +01:00
1 parent 92166c16e8
commit f03933940c
@@ -55,31 +55,34 @@ jobs:
          # current development version, check all major OSes:
          - {os: macOS-latest,   r: 'devel', allowfail: false}
          - {os: windows-latest, r: 'devel', allowfail: false}
-          - {os: ubuntu-latest,  r: 'devel', allowfail: false}
+          - {os: ubuntu-latest,  r: 'devel', allowfail: false, http-user-agent: 'release'}

          # current 'release' version, check all major OSes:
          - {os: macOS-latest,   r: 'release', allowfail: false}
          - {os: windows-latest, r: 'release', allowfail: false}
          - {os: ubuntu-latest,  r: 'release', allowfail: false}

-          # older versions (see also check-old.yaml for even older versions):
+          # older versions (see also check-old-tinytest.yaml for even older versions):
          - {os: ubuntu-latest, r: '4.3', allowfail: false}
          - {os: ubuntu-latest, r: '4.2', allowfail: false}
          - {os: ubuntu-latest, r: '4.1', allowfail: false}
-          - {os: ubuntu-latest, r: '4.0', allowfail: false} # when a new R releases, this one has to move to check-old.yaml
+          - {os: ubuntu-latest, r: '4.0', allowfail: false}
+          - {os: ubuntu-latest, r: '3.6', allowfail: false}
+          # when testthat loses support for a version, move it to check-old-tinytest.yaml

    env:
      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
      R_KEEP_PKG_SOURCE: yes

    steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4

      - uses: r-lib/actions/setup-pandoc@v2

      - uses: r-lib/actions/setup-r@v2
        with:
          r-version: ${{ matrix.config.r }}
+          http-user-agent: ${{ matrix.config.http-user-agent }}
          # use RStudio Package Manager to quickly install packages
          use-public-rspm: true

@@ -87,17 +90,9 @@ jobs:
        with:
          extra-packages: any::rcmdcheck
          needs: check
+          upgrade: 'TRUE'

      - 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
-
-      - name: Show tinytest output
-        if: always()
-        run: |
-          find . -name 'tinytest.Rout*' -exec cat '{}' \; || true
-        shell: bash
+        with:
+          upload-snapshots: true
+          build_args: 'c("--no-manual","--compact-vignettes=gs+qpdf")'
@@ -110,6 +110,9 @@ jobs:
          # this is a required value to run the unit tests:
          R_RUN_TINYTEST: true
        run: |
+          mv tests/testthat inst/
+          rm tests/testthat.R
+          mv tests/tinytest.R.old tests/tinytest.R
          cd ..
          R CMD build AMR
          R CMD check --as-cran --no-manual --run-donttest AMR_*.tar.gz
@@ -39,7 +39,6 @@ jobs:
    runs-on: ubuntu-latest
    
    steps:
-      
      - name: Checkout code
        uses: actions/checkout@v3
      
@@ -1,5 +1,5 @@
 Package: AMR
-Version: 2.1.1.9129
+Version: 2.1.1.9131
 Date: 2025-01-27
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)
@@ -1,4 +1,4 @@
-# AMR 2.1.1.9129
+# AMR 2.1.1.9131

 *(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using [the instructions here](https://msberends.github.io/AMR/#latest-development-version).)*

@@ -1,6 +1,6 @@
 Metadata-Version: 2.2
 Name: AMR
-Version: 2.1.1.9129
+Version: 2.1.1.9131
 Summary: A Python wrapper for the AMR R package
 Home-page: https://github.com/msberends/AMR
 Author: Matthijs Berends
@@ -2,7 +2,7 @@ from setuptools import setup, find_packages

 setup(
    name='AMR',
-    version='2.1.1.9129',
+    version='2.1.1.9131',
    packages=find_packages(),
    install_requires=[
        'rpy2',
@@ -244,7 +244,7 @@ ggplot_pca <- function(x,
    g <- g + ggplot2::geom_path(
      data = ell,
      ggplot2::aes(colour = groups, group = groups),
-      size = ellipse_size,
+      linewidth = ellipse_size,
      alpha = points_alpha
    )
  }
@@ -212,7 +212,6 @@ ggplot_sir <- function(data,
  meet_criteria(x.title, allow_class = "character", has_length = 1, allow_NULL = TRUE)
  meet_criteria(y.title, allow_class = "character", has_length = 1, allow_NULL = TRUE)
  
-  # we work with aes_string later on
  x_deparse <- deparse(substitute(x))
  if (x_deparse != "x") {
    x <- x_deparse
@@ -310,7 +309,6 @@ geom_sir <- function(position = NULL,
    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") {
    x <- x_deparse
@@ -335,7 +333,7 @@ geom_sir <- function(position = NULL,
        combine_SI = combine_SI
      )
    },
-    mapping = ggplot2::aes_string(x = x, y = y, fill = fill),
+    mapping = utils::modifyList(ggplot2::aes(), list(x = str2lang(x), y = str2lang(y), fill = str2lang(fill))),
    position = position,
    ...
  )
@@ -956,7 +956,6 @@ facet_sir <- function(facet = c("interpretation", "antibiotic"), nrow = NULL) {
  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") {
    facet <- facet_deparse
@@ -1107,13 +1106,10 @@ labels_sir_count <- function(position = NULL,
  if (identical(position, "fill")) {
    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"
-    ),
+    mapping = utils::modifyList(ggplot2::aes(), list(label = str2lang("lbl"), x = str2lang(x), y = str2lang("value"))),
    position = position,
    inherit.aes = FALSE,
    size = datalabels.size,
@@ -13,9 +13,12 @@ version="$1"
 output_file="data-raw/gpt_training_text_v${version}.txt"

 # Clear the output file if it exists
-echo "This files contains all context you must know about the AMR package for R." > "$output_file"
+echo "This knowledge base contains all context you must know about the AMR package for R. You are a GPT trained to be an assistant for the AMR package in R. You are an incredible R specialist, especially trained in this package and in the tidyverse." > "$output_file"
+echo "" >> "$output_file"
 echo "First and foremost, you are trained on version ${version}. Remember this whenever someone asks which AMR package version you’re at." >> "$output_file"
-echo "--------------------------------" >> "$output_file"
+echo "" >> "$output_file"
+echo "Below are the contents of the `NAMESPACE` file, the `index.md` file, and all the `man/*.Rd` files (documentation) in the package. Every file content is split using 100 hypens." >> "$output_file"
+echo "----------------------------------------------------------------------------------------------------" >> "$output_file"
 echo "" >> "$output_file"

 # Function to remove header block (delimited by # ======)
@@ -23,8 +26,9 @@ remove_header() {
  sed '/# =\{6,\}/,/# =\{6,\}/d' "$1"
 }

-# Process all .R files in the 'R' folder
+# # Process all .R files in the 'R' folder
 # for file in R/*.R; do
+#   echo "--------------------------------------------------" >> "$output_file"
 #   echo "THE PART HEREAFTER CONTAINS CONTENTS FROM FILE '$file':" >> "$output_file"
 #   echo -e "\n" >> "$output_file"
 #   remove_header "$file" >> "$output_file"
@@ -34,6 +38,7 @@ remove_header() {
 # Process important metadata files (DESCRIPTION, NAMESPACE, index.md)
 for file in NAMESPACE index.md; do
  if [[ -f $file ]]; then
+    echo "----------------------------------------------------------------------------------------------------" >> "$output_file"
    echo "THE PART HEREAFTER CONTAINS CONTENTS FROM FILE '$file':" >> "$output_file"
    echo -e "\n" >> "$output_file"
    cat "$file" >> "$output_file"
@@ -43,6 +48,7 @@ done

 # Process all .Rd files from the 'man' folder
 for file in man/*.Rd; do
+  echo "----------------------------------------------------------------------------------------------------" >> "$output_file"
  echo "THE PART HEREAFTER CONTAINS CONTENTS FROM FILE '$file':" >> "$output_file"
  echo -e "\n" >> "$output_file"
  remove_header "$file" >> "$output_file"
@@ -51,19 +57,20 @@ done

 # Process all .Rmd files in the 'vignettes' folder
 for file in vignettes/*.Rmd; do
+  echo "----------------------------------------------------------------------------------------------------" >> "$output_file"
  echo "THE PART HEREAFTER CONTAINS CONTENTS FROM FILE '$file':" >> "$output_file"
  echo -e "\n" >> "$output_file"
  remove_header "$file" >> "$output_file"
  echo -e "\n\n" >> "$output_file"
 done

-# Process all .Rmd files in the 'vignettes' folder
-echo "THE PART HEREAFTER CONTAINS THE README OF OUR PYTHON PACKAGE" >> "$output_file"
-echo -e "\n" >> "$output_file"
-for file in PythonPackage/AMR/README.md; do
-  remove_header "$file" >> "$output_file"
-  echo -e "\n\n" >> "$output_file"
-done
+# Process README.md
+# echo "THE PART HEREAFTER CONTAINS THE README OF OUR PYTHON PACKAGE" >> "$output_file"
+# echo -e "\n" >> "$output_file"
+# for file in PythonPackage/AMR/README.md; do
+#   remove_header "$file" >> "$output_file"
+#   echo -e "\n\n" >> "$output_file"
+# done

 # Process test files (if available) in the 'tests' folder
 # for file in tests/*.R; do
@@ -1,7 +1,11 @@
-This files contains all context you must know about the AMR package for R.
-First and foremost, you are trained on version 2.1.1.9129. Remember this whenever someone asks which AMR package version you’re at.
--------------------------------
+This knowledge base contains all context you must know about the AMR package for R. You are a GPT trained to be an assistant for the AMR package in R. You are an incredible R specialist, especially trained in this package and in the tidyverse.

+First and foremost, you are trained on version 2.1.1.9131. Remember this whenever someone asks which AMR package version you’re at.
+
+Below are the contents of the  file, the  file, and all the  files (documentation) in the package. Every file content is split using 100 hypens.
+----------------------------------------------------------------------------------------------------
+
+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'NAMESPACE':


@@ -371,6 +375,7 @@ importFrom(stats,var)



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'index.md':


@@ -688,6 +693,7 @@ This R package is free, open-source software and licensed under the [GNU General



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/AMR-deprecated.Rd':


@@ -710,6 +716,7 @@ These functions are so-called '\link{Deprecated}'. \strong{They will be removed



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/AMR-options.Rd':


@@ -774,6 +781,7 @@ Now the team settings are configured in only one place, and can be maintained th



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/AMR.Rd':


@@ -870,6 +878,7 @@ Other contributors:



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/WHOCC.Rd':


@@ -901,6 +910,7 @@ ab_tradenames("flucloxacillin")



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/WHONET.Rd':


@@ -957,6 +967,7 @@ WHONET



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/ab_from_text.Rd':


@@ -1057,6 +1068,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/ab_property.Rd':


@@ -1235,6 +1247,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/add_custom_antimicrobials.Rd':


@@ -1345,6 +1358,7 @@ x[, betalactams()]



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/add_custom_microorganisms.Rd':


@@ -1464,6 +1478,7 @@ mo_gramstain(c("C. freundii complex", "C. braakii complex"))



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/age.Rd':


@@ -1518,6 +1533,7 @@ To split ages into groups, use the \code{\link[=age_groups]{age_groups()}} funct



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/age_groups.Rd':


@@ -1600,6 +1616,7 @@ To determine ages, based on one or more reference dates, use the \code{\link[=ag



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/antibiogram.Rd':


@@ -2002,6 +2019,7 @@ plot(ab2)



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/antibiotics.Rd':


@@ -2096,6 +2114,7 @@ antivirals



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/antimicrobial_class_selectors.Rd':


@@ -2476,6 +2495,7 @@ if (require("data.table")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/as.ab.Rd':


@@ -2587,6 +2607,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/as.av.Rd':


@@ -2683,6 +2704,7 @@ av_name("acicl")



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/as.disk.Rd':


@@ -2760,6 +2782,7 @@ as.sir(df, uti = TRUE)



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/as.mic.Rd':


@@ -2901,6 +2924,7 @@ if (require("ggplot2")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/as.mo.Rd':


@@ -3167,6 +3191,7 @@ The \code{\link[=mo_property]{mo_*}} functions (such as \code{\link[=mo_genus]{m



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/as.sir.Rd':


@@ -3562,6 +3587,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/atc_online.Rd':


@@ -3649,6 +3675,7 @@ if (requireNamespace("curl") && requireNamespace("rvest") && requireNamespace("x



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/av_from_text.Rd':


@@ -3712,6 +3739,7 @@ av_from_text("28/03/2020 valaciclovir po tid", type = "admin")



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/av_property.Rd':


@@ -3835,6 +3863,7 @@ av_name("J05AB01")



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/availability.Rd':


@@ -3874,6 +3903,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/bug_drug_combinations.Rd':


@@ -3960,6 +3990,7 @@ bug_drug_combinations(example_isolates,



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/clinical_breakpoints.Rd':


@@ -4038,6 +4069,7 @@ clinical_breakpoints



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/count.Rd':


@@ -4241,6 +4273,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/custom_eucast_rules.Rd':


@@ -4395,6 +4428,7 @@ x2



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/dosage.Rd':


@@ -4434,6 +4468,7 @@ dosage



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/eucast_rules.Rd':


@@ -4588,6 +4623,7 @@ eucast_dosage(c("tobra", "genta", "cipro"), "iv", version_breakpoints = 10)



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/example_isolates.Rd':


@@ -4625,6 +4661,7 @@ example_isolates



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/example_isolates_unclean.Rd':


@@ -4660,6 +4697,7 @@ example_isolates_unclean



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/export_ncbi_biosample.Rd':


@@ -4687,6 +4725,7 @@ Export Data Set as NCBI BioSample Antibiogram



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/first_isolate.Rd':


@@ -4871,6 +4910,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/g.test.Rd':


@@ -5018,6 +5058,7 @@ g.test(x)



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/get_episode.Rd':


@@ -5217,6 +5258,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/ggplot_pca.Rd':


@@ -5354,6 +5396,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/ggplot_sir.Rd':


@@ -5540,6 +5583,7 @@ if (require("ggplot2") && require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/guess_ab_col.Rd':


@@ -5594,6 +5638,7 @@ guess_ab_col(df, as.ab("augmentin"))



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/intrinsic_resistant.Rd':


@@ -5632,6 +5677,7 @@ intrinsic_resistant



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/italicise_taxonomy.Rd':


@@ -5670,6 +5716,7 @@ cat(italicise_taxonomy("An overview of S. aureus isolates", type = "ansi"))



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/join.Rd':


@@ -5750,6 +5797,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/key_antimicrobials.Rd':


@@ -5889,6 +5937,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/kurtosis.Rd':


@@ -5929,6 +5978,7 @@ kurtosis(rnorm(10000), excess = TRUE)



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/like.Rd':


@@ -6013,6 +6063,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/mdro.Rd':


@@ -6251,6 +6302,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/mean_amr_distance.Rd':


@@ -6349,6 +6401,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/microorganisms.Rd':


@@ -6459,6 +6512,7 @@ microorganisms



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/microorganisms.codes.Rd':


@@ -6503,6 +6557,7 @@ mo_is_intrinsic_resistant("eco", ab = "vancomycin")



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/microorganisms.groups.Rd':


@@ -6543,6 +6598,7 @@ microorganisms.groups[microorganisms.groups$mo_group == "B_BCTRD_FRGL-C", ]



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/mo_matching_score.Rd':


@@ -6625,6 +6681,7 @@ mo_matching_score(



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/mo_property.Rd':


@@ -6991,6 +7048,7 @@ Data set \link{microorganisms}



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/mo_source.Rd':


@@ -7104,6 +7162,7 @@ If the original file (in the previous case an Excel file) is moved or deleted, t



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/pca.Rd':


@@ -7199,6 +7258,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/plot.Rd':


@@ -7464,6 +7524,7 @@ if (require("ggplot2")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/proportion.Rd':


@@ -7749,6 +7810,7 @@ if (require("dplyr")) {



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/random.Rd':


@@ -7808,6 +7870,7 @@ random_disk(25, "Streptococcus pneumoniae", "ampicillin") # range 12-27



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/resistance_predict.Rd':


@@ -7961,6 +8024,7 @@ Models: \code{\link[=lm]{lm()}} \code{\link[=glm]{glm()}}



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/skewness.Rd':


@@ -8000,6 +8064,7 @@ skewness(runif(1000))



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/top_n_microorganisms.Rd':


@@ -8050,6 +8115,7 @@ top_n_microorganisms(example_isolates,



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'man/translate.Rd':


@@ -8135,6 +8201,7 @@ ab_name("amox/clav")



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'vignettes/AMR.Rmd':


@@ -8493,6 +8560,7 @@ our_data_1st %>%



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'vignettes/AMR_for_Python.Rmd':


@@ -8694,6 +8762,7 @@ Whether you're cleaning data or analysing resistance patterns, the `AMR` Python



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'vignettes/AMR_with_tidymodels.Rmd':


@@ -8883,6 +8952,7 @@ This workflow is extensible to other antibiotic classes and resistance patterns,



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'vignettes/EUCAST.Rmd':


@@ -8989,6 +9059,7 @@ knitr::kable(eucast_rules(data), align = "lccccccc")



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'vignettes/MDR.Rmd':


@@ -9158,6 +9229,7 @@ freq(my_TB_data$mdr)



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'vignettes/PCA.Rmd':


@@ -9257,6 +9329,7 @@ ggplot_pca(pca_result, ellipse = TRUE) +



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'vignettes/WHONET.Rmd':


@@ -9362,6 +9435,7 @@ tryCatch(



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'vignettes/datasets.Rmd':


@@ -9737,6 +9811,7 @@ microorganisms.codes %>%



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'vignettes/resistance_predict.Rmd':


@@ -9874,6 +9949,7 @@ summary(model)$coefficients



+----------------------------------------------------------------------------------------------------
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'vignettes/welcome_to_AMR.Rmd':


@@ -9946,204 +10022,3 @@ This AMR package for R is free, open-source software and licensed under the [GNU



-THE PART HEREAFTER CONTAINS THE README OF OUR PYTHON PACKAGE
-
-
---
-title: "AMR for Python"
-output: 
-  rmarkdown::html_vignette:
-    toc: true
-    toc_depth: 3
-vignette: >
-  %\VignetteIndexEntry{AMR for Python}
-  %\VignetteEncoding{UTF-8}
-  %\VignetteEngine{knitr::rmarkdown}
-editor_options: 
-  chunk_output_type: console
---
-
-```{r setup, include = FALSE, results = 'markup'}
-knitr::opts_chunk$set(
-  warning = FALSE,
-  collapse = TRUE,
-  comment = "#>",
-  fig.width = 7.5,
-  fig.height = 5
-)
-```
-
-# Introduction
-
-The `AMR` package for R is a powerful tool for antimicrobial resistance (AMR) analysis. It provides extensive features for handling microbial and antimicrobial data. However, for those who work primarily in Python, we now have a more intuitive option available: the [`AMR` Python Package Index](https://pypi.org/project/AMR/).
-
-This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` package internally. Despite the need to have R installed, Python users can now easily work with AMR data directly through Python code.
-
-# Install
-
-1. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
-
-    ```bash
-    pip install AMR
-    ```
-
-2. Make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
-
-    For Linux:
-
-    ```bash
-    # Ubuntu / Debian
-    sudo apt install r-base
-    # Fedora:
-    sudo dnf install R
-    # CentOS/RHEL
-    sudo yum install R
-    ```
-    
-    For macOS (using [Homebrew](https://brew.sh)):
-    
-    ```bash
-    brew install r
-    ```
-    
-    For Windows, visit the [CRAN download page](https://cran.r-project.org) to download and install R.
-
-# Examples of Usage
-
-## Cleaning Taxonomy
-
-Here’s an example that demonstrates how to clean microorganism and drug names using the `AMR` Python package:
-
-```python
-import pandas as pd
-import AMR
-
-# Sample data
-data = {
-    "MOs": ['E. coli', 'ESCCOL', 'esco', 'Esche coli'],
-    "Drug": ['Cipro', 'CIP', 'J01MA02', 'Ciproxin']
-}
-df = pd.DataFrame(data)
-
-# Use AMR functions to clean microorganism and drug names
-df['MO_clean'] = AMR.mo_name(df['MOs'])
-df['Drug_clean'] = AMR.ab_name(df['Drug'])
-
-# Display the results
-print(df)
-```
-
-| MOs         | Drug      | MO_clean           | Drug_clean    |
-|-------------|-----------|--------------------|---------------|
-| E. coli     | Cipro     | Escherichia coli   | Ciprofloxacin |
-| ESCCOL      | CIP       | Escherichia coli   | Ciprofloxacin |
-| esco        | J01MA02   | Escherichia coli   | Ciprofloxacin |
-| Esche coli  | Ciproxin  | Escherichia coli   | Ciprofloxacin |
-
-### Explanation
-
-* **mo_name:** This function standardises microorganism names. Here, different variations of *Escherichia coli* (such as "E. coli", "ESCCOL", "esco", and "Esche coli") are all converted into the correct, standardised form, "Escherichia coli".
-
-* **ab_name**: Similarly, this function standardises antimicrobial names. The different representations of ciprofloxacin (e.g., "Cipro", "CIP", "J01MA02", and "Ciproxin") are all converted to the standard name, "Ciprofloxacin".
-
-## Calculating AMR
-
-```python
-import AMR
-import pandas as pd
-
-df = AMR.example_isolates
-result = AMR.resistance(df["AMX"])
-print(result)
-```
-
-```
-[0.59555556]
-```
-
-## Generating Antibiograms
-
-One of the core functions of the `AMR` package is generating an antibiogram, a table that summarises the antimicrobial susceptibility of bacterial isolates. Here’s how you can generate an antibiogram from Python:
-
-```python
-result2a = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]])
-print(result2a)
-```
-
-| Pathogen        | Amoxicillin     | Ciprofloxacin   | Piperacillin/tazobactam  |
-|-----------------|-----------------|-----------------|--------------------------|
-| CoNS            | 7% (10/142)     | 73% (183/252)   | 30% (10/33)              |
-| E. coli         | 50% (196/392)   | 88% (399/456)   | 94% (393/416)            |
-| K. pneumoniae   | 0% (0/58)       | 96% (53/55)     | 89% (47/53)              |
-| P. aeruginosa   | 0% (0/30)       | 100% (30/30)    | None                     |
-| P. mirabilis    | None            | 94% (34/36)     | None                     |
-| S. aureus       | 6% (8/131)      | 90% (171/191)   | None                     |
-| S. epidermidis  | 1% (1/91)       | 64% (87/136)    | None                     |
-| S. hominis      | None            | 80% (56/70)     | None                     |
-| S. pneumoniae   | 100% (112/112)  | None            | 100% (112/112)           |
-
-
-```python
-result2b = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]], mo_transform = "gramstain")
-print(result2b)
-```
-
-| Pathogen       | Amoxicillin     | Ciprofloxacin    | Piperacillin/tazobactam  |
-|----------------|-----------------|------------------|--------------------------|
-| Gram-negative  | 36% (226/631)   | 91% (621/684)    | 88% (565/641)            |
-| Gram-positive  | 43% (305/703)   | 77% (560/724)    | 86% (296/345)            |
-
-
-In this example, we generate an antibiogram by selecting various antibiotics.
-
-## Taxonomic Data Sets Now in Python!
-
-As a Python user, you might like that the most important data sets of the `AMR` R package, `microorganisms`, `antibiotics`, `clinical_breakpoints`, and `example_isolates`, are now available as regular Python data frames:
-
-```python
-AMR.microorganisms
-```
-
-| mo           | fullname                           | status   | kingdom  | gbif      | gbif_parent | gbif_renamed_to | prevalence |
-|--------------|------------------------------------|----------|----------|-----------|-------------|-----------------|------------|
-| B_GRAMN      | (unknown Gram-negatives)           | unknown  | Bacteria | None      | None        | None            | 2.0        |
-| B_GRAMP      | (unknown Gram-positives)           | unknown  | Bacteria | None      | None        | None            | 2.0        |
-| B_ANAER-NEG  | (unknown anaerobic Gram-negatives) | unknown  | Bacteria | None      | None        | None            | 2.0        |
-| B_ANAER-POS  | (unknown anaerobic Gram-positives) | unknown  | Bacteria | None      | None        | None            | 2.0        |
-| B_ANAER      | (unknown anaerobic bacteria)       | unknown  | Bacteria | None      | None        | None            | 2.0        |
-| ...          | ...                                | ...      | ...      | ...       | ...         | ...             | ...        |
-| B_ZYMMN_POMC | Zymomonas pomaceae                 | accepted | Bacteria | 10744418  | 3221412     | None            | 2.0        |
-| B_ZYMPH      | Zymophilus                         | synonym  | Bacteria | None      | 9475166     | None            | 2.0        |
-| B_ZYMPH_PCVR | Zymophilus paucivorans             | synonym  | Bacteria | None      | None        | None            | 2.0        |
-| B_ZYMPH_RFFN | Zymophilus raffinosivorans         | synonym  | Bacteria | None      | None        | None            | 2.0        |
-| F_ZYZYG      | Zyzygomyces                        | unknown  | Fungi    | None      | 7581        | None            | 2.0        |
-
-```python
-AMR.antibiotics
-```
-
-| ab  | cid         | name                 | group                      | oral_ddd | oral_units | iv_ddd | iv_units |
-|-----|-------------|----------------------|----------------------------|----------|------------|--------|----------|
-| AMA | 4649.0      | 4-aminosalicylic acid| Antimycobacterials         | 12.00    | g          | NaN    | None     |
-| ACM | 6450012.0   | Acetylmidecamycin    | Macrolides/lincosamides    | NaN      | None       | NaN    | None     |
-| ASP | 49787020.0  | Acetylspiramycin     | Macrolides/lincosamides    | NaN      | None       | NaN    | None     |
-| ALS | 8954.0      | Aldesulfone sodium   | Other antibacterials       | 0.33     | g          | NaN    | None     |
-| AMK | 37768.0     | Amikacin             | Aminoglycosides            | NaN      | None       | 1.0    | g        |
-| ... | ...         | ...                  | ...                        | ...      | ...        | ...    | ...      |
-| VIR | 11979535.0  | Virginiamycine       | Other antibacterials       | NaN      | None       | NaN    | None     |
-| VOR | 71616.0     | Voriconazole         | Antifungals/antimycotics   | 0.40     | g          | 0.4    | g        |
-| XBR | 72144.0     | Xibornol             | Other antibacterials       | NaN      | None       | NaN    | None     |
-| ZID | 77846445.0  | Zidebactam           | Other antibacterials       | NaN      | None       | NaN    | None     |
-| ZFD | NaN         | Zoliflodacin         | None                       | NaN      | None       | NaN    | None     |
-
-
-# Conclusion
-
-With the `AMR` Python package, Python users can now effortlessly call R functions from the `AMR` R package. This eliminates the need for complex `rpy2` configurations and provides a clean, easy-to-use interface for antimicrobial resistance analysis. The examples provided above demonstrate how this can be applied to typical workflows, such as standardising microorganism and antimicrobial names or calculating resistance.
-
-By just running `import AMR`, users can seamlessly integrate the robust features of the R `AMR` package into Python workflows.
-
-Whether you're cleaning data or analysing resistance patterns, the `AMR` Python package makes it easy to work with AMR data in Python.
-
-
-
@@ -2210,6 +2210,6 @@ devtools::load_all(".")

 # run the unit tests
 Sys.setenv(NOT_CRAN = "true")
-testthat::test_file("inst/tests/testthat/test-data.R")
-testthat::test_file("inst/tests/testthat/test-mo.R")
-testthat::test_file("inst/tests/testthat/test-mo_property.R")
+testthat::test_file("tests/testthat/test-data.R")
+testthat::test_file("tests/testthat/test-mo.R")
+testthat::test_file("tests/testthat/test-mo_property.R")
@@ -0,0 +1,45 @@
+# ==================================================================== #
+# TITLE:                                                               #
+# AMR: An R Package for Working with Antimicrobial Resistance Data     #
+#                                                                      #
+# SOURCE CODE:                                                         #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# PLEASE CITE THIS SOFTWARE AS:                                        #
+# Berends MS, Luz CF, Friedrich AW, et al. (2022).                     #
+# AMR: An R Package for Working with Antimicrobial Resistance Data.    #
+# Journal of Statistical Software, 104(3), 1-31.                       #
+# https://doi.org/10.18637/jss.v104.i03                                #
+#                                                                      #
+# Developed at the University of Groningen and the University Medical  #
+# Center Groningen in The Netherlands, in collaboration with many      #
+# colleagues from around the world, see our website.                   #
+#                                                                      #
+# 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/   #
+# ==================================================================== #
+
+library(testthat)
+library(AMR)
+
+# add functions from the tinytest package (which we use for older R versions)
+expect_inherits <- function(x, y, ...) {
+  expect(inherits(x, y),
+         failure_message = paste0("object has class ", paste0(class(x), collapse = "/"),
+                                  ", required is class ", paste0(y, collapse = "/")))
+}
+expect_stdout <- expect_output
+if (getRversion() < "4.0.0") {
+  deparse1 <- AMR:::deparse1
+}
+
+# start unit tests
+test_check("AMR")
@@ -27,15 +27,6 @@
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #

-if (tryCatch(!is.function(expect_stout), error = function(e) TRUE)) {
-  expect_stout <<- testthat::expect_output
-}
-if (tryCatch(!is.function(expect_inherits), error = function(e) TRUE)) {
-  expect_inherits <<- function(x, y, ...) testthat::expect(inherits(x, y),
-                                                           failure_message = paste0("Expected class ", paste(y, collapse = "/"),
-                                                                                    ", got class ", paste(class(x), collapse = "/")))
-}
-
 expect_equal(AMR:::percentage(0.25), "25%")
 expect_equal(AMR:::percentage(0.5), "50%")
 expect_equal(AMR:::percentage(0.500, digits = 1), "50.0%")
@@ -70,7 +70,6 @@ call_functions <- c(
  "read_excel" = "readxl",
  # ggplot2
  "aes" = "ggplot2",
-  "aes_string" = "ggplot2",
  "arrow" = "ggplot2",
  "autoplot" = "ggplot2",
  "element_blank" = "ggplot2",
@@ -29,9 +29,6 @@

 # we use {tinytest} for older R versions to allow unit testing in R >= 3.0.0.

-# use this to quickly use testtthat for more informative errors:
-# testthat::test_dir("inst/tests")
-
 # test only on GitHub Actions - not on CRAN as tests are lengthy
 if (identical(Sys.getenv("R_RUN_TINYTEST"), "true")) {
  # env var 'R_LIBS_USER' gets overwritten during 'R CMD check' in GitHub Actions, so:
@@ -71,9 +68,9 @@ if (identical(Sys.getenv("R_RUN_TINYTEST"), "true")) {
    
    suppressMessages(
      out <- test_package("AMR",
-                          testdir = ifelse(dir.exists("inst/tests"),
-                                           "inst/tests",
-                                           "tests"
+                          testdir = ifelse(dir.exists("inst/testthat"),
+                                           "inst/testthat",
+                                           "testthat"
                          ),
                          verbose = FALSE,
                          color = FALSE