(v2.1.1.9112) unit test

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: AMR
-Version: 2.1.1.9111
+Version: 2.1.1.9112
 Date: 2024-12-06
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 2.1.1.9111
+# AMR 2.1.1.9112
 
 *(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using [the instructions here](https://msberends.github.io/AMR/#latest-development-version).)*
 

PythonPackage/AMR/AMR.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: AMR
-Version: 2.1.1.9111
+Version: 2.1.1.9112
 Summary: A Python wrapper for the AMR R package
 Home-page: https://github.com/msberends/AMR
 Author: Dr. Matthijs Berends

PythonPackage/AMR/setup.py

@@ -2,7 +2,7 @@ from setuptools import setup, find_packages
 
 setup(
     name='AMR',
-    version='2.1.1.9111',
+    version='2.1.1.9112',
     packages=find_packages(),
     install_requires=[
         'rpy2',

R/ab_selectors.R

@@ -71,7 +71,7 @@
 #' 
 #' # you can combine selectors like you are used with tidyverse
 #' # e.g., for betalactams, but not the ones with an enzyme inhibitor:
-#' example_isolates |> select(betalactams(), -betalactams_with_inhibitor())
+#' example_isolates %>% select(betalactams(), -betalactams_with_inhibitor())
 #' 
 #' # select only antibiotic columns with DDDs for oral treatment
 #' example_isolates %>% select(administrable_per_os())

R/sir.R

@@ -1658,15 +1658,16 @@ get_skimmers.sir <- function(column) {
 print.sir <- function(x, ...) {
   x_name <- deparse(substitute(x))
   cat("Class 'sir'\n")
-  if (!is.null(attributes(x)$guideline) && !all(is.na(attributes(x)$guideline))) {
-    cat(font_blue(word_wrap("These values were interpreted using ",
-                            font_bold(vector_and(attributes(x)$guideline, quotes = FALSE)),
-                            " based on ",
-                            vector_and(attributes(x)$method, quotes = FALSE),
-                            " values. ",
-                            "Use `sir_interpretation_history(", x_name, ")` to return a full logbook.")))
-    cat("\n")
-  }
+  # TODO for #170
+  # if (!is.null(attributes(x)$guideline) && !all(is.na(attributes(x)$guideline))) {
+  #   cat(font_blue(word_wrap("These values were interpreted using ",
+  #                           font_bold(vector_and(attributes(x)$guideline, quotes = FALSE)),
+  #                           " based on ",
+  #                           vector_and(attributes(x)$method, quotes = FALSE),
+  #                           " values. ",
+  #                           "Use `sir_interpretation_history(", x_name, ")` to return a full logbook.")))
+  #   cat("\n")
+  # }
   print(as.character(x), quote = FALSE)
 }
 
@@ -1749,23 +1750,25 @@ summary.sir <- function(object, ...) {
 c.sir <- function(...) {
   lst <- list(...)
   
-  guideline <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$guideline %or% NA_character_)
-  mo <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$mo %or% NA_character_)
-  ab <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ab %or% NA_character_)
-  method <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$method %or% NA_character_)
-  ref_tbl <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_tbl %or% NA_character_)
-  ref_breakpoints <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_breakpoints %or% NA_character_)
+  # TODO for #170
+  # guideline <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$guideline %or% NA_character_)
+  # mo <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$mo %or% NA_character_)
+  # ab <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ab %or% NA_character_)
+  # method <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$method %or% NA_character_)
+  # ref_tbl <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_tbl %or% NA_character_)
+  # ref_breakpoints <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_breakpoints %or% NA_character_)
   
   out <- as.sir(unlist(lapply(list(...), as.character)))
   
-  if (!all(is.na(guideline))) {
-    attributes(out)$guideline <- guideline
-    attributes(out)$mo <- mo
-    attributes(out)$ab <- ab
-    attributes(out)$method <- method
-    attributes(out)$ref_tbl <- ref_tbl
-    attributes(out)$ref_breakpoints <- ref_breakpoints
-  }
+  # TODO for #170
+  # if (!all(is.na(guideline))) {
+  #   attributes(out)$guideline <- guideline
+  #   attributes(out)$mo <- mo
+  #   attributes(out)$ab <- ab
+  #   attributes(out)$method <- method
+  #   attributes(out)$ref_tbl <- ref_tbl
+  #   attributes(out)$ref_breakpoints <- ref_breakpoints
+  # }
   
   out
 }

data-raw/gpt_training_text_v2.1.1.9112.txt

@@ -1,5 +1,5 @@
 This files contains all context you must know about the AMR package for R.
-First and foremost, you are trained on version 2.1.1.9111. Remember this whenever someone asks which AMR package version you’re at.
+First and foremost, you are trained on version 2.1.1.9112. Remember this whenever someone asks which AMR package version you’re at.
 --------------------------------
 
 THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'NAMESPACE':
@@ -2130,7 +2130,7 @@ example_isolates \%>\% select(mo, aminoglycosides())
 
 # you can combine selectors like you are used with tidyverse
 # e.g., for betalactams, but not the ones with an enzyme inhibitor:
-example_isolates |> select(betalactams(), -betalactams_with_inhibitor())
+example_isolates \%>\% select(betalactams(), -betalactams_with_inhibitor())
 
 # select only antibiotic columns with DDDs for oral treatment
 example_isolates \%>\% select(administrable_per_os())

man/antibiotic_class_selectors.Rd

@@ -203,7 +203,7 @@ example_isolates \%>\% select(mo, aminoglycosides())
 
 # you can combine selectors like you are used with tidyverse
 # e.g., for betalactams, but not the ones with an enzyme inhibitor:
-example_isolates |> select(betalactams(), -betalactams_with_inhibitor())
+example_isolates \%>\% select(betalactams(), -betalactams_with_inhibitor())
 
 # select only antibiotic columns with DDDs for oral treatment
 example_isolates \%>\% select(administrable_per_os())