interpretation fixes

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 2.0.0.9033
-Date: 2023-07-10
+Version: 2.0.0.9034
+Date: 2023-07-11
 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 2.0.0.9033
+# AMR 2.0.0.9034
 
 ## New
 * Clinical breakpoints and intrinsic resistance of EUCAST 2023 and CLSI 2023 have been added for `as.sir()`. EUCAST 2023 (v13.0) is now the new default guideline for all MIC and disks diffusion interpretations
@@ -15,7 +15,7 @@
 ## Changed
 * Updated algorithm of `as.mo()` by giving more weight to fungi
 * `mo_rank()` now returns `NA` for 'unknown' microorganisms (`B_ANAER`, `B_ANAER-NEG`, `B_ANAER-POS`, `B_GRAMN`, `B_GRAMP`, `F_FUNGUS`, `F_YEAST`, and `UNKNOWN`)
-* When printing MO codes in a tibble, a mouse-hover now shows the full name of the microorganism
+* When printing microorganism or antibiotic codes in a tibble, a mouse-hover now shows the full name of the code
 * Plots for MIC and disk diffusion values:
   * Now have settable arguments for breakpoint type and PK/PD, like `as.sir()`
   * Will now contain the name of the guideline table in the subtitle of the plot

R/aa_helper_functions.R

@@ -501,8 +501,19 @@ word_wrap <- function(...,
   }
 
   # format backticks
+  if (pkg_is_available("cli") &&
+      tryCatch(getExportedValue("isAvailable", ns = asNamespace("rstudioapi"))(), error = function(e) return(FALSE))) {
+    parts <- strsplit(msg, "`", fixed = TRUE)[[1]]
+    cmds <- parts %in% paste0(ls(envir = asNamespace("AMR")), "()")
+    # functions with a dot are not allowed: https://github.com/rstudio/rstudio/issues/11273#issuecomment-1156193252
+    parts[cmds & parts %like% "[.]"] <- font_url(url = paste0("ide:help:AMR::", gsub("()", "", parts[cmds & parts %like% "[.]"], fixed = TRUE)),
+                                                 txt = parts[cmds & parts %like% "[.]"])
+    parts[cmds & parts %unlike% "[.]"] <- font_url(url = paste0("ide:run:AMR::", parts[cmds & parts %unlike% "[.]"]),
+                                                   txt = parts[cmds & parts %unlike% "[.]"])
+    msg <- paste0(parts, collapse = "`")
+  }
   msg <- gsub("`(.+?)`", font_grey_bg("\\1"), msg)
-
+  
   # clean introduced whitespace between fullstops
   msg <- gsub("[.] +[.]", "..", msg)
   # remove extra space that was introduced (e.g. "Smith et al. , 2022")

R/ab.R

@@ -545,6 +545,13 @@ is.ab <- function(x) {
 pillar_shaft.ab <- function(x, ...) {
   out <- trimws(format(x))
   out[is.na(x)] <- font_na(NA)
+  
+  # add the names to the drugs as mouse-over!
+  if (tryCatch(isTRUE(getExportedValue("ansi_has_hyperlink_support", ns = asNamespace("cli"))()), error = function(e) FALSE)) {
+    out[!is.na(x)] <- font_url(url = ab_name(x[!is.na(x)], language = NULL),
+                               txt = out[!is.na(x)])
+  }
+  
   create_pillar_column(out, align = "left", min_width = 4)
 }
 

R/sir.R

@@ -741,6 +741,10 @@ as_sir_method <- function(method_short,
   check_reference_data(reference_data, .call_depth = -2)
   meet_criteria(breakpoint_type, allow_class = "character", is_in = reference_data$type, has_length = 1, .call_depth = -2)
 
+  if (message_not_thrown_before("as.sir", "sir_interpretation_history")) {
+    message_("Run `sir_interpretation_history()` afterwards to retrieve a logbook with all the details of the breakpoint interpretations.\n\n")  
+  }
+  
   # for dplyr's across()
   cur_column_dplyr <- import_fn("cur_column", "dplyr", error_on_fail = FALSE)
   if (!is.null(cur_column_dplyr) && tryCatch(is.data.frame(get_current_data("ab", call = 0)), error = function(e) FALSE)) {
@@ -879,7 +883,7 @@ as_sir_method <- function(method_short,
   rise_warning <- FALSE
   rise_note <- FALSE
   method_coerced <- toupper(method)
-  ab_coerced <- ab
+  ab_coerced <- as.ab(ab)
   
   if (identical(reference_data, AMR::clinical_breakpoints)) {
     breakpoints <- reference_data %pm>%
@@ -945,10 +949,10 @@ as_sir_method <- function(method_short,
     new_sir <- rep(NA_sir_, length(rows))
 
     # find different mo properties, as fast as possible
-    mo_current_genus <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$genus[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$genus)]
-    mo_current_family <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$family[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$family)]
-    mo_current_order <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$order[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$order)]
-    mo_current_class <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$class[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$class)]
+    mo_current_genus <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$genus[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$fullname)]
+    mo_current_family <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$family[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$fullname)]
+    mo_current_order <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$order[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$fullname)]
+    mo_current_class <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$class[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$fullname)]
     mo_current_rank <- AMR_env$MO_lookup$rank[match(mo_current, AMR_env$MO_lookup$mo)]
     mo_current_name <- AMR_env$MO_lookup$fullname[match(mo_current, AMR_env$MO_lookup$mo)]
     if (mo_current %in% AMR::microorganisms.groups$mo) {
@@ -1064,17 +1068,17 @@ as_sir_method <- function(method_short,
         data.frame(
           datetime = rep(Sys.time(), length(rows)),
           index = rows,
-          ab_input = rep(ab.bak, length(rows)),
-          ab_guideline = rep(ab_coerced, length(rows)),
-          mo_input = rep(mo.bak[match(mo_current, df$mo)][1], length(rows)),
-          mo_guideline = rep(breakpoints_current[, "mo", drop = TRUE], length(rows)),
+          ab_user = rep(ab.bak, length(rows)),
+          mo_user = rep(mo.bak[match(mo_current, df$mo)][1], length(rows)),
+          ab = rep(ab_coerced, length(rows)),
+          mo = rep(breakpoints_current[, "mo", drop = TRUE], length(rows)),
+          input = as.double(values),
+          outcome = as.sir(new_sir),
+          method = rep(method_coerced, length(rows)),
+          breakpoint_S_R = rep(paste0(breakpoints_current[, "breakpoint_S", drop = TRUE], "-", breakpoints_current[, "breakpoint_R", drop = TRUE]), length(rows)),
           guideline = rep(guideline_coerced, length(rows)),
           ref_table = rep(breakpoints_current[, "ref_tbl", drop = TRUE], length(rows)),
           uti = rep(breakpoints_current[, "uti", drop = TRUE], length(rows)),
-          method = rep(method_coerced, length(rows)),
-          input = as.double(values),
-          outcome = as.sir(new_sir),
-          breakpoint_S_R = rep(paste0(breakpoints_current[, "breakpoint_S", drop = TRUE], "-", breakpoints_current[, "breakpoint_R", drop = TRUE]), length(rows)),
           stringsAsFactors = FALSE
         )
       )
@@ -1114,8 +1118,6 @@ sir_interpretation_history <- function(clean = FALSE) {
     message_("No results to return. Run `as.sir()` on MIC values or disk diffusion zones first to see a 'logbook' data set here.")
     return(invisible(NULL))
   }
-  out$ab_guideline <- as.ab(out$ab_guideline)
-  out$mo_guideline <- as.mo(out$mo_guideline)
   out$outcome <- as.sir(out$outcome)
   # keep stored for next use
   if (isTRUE(clean)) {

R/zzz.R

@@ -58,18 +58,19 @@ AMR_env$av_previously_coerced <- data.frame(
 AMR_env$sir_interpretation_history <- data.frame(
   datetime = Sys.time()[0],
   index = integer(0),
-  ab_input = character(0),
-  ab_guideline = set_clean_class(character(0), c("ab", "character")),
-  mo_input = character(0),
-  mo_guideline = set_clean_class(character(0), c("mo", "character")),
-  guideline = character(0),
-  ref_table = character(0),
-  method = character(0),
+  ab_user = character(0),
+  mo_user = character(0),
+  ab = set_clean_class(character(0), c("ab", "character")),
+  mo = set_clean_class(character(0), c("mo", "character")),
   input = double(0),
   outcome = NA_sir_[0],
+  method = character(0),
   breakpoint_S_R = character(0),
+  guideline = character(0),
+  ref_table = character(0),
   stringsAsFactors = FALSE
 )
+
 AMR_env$custom_ab_codes <- character(0)
 AMR_env$custom_mo_codes <- character(0)
 AMR_env$is_dark_theme <- NULL

inst/tinytest/test-data.R

@@ -38,6 +38,8 @@ expect_identical(class(antibiotics$ab), c("ab", "character"))
 # check cross table reference
 expect_true(all(microorganisms.codes$mo %in% microorganisms$mo))
 expect_true(all(example_isolates$mo %in% microorganisms$mo))
+expect_true(all(microorganisms.groups$mo %in% microorganisms$mo))
+expect_true(all(microorganisms.groups$mo_group %in% microorganisms$mo))
 expect_true(all(clinical_breakpoints$mo %in% microorganisms$mo))
 expect_true(all(clinical_breakpoints$ab %in% antibiotics$ab))
 expect_true(all(intrinsic_resistant$mo %in% microorganisms$mo))

inst/tinytest/test-sir.R

@@ -108,6 +108,18 @@ if (AMR:::pkg_is_available("skimr", min_version = "2.0.0", also_load = TRUE)) {
 
 expect_equal(as.sir(c("", "-", NA, "NULL")), c(NA_sir_, NA_sir_, NA_sir_, NA_sir_))
 
+mics <- as.mic(2 ^ c(-2:5)) # 0.25 to 32 in factors of 2
+expect_identical(as.character(as.sir(mics, mo = "Enterobacterales", ab = "AMC", guideline = "EUCAST 2022",
+                                     uti = FALSE, include_PKPD = FALSE)),
+                 c("S", "S", "S", "S", "S", "S", "R", "R"))
+expect_identical(as.character(as.sir(mics, mo = "Enterobacterales", ab = "AMC", guideline = "EUCAST 2022",
+                                     uti = TRUE, include_PKPD = FALSE)),
+                 c("S", "S", "S", "S", "S", "S", "S", "S"))
+expect_identical(as.character(as.sir(mics, mo = "Escherichia coli", ab = "AMC", guideline = "EUCAST 2022",
+                                     uti = FALSE, include_PKPD = FALSE)),
+                 c("S", "S", "S", "S", "S", "S", "R", "R"))
+
+
 # S. pneumoniae/ampicillin in EUCAST 2020: 0.5-2 ug/ml (R is only > 2)
 expect_equal(suppressMessages(
   as.character(

man/AMR.Rd

@@ -32,7 +32,7 @@ The \code{AMR} package is a \href{https://msberends.github.io/AMR/#copyright}{fr
 
 This work was published in the Journal of Statistical Software (Volume 104(3); \doi{jss.v104.i03}) and formed the basis of two PhD theses (\doi{10.33612/diss.177417131} and \doi{10.33612/diss.192486375}).
 
-After installing this package, R knows \href{https://msberends.github.io/AMR/reference/microorganisms.html}{\strong{~52 000 microorganisms}} (updated december 2022) and all \href{https://msberends.github.io/AMR/reference/antibiotics.html}{\strong{~600 antibiotic, antimycotic and antiviral drugs}} by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). \strong{It was designed to work in any setting, including those with very limited resources}. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the \href{https://www.rug.nl}{University of Groningen}, in collaboration with non-profit organisations \href{https://www.certe.nl}{Certe Medical Diagnostics and Advice Foundation} and \href{https://www.umcg.nl}{University Medical Center Groningen}.
+After installing this package, R knows \href{https://msberends.github.io/AMR/reference/microorganisms.html}{\strong{~52 000 microorganisms}} (updated December 2022) and all \href{https://msberends.github.io/AMR/reference/antibiotics.html}{\strong{~600 antibiotic, antimycotic and antiviral drugs}} by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). \strong{It was designed to work in any setting, including those with very limited resources}. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the \href{https://www.rug.nl}{University of Groningen}, in collaboration with non-profit organisations \href{https://www.certe.nl}{Certe Medical Diagnostics and Advice Foundation} and \href{https://www.umcg.nl}{University Medical Center Groningen}.
 
 The \code{AMR} package is available in English, Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
 }