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(v1.4.0.9056) subsetting ab class selectors for base R

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dr. M.S. (Matthijs) Berends 2021-01-03 23:40:05 +01:00
parent ecac443f86
commit 63a4dda467
20 changed files with 334 additions and 199 deletions
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29
.github/workflows/check.yaml vendored
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@ -59,9 +59,6 @@ jobs:
- {os: ubuntu-16.04, r: 'devel', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
- {os: ubuntu-16.04, r: 'release', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
- {os: ubuntu-16.04, r: 'oldrel', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
- {os: ubuntu-20.04, r: 'devel', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
- {os: ubuntu-20.04, r: 'release', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
- {os: ubuntu-20.04, r: 'oldrel', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
- {os: ubuntu-16.04, r: '4.0', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
- {os: ubuntu-16.04, r: '3.6', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
- {os: ubuntu-16.04, r: '3.5', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
@ -70,7 +67,13 @@ jobs:
- {os: ubuntu-16.04, r: '3.2', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
- {os: ubuntu-16.04, r: '3.1', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
- {os: ubuntu-16.04, r: '3.0', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
- {os: ubuntu-20.04, r: 'devel', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
- {os: ubuntu-20.04, r: 'release', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
- {os: ubuntu-20.04, r: 'oldrel', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
- {os: ubuntu-20.04, r: '3.2', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
- {os: ubuntu-20.04, r: '3.1', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
- {os: ubuntu-20.04, r: '3.0', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
env:
R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
RSPM: ${{ matrix.config.rspm }}
@ -92,21 +95,21 @@ jobs:
shell: Rscript {0}
- name: Cache R packages
if: runner.os != 'Windows' && matrix.config.r != '3.0' && matrix.config.r != '3.1' && matrix.config.r != '3.2'
if: runner.os != 'Windows'
uses: actions/cache@v1
with:
path: ${{ env.R_LIBS_USER }}
key: ${{ runner.os }}-r-${{ matrix.config.r }}-3-${{ hashFiles('.github/depends.Rds') }}
restore-keys: ${{ runner.os }}-r-${{ matrix.config.r }}-3-
key: ${{ matrix.config.os }}-r-${{ matrix.config.r }}-3-${{ hashFiles('.github/depends.Rds') }}
restore-keys: ${{ matrix.config.os }}-r-${{ matrix.config.r }}-3-
- name: Install Linux dependencies
if: runner.os == 'Linux' && matrix.config.r != '3.0' && matrix.config.r != '3.1' && matrix.config.r != '3.2'
if: runner.os == 'Linux'
env:
RHUB_PLATFORM: linux-x86_64-ubuntu-gcc
# 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 a quite new R version
run: |
Rscript -e "remotes::install_github('r-hub/sysreqs')"
sysreqs=$(Rscript -e "cat(sysreqs::sysreq_commands('DESCRIPTION'))")
sudo -s eval "$sysreqs"
sudo apt install -y libssl-dev pandoc pandoc-citeproc libxml2-dev libicu-dev libcurl4-openssl-dev
- name: Install macOS dependencies
if: matrix.config.os == 'macOS-latest' && matrix.config.r == 'devel'
@ -114,10 +117,9 @@ jobs:
brew install mariadb-connector-c
- name: Install dependencies
if: matrix.config.r != '3.0' && matrix.config.r != '3.1' && matrix.config.r != '3.2'
if: always()
run: |
remotes::install_deps(dependencies = TRUE)
remotes::install_cran("rcmdcheck")
utils::install.packages(strsplit(utils::packageDescription("AMR")$Suggests, ",\n")[[1]])
shell: Rscript {0}
- name: Session info
@ -139,6 +141,7 @@ jobs:
env:
_R_CHECK_CRAN_INCOMING_: false
_R_CHECK_FORCE_SUGGESTS_: false
# these are set already in --as-cran:
_R_CHECK_LENGTH_1_CONDITION_: verbose
_R_CHECK_LENGTH_1_LOGIC2_: verbose
run: |

4
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR
Version: 1.4.0.9055
Date: 2020-12-31
Version: 1.4.0.9056
Date: 2021-01-03
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

30
NEWS.md
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@ -1,6 +1,5 @@
# AMR 1.4.0.9055
## <small>Last updated: 31 December 2020</small>
# AMR 1.4.0.9056
## <small>Last updated: 3 January 2021</small>
### New
* Functions `get_episode()` and `is_new_episode()` to determine (patient) episodes which are not necessarily based on microorganisms. 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. They also support `dplyr`s grouping (i.e. using `group_by()`):
```r
@ -11,7 +10,7 @@
```
* 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.
* Function `mo_is_intrinsic_resistant()` to test for intrinsic resistance, based on [EUCAST Intrinsic Resistance and Unusual Phenotypes v3.2](https://www.eucast.org/expert_rules_and_intrinsic_resistance/) from 2020.
* Functions `random_mic()`, `random_disk()` and `random_rsi()` for random number generation. They take microorganism names and antibiotic names as input to make generation more realistic.
* Functions `random_mic()`, `random_disk()` and `random_rsi()` for random value generation. The functions `random_mic()` and `random_disk()` take microorganism names and antibiotic names as input to make generation more realistic.
### Changed
* New argument `ampc_cephalosporin_resistance` in `eucast_rules()` to correct for AmpC de-repressed cephalosporin-resistant mutants
@ -22,7 +21,21 @@
* `as.rsi()` on a data.frame will not print a message anymore if the values are already clean R/SI values
* If using `as.rsi()` on MICs or disk diffusion while there is intrinsic antimicrobial resistance, a warning will be thrown to remind about this
* Fix for using `as.rsi()` on a `data.frame` that only contains one column for antibiotic interpretations
* Some functions are now context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the data argument does not need to be set anymore. This is the case for the new functions `mo_is_gram_negative()`, `mo_is_gram_positive()`, `mo_is_intrinsic_resistant()` and for the existing functions `first_isolate()`, `key_antibiotics()`, `mdro()`, `brmo()`, `mrgn()`, `mdr_tb()`, `mdr_cmi2012()`, `eucast_exceptional_phenotypes()`. This was already the case for antibiotic selection functions (such as using `penicillins()` in `dplyr::select()`).
* Some functions are now context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the data argument does not need to be set anymore. This is the case for the new functions:
* `mo_is_gram_negative()`
* `mo_is_gram_positive()`
* `mo_is_intrinsic_resistant()`
... and for the existing functions:
* `first_isolate()`,
* `key_antibiotics()`,
* `mdro()`,
* `brmo()`,
* `mrgn()`,
* `mdr_tb()`,
* `mdr_cmi2012()`,
* `eucast_exceptional_phenotypes()`
```r
# to select first isolates that are Gram-negative
# and view results of cephalosporins and aminoglycosides:
@ -32,6 +45,12 @@
select(mo, cephalosporins(), aminoglycosides()) %>%
as_tibble()
```
* For antibiotic selection functions (such as `cephalosporins()`, `aminoglycosides()`) to select columns based on a certain antibiotic group, the dependency on the `tidyselect` package was removed, meaning that they can now also be used without the need to have this package installed and now also work in base R function calls:
```r
# above example in base R:
example_isolates[which(first_isolate() & mo_is_gram_negative()),
c("mo", cephalosporins(), aminoglycosides())]
```
* For all function arguments in the code, it is now defined what the exact type of user input should be (inspired by the [`typed`](https://github.com/moodymudskipper/typed) package). If the user input for a certain function does not meet the requirements for a specific argument (such as the class or length), an informative error will be thrown. This makes the package more robust and the use of it more reproducible and reliable. In total, more than 420 arguments were defined.
* Fix for `set_mo_source()`, that previously would not remember the file location of the original file
* Deprecated function `p_symbol()` that not really fits the scope of this package. It will be removed in a future version. See [here](https://github.com/msberends/AMR/blob/v1.4.0/R/p_symbol.R) for the source code to preserve it.
@ -47,7 +66,6 @@
* Fix for printing class <mo> in tibbles when all values are `NA`
* Fix for `mo_shortname()` when the input contains `NA`
* If `as.mo()` takes more than 30 seconds, some suggestions will be done to improve speed
* Lost dependency on the `tidyselect` package for using antibiotic selectors such as `carbapenems()` and `aminoglycosides()`
### Other
* All messages and warnings thrown by this package now break sentences on whole words

67
R/aa_helper_functions.R
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@ -527,43 +527,74 @@ meet_criteria <- function(object,
}
get_current_data <- function(arg_name, call) {
# this mimics dplyr::cur_data_all for users that use our context-aware functions in dplyr verbs
cur_data_all_dplyr <- import_fn("cur_data_all", "dplyr", error_on_fail = FALSE)
if (is.null(cur_data_all_dplyr)) {
# dplyr not installed
stop_("argument `", arg_name, "` is missing, with no default", call = call)
# try a (base R) method, by going over the complete system call stack with sys.frames()
not_set <- TRUE
frms <- lapply(sys.frames(), function(el) {
if (tryCatch(not_set == TRUE && ".data" %in% names(el) && is.data.frame(el$`.data`), error = function(e) FALSE)) {
# dplyr? - an element `.data` will be in the system call stack
not_set <<- FALSE
el$`.data`
} else if (tryCatch(not_set == TRUE && any(c("x", "xx") %in% names(el)), error = function(e) FALSE)) {
# otherwise try base R:
# an element `x` will be in this environment for only cols, e.g. `example_isolates[, carbapenems()]`
# an element `xx` will be in this environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]`
if (is.data.frame(el$xx)) {
not_set <<- FALSE
el$xx
} else if (is.data.frame(el$x)) {
not_set <<- FALSE
el$x
} else {
NULL
}
tryCatch(cur_data_all_dplyr(),
# dplyr installed, but not used inside dplyr verb
error = function(e) stop_("argument `", arg_name, "` is missing with no default ",
} else {
NULL
}
})
vars_df <- tryCatch(frms[[which(!vapply(FUN.VALUE = logical(1), frms, is.null))]], error = function(e) NULL)
if (is.data.frame(vars_df)) {
return(vars_df)
}
# nothing worked, so:
if (is.na(arg_name)) {
stop_("this function must be used inside valid dplyr selection verbs or inside a data.frame call",
call = call)
} else {
stop_("argument `", arg_name, "` is missing with no default ",
"or function not used inside a valid dplyr verb",
# tryCatch adds 4 system calls, subtract them
call = call - 4))
call = call)
}
}
unique_call_id <- function() {
unique_call_id <- function(entire_session = FALSE) {
if (entire_session == TRUE) {
c(envir = "session",
call = "session")
} else {
# combination of environment ID (like "0x7fed4ee8c848")
# and highest system call
c(envir = gsub("<environment: (.*)>", "\\1", utils::capture.output(sys.frames()[[1]])),
call = paste0(deparse(sys.calls()[[1]]), collapse = ""))
}
}
remember_thrown_message <- function(fn) {
remember_thrown_message <- function(fn, entire_session = FALSE) {
# this is to prevent that messages/notes will be printed for every dplyr group
# e.g. this would show a msg 4 times: example_isolates %>% group_by(hospital_id) %>% filter(mo_is_gram_negative())
assign(x = paste0("uniquecall_", fn),
value = unique_call_id(),
assign(x = paste0("thrown_msg_", fn),
value = unique_call_id(entire_session = entire_session),
envir = pkg_env)
}
message_not_thrown_before <- function(fn) {
is.null(pkg_env[[paste0("uniquecall_", fn)]]) || !identical(pkg_env[[paste0("uniquecall_", fn)]], unique_call_id())
message_not_thrown_before <- function(fn, entire_session = FALSE) {
is.null(pkg_env[[paste0("thrown_msg_", fn)]]) || !identical(pkg_env[[paste0("thrown_msg_", fn)]], unique_call_id(entire_session))
}
reset_all_thrown_messages <- function() {
# for unit tests, where the environment and highest system call do not change
pkg_env_contents <- ls(envir = pkg_env)
rm(list = pkg_env_contents[pkg_env_contents %like% "^uniquecall_"],
rm(list = pkg_env_contents[pkg_env_contents %like% "^thrown_msg_"],
envir = pkg_env)
}
@ -571,7 +602,7 @@ has_colour <- function() {
# this is a base R version of crayon::has_color, but disables colours on emacs
if (Sys.getenv("EMACS") != "" || Sys.getenv("INSIDE_EMACS") != "") {
# disable on emacs, only supports 8 colours
# disable on emacs, which only supports 8 colours
return(FALSE)
}
enabled <- getOption("crayon.enabled")

23
R/ab_class_selectors.R
View File

@ -162,28 +162,7 @@ ab_selector <- function(ab_class, function_name) {
meet_criteria(ab_class, allow_class = "character", has_length = 1, .call_depth = 1)
meet_criteria(function_name, allow_class = "character", has_length = 1, .call_depth = 1)
for (i in seq_len(length(sys.frames()))) {
# dplyr?
if (".data" %in% names(sys.frames()[[i]])) {
vars_df <- sys.frames()[[i]]$`.data`
if (is.data.frame(vars_df)) {
break
}
}
# then try base R - an element `x` will be in the system call stack
vars_df <- tryCatch(sys.frames()[[i]]$x, error = function(e) NULL)
if (!is.null(vars_df) && is.data.frame(vars_df)) {
# when using e.g. example_isolates[, carbapenems()] or example_isolates %>% select(carbapenems())
break
} else if (!is.null(vars_df) && is.list(vars_df)) {
# when using e.g. example_isolates %>% filter(across(carbapenems(), ~. == "R"))
vars_df <- tryCatch(as.data.frame(vars_df, stringsAsFactors = FALSE), error = function(e) NULL)
if (!is.null(vars_df)) {
break
}
}
}
stop_ifnot(is.data.frame(vars_df), "this function must be used inside dplyr selection verbs or within a data.frame call.", call = -2)
vars_df <- get_current_data(arg_name = NA, call = -3)
ab_in_data <- get_column_abx(vars_df, info = FALSE)
if (length(ab_in_data) == 0) {

111
R/mo_property.R
View File

@ -162,8 +162,8 @@
#' }
mo_name <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_name")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_name")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -179,8 +179,8 @@ mo_fullname <- mo_name
#' @export
mo_shortname <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_shortname")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_shortname")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -217,8 +217,8 @@ mo_shortname <- function(x, language = get_locale(), ...) {
#' @export
mo_subspecies <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_subspecies")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_subspecies")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -230,8 +230,8 @@ mo_subspecies <- function(x, language = get_locale(), ...) {
#' @export
mo_species <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_species")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_species")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -243,8 +243,8 @@ mo_species <- function(x, language = get_locale(), ...) {
#' @export
mo_genus <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_genus")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_genus")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -256,8 +256,8 @@ mo_genus <- function(x, language = get_locale(), ...) {
#' @export
mo_family <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_family")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_family")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -269,8 +269,8 @@ mo_family <- function(x, language = get_locale(), ...) {
#' @export
mo_order <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_order")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_order")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -282,8 +282,8 @@ mo_order <- function(x, language = get_locale(), ...) {
#' @export
mo_class <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_class")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_class")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -295,8 +295,8 @@ mo_class <- function(x, language = get_locale(), ...) {
#' @export
mo_phylum <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_phylum")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_phylum")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -308,8 +308,8 @@ mo_phylum <- function(x, language = get_locale(), ...) {
#' @export
mo_kingdom <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_kingdom")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_kingdom")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -325,8 +325,8 @@ mo_domain <- mo_kingdom
#' @export
mo_type <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_type")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_type")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -338,8 +338,8 @@ mo_type <- function(x, language = get_locale(), ...) {
#' @export
mo_gramstain <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_gramstain")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_gramstain")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -376,8 +376,8 @@ mo_gramstain <- function(x, language = get_locale(), ...) {
#' @export
mo_is_gram_negative <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_is_gram_negative")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_is_gram_negative")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -395,8 +395,8 @@ mo_is_gram_negative <- function(x, language = get_locale(), ...) {
#' @export
mo_is_gram_positive <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_is_gram_positive")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_is_gram_positive")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -414,8 +414,8 @@ mo_is_gram_positive <- function(x, language = get_locale(), ...) {
#' @export
mo_is_intrinsic_resistant <- function(x, ab, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_is_intrinsic_resistant")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_is_intrinsic_resistant")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(ab, allow_NA = FALSE)
@ -433,11 +433,12 @@ mo_is_intrinsic_resistant <- function(x, ab, language = get_locale(), ...) {
stop_("length of `x` and `ab` must be equal, or one of them must be of length 1.")
}
# show used version number once
if (message_not_thrown_before("intrinsic_resistant_version")) {
# show used version number once per session (pkg_env will reload every session)
if (message_not_thrown_before("intrinsic_resistant_version", entire_session = TRUE)) {
message_("Determining intrinsic resistance based on ",
format_eucast_version_nr(3.2, markdown = FALSE), ".")
remember_thrown_message("intrinsic_resistant_version")
format_eucast_version_nr(3.2, markdown = FALSE), ". ",
font_red("This note will be shown once per session."))
remember_thrown_message("intrinsic_resistant_version", entire_session = TRUE)
}
# runs against internal vector: INTRINSIC_R (see zzz.R)
@ -448,8 +449,8 @@ mo_is_intrinsic_resistant <- function(x, ab, language = get_locale(), ...) {
#' @export
mo_snomed <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_snomed")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_snomed")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -461,8 +462,8 @@ mo_snomed <- function(x, language = get_locale(), ...) {
#' @export
mo_ref <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_ref")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_ref")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -474,8 +475,8 @@ mo_ref <- function(x, language = get_locale(), ...) {
#' @export
mo_authors <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_authors")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_authors")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -490,8 +491,8 @@ mo_authors <- function(x, language = get_locale(), ...) {
#' @export
mo_year <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_year")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_year")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -506,8 +507,8 @@ mo_year <- function(x, language = get_locale(), ...) {
#' @export
mo_rank <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_rank")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_rank")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -519,8 +520,8 @@ mo_rank <- function(x, language = get_locale(), ...) {
#' @export
mo_taxonomy <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_taxonomy")
# 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)
@ -545,8 +546,8 @@ mo_taxonomy <- function(x, language = get_locale(), ...) {
#' @export
mo_synonyms <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_synonyms")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_synonyms")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
@ -578,8 +579,8 @@ mo_synonyms <- function(x, language = get_locale(), ...) {
#' @export
mo_info <- function(x, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_info")
# 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)
@ -608,8 +609,8 @@ mo_info <- function(x, language = get_locale(), ...) {
#' @export
mo_url <- function(x, open = FALSE, language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_url")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_url")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(open, allow_class = "logical", has_length = 1)
@ -645,8 +646,8 @@ mo_url <- function(x, open = FALSE, language = get_locale(), ...) {
#' @export
mo_property <- function(x, property = "fullname", language = get_locale(), ...) {
if (missing(x)) {
# this supports using in dplyr verbs: ... %>% filter(mo_is_intrinsic_resistant(ab = "amox"))
x <- find_mo_col("mo_property")
# this tries to find the data and an <mo> column
x <- find_mo_col(fn = "mo_property")
}
meet_criteria(x, allow_NA = TRUE)
meet_criteria(property, allow_class = "character", has_length = 1, is_in = colnames(microorganisms))
@ -700,7 +701,7 @@ mo_validate <- function(x, property, language, ...) {
}
find_mo_col <- function(fn) {
# this function tries to find an mo column using dplyr::cur_data_all() for mo_is_*() functions,
# this function tries to find an mo column in the data the function was called in,
# which is useful when functions are used within dplyr verbs
df <- get_current_data(arg_name = "x", call = -3) # will return an error if not found
mo <- NULL

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4
data-raw/reproduction_of_intrinsic_resistant.R
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@ -24,6 +24,7 @@
# ==================================================================== #
library(AMR)
library(dplyr)
int_resis <- data.frame(microorganism = microorganisms$mo, stringsAsFactors = FALSE)
for (i in seq_len(nrow(antibiotics))) {
int_resis$new <- as.rsi("S")
@ -45,3 +46,6 @@ int_resis2$microorganism <- mo_name(int_resis2$microorganism, language = NULL)
intrinsic_resistant <- as.data.frame(int_resis2, stringsAsFactors = FALSE)
usethis::use_data(intrinsic_resistant, internal = FALSE, overwrite = TRUE, version = 2, compress = "xz")
rm(intrinsic_resistant)
# AFTER THIS:
# DO NOT FORGET TO UPDATE THE VERSION NUMBER IN mo_is_intrinsic_resistant()

2
docs/404.html
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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.github.io/AMR//index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9056</span>
</span>
</div>

2
docs/LICENSE-text.html
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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9056</span>
</span>
</div>

2
docs/articles/index.html
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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9056</span>
</span>
</div>

2
docs/authors.html
View File

@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9056</span>
</span>
</div>

14
docs/index.html
View File

@ -43,7 +43,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9056</span>
</span>
</div>
@ -227,6 +227,8 @@ Since you are one of our users, we would like to know how you use the package an
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">mo</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>
<span class="co">#&gt; NOTE: Using column 'mo' as input for mo_is_gram_negative()</span>
<span class="co">#&gt; NOTE: Using column 'mo' as input for mo_is_intrinsic_resistant()</span>
<span class="co">#&gt; NOTE: Determining intrinsic resistance based on 'EUCAST Expert Rules' and</span>
<span class="co">#&gt; 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2 from 2020.</span>
<span class="co">#&gt; Selecting aminoglycosides: 'AMK' (amikacin), 'GEN' (gentamicin), </span>
<span class="co">#&gt; 'KAN' (kanamycin), 'TOB' (tobramycin)</span>
<span class="co">#&gt; Selecting carbapenems: 'IPM' (imipenem), 'MEM' (meropenem)</span></code></pre></div>
@ -298,6 +300,12 @@ Since you are one of our users, we would like to know how you use the package an
</tr>
</tbody>
</table>
<p>A base R equivalent would be:</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">example_isolates</span><span class="op">$</span><span class="va">mo</span> <span class="op">&lt;-</span> <span class="fu"><a href="reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">$</span><span class="va">mo</span><span class="op">)</span>
<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html">which</a></span><span class="op">(</span><span class="fu"><a href="reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&amp;</span>
<span class="fu"><a href="reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span>ab <span class="op">=</span> <span class="st">"cefotax"</span><span class="op">)</span><span class="op">)</span>,
<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"mo"</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">]</span></code></pre></div>
</div>
<div id="partners" class="section level4">
<h4 class="hasAnchor">
@ -339,7 +347,7 @@ Since you are one of our users, we would like to know how you use the package an
<a href="#latest-released-version" class="anchor"></a>Latest released version</h4>
<p><a href="https://cran.r-project.org/package=AMR"><img src="https://www.r-pkg.org/badges/version-ago/AMR" alt="CRAN"></a> <a href="https://cran.r-project.org/package=AMR"><img src="https://cranlogs.r-pkg.org/badges/grand-total/AMR" alt="CRANlogs"></a></p>
<p>This package is available <a href="https://cran.r-project.org/package=AMR">here on the official R network (CRAN)</a>, which has a peer-reviewed submission process. Install this package in R from CRAN by using the command:</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"AMR"</span><span class="op">)</span></code></pre></div>
<p>It will be downloaded and installed automatically. For RStudio, click on the menu <em>Tools</em> &gt; <em>Install Packages…</em> and then type in “AMR” and press <kbd>Install</kbd>.</p>
<p><strong>Note:</strong> Not all functions on this website may be available in this latest release. To use all functions and data sets mentioned on this website, install the latest development version.</p>
@ -349,7 +357,7 @@ Since you are one of our users, we would like to know how you use the package an
<a href="#latest-development-version" class="anchor"></a>Latest development version</h4>
<p><img src="https://github.com/msberends/AMR/workflows/R-code-check/badge.svg?branch=master" alt="R-code-check"><a href="https://www.codefactor.io/repository/github/msberends/amr"><img src="https://www.codefactor.io/repository/github/msberends/amr/badge" alt="CodeFactor"></a> <a href="https://codecov.io/gh/msberends/AMR?branch=master"><img src="https://codecov.io/gh/msberends/AMR/branch/master/graph/badge.svg" alt="Codecov"></a></p>
<p>The latest and unpublished development version can be installed from GitHub using:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html">install.packages</a></span><span class="op">(</span><span class="st">"remotes"</span><span class="op">)</span>
<span class="fu">remotes</span><span class="fu">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html">install_github</a></span><span class="op">(</span><span class="st">"msberends/AMR"</span><span class="op">)</span></code></pre></div>
</div>

130
docs/news/index.html
View File

@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9056</span>
</span>
</div>
@ -236,13 +236,13 @@
<small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
</div>
<div id="amr-1409055" class="section level1">
<h1 class="page-header" data-toc-text="1.4.0.9055">
<a href="#amr-1409055" class="anchor"></a>AMR 1.4.0.9055<small> Unreleased </small>
<div id="amr-1409056" class="section level1">
<h1 class="page-header" data-toc-text="1.4.0.9056">
<a href="#amr-1409056" class="anchor"></a>AMR 1.4.0.9056<small> Unreleased </small>
</h1>
<div id="last-updated-31-december-2020" class="section level2">
<div id="last-updated-3-january-2021" class="section level2">
<h2 class="hasAnchor">
<a href="#last-updated-31-december-2020" class="anchor"></a><small>Last updated: 31 December 2020</small>
<a href="#last-updated-3-january-2021" class="anchor"></a><small>Last updated: 3 January 2021</small>
</h2>
<div id="new" class="section level3">
<h3 class="hasAnchor">
@ -259,7 +259,7 @@
</li>
<li><p>Functions <code><a href="../reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><a href="../reference/mo_property.html">mo_is_gram_positive()</a></code> as wrappers around <code><a href="../reference/mo_property.html">mo_gramstain()</a></code>. They always return <code>TRUE</code> or <code>FALSE</code> (except when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>), thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</p></li>
<li><p>Function <code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> to test for intrinsic resistance, based on <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST Intrinsic Resistance and Unusual Phenotypes v3.2</a> from 2020.</p></li>
<li><p>Functions <code><a href="../reference/random.html">random_mic()</a></code>, <code><a href="../reference/random.html">random_disk()</a></code> and <code><a href="../reference/random.html">random_rsi()</a></code> for random number generation. They take microorganism names and antibiotic names as input to make generation more realistic.</p></li>
<li><p>Functions <code><a href="../reference/random.html">random_mic()</a></code>, <code><a href="../reference/random.html">random_disk()</a></code> and <code><a href="../reference/random.html">random_rsi()</a></code> for random value generation. The functions <code><a href="../reference/random.html">random_mic()</a></code> and <code><a href="../reference/random.html">random_disk()</a></code> take microorganism names and antibiotic names as input to make generation more realistic.</p></li>
</ul>
</div>
<div id="changed" class="section level3">
@ -280,7 +280,30 @@
</ul>
</li>
<li>
<p>Some functions are now context-aware when used inside <code>dplyr</code> verbs, such as <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>. This means that then the data argument does not need to be set anymore. This is the case for the new functions <code><a href="../reference/mo_property.html">mo_is_gram_negative()</a></code>, <code><a href="../reference/mo_property.html">mo_is_gram_positive()</a></code>, <code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> and for the existing functions <code><a href="../reference/first_isolate.html">first_isolate()</a></code>, <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code>, <code><a href="../reference/mdro.html">mdro()</a></code>, <code><a href="../reference/mdro.html">brmo()</a></code>, <code><a href="../reference/mdro.html">mrgn()</a></code>, <code><a href="../reference/mdro.html">mdr_tb()</a></code>, <code><a href="../reference/mdro.html">mdr_cmi2012()</a></code>, <code><a href="../reference/mdro.html">eucast_exceptional_phenotypes()</a></code>. This was already the case for antibiotic selection functions (such as using <code><a href="../reference/antibiotic_class_selectors.html">penicillins()</a></code> in <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code>).</p>
<p>Some functions are now context-aware when used inside <code>dplyr</code> verbs, such as <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>. This means that then the data argument does not need to be set anymore. This is the case for the new functions:</p>
<ul>
<li><code><a href="../reference/mo_property.html">mo_is_gram_negative()</a></code></li>
<li><code><a href="../reference/mo_property.html">mo_is_gram_positive()</a></code></li>
<li><code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code></li>
</ul>
<p>… and for the existing functions:</p>
<ul>
<li>
<code><a href="../reference/first_isolate.html">first_isolate()</a></code>,</li>
<li>
<code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code>,</li>
<li>
<code><a href="../reference/mdro.html">mdro()</a></code>,</li>
<li>
<code><a href="../reference/mdro.html">brmo()</a></code>,</li>
<li>
<code><a href="../reference/mdro.html">mrgn()</a></code>,</li>
<li>
<code><a href="../reference/mdro.html">mdr_tb()</a></code>,</li>
<li>
<code><a href="../reference/mdro.html">mdr_cmi2012()</a></code>,</li>
<li><code><a href="../reference/mdro.html">eucast_exceptional_phenotypes()</a></code></li>
</ul>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># to select first isolates that are Gram-negative </span>
@ -291,6 +314,14 @@
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">mo</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">cephalosporins</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://tibble.tidyverse.org/reference/as_tibble.html">as_tibble</a></span><span class="op">(</span><span class="op">)</span></code></pre></div>
</li>
<li>
<p>For antibiotic selection functions (such as <code><a href="../reference/antibiotic_class_selectors.html">cephalosporins()</a></code>, <code><a href="../reference/antibiotic_class_selectors.html">aminoglycosides()</a></code>) to select columns based on a certain antibiotic group, the dependency on the <code>tidyselect</code> package was removed, meaning that they can now also be used without the need to have this package installed and now also work in base R function calls:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># above example in base R:</span>
<span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html">which</a></span><span class="op">(</span><span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="op">)</span> <span class="op">&amp;</span> <span class="fu"><a href="../reference/mo_property.html">mo_is_gram_negative</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>,
<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"mo"</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">cephalosporins</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">]</span></code></pre></div>
</li>
<li><p>For all function arguments in the code, it is now defined what the exact type of user input should be (inspired by the <a href="https://github.com/moodymudskipper/typed"><code>typed</code></a> package). If the user input for a certain function does not meet the requirements for a specific argument (such as the class or length), an informative error will be thrown. This makes the package more robust and the use of it more reproducible and reliable. In total, more than 420 arguments were defined.</p></li>
<li><p>Fix for <code><a href="../reference/mo_source.html">set_mo_source()</a></code>, that previously would not remember the file location of the original file</p></li>
<li><p>Deprecated function <code><a href="../reference/AMR-deprecated.html">p_symbol()</a></code> that not really fits the scope of this package. It will be removed in a future version. See <a href="https://github.com/msberends/AMR/blob/v1.4.0/R/p_symbol.R">here</a> for the source code to preserve it.</p></li>
@ -306,7 +337,6 @@
<li><p>Fix for printing class <mo> in tibbles when all values are <code>NA</code></mo></p></li>
<li><p>Fix for <code><a href="../reference/mo_property.html">mo_shortname()</a></code> when the input contains <code>NA</code></p></li>
<li><p>If <code><a href="../reference/as.mo.html">as.mo()</a></code> takes more than 30 seconds, some suggestions will be done to improve speed</p></li>
<li><p>Lost dependency on the <code>tidyselect</code> package for using antibiotic selectors such as <code><a href="../reference/antibiotic_class_selectors.html">carbapenems()</a></code> and <code><a href="../reference/antibiotic_class_selectors.html">aminoglycosides()</a></code></p></li>
</ul>
</div>
<div id="other" class="section level3">
@ -338,7 +368,7 @@
<li>
<p>Data set <code>intrinsic_resistant</code>. This data set contains all bug-drug combinations where the ‘bug’ is intrinsic resistant to the ‘drug’ according to the latest EUCAST insights. It contains just two columns: <code>microorganism</code> and <code>antibiotic</code>.</p>
<p>Curious about which enterococci are actually intrinsic resistant to vancomycin?</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
@ -361,7 +391,7 @@
<ul>
<li>
<p>Support for using <code>dplyr</code>’s <code><a href="https://dplyr.tidyverse.org/reference/across.html">across()</a></code> to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># until dplyr 1.0.0</span>
<span class="va">your_data</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_if</a></span><span class="op">(</span><span class="va">is.mic</span>, <span class="va">as.rsi</span><span class="op">)</span>
@ -379,7 +409,7 @@
</li>
<li>
<p>Added intelligent data cleaning to <code><a href="../reference/as.disk.html">as.disk()</a></code>, so numbers can also be extracted from text and decimal numbers will always be rounded up:</p>
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/as.disk.html">as.disk</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"disk zone: 23.4 mm"</span>, <span class="fl">23.4</span><span class="op">)</span><span class="op">)</span>
<span class="co">#&gt; Class &lt;disk&gt;</span>
@ -440,7 +470,7 @@
<li><p>Function <code><a href="../reference/ab_from_text.html">ab_from_text()</a></code> to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses <code><a href="../reference/as.ab.html">as.ab()</a></code> internally</p></li>
<li>
<p><a href="https://tidyselect.r-lib.org/reference/language.html">Tidyverse selection helpers</a> for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> and <code><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html">tidyr::pivot_longer()</a></code>:</p>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
@ -629,7 +659,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline</p></li>
<li>
<p>Interpretation from MIC values (and disk zones) to R/SI can now be used with <code><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at()</a></code> of the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">yourdata</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span><span class="op">(</span><span class="va">antibiotic1</span><span class="op">:</span><span class="va">antibiotic25</span><span class="op">)</span>, <span class="va">as.rsi</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span><span class="op">)</span>
@ -658,7 +688,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Support for LOINC codes in the <code>antibiotics</code> data set. Use <code><a href="../reference/ab_property.html">ab_loinc()</a></code> to retrieve LOINC codes, or use a LOINC code for input in any <code>ab_*</code> function:</p>
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/ab_property.html">ab_loinc</a></span><span class="op">(</span><span class="st">"ampicillin"</span><span class="op">)</span>
<span class="co">#&gt; [1] "21066-6" "3355-5" "33562-0" "33919-2" "43883-8" "43884-6" "87604-5"</span>
@ -669,7 +699,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>Support for SNOMED CT codes in the <code>microorganisms</code> data set. Use <code><a href="../reference/mo_property.html">mo_snomed()</a></code> to retrieve SNOMED codes, or use a SNOMED code for input in any <code>mo_*</code> function:</p>
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/mo_property.html">mo_snomed</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>
<span class="co">#&gt; [1] 115329001 3092008 113961008</span>
@ -734,11 +764,11 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:</p>
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="va">somebugs</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Enterobacteriaceae"</span><span class="op">)</span> <span class="va">...</span></code></pre></div>
<p>then please adjust this to:</p>
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">somebugs</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Enterobacterales"</span><span class="op">)</span> <span class="va">...</span></code></pre></div>
</li>
@ -752,7 +782,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Functions <code><a href="../reference/proportion.html">susceptibility()</a></code> and <code><a href="../reference/proportion.html">resistance()</a></code> as aliases of <code><a href="../reference/proportion.html">proportion_SI()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code>, respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.</p>
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
<span class="va">example_isolates</span> <span class="op">%&gt;%</span>
@ -781,7 +811,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>More intelligent way of coping with some consonants like “l” and “r”</p></li>
<li>
<p>Added a score (a certainty percentage) to <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code>, that is calculated using the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance</a>:</p>
<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"Stafylococcus aureus"</span>,
<span class="st">"staphylokok aureuz"</span><span class="op">)</span><span class="op">)</span>
@ -840,14 +870,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Determination of first isolates now <strong>excludes</strong> all ‘unknown’ microorganisms at default, i.e. microbial code <code>"UNKNOWN"</code>. They can be included with the new argument <code>include_unknown</code>:</p>
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="va">...</span>, include_unknown <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div>
<p>For WHONET users, this means that all records/isolates with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default, since <code>as.mo("con") = "UNKNOWN"</code>. The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.</p>
</li>
<li>
<p>For code consistency, classes <code>ab</code> and <code>mo</code> will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in <code>NA</code>:</p>
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># how it works in base R:</span>
<span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/factor.html">factor</a></span><span class="op">(</span><span class="st">"A"</span><span class="op">)</span>
@ -872,7 +902,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Function <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> to quickly get a <code>data.frame</code> with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with <code><a href="../reference/mo_property.html">mo_shortname()</a></code> at default:</p>
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
<span class="co">#&gt; NOTE: Using column `mo` as input for `col_mo`.</span>
@ -895,13 +925,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<span class="co">#&gt; 4 Gram-negative AMX 227 0 405 632</span>
<span class="co">#&gt; NOTE: Use 'format()' on this result to get a publicable/printable format.</span></code></pre></div>
<p>You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R <code><a href="https://rdrr.io/r/base/format.html">format()</a></code> function:</p>
<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="https://rdrr.io/r/base/format.html">format</a></span><span class="op">(</span><span class="va">x</span>, combine_IR <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
</li>
<li>
<p>Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for <code>portion_*</code> functions or <code>count_*</code> functions. This can be used to determine the empiric susceptibility of a combination therapy. A new argument <code>only_all_tested</code> (<strong>which defaults to <code>FALSE</code></strong>) replaces the old <code>also_single_tested</code> and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the <code>portion</code> and <code>count</code> help pages), where the %SI is being determined:</p>
<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># --------------------------------------------------------------------</span>
<span class="co"># only_all_tested = FALSE only_all_tested = TRUE</span>
@ -923,7 +953,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p><code>tibble</code> printing support for classes <code>rsi</code>, <code>mic</code>, <code>disk</code>, <code>ab</code> <code>mo</code>. When using <code>tibble</code>s containing antimicrobial columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red. Microbial IDs (class <code>mo</code>) will emphasise on the genus and species, not on the kingdom.</p>
<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># (run this on your own console, as this page does not support colour printing)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org">dplyr</a></span><span class="op">)</span>
@ -1006,7 +1036,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Function <code><a href="../reference/proportion.html">rsi_df()</a></code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code><a href="../reference/count.html">count_df()</a></code> and <code>portion_df()</code> to immediately show resistance percentages and number of available isolates:</p>
<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">AMX</span>, <span class="va">CIP</span><span class="op">)</span> <span class="op">%&gt;%</span>
@ -1033,7 +1063,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li>UPEC (Uropathogenic <em>E. coli</em>)</li>
</ul>
<p>All these lead to the microbial ID of <em>E. coli</em>:</p>
<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"UPEC"</span><span class="op">)</span>
<span class="co"># B_ESCHR_COL</span>
@ -1138,7 +1168,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>when all values are unique it now shows a message instead of a warning</p></li>
<li>
<p>support for boxplots:</p>
<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span> <span class="op">%&gt;%</span>
@ -1233,7 +1263,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:</p>
<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/filter_ab_class.html">filter_aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>
<span class="fu"><a href="../reference/filter_ab_class.html">filter_carbapenems</a></span><span class="op">(</span><span class="op">)</span>
@ -1247,7 +1277,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<span class="fu"><a href="../reference/filter_ab_class.html">filter_macrolides</a></span><span class="op">(</span><span class="op">)</span>
<span class="fu"><a href="../reference/filter_ab_class.html">filter_tetracyclines</a></span><span class="op">(</span><span class="op">)</span></code></pre></div>
<p>The <code>antibiotics</code> data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set. For example:</p>
<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span><span class="op">(</span>result <span class="op">=</span> <span class="st">"R"</span><span class="op">)</span>
<span class="co"># Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R</span>
@ -1256,7 +1286,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions:</p>
<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">ab_property</span> <span class="op">-&gt;</span> <span class="fu">atc_property</span><span class="op">(</span><span class="op">)</span>
<span class="va">ab_name</span> <span class="op">-&gt;</span> <span class="fu">atc_name</span><span class="op">(</span><span class="op">)</span>
@ -1277,7 +1307,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>New function <code><a href="../reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.</p></li>
<li>
<p>New function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="../reference/plot.html">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/resistance_predict.html">resistance_predict</a></span><span class="op">(</span><span class="va">septic_patients</span>, col_ab <span class="op">=</span> <span class="st">"amox"</span><span class="op">)</span>
<span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
@ -1285,13 +1315,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="va">...</span><span class="op">)</span>
<span class="co"># or</span>
<span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="va">...</span><span class="op">)</span></code></pre></div>
<p>is equal to:</p>
<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>only_firsts <span class="op">=</span> <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="va">...</span><span class="op">)</span><span class="op">)</span> <span class="op">%&gt;%</span>
@ -1324,7 +1354,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Now handles incorrect spelling, like <code>i</code> instead of <code>y</code> and <code>f</code> instead of <code>ph</code>:</p>
<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># mo_fullname() uses as.mo() internally</span>
@ -1336,7 +1366,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default <code>allow_uncertain = TRUE</code> is equal to uncertainty level 2. Run <code><a href="../reference/as.mo.html">?as.mo</a></code> for more info about these levels.</p>
<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># equal:</span>
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">...</span>, allow_uncertain <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>
@ -1351,7 +1381,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>All microbial IDs that found are now saved to a local file <code>~/.Rhistory_mo</code>. Use the new function <code>clean_mo_history()</code> to delete this file, which resets the algorithms.</p></li>
<li>
<p>Incoercible results will now be considered ‘unknown’, MO code <code>UNKNOWN</code>. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:</p>
<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"qwerty"</span>, language <span class="op">=</span> <span class="st">"es"</span><span class="op">)</span>
<span class="co"># Warning: </span>
@ -1401,7 +1431,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span>
<span class="co"># OLD WAY</span>
@ -1485,7 +1515,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Fewer than 3 characters as input for <code>as.mo</code> will return NA</p></li>
<li>
<p>Function <code>as.mo</code> (and all <code>mo_*</code> wrappers) now supports genus abbreviations with “species” attached</p>
<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. species"</span><span class="op">)</span> <span class="co"># B_ESCHR</span>
<span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="st">"E. spp."</span><span class="op">)</span> <span class="co"># "Escherichia species"</span>
@ -1502,7 +1532,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Support for grouping variables, test with:</p>
<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op">%&gt;%</span>
@ -1510,7 +1540,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>Support for (un)selecting columns:</p>
<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span>
<span class="fu">freq</span><span class="op">(</span><span class="va">hospital_id</span><span class="op">)</span> <span class="op">%&gt;%</span>
@ -1590,7 +1620,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
</ul>
<p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>
<span class="co"># [1] "Gram negative"</span>
@ -1601,7 +1631,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<span class="fu"><a href="../reference/mo_property.html">mo_fullname</a></span><span class="op">(</span><span class="st">"S. group A"</span>, language <span class="op">=</span> <span class="st">"pt"</span><span class="op">)</span> <span class="co"># Portuguese</span>
<span class="co"># [1] "Streptococcus grupo A"</span></code></pre></div>
<p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"Esc blattae"</span><span class="op">)</span>
<span class="co"># Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)</span>
@ -1616,7 +1646,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Function <code>is.rsi.eligible</code> to check for columns that have valid antimicrobial results, but do not have the <code>rsi</code> class yet. Transform the columns of your raw data with: <code>data %&gt;% mutate_if(is.rsi.eligible, as.rsi)</code></p></li>
<li>
<p>Functions <code>as.mo</code> and <code>is.mo</code> as replacements for <code>as.bactid</code> and <code>is.bactid</code> (since the <code>microoganisms</code> data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The <code>as.mo</code> function determines microbial IDs using intelligent rules:</p>
<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span>
<span class="co"># [1] B_ESCHR_COL</span>
@ -1625,7 +1655,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"S group A"</span><span class="op">)</span>
<span class="co"># [1] B_STRPTC_GRA</span></code></pre></div>
<p>And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:</p>
<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">thousands_of_E_colis</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html">rep</a></span><span class="op">(</span><span class="st">"E. coli"</span>, <span class="fl">25000</span><span class="op">)</span>
<span class="fu">microbenchmark</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><span class="op">(</span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">thousands_of_E_colis</span><span class="op">)</span>, unit <span class="op">=</span> <span class="st">"s"</span><span class="op">)</span>
@ -1659,7 +1689,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</p></li>
<li>
<p>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.:</p>
<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="fu">ab_official</span><span class="op">(</span><span class="st">"Bactroban"</span><span class="op">)</span>
<span class="co"># [1] "Mupirocin"</span>
@ -1676,7 +1706,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Added arguments <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code></p></li>
<li>
<p>Support for quasiquotation in the functions series <code>count_*</code> and <code>portions_*</code>, and <code>n_rsi</code>. This allows to check for more than 2 vectors or columns.</p>
<div class="sourceCode" id="cb41"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">septic_patients</span> <span class="op">%&gt;%</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">amox</span>, <span class="va">cipr</span><span class="op">)</span> <span class="op">%&gt;%</span> <span class="fu"><a href="../reference/count.html">count_IR</a></span><span class="op">(</span><span class="op">)</span>
<span class="co"># which is the same as:</span>
@ -1696,12 +1726,12 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Added longest en shortest character length in the frequency table (<code>freq</code>) header of class <code>character</code></p></li>
<li>
<p>Support for types (classes) list and matrix for <code>freq</code></p>
<div class="sourceCode" id="cb42"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">my_matrix</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/with.html">with</a></span><span class="op">(</span><span class="va">septic_patients</span>, <span class="fu"><a href="https://rdrr.io/r/base/matrix.html">matrix</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="va">age</span>, <span class="va">gender</span><span class="op">)</span>, ncol <span class="op">=</span> <span class="fl">2</span><span class="op">)</span><span class="op">)</span>
<span class="fu">freq</span><span class="op">(</span><span class="va">my_matrix</span><span class="op">)</span></code></pre></div>
<p>For lists, subsetting is possible:</p>
<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb44"><pre class="downlit sourceCode r">
<code class="sourceCode R">
<span class="va">my_list</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span>age <span class="op">=</span> <span class="va">septic_patients</span><span class="op">$</span><span class="va">age</span>, gender <span class="op">=</span> <span class="va">septic_patients</span><span class="op">$</span><span class="va">gender</span><span class="op">)</span>
<span class="va">my_list</span> <span class="op">%&gt;%</span> <span class="fu">freq</span><span class="op">(</span><span class="va">age</span><span class="op">)</span>

2
docs/pkgdown.yml
View File

@ -12,7 +12,7 @@ articles:
datasets: datasets.html
resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html
last_built: 2020-12-31T12:43Z
last_built: 2021-01-03T22:35Z
urls:
reference: https://msberends.github.io/AMR//reference
article: https://msberends.github.io/AMR//articles

2
docs/reference/index.html
View File

@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9056</span>
</span>
</div>

2
docs/survey.html
View File

@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9055</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9056</span>
</span>
</div>

4
git_premaster.sh
View File

@ -123,9 +123,9 @@ echo
echo "••••••••••••••••••••"
echo "• Building package •"
echo "••••••••••••••••••••"
echo "• Removing old build..."
echo "• Removing old build from 'data-raw/'..."
rm data-raw/AMR_*.tar.gz
echo "• Building to 'data-raw'..."
echo "• Building 'data-raw/AMR_${new_version}.tar.gz'..."
Rscript -e "x <- devtools::build(path = 'data-raw', vignettes = FALSE, manual = FALSE, binary = FALSE, quiet = TRUE)"
echo "• Installing..."
Rscript -e "devtools::install(quiet = TRUE, dependencies = FALSE)"

11
index.md
View File

@ -35,6 +35,8 @@ example_isolates %>%
select(mo, aminoglycosides(), carbapenems())
#> NOTE: Using column 'mo' as input for mo_is_gram_negative()
#> NOTE: Using column 'mo' as input for mo_is_intrinsic_resistant()
#> NOTE: Determining intrinsic resistance based on 'EUCAST Expert Rules' and
#> 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2 from 2020.
#> Selecting aminoglycosides: 'AMK' (amikacin), 'GEN' (gentamicin),
#> 'KAN' (kanamycin), 'TOB' (tobramycin)
#> Selecting carbapenems: 'IPM' (imipenem), 'MEM' (meropenem)
@ -52,6 +54,15 @@ With only having defined a row filter on Gram-negative bacteria with intrinsic r
|*Stenotrophomonas maltophilia* | R | R | R | R | R | R |
|*Pseudomonas aeruginosa* | S | S | R | S | | S |
A base R equivalent would be:
```r
example_isolates$mo <- mo_fullname(example_isolates$mo)
example_isolates[which(mo_is_gram_negative() &
mo_is_intrinsic_resistant(ab = "cefotax")),
c("mo", aminoglycosides(), carbapenems())]
```
#### Partners
The development of this package is part of, related to, or made possible by:

70
tests/testthat/test-zzz.R
View File

@ -29,16 +29,13 @@ test_that("imports work", {
skip_on_cran()
# Check if these function still exist in the package (all are in Suggests field)
# Since GitHub Action runs every night, we will be emailed when a dependency fails based on this unit test
# Since GitHub Action runs every night, we will get emailed when a dependency fails based on this unit test
# functions used by import_fn()
import_functions <- c(
"anti_join" = "dplyr",
"cur_column" = "dplyr",
"cur_data" = "dplyr",
"document_position" = "rstudioapi",
"document_range" = "rstudioapi",
"freq.default" = "cleaner",
"full_join" = "dplyr",
"getSourceEditorContext" = "rstudioapi",
"has_internet" = "curl",
"html_attr" = "rvest",
"html_children" = "rvest",
@ -46,22 +43,75 @@ test_that("imports work", {
"html_nodes" = "rvest",
"html_table" = "rvest",
"html_text" = "rvest",
"inline_hist" = "skimr",
"inner_join" = "dplyr",
"insertText" = "rstudioapi",
"left_join" = "dplyr",
"new_pillar_shaft_simple" = "pillar",
"read_excel" = "readxl",
"read_html" = "xml2",
"right_join" = "dplyr",
"semi_join" = "dplyr",
"sfl" = "skimr",
"showQuestion" = "rstudioapi")
# functions that are called directly
call_functions <- c(
# cleaner
"freq.default" = "cleaner",
# skmir
"inline_hist" = "skimr",
"sfl" = "skimr",
# set_mo_source
"read_excel" = "readxl",
# ggplot_rsi
"aes_string" = "ggplot2",
"element_blank" = "ggplot2",
"element_line" = "ggplot2",
"element_text" = "ggplot2",
"facet_wrap" = "ggplot2",
"geom_text" = "ggplot2",
"ggplot" = "ggplot2",
"labs" = "ggplot2",
"layer" = "ggplot2",
"position_fill" = "ggplot2",
"scale_fill_manual" = "ggplot2",
"scale_y_continuous" = "ggplot2",
"theme" = "ggplot2",
"theme_minimal" = "ggplot2",
# ggplot_pca
"aes" = "ggplot2",
"arrow" = "ggplot2",
"element_blank" = "ggplot2",
"element_line" = "ggplot2",
"element_text" = "ggplot2",
"expand_limits" = "ggplot2",
"geom_path" = "ggplot2",
"geom_point" = "ggplot2",
"geom_segment" = "ggplot2",
"geom_text" = "ggplot2",
"ggplot" = "ggplot2",
"labs" = "ggplot2",
"theme" = "ggplot2",
"theme_minimal" = "ggplot2",
"unit" = "ggplot2",
"xlab" = "ggplot2",
"ylab" = "ggplot2",
# resistance_predict
"aes" = "ggplot2",
"geom_errorbar" = "ggplot2",
"geom_point" = "ggplot2",
"geom_ribbon" = "ggplot2",
"ggplot" = "ggplot2",
"labs" = "ggplot2"
)
import_functions <- c(import_functions, call_functions)
# check if all are in Suggests field
expect_true(all(unique(import_functions) %in% strsplit(packageDescription("AMR")$Suggests, ",\n")[[1]]))
for (i in seq_len(length(import_functions))) {
fn <- names(import_functions)[i]
pkg <- unname(import_functions[i])
expect(!is.null(import_fn(name = fn, pkg = pkg, error_on_fail = FALSE)),
failure_message = paste0("Function ", pkg, "::", fn, "() does not exist"))
failure_message = paste0("Function ", pkg, "::", fn, "() does not exist anymore"))
}
})