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extend vctrs support
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parent
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Package: AMR
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Version: 1.8.2.9039
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Date: 2022-10-30
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Version: 1.8.2.9040
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Date: 2022-10-31
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Title: Antimicrobial Resistance Data Analysis
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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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data analysis and to work with microbial and antimicrobial properties by
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33
NEWS.md
33
NEWS.md
@ -1,4 +1,4 @@
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# AMR 1.8.2.9039
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# AMR 1.8.2.9040
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This version will eventually become v2.0! We're happy to reach a new major milestone soon!
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@ -15,32 +15,35 @@ This version will eventually become v2.0! We're happy to reach a new major miles
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### New
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* EUCAST 2022 and CLSI 2022 guidelines have been added for `as.rsi()`. EUCAST 2022 is now the new default guideline for all MIC and disks diffusion interpretations.
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* Support for the following languages: Chinese, Greek, Japanese, Polish, Turkish and Ukrainian. We are very grateful for the valuable input by our colleagues from other countries. The `AMR` package is now available in 16 languages. The automatic language determination will give a note at start-up on systems in supported languages.
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* All new algorithm for `as.mo()` (and thus all `mo_*()` functions) while still following our original set-up as described in our paper (DOI 10.18637/jss.v104.i03).
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* A new argument `keep_synonyms` allows to *not* correct for updated taxonomy, in favour of the now deleted argument `allow_uncertain`
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* It has increased tremendously in speed and returns generally more consequent results
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* Sequential coercion is now extremely fast as results are stored to the package environment, although coercion of unknown values must be run once per session. Previous results can be reset/removed with the new `mo_reset_session()` function.
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* Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net)
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* Function `rsi_confidence_interval()` to add confidence intervals in AMR calculation. This is also included in `rsi_df()` and `proportion_df()`
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* Function `mean_amr_distance()` to calculate the mean AMR distance. The mean AMR distance is a normalised numeric value to compare AMR test results and can help to identify similar isolates, without comparing antibiograms by hand.
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* Function `rsi_interpretation_history()` to view the history of previous runs of `as.rsi()`. This returns a 'logbook' with the selected guideline, reference table and specific interpretation of each row in a data set on which `as.rsi()` was run.
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* Function `mo_current()` to get the currently valid taxonomic name of a microorganism
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* Function `add_custom_antimicrobials()` to add custom antimicrobial codes and names to the `AMR` package
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* Support for `data.frame`-enhancing R packages, more specifically: `data.table::data.table`, `janitor::tabyl`, `tibble::tibble`, and `tsibble::tsibble`. AMR package functions that have a data set as output (such as `rsi_df()` and `bug_drug_combinations()`), will now return the same data type as the input.
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* All data sets in this package are now exported as `tibble`, instead of base R `data.frame`s. Older R versions are still supported.
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* Support for the following languages: Chinese, Greek, Japanese, Polish, Turkish and Ukrainian. We are very grateful for the valuable input by our colleagues from other countries. The `AMR` package is now available in 16 languages. The automatic language determination will give a note at start-up on systems in supported languages.
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* Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info [in this article on our website](https://msberends.github.io/AMR/articles/datasets.html).
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* Support for using antibiotic selectors in scoped `dplyr` verbs (with or without `vars()`), such as in: `... %>% summarise_at(aminoglycosides(), resistance)`, see `resistance()`
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* Support for antimicrobial interpretation of anaerobic bacteria, by adding a 'placeholder' code `B_ANAER` to the `microorganisms` data set and add the breakpoints of anaerobics to the `rsi_interpretation` data set, which is used by `as.rsi()` when interpreting MIC and disk diffusion values
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* Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net)
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* New functions!
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* Function `rsi_confidence_interval()` to add confidence intervals in AMR calculation. This is also included in `rsi_df()` and `proportion_df()`
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* Function `mean_amr_distance()` to calculate the mean AMR distance. The mean AMR distance is a normalised numeric value to compare AMR test results and can help to identify similar isolates, without comparing antibiograms by hand.
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* Function `rsi_interpretation_history()` to view the history of previous runs of `as.rsi()`. This returns a 'logbook' with the selected guideline, reference table and specific interpretation of each row in a data set on which `as.rsi()` was run.
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* Function `mo_current()` to get the currently valid taxonomic name of a microorganism
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* Function `add_custom_antimicrobials()` to add custom antimicrobial codes and names to the `AMR` package
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* New and updated entries for the `antibiotics` data set
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* The following 20 antibiotics have been added (also includes the [new J01RA ATC group](https://www.whocc.no/atc_ddd_index/?code=J01RA&showdescription=no)): azithromycin/fluconazole/secnidazole (AFC), cefepime/amikacin (CFA), cefixime/ornidazole (CEO), ceftriaxone/beta-lactamase inhibitor (CEB), ciprofloxacin/metronidazole (CIM), ciprofloxacin/ornidazole (CIO), ciprofloxacin/tinidazole (CIT), furazidin (FUR), isoniazid/sulfamethoxazole/trimethoprim/pyridoxine (IST), lascufloxacin (LSC), levofloxacin/ornidazole (LEO), nemonoxacin (NEM), norfloxacin/metronidazole (NME), norfloxacin/tinidazole (NTI), ofloxacin/ornidazole (OOR), oteseconazole (OTE), rifampicin/ethambutol/isoniazid (REI), sarecycline (SRC), tetracycline/oleandomycin (TOL), and thioacetazone (TAT)
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* Added some missing ATC codes
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* Updated DDDs and PubChem Compound IDs
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* Updated some antibiotic name spelling, now used by WHOCC (such as cephalexin -> cefalexin, and phenethicillin -> pheneticillin)
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* Antibiotic code "CEI" for ceftolozane/tazobactam has been replaced with "CZT" to comply with EARS-Net and WHONET 2022. The old code will still work in all cases when using `as.ab()` or any of the `ab_*()` functions.
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* Support for antimicrobial interpretation of anaerobic bacteria, by adding a 'placeholder' code `B_ANAER` to the `microorganisms` data set and add the breakpoints of anaerobics to the `rsi_interpretation` data set, which is used by `as.rsi()` when interpreting MIC and disk diffusion values
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* Support for `data.frame`-enhancing R packages, more specifically: `data.table::data.table`, `janitor::tabyl`, `tibble::tibble`, and `tsibble::tsibble`. AMR package functions that have a data set as output (such as `rsi_df()` and `bug_drug_combinations()`), will now return the same data type as the input.
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* All data sets in this package are now exported as `tibble`, instead of base R `data.frame`s. Older R versions are still supported.
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* Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info [in this article on our website](https://msberends.github.io/AMR/articles/datasets.html).
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* Support for using antibiotic selectors in scoped `dplyr` verbs (with or without `vars()`), such as in: `... %>% summarise_at(aminoglycosides(), resistance)`, see `resistance()`
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### Changed
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* Fix for using `as.rsi()` on certain EUCAST breakpoints for MIC values
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* Fix for using `as.rsi()` on `NA` values (e.g. `as.rsi(as.disk(NA), ...)`)
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* Fix for using `as.rsi()` on drug-drug combinations with multiple breakpoints for different body sites
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* Fix for using `as.rsi()` on bug-drug combinations with multiple breakpoints for different body sites
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* Removed `as.integer()` for MIC values, since MIC are not integer values and running `table()` on MIC values consequently failed for not being able to retrieve the level position (as that's how normally `as.integer()` on `factor`s work)
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* `droplevels()` on MIC will now return a common `factor` at default and will lose the `mic` class. Use `droplevels(..., as.mic = TRUE)` to keep the `mic` class.
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* Small fix for using `ab_from_text()`
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@ -48,7 +51,7 @@ This version will eventually become v2.0! We're happy to reach a new major miles
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* Using any `random_*()` function (such as `random_mic()`) is now possible by directly calling the package without loading it first: `AMR::random_mic(10)`
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* Added *Toxoplasma gondii* (`P_TXPL_GOND`) to the `microorganisms` data set, together with its genus, family, and order
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* Changed value in column `prevalence` of the `microorganisms` data set from 3 to 2 for these genera: *Acholeplasma*, *Alistipes*, *Alloprevotella*, *Bergeyella*, *Borrelia*, *Brachyspira*, *Butyricimonas*, *Cetobacterium*, *Chlamydia*, *Chlamydophila*, *Deinococcus*, *Dysgonomonas*, *Elizabethkingia*, *Empedobacter*, *Haloarcula*, *Halobacterium*, *Halococcus*, *Myroides*, *Odoribacter*, *Ornithobacterium*, *Parabacteroides*, *Pedobacter*, *Phocaeicola*, *Porphyromonas*, *Riemerella*, *Sphingobacterium*, *Streptobacillus*, *Tenacibaculum*, *Terrimonas*, *Victivallis*, *Wautersiella*, *Weeksella*
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* Fix for using the form `df[carbapenems() == "R", ]` when using the latest `vctrs` package
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* Extended support for the `vctrs` package, used internally by the tidyverse. This allows to change values of class `mic`, `disk`, `rsi`, `mo` and `ab` in tibbles, and to use antibiotic selectors for selecting/filtering, e.g. `df[carbapenems() == "R", ]`
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* Fix for using `info = FALSE` in `mdro()`
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* For all interpretation guidelines using `as.rsi()` on amoxicillin, the rules for ampicillin will be used if amoxicillin rules are not available
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* Fix for using `ab_atc()` on non-existing ATC codes
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46
R/vctrs.R
46
R/vctrs.R
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y
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}
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vec_cast.character.ab <- function(x, to, ...) {
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unclass(x)
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as.character(x)
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}
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vec_cast.ab.character <- function(x, to, ...) {
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return_after_integrity_check(x, "antimicrobial code", as.character(AMR_env$AB_lookup$ab))
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}
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# S3: mo
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@ -75,7 +78,10 @@ vec_ptype2.mo.character <- function(x, y, ...) {
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y
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}
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vec_cast.character.mo <- function(x, to, ...) {
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unclass(x)
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as.character(x)
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}
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vec_cast.mo.character <- function(x, to, ...) {
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return_after_integrity_check(x, "microorganism code", as.character(AMR::microorganisms$mo))
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}
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# S3: disk
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@ -88,15 +94,49 @@ vec_ptype2.disk.integer <- function(x, y, ...) {
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vec_cast.integer.disk <- function(x, to, ...) {
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unclass(x)
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}
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vec_cast.disk.integer <- function(x, to, ...) {
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as.disk(x)
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}
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vec_cast.double.disk <- function(x, to, ...) {
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unclass(x)
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}
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vec_cast.disk.double <- function(x, to, ...) {
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as.disk(x)
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}
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vec_cast.character.disk <- function(x, to, ...) {
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unclass(x)
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}
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vec_cast.disk.character <- function(x, to, ...) {
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as.disk(x)
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}
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# S3: mic
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vec_cast.character.mic <- function(x, to, ...) {
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as.character(x)
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}
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vec_cast.double.mic <- function(x, to, ...) {
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# this calls as.double.mic()
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as.double(x)
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}
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vec_cast.mic.double <- function(x, to, ...) {
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as.mic(x)
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}
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vec_cast.mic.character <- function(x, to, ...) {
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as.mic(x)
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}
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vec_math.mic <- function(.fn, x, ...) {
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.fn(as.double(x), ...)
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}
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# S3: rsi
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vec_ptype2.character.rsi <- function(x, y, ...) {
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x
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}
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vec_ptype2.rsi.character <- function(x, y, ...) {
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y
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}
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vec_cast.character.rsi <- function(x, to, ...) {
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as.character(x)
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}
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vec_cast.rsi.character <- function(x, to, ...) {
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as.rsi(x)
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}
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38
R/zzz.R
38
R/zzz.R
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s3_register("ggplot2::fortify", "mic")
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s3_register("ggplot2::fortify", "disk")
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# Support vctrs package for use in e.g. dplyr verbs
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s3_register("vctrs::vec_ptype2", "ab.character")
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s3_register("vctrs::vec_ptype2", "character.ab")
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s3_register("vctrs::vec_cast", "character.ab")
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s3_register("vctrs::vec_ptype2", "mo.character")
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s3_register("vctrs::vec_ptype2", "character.mo")
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s3_register("vctrs::vec_cast", "character.mo")
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s3_register("vctrs::vec_ptype2", "ab_selector.character")
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# S3: ab_selector
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s3_register("vctrs::vec_ptype2", "character.ab_selector")
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s3_register("vctrs::vec_ptype2", "ab_selector.character")
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s3_register("vctrs::vec_cast", "character.ab_selector")
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s3_register("vctrs::vec_ptype2", "ab_selector_any_all.logical")
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# S3: ab_selector_any_all
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s3_register("vctrs::vec_ptype2", "logical.ab_selector_any_all")
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s3_register("vctrs::vec_ptype2", "ab_selector_any_all.logical")
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s3_register("vctrs::vec_cast", "logical.ab_selector_any_all")
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s3_register("vctrs::vec_ptype2", "disk.integer")
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# S3: ab
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s3_register("vctrs::vec_ptype2", "character.ab")
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s3_register("vctrs::vec_ptype2", "ab.character")
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s3_register("vctrs::vec_cast", "character.ab")
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s3_register("vctrs::vec_cast", "ab.character")
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# S3: mo
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s3_register("vctrs::vec_ptype2", "character.mo")
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s3_register("vctrs::vec_ptype2", "mo.character")
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s3_register("vctrs::vec_cast", "character.mo")
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s3_register("vctrs::vec_cast", "mo.character")
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# S3: disk
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s3_register("vctrs::vec_ptype2", "integer.disk")
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s3_register("vctrs::vec_ptype2", "disk.integer")
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s3_register("vctrs::vec_cast", "integer.disk")
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s3_register("vctrs::vec_cast", "disk.integer")
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s3_register("vctrs::vec_cast", "double.disk")
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s3_register("vctrs::vec_cast", "disk.double")
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s3_register("vctrs::vec_cast", "character.disk")
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s3_register("vctrs::vec_cast", "disk.character")
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# S3: mic
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s3_register("vctrs::vec_cast", "character.mic")
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s3_register("vctrs::vec_cast", "double.mic")
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s3_register("vctrs::vec_cast", "mic.character")
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s3_register("vctrs::vec_cast", "mic.double")
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s3_register("vctrs::vec_math", "mic")
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# S3: rsi
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s3_register("vctrs::vec_ptype2", "character.rsi")
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s3_register("vctrs::vec_ptype2", "rsi.character")
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s3_register("vctrs::vec_cast", "character.rsi")
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s3_register("vctrs::vec_cast", "rsi.character")
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# if mo source exists, fire it up (see mo_source())
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if (tryCatch(file.exists(getOption("AMR_mo_source", "~/mo_source.rds")), error = function(e) FALSE)) {
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Binary file not shown.
53
inst/tinytest/test-vctrs.R
Executable file
53
inst/tinytest/test-vctrs.R
Executable file
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# ==================================================================== #
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# TITLE #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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# #
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# SOURCE #
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# https://github.com/msberends/AMR #
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# #
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# CITE AS #
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# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
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# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
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# Data. Journal of Statistical Software, 104(3), 1-31. #
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# doi:10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen, the Netherlands, in #
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# collaboration with non-profit organisations Certe Medical #
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# Diagnostics & Advice, and University Medical Center Groningen. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
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# Visit our website for the full manual and a complete tutorial about #
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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# extra tests for {vctrs} pkg support
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if (pkg_is_available("dplyr", also_load = FALSE)) {
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test <- dplyr::tibble(ab = as.ab("CIP"),
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mo = as.mo("Escherichia coli"),
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mic = as.mic(2),
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disk = as.disk(20),
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rsi = as.rsi("S"))
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check1 <- lapply(test, class)
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test[1, "ab"] <- "GEN"
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test[1, "mo"] <- "B_KLBSL_PNMN"
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test[1, "mic"] <- ">=32"
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test[1, "mic"] <- 32
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test[1, "disk"] <- "35"
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test[1, "disk"] <- 25
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test[1, "disk"] <- 26L
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test[1, "rsi"] <- "R"
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check2 <- lapply(test, class)
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expect_identical(check1, check2)
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test <- dplyr::tibble(cipro = as.rsi("S"),
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variable = "test")
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expect_equal(nrow(test[quinolones() == "S", ]), 1)
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expect_equal(nrow(test[quinolones() == "R", ]), 0)
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}
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