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(v2.1.1.9199) fix eucast

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dr. M.S. (Matthijs) Berends 2025-03-14 13:43:22 +01:00
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2
DESCRIPTION
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@ -1,5 +1,5 @@
Package: AMR
Version: 2.1.1.9198
Version: 2.1.1.9199
Date: 2025-03-14
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)

2
NEWS.md
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@ -1,4 +1,4 @@
# AMR 2.1.1.9198
# AMR 2.1.1.9199
*(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).)*

2
PythonPackage/AMR/AMR.egg-info/PKG-INFO
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@ -1,6 +1,6 @@
Metadata-Version: 2.2
Name: AMR
Version: 2.1.1.9198
Version: 2.1.1.9199
Summary: A Python wrapper for the AMR R package
Home-page: https://github.com/msberends/AMR
Author: Matthijs Berends

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PythonPackage/AMR/dist/amr-2.1.1.9198-py3-none-any.whl → PythonPackage/AMR/dist/amr-2.1.1.9199-py3-none-any.whl vendored
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PythonPackage/AMR/setup.py
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@ -2,7 +2,7 @@ from setuptools import setup, find_packages
setup(
name='AMR',
version='2.1.1.9198',
version='2.1.1.9199',
packages=find_packages(),
install_requires=[
'rpy2',

7
R/aa_helper_functions.R
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@ -532,9 +532,14 @@ word_wrap <- function(...,
url = paste0("ide:run:AMR::", parts[cmds & parts %unlike% "[.]"]),
txt = parts[cmds & parts %unlike% "[.]"]
)
# datasets should give help page as well
parts[parts %in% c("antimicrobials", "microorganisms", "microorganisms.codes", "microorganisms.groups")] <- font_url(
url = paste0("ide:help:AMR::", gsub("()", "", parts[parts %in% c("antimicrobials", "microorganisms", "microorganisms.codes", "microorganisms.groups")], fixed = TRUE)),
txt = parts[parts %in% c("antimicrobials", "microorganisms", "microorganisms.codes", "microorganisms.groups")]
)
# text starting with `?` must also lead to the help page
parts[parts %like% "^[?]"] <- font_url(
url = paste0("ide:help:AMR::", gsub("()", "", gsub("^[?]", "", parts[parts %like% "^[?]"]), fixed = TRUE)),
url = paste0("ide:help:AMR::", parts[parts %like% "^[?]"]),
txt = parts[parts %like% "^[?]"]
)
msg <- paste0(parts, collapse = "`")

9
R/mo.R
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@ -242,7 +242,14 @@ as.mo <- function(x,
# one exception: "Fungi" matches the kingdom, but instead it should return the 'unknown' code for fungi
out[out == "F_[KNG]_FUNGI"] <- "F_FUNGUS"
# From known codes ----
out[is.na(out) & toupper(x) %in% AMR::microorganisms.codes$code] <- AMR::microorganisms.codes$mo[match(toupper(x)[is.na(out) & toupper(x) %in% AMR::microorganisms.codes$code], AMR::microorganisms.codes$code)]
ind <- is.na(out) & toupper(x) %in% AMR::microorganisms.codes$code
out[ind] <- AMR::microorganisms.codes$mo[match(toupper(x)[ind], AMR::microorganisms.codes$code)]
if (length(which(ind)) > 0 && isTRUE(info) && message_not_thrown_before("as.mo_microorganisms.codes", is.na(out), toupper(x))) {
message_(
"Retrieved value", ifelse(sum(ind) > 1, "s", ""),
" from the `microorganisms.codes` data set for ", vector_and(toupper(x)[ind]), "."
)
}
# From SNOMED ----
# based on this extremely fast gem: https://stackoverflow.com/a/11002456/4575331
snomeds <- unlist(AMR_env$MO_lookup$snomed)

130
_pkgdown.yml
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@ -65,72 +65,70 @@ home:
structure: [toc, links, authors]
navbar:
title: "AMR (for R)"
left:
# - text: "Home"
# icon: "fa-home"
# href: "index.html"
- text: "How to"
icon: "fa-question-circle"
menu:
- text: "Conduct AMR Analysis"
icon: "fa-directions"
href: "articles/AMR.html"
- text: "Generate Antibiogram (Trad./Syndromic/WISCA)"
icon: "fa-file-prescription"
href: "reference/antibiogram.html" # reference instead of an article
- text: "Predict Antimicrobial Resistance"
icon: "fa-dice"
href: "articles/resistance_predict.html"
- text: "Download Data Sets for Own Use"
icon: "fa-database"
href: "articles/datasets.html"
- text: "Use AMR for Predictive Modelling (tidymodels)"
icon: "fa-square-root-variable"
href: "articles/AMR_with_tidymodels.html"
- text: "Set User- Or Team-specific Package Settings"
icon: "fa-gear"
href: "reference/AMR-options.html"
- text: "Conduct Principal Component Analysis for AMR"
icon: "fa-compress"
href: "articles/PCA.html"
- text: "Determine Multi-Drug Resistance (MDR)"
icon: "fa-skull-crossbones"
href: "articles/MDR.html"
- text: "Work with WHONET Data"
icon: "fa-globe-americas"
href: "articles/WHONET.html"
# - text: "Import Data From SPSS/Stata"
# icon: "fa-file-upload"
# href: "articles/SPSS.html"
- text: "Apply Eucast Rules"
icon: "fa-exchange-alt"
href: "articles/EUCAST.html"
- text: "Get Taxonomy of a Microorganism"
icon: "fa-bug"
href: "reference/mo_property.html" # reference instead of an article
- text: "Get Properties of an Antibiotic Drug"
icon: "fa-capsules"
href: "reference/ab_property.html" # reference instead of an article
- text: "Get Properties of an Antiviral Drug"
icon: "fa-capsules"
href: "reference/av_property.html" # reference instead of an article
- text: "AMR for Python"
icon: "fab fa-python"
href: "articles/AMR_for_Python.html"
- text: "Manual"
icon: "fa-book-open"
href: "reference/index.html"
- text: "Authors"
icon: "fa-users"
href: "authors.html"
right:
- text: "Changelog"
icon: "far fa-newspaper"
href: "news/index.html"
- text: "Source Code"
icon: "fab fa-github"
href: "https://github.com/msberends/AMR"
structure:
title: "AMR (for R)"
left:
- text: "How to"
icon: "fa-question-circle"
menu:
- text: "Conduct AMR Analysis"
icon: "fa-directions"
href: "articles/AMR.html"
- text: "Generate Antibiogram (Trad./Syndromic/WISCA)"
icon: "fa-file-prescription"
href: "reference/antibiogram.html" # reference instead of an article
- text: "Predict Antimicrobial Resistance"
icon: "fa-dice"
href: "articles/resistance_predict.html"
- text: "Download Data Sets for Own Use"
icon: "fa-database"
href: "articles/datasets.html"
- text: "Use AMR for Predictive Modelling (tidymodels)"
icon: "fa-square-root-variable"
href: "articles/AMR_with_tidymodels.html"
- text: "Set User- Or Team-specific Package Settings"
icon: "fa-gear"
href: "reference/AMR-options.html"
- text: "Conduct Principal Component Analysis for AMR"
icon: "fa-compress"
href: "articles/PCA.html"
- text: "Determine Multi-Drug Resistance (MDR)"
icon: "fa-skull-crossbones"
href: "articles/MDR.html"
- text: "Work with WHONET Data"
icon: "fa-globe-americas"
href: "articles/WHONET.html"
- text: "Apply Eucast Rules"
icon: "fa-exchange-alt"
href: "articles/EUCAST.html"
- text: "Get Taxonomy of a Microorganism"
icon: "fa-bug"
href: "reference/mo_property.html" # reference instead of an article
- text: "Get Properties of an Antibiotic Drug"
icon: "fa-capsules"
href: "reference/ab_property.html" # reference instead of an article
- text: "Get Properties of an Antiviral Drug"
icon: "fa-capsules"
href: "reference/av_property.html" # reference instead of an article
- text: "AMR for Python"
icon: "fab fa-python"
href: "articles/AMR_for_Python.html"
- text: "Manual"
icon: "fa-book-open"
href: "reference/index.html"
- text: "Authors"
icon: "fa-users"
href: "authors.html"
right: [search, amrchangelog, amrgit]
components:
amrchangelog:
icon: fa-newspaper
href: news/index.html
aria-label: Changelog
amrgit:
icon: fa-github
href: https://github.com/msberends/AMR"
aria-label: Source Code
reference:
- title: "Introduction to the package"

2
data-raw/gpt_training_text_v2.1.1.9198.txt → data-raw/gpt_training_text_v2.1.1.9199.txt
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@ -1,6 +1,6 @@
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 2.1.1.9198. Remember this whenever someone asks which AMR package version you’re at.
First and foremost, you are trained on version 2.1.1.9199. 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.
----------------------------------------------------------------------------------------------------

2
tests/testthat/test-_deprecated.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("deprecated works", {
test_that("test-_deprecated.R", {
expect_warning(example_isolates[, ab_class("mycobact")])
expect_warning(example_isolates[, ab_selector(name %like% "trim")])
})

2
tests/testthat/test-_misc.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("misc works", {
test_that("test-misc.R", {
expect_equal(AMR:::percentage(0.25), "25%")
expect_equal(AMR:::percentage(0.5), "50%")
expect_equal(AMR:::percentage(0.500, digits = 1), "50.0%")

2
tests/testthat/test-ab.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("ab works", {
test_that("test-ab.R", {
ab_reset_session()
expect_equal(

2
tests/testthat/test-ab_from_text.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("ab_from_text works", {
test_that("test-ab_from_text.R", {
ab_reset_session()
expect_identical(

2
tests/testthat/test-ab_property.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("ab_property works", {
test_that("test-ab_property.R", {
ab_reset_session()
expect_identical(ab_name("AMX", language = NULL), "Amoxicillin")

2
tests/testthat/test-age.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("age works", {
test_that("test-age.R", {
expect_equal(
age(
x = c("1980-01-01", "1985-01-01", "1990-01-01"),

2
tests/testthat/test-amr_selectors.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("amr selectors works", {
test_that("test-amr selectors.R", {
# antibiotic class selectors
expect_equal(ncol(example_isolates[, aminoglycosides(), drop = FALSE]), 4, tolerance = 0.5)
expect_equal(ncol(example_isolates[, aminopenicillins(), drop = FALSE]), 2, tolerance = 0.5)

2
tests/testthat/test-antibiogram.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("antibiogram works", {
test_that("test-antibiogram.R", {
# Traditional antibiogram ----------------------------------------------
ab1 <- antibiogram(example_isolates,

2
tests/testthat/test-atc_online.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("atc_online works", {
test_that("test-atc_online.R", {
if (AMR:::pkg_is_available("curl") &&
AMR:::pkg_is_available("rvest") &&
AMR:::pkg_is_available("xml2") &&

2
tests/testthat/test-av.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("av works", {
test_that("test-av.R", {
expect_equal(
as.character(as.av(c(
"J05AB01",

2
tests/testthat/test-av_from_text.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("av_from_text works", {
test_that("test-av_from_text.R", {
expect_identical(
av_from_text("28/03/2020 regular aciclovir 500mg po tds")[[1]],
as.av("Aciclovir")

2
tests/testthat/test-av_property.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("ab_property works", {
test_that("test-ab_property.R", {
expect_identical(av_name("ACI", language = NULL), "Aciclovir")
expect_identical(av_atc("ACI"), "J05AB01")
expect_identical(av_cid("ACI"), as.integer(135398513))

2
tests/testthat/test-availability.R
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@ -27,6 +27,6 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("availibility works", {
test_that("test-availibility.R", {
expect_inherits(availability(example_isolates), "data.frame")
})

2
tests/testthat/test-bug_drug_combinations.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("bug/drug works", {
test_that("test-bug/drug.R", {
b <- suppressWarnings(bug_drug_combinations(example_isolates))
expect_inherits(b, "bug_drug_combinations")
expect_output(suppressMessages(print(b)))

2
tests/testthat/test-count.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("count works", {
test_that("test-count.R", {
expect_equal(count_resistant(example_isolates$AMX), count_R(example_isolates$AMX))
expect_equal(count_susceptible(example_isolates$AMX), count_SI(example_isolates$AMX))
expect_equal(count_all(example_isolates$AMX), n_sir(example_isolates$AMX))

2
tests/testthat/test-custom_antimicrobials.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("custom ab works", {
test_that("test-custom ab.R", {
ab_reset_session()
expect_message(as.ab("testab", info = TRUE))

2
tests/testthat/test-custom_microorganisms.R
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@ -28,7 +28,7 @@
# ==================================================================== #
test_that("custom mo works", {
test_that("test-custom mo.R", {
expect_identical(
as.mo("Enterobacter asburiae/cloacae"),
as.mo("Enterobacter asburiae")

2
tests/testthat/test-data.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("data works", {
test_that("test-data.R", {
# IDs should always be unique
expect_identical(nrow(microorganisms), length(unique(microorganisms$mo)))
expect_identical(class(microorganisms$mo), c("mo", "character"))

2
tests/testthat/test-disk.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("disk works", {
test_that("test-disk.R", {
expect_true(as.disk(8) == as.disk("8"))
expect_true(is.disk(as.disk(8)))

19
tests/testthat/test-eucast_rules.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("eucast_rules works", {
test_that("test-eucast_rules.R", {
# thoroughly check input table
expect_equal(
colnames(AMR:::EUCAST_RULES_DF),
@ -42,8 +42,14 @@ test_that("eucast_rules works", {
)
MOs_mentioned <- unique(AMR:::EUCAST_RULES_DF$this_value)
MOs_mentioned <- sort(trimws(unlist(strsplit(MOs_mentioned[!AMR:::is_valid_regex(MOs_mentioned)], ",", fixed = TRUE))))
MOs_test <- suppressWarnings(suppressMessages(mo_name(MOs_mentioned, keep_synonyms = TRUE, language = NULL)))
expect_true(length(MOs_mentioned[MOs_test != MOs_mentioned]) == 0)
MOs_test <- suppressWarnings(
trimws(paste(
mo_genus(MOs_mentioned, keep_synonyms = TRUE, language = NULL),
mo_species(MOs_mentioned, keep_synonyms = TRUE, language = NULL)
))
)
MOs_test[MOs_test == ""] <- mo_fullname(MOs_mentioned[MOs_test == ""], keep_synonyms = TRUE, language = NULL)
expect_equal(MOs_mentioned, MOs_test)
expect_error(suppressWarnings(eucast_rules(example_isolates, col_mo = "Non-existing")))
expect_error(eucast_rules(x = "text"))
@ -108,7 +114,7 @@ test_that("eucast_rules works", {
TIC = as.sir("R"),
PIP = as.sir("S")
) %>%
eucast_rules(col_mo = "mo", version_expertrules = 3.1, info = FALSE) %>%
eucast_rules(col_mo = "mo", version_expertrules = 3.1, info = FALSE, overwrite = TRUE) %>%
pull(PIP) %>%
unique() %>%
as.character()
@ -127,6 +133,7 @@ test_that("eucast_rules works", {
stringsAsFactors = FALSE
),
version_expertrules = 3.1,
overwrite = TRUE,
only_sir_columns = FALSE
)$CLR))
b <- example_isolates$ERY
@ -168,6 +175,7 @@ test_that("eucast_rules works", {
cefotax = as.sir(c("S", "S"))
),
ampc_cephalosporin_resistance = TRUE,
overwrite = TRUE,
info = FALSE
)$cefotax,
as.sir(c("S", "R"))
@ -180,6 +188,7 @@ test_that("eucast_rules works", {
cefotax = as.sir(c("S", "S"))
),
ampc_cephalosporin_resistance = NA,
overwrite = TRUE,
info = FALSE
)$cefotax,
as.sir(c("S", NA))
@ -192,6 +201,7 @@ test_that("eucast_rules works", {
cefotax = as.sir(c("S", "S"))
),
ampc_cephalosporin_resistance = NULL,
overwrite = TRUE,
info = FALSE
)$cefotax,
as.sir(c("S", "S"))
@ -218,6 +228,7 @@ test_that("eucast_rules works", {
rules = "custom",
custom_rules = x,
info = FALSE,
overwrite = TRUE,
verbose = TRUE
)),
8,

2
tests/testthat/test-first_isolate.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("first_isolate works", {
test_that("test-first_isolate.R", {
# all four methods
expect_equal(
sum(first_isolate(x = example_isolates, method = "isolate-based", info = TRUE), na.rm = TRUE),

2
tests/testthat/test-g.test.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("g.test works", {
test_that("test-g.test.R", {
# GOODNESS-OF-FIT
# example 1: clearfield rice vs. red rice

2
tests/testthat/test-get_episode.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("get_episode works", {
test_that("test-get_episode.R", {
x <- data.frame(dates = as.Date(c("2021-01-01", "2021-01-02", "2021-01-05", "2021-01-08", "2021-02-21", "2021-02-22", "2021-02-23", "2021-02-24", "2021-03-01", "2021-03-01")))
x$absolute <- get_episode(x$dates, episode_days = 7)
x$relative <- get_episode(x$dates, case_free_days = 7)

2
tests/testthat/test-ggplot_sir.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("ggplot_sir works", {
test_that("test-ggplot_sir.R", {
if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE) &&
AMR:::pkg_is_available("ggplot2", also_load = TRUE)) {
pdf(NULL) # prevent Rplots.pdf being created

2
tests/testthat/test-guess_ab_col.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("guess_ab_col works", {
test_that("test-guess_ab_col.R", {
expect_equal(
guess_ab_col(example_isolates, "amox"),
"AMX"

2
tests/testthat/test-italicise_taxonomy.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("italicise_taxonomy works", {
test_that("test-italicise_taxonomy.R", {
expect_identical(
italicise_taxonomy("test for E. coli"),
"test for *E. coli*"

2
tests/testthat/test-join_microorganisms.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("join_microorganisms works", {
test_that("test-join_microorganisms.R", {
unjoined <- example_isolates
inner <- inner_join_microorganisms(example_isolates)
left <- left_join_microorganisms(example_isolates)

2
tests/testthat/test-key_antimicrobials.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("key_antimicrobials works", {
test_that("test-key_antimicrobials.R", {
expect_equal(length(key_antimicrobials(example_isolates, antifungal = NULL)), nrow(example_isolates))
expect_false(all(is.na(key_antimicrobials(example_isolates, antifungal = NULL))))
expect_true(antimicrobials_equal("SSS", "SSS", type = "points"))

2
tests/testthat/test-kurtosis.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("kurtosis works", {
test_that("test-kurtosis.R", {
expect_equal(kurtosis(example_isolates$age),
5.227999,
tolerance = 0.00001

2
tests/testthat/test-like.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("like works", {
test_that("test-like.R", {
expect_true(sum("test" %like% c("^t", "^s")) == 1)
expect_true("test" %like% "test")

2
tests/testthat/test-mdro.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("mdro works", {
test_that("test-mdro.R", {
expect_error(mdro(example_isolates, guideline = c("BRMO", "MRGN"), info = TRUE))
expect_error(mdro(example_isolates, col_mo = "invalid", info = TRUE))

2
tests/testthat/test-mean_amr_distance.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("mean_amr_distance works", {
test_that("test-mean_amr_distance.R", {
vctr_disk <- as.disk(c(20:25))
vctr_mic <- as.mic(2^c(0:5))
vctr_sir <- as.sir(c("S", "S", "I", "I", "R", "R"))

2
tests/testthat/test-mic.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("mic works", {
test_that("test-mic.R", {
# used in multiple functions, also in plotting
expect_true(all(as.mic(AMR:::COMMON_MIC_VALUES) %in% AMR:::VALID_MIC_LEVELS))
expect_true(all(paste0("<=", as.mic(AMR:::COMMON_MIC_VALUES)) %in% AMR:::VALID_MIC_LEVELS))

2
tests/testthat/test-mo.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("mo works", {
test_that("test-mo.R", {
MOs <- subset(microorganisms, !is.na(mo) & nchar(mo) > 3)
expect_identical(as.character(MOs$mo), as.character(as.mo(MOs$mo, keep_synonyms = TRUE)))

2
tests/testthat/test-mo_property.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("mo_property works", {
test_that("test-mo_property.R", {
expect_equal(mo_kingdom("Escherichia coli"), "Bacteria")
expect_equal(mo_kingdom("Escherichia coli"), mo_domain("Escherichia coli"))
expect_equal(mo_phylum("Escherichia coli"), "Pseudomonadota")

2
tests/testthat/test-pca.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("pca works", {
test_that("test-pca.R", {
resistance_data <- structure(
list(
order = c("Bacillales", "Enterobacterales", "Enterobacterales"),

2
tests/testthat/test-plotting.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("plotting works", {
test_that("test-plotting.R", {
if (AMR:::pkg_is_available("ggplot2", also_load = TRUE)) {
pdf(NULL) # prevent Rplots.pdf being created

2
tests/testthat/test-proportion.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("proportion works", {
test_that("test-proportion.R", {
expect_equal(proportion_R(example_isolates$AMX), resistance(example_isolates$AMX))
expect_equal(proportion_SI(example_isolates$AMX), susceptibility(example_isolates$AMX))
# AMX resistance in `example_isolates`

2
tests/testthat/test-random.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("random works", {
test_that("test-random.R", {
expect_inherits(random_mic(100), "mic")
expect_inherits(random_mic(100, mo = "Klebsiella pneumoniae"), "mic")
expect_inherits(random_mic(100, mo = "Klebsiella pneumoniae", ab = "meropenem"), "mic")

2
tests/testthat/test-resistance_predict.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("resistance_predict works", {
test_that("test-resistance_predict.R", {
if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) {
expect_output(AMX_R <- example_isolates %>%
filter(mo == "B_ESCHR_COLI") %>%

2
tests/testthat/test-sir.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("sir works", {
test_that("test-sir.R", {
# Existing SIR ------------------------------------------------------------
# we must only have EUCAST and CLSI, because otherwise the rules in as.sir() will fail

2
tests/testthat/test-skewness.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("skewness works", {
test_that("test-skewness.R", {
expect_equal(skewness(example_isolates$age),
-1.212888,
tolerance = 0.00001

2
tests/testthat/test-top_n_microorganisms.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("top_n_microorganisms works", {
test_that("test-top_n_microorganisms.R", {
out1 <- top_n_microorganisms(example_isolates, n = 3)
out2 <- top_n_microorganisms(example_isolates, n = 5, property = "genus")
out3 <- top_n_microorganisms(example_isolates, n = 5, property = "genus", n_for_each = 3)

2
tests/testthat/test-translate.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("translate works", {
test_that("test-translate.R", {
expect_identical(mo_genus("B_GRAMP", language = "pt"), "(gênero desconhecido)")
expect_identical(mo_fullname("CoNS", "cs"), "Koaguláza-negativní stafylokok (KNS)")

2
tests/testthat/test-vctrs.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("vctrs works", {
test_that("test-vctrs.R", {
# extra tests for {vctrs} pkg support
if (AMR:::pkg_is_available("tibble")) {
test <- tibble::tibble(

2
tests/testthat/test-zzz.R
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@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
test_that("zzz works", {
test_that("test-zzz.R", {
# Check if these functions still exist in their package (all are in Suggests field)
# Since GitHub Actions runs every night, we will get emailed when a dependency fails based on this unit test