extend vctrs support

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 1.8.2.9039
+Version: 1.8.2.9040
-Date: 2022-10-30
+Date: 2022-10-31
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)
   data analysis and to work with microbial and antimicrobial properties by

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 1.8.2.9039
+# AMR 1.8.2.9040
 
 This version will eventually become v2.0! We're happy to reach a new major milestone soon!
 
@@ -15,32 +15,35 @@ This version will eventually become v2.0! We're happy to reach a new major miles
 
 ### New
 * EUCAST 2022 and CLSI 2022 guidelines have been added for `as.rsi()`. EUCAST 2022 is now the new default guideline for all MIC and disks diffusion interpretations.
+* Support for 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.
 * 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).
   * A new argument `keep_synonyms` allows to *not* correct for updated taxonomy, in favour of the now deleted argument `allow_uncertain`
   * It has increased tremendously in speed and returns generally more consequent results
   * 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.
-* Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net) 
+  * Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net)
-* Function `rsi_confidence_interval()` to add confidence intervals in AMR calculation. This is also included in `rsi_df()` and `proportion_df()`
+  
-* 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.
+* New functions!
-* 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.
+  * Function `rsi_confidence_interval()` to add confidence intervals in AMR calculation. This is also included in `rsi_df()` and `proportion_df()`
-* Function `mo_current()` to get the currently valid taxonomic name of a microorganism
+  * 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.
-* Function `add_custom_antimicrobials()` to add custom antimicrobial codes and names to the `AMR` package
+  * 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.
-* 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.
+  * Function `mo_current()` to get the currently valid taxonomic name of a microorganism
-* All data sets in this package are now exported as `tibble`, instead of base R `data.frame`s. Older R versions are still supported.
+  * Function `add_custom_antimicrobials()` to add custom antimicrobial codes and names to the `AMR` package
-* 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.
-* Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info [in this article on our website](https://msberends.github.io/AMR/articles/datasets.html).
-* Support for using antibiotic selectors in scoped `dplyr` verbs (with or without `vars()`), such as in: `... %>% summarise_at(aminoglycosides(), resistance)`, see `resistance()`
-* 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
 * New and updated entries for the `antibiotics` data set
   * 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)
   * Added some missing ATC codes
   * Updated DDDs and PubChem Compound IDs
   * Updated some antibiotic name spelling, now used by WHOCC (such as cephalexin -> cefalexin, and phenethicillin -> pheneticillin)
+  * 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.
+  * 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
+* 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.
+* All data sets in this package are now exported as `tibble`, instead of base R `data.frame`s. Older R versions are still supported.
+* Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info [in this article on our website](https://msberends.github.io/AMR/articles/datasets.html).
+* Support for using antibiotic selectors in scoped `dplyr` verbs (with or without `vars()`), such as in: `... %>% summarise_at(aminoglycosides(), resistance)`, see `resistance()`
 
 ### Changed
 * Fix for using `as.rsi()` on certain EUCAST breakpoints for MIC values
 * Fix for using `as.rsi()` on `NA` values (e.g. `as.rsi(as.disk(NA), ...)`)
-* Fix for using `as.rsi()` on drug-drug combinations with multiple breakpoints for different body sites
+* Fix for using `as.rsi()` on bug-drug combinations with multiple breakpoints for different body sites
 * Removed `as.integer()` for MIC values, since MIC are not integer values and running `table()` on MIC values  consequently failed for not being able to retrieve the level position (as that's how normally `as.integer()` on `factor`s work)
 * `droplevels()` on MIC will now return a common `factor` at default and will lose the `mic` class. Use `droplevels(..., as.mic = TRUE)` to keep the `mic` class.
 * Small fix for using `ab_from_text()`
@@ -48,7 +51,7 @@ This version will eventually become v2.0! We're happy to reach a new major miles
 * Using any `random_*()` function (such as `random_mic()`) is now possible by directly calling the package without loading it first: `AMR::random_mic(10)`
 * Added *Toxoplasma gondii* (`P_TXPL_GOND`) to the `microorganisms` data set, together with its genus, family, and order
 * Changed value in column `prevalence` of the `microorganisms` data set from 3 to 2 for these genera: *Acholeplasma*, *Alistipes*, *Alloprevotella*, *Bergeyella*, *Borrelia*, *Brachyspira*, *Butyricimonas*, *Cetobacterium*, *Chlamydia*, *Chlamydophila*, *Deinococcus*, *Dysgonomonas*, *Elizabethkingia*, *Empedobacter*, *Haloarcula*, *Halobacterium*, *Halococcus*, *Myroides*, *Odoribacter*, *Ornithobacterium*, *Parabacteroides*, *Pedobacter*, *Phocaeicola*, *Porphyromonas*, *Riemerella*, *Sphingobacterium*, *Streptobacillus*, *Tenacibaculum*, *Terrimonas*, *Victivallis*, *Wautersiella*, *Weeksella*
-* Fix for using the form `df[carbapenems() == "R", ]` when using the latest `vctrs` package
+* 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", ]`
 * Fix for using `info = FALSE` in `mdro()`
 * For all interpretation guidelines using `as.rsi()` on amoxicillin, the rules for ampicillin will be used if amoxicillin rules are not available
 * Fix for using `ab_atc()` on non-existing ATC codes

R/vctrs.R

@@ -64,7 +64,10 @@ vec_ptype2.ab.character <- function(x, y, ...) {
   y
 }
 vec_cast.character.ab <- function(x, to, ...) {
-  unclass(x)
+  as.character(x)
+}
+vec_cast.ab.character <- function(x, to, ...) {
+  return_after_integrity_check(x, "antimicrobial code", as.character(AMR_env$AB_lookup$ab))
 }
 
 # S3: mo
@@ -75,7 +78,10 @@ vec_ptype2.mo.character <- function(x, y, ...) {
   y
 }
 vec_cast.character.mo <- function(x, to, ...) {
-  unclass(x)
+  as.character(x)
+}
+vec_cast.mo.character <- function(x, to, ...) {
+  return_after_integrity_check(x, "microorganism code", as.character(AMR::microorganisms$mo))
 }
 
 # S3: disk
@@ -88,15 +94,49 @@ vec_ptype2.disk.integer <- function(x, y, ...) {
 vec_cast.integer.disk <- function(x, to, ...) {
   unclass(x)
 }
+vec_cast.disk.integer <- function(x, to, ...) {
+  as.disk(x)
+}
+vec_cast.double.disk <- function(x, to, ...) {
+  unclass(x)
+}
+vec_cast.disk.double <- function(x, to, ...) {
+  as.disk(x)
+}
+vec_cast.character.disk <- function(x, to, ...) {
+  unclass(x)
+}
+vec_cast.disk.character <- function(x, to, ...) {
+  as.disk(x)
+}
 
 # S3: mic
 vec_cast.character.mic <- function(x, to, ...) {
   as.character(x)
 }
 vec_cast.double.mic <- function(x, to, ...) {
-  # this calls as.double.mic()
   as.double(x)
 }
+vec_cast.mic.double <- function(x, to, ...) {
+  as.mic(x)
+}
+vec_cast.mic.character <- function(x, to, ...) {
+  as.mic(x)
+}
 vec_math.mic <- function(.fn, x, ...) {
   .fn(as.double(x), ...)
 }
+
+# S3: rsi
+vec_ptype2.character.rsi <- function(x, y, ...) {
+  x
+}
+vec_ptype2.rsi.character <- function(x, y, ...) {
+  y
+}
+vec_cast.character.rsi <- function(x, to, ...) {
+  as.character(x)
+}
+vec_cast.rsi.character <- function(x, to, ...) {
+  as.rsi(x)
+}

R/zzz.R

@@ -116,24 +116,44 @@ if (utf8_supported && !is_latex) {
   s3_register("ggplot2::fortify", "mic")
   s3_register("ggplot2::fortify", "disk")
   # Support vctrs package for use in e.g. dplyr verbs
-  s3_register("vctrs::vec_ptype2", "ab.character")
+  # S3: ab_selector
-  s3_register("vctrs::vec_ptype2", "character.ab")
-  s3_register("vctrs::vec_cast", "character.ab")
-  s3_register("vctrs::vec_ptype2", "mo.character")
-  s3_register("vctrs::vec_ptype2", "character.mo")
-  s3_register("vctrs::vec_cast", "character.mo")
-  s3_register("vctrs::vec_ptype2", "ab_selector.character")
   s3_register("vctrs::vec_ptype2", "character.ab_selector")
+  s3_register("vctrs::vec_ptype2", "ab_selector.character")
   s3_register("vctrs::vec_cast", "character.ab_selector")
-  s3_register("vctrs::vec_ptype2", "ab_selector_any_all.logical")
+  # S3: ab_selector_any_all
   s3_register("vctrs::vec_ptype2", "logical.ab_selector_any_all")
+  s3_register("vctrs::vec_ptype2", "ab_selector_any_all.logical")
   s3_register("vctrs::vec_cast", "logical.ab_selector_any_all")
-  s3_register("vctrs::vec_ptype2", "disk.integer")
+  # S3: ab
+  s3_register("vctrs::vec_ptype2", "character.ab")
+  s3_register("vctrs::vec_ptype2", "ab.character")
+  s3_register("vctrs::vec_cast", "character.ab")
+  s3_register("vctrs::vec_cast", "ab.character")
+  # S3: mo
+  s3_register("vctrs::vec_ptype2", "character.mo")
+  s3_register("vctrs::vec_ptype2", "mo.character")
+  s3_register("vctrs::vec_cast", "character.mo")
+  s3_register("vctrs::vec_cast", "mo.character")
+  # S3: disk
   s3_register("vctrs::vec_ptype2", "integer.disk")
+  s3_register("vctrs::vec_ptype2", "disk.integer")
   s3_register("vctrs::vec_cast", "integer.disk")
+  s3_register("vctrs::vec_cast", "disk.integer")
+  s3_register("vctrs::vec_cast", "double.disk")
+  s3_register("vctrs::vec_cast", "disk.double")
+  s3_register("vctrs::vec_cast", "character.disk")
+  s3_register("vctrs::vec_cast", "disk.character")
+  # S3: mic
   s3_register("vctrs::vec_cast", "character.mic")
   s3_register("vctrs::vec_cast", "double.mic")
+  s3_register("vctrs::vec_cast", "mic.character")
+  s3_register("vctrs::vec_cast", "mic.double")
   s3_register("vctrs::vec_math", "mic")
+  # S3: rsi
+  s3_register("vctrs::vec_ptype2", "character.rsi")
+  s3_register("vctrs::vec_ptype2", "rsi.character")
+  s3_register("vctrs::vec_cast", "character.rsi")
+  s3_register("vctrs::vec_cast", "rsi.character")
 
   # if mo source exists, fire it up (see mo_source())
   if (tryCatch(file.exists(getOption("AMR_mo_source", "~/mo_source.rds")), error = function(e) FALSE)) {

inst/tinytest/test-vctrs.R

@@ -0,0 +1,53 @@
+# ==================================================================== #
+# TITLE                                                                #
+# AMR: An R Package for Working with Antimicrobial Resistance Data     #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# CITE AS                                                              #
+# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C    #
+# (2022). AMR: An R Package for Working with Antimicrobial Resistance  #
+# Data. Journal of Statistical Software, 104(3), 1-31.                 #
+# doi:10.18637/jss.v104.i03                                            #
+#                                                                      #
+# Developed at the University of Groningen, the Netherlands, in        #
+# collaboration with non-profit organisations Certe Medical            #
+# Diagnostics & Advice, and University Medical Center Groningen.       #
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+# extra tests for {vctrs} pkg support
+if (pkg_is_available("dplyr", also_load = FALSE)) {
+  test <- dplyr::tibble(ab = as.ab("CIP"),
+                        mo = as.mo("Escherichia coli"),
+                        mic = as.mic(2),
+                        disk = as.disk(20),
+                        rsi = as.rsi("S"))
+  check1 <- lapply(test, class)
+  test[1, "ab"] <- "GEN"
+  test[1, "mo"] <- "B_KLBSL_PNMN"
+  test[1, "mic"] <- ">=32"
+  test[1, "mic"] <- 32
+  test[1, "disk"] <- "35"
+  test[1, "disk"] <- 25
+  test[1, "disk"] <- 26L
+  test[1, "rsi"] <- "R"
+  check2 <- lapply(test, class)
+  expect_identical(check1, check2)
+  
+  test <- dplyr::tibble(cipro = as.rsi("S"),
+                        variable = "test")
+  expect_equal(nrow(test[quinolones() == "S", ]), 1)
+  expect_equal(nrow(test[quinolones() == "R", ]), 0)
+}