(v2.1.1.9191) unit tests

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 2.1.1.9190
+Version: 2.1.1.9191
-Date: 2025-03-09
+Date: 2025-03-10
 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 2.1.1.9190
+# AMR 2.1.1.9191
 
 *(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: 2.2
 Name: AMR
-Version: 2.1.1.9190
+Version: 2.1.1.9191
 Summary: A Python wrapper for the AMR R package
 Home-page: https://github.com/msberends/AMR
 Author: Matthijs Berends

PythonPackage/AMR/setup.py

@@ -2,7 +2,7 @@ from setuptools import setup, find_packages
 
 setup(
     name='AMR',
-    version='2.1.1.9190',
+    version='2.1.1.9191',
     packages=find_packages(),
     install_requires=[
         'rpy2',

R/antibiogram.R

@@ -870,7 +870,9 @@ antibiogram.default <- function(x,
   if (formatting_type == 20) out <- out %pm>% pm_summarise(out_value = paste0(round(coverage * 100, digits = digits), "% (", round(lower_ci * 100, digits = digits), "-", round(upper_ci * 100, digits = digits), "%,", n_susceptible, "/", n_tested, ")"))
   if (formatting_type == 21) out <- out %pm>% pm_summarise(out_value = paste0(round(coverage * 100, digits = digits), " (", round(lower_ci * 100, digits = digits), "-", round(upper_ci * 100, digits = digits), ",N=", n_susceptible, "/", n_tested, ")"))
   if (formatting_type == 22) out <- out %pm>% pm_summarise(out_value = paste0(round(coverage * 100, digits = digits), "% (", round(lower_ci * 100, digits = digits), "-", round(upper_ci * 100, digits = digits), "%,N=", n_susceptible, "/", n_tested, ")"))
-  out$out_value[out$out_value %like% "^NA"] <- NA_character_
+  if (formatting_type >= 4) {
+    out$out_value[out$out_value %like% "^NA"] <- NA_character_
+  }
 
   # transform names of antimicrobials
   ab_naming_function <- function(x, t, l, s) {
@@ -1260,6 +1262,15 @@ autoplot.antibiogram <- function(object, ...) {
   if (!"mo" %in% colnames(df)) {
     df$mo <- ""
   }
+  groups <- colnames(df)[seq_len(which(colnames(df) %in% c("mo", "ab"))[1] - 1)]
+  group_name <- paste(groups, collapse = "/")
+  if (length(groups) > 1) {
+    df$syndromic_group <- apply(df[groups], 1, function(x) {
+      paste(stats::na.omit(x), collapse = "/")
+    })
+  } else if ("syndromic_group" %in% colnames(df)) {
+    group_name <- colnames(object)[1]
+  }
   out <- ggplot2::ggplot(df,
     mapping = ggplot2::aes(
       x = ab,
@@ -1272,7 +1283,6 @@ autoplot.antibiogram <- function(object, ...) {
     )
   ) +
     ggplot2::geom_col(position = ggplot2::position_dodge2(preserve = "single")) +
-    ggplot2::facet_wrap("mo") +
     ggplot2::geom_errorbar(
       mapping = ggplot2::aes(ymin = lower_ci * 100, ymax = upper_ci * 100),
       position = ggplot2::position_dodge2(preserve = "single", width = 1)
@@ -1281,11 +1291,15 @@ autoplot.antibiogram <- function(object, ...) {
       y = ifelse(isTRUE(attributes(object)$combine_SI), "%SI", "%S"),
       x = NULL,
       fill = if ("syndromic_group" %in% colnames(df)) {
-        colnames(object)[1]
+        group_name
       } else {
         NULL
       }
     )
+  if (!all(df$mo == "", na.rm = TRUE)) {
+    out <- out +
+      ggplot2::facet_wrap("mo")
+  }
   out
 }
 

data-raw/gpt_training_text_v2.1.1.9191.txt

@@ -1,6 +1,6 @@
 This knowledge base contains all context you must know about the AMR package for R. You are a GPT trained to be an assistant for the AMR package in R. You are an incredible R specialist, especially trained in this package and in the tidyverse.
 
-First and foremost, you are trained on version 2.1.1.9190. Remember this whenever someone asks which AMR package version you’re at.
+First and foremost, you are trained on version 2.1.1.9191. Remember this whenever someone asks which AMR package version you’re at.
 
 Below are the contents of the  file, the  file, and all the  files (documentation) in the package. Every file content is split using 100 hypens.
 ----------------------------------------------------------------------------------------------------

tests/testthat/test-antibiogram.R

@@ -31,18 +31,18 @@ test_that("antibiogram works", {
   # Traditional antibiogram ----------------------------------------------
 
   ab1 <- antibiogram(example_isolates,
-    antibiotics = c(aminoglycosides(), carbapenems())
+    antimicrobials = c(aminoglycosides(), carbapenems())
   )
 
   ab2 <- antibiogram(example_isolates,
-    antibiotics = aminoglycosides(),
+    antimicrobials = aminoglycosides(),
     ab_transform = "atc",
     mo_transform = "gramstain",
     add_total_n = TRUE
   )
 
   ab3 <- antibiogram(example_isolates,
-    antibiotics = carbapenems(),
+    antimicrobials = carbapenems(),
     ab_transform = "ab",
     mo_transform = "name",
     formatting_type = 1
@@ -58,14 +58,14 @@ test_that("antibiogram works", {
 
   # Combined antibiogram -------------------------------------------------
 
-  # combined antibiotics yield higher empiric coverage
+  # combined antibiogram yield higher empiric coverage
   ab4 <- antibiogram(example_isolates,
-    antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
+    antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"),
     mo_transform = "gramstain"
   )
 
   ab5 <- antibiogram(example_isolates,
-    antibiotics = c("TZP", "TZP+TOB"),
+    antimicrobials = c("TZP", "TZP+TOB"),
     mo_transform = "gramstain",
     ab_transform = "name",
     sep = " & ",
@@ -81,7 +81,7 @@ test_that("antibiogram works", {
 
   # the data set could contain a filter for e.g. respiratory specimens
   ab6 <- antibiogram(example_isolates,
-    antibiotics = c(aminoglycosides(), carbapenems()),
+    antimicrobials = c(aminoglycosides(), carbapenems()),
     syndromic_group = "ward",
     ab_transform = NULL
   )
@@ -90,7 +90,7 @@ test_that("antibiogram works", {
   # (i.e., this table will be in Dutch on Dutch systems)
   ex1 <- example_isolates[which(mo_genus() == "Escherichia"), ]
   ab7 <- antibiogram(ex1,
-    antibiotics = aminoglycosides(),
+    antimicrobials = aminoglycosides(),
     ab_transform = "name",
     syndromic_group = ifelse(ex1$ward == "ICU",
       "IC", "Geen IC"
@@ -108,7 +108,7 @@ test_that("antibiogram works", {
 
   # the data set could contain a filter for e.g. respiratory specimens
   ab8 <- suppressWarnings(antibiogram(example_isolates,
-    antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
+    antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"),
     wisca = TRUE
   ))
 
@@ -118,11 +118,12 @@ test_that("antibiogram works", {
   expect_equal(colnames(ab8), c("Piperacillin/tazobactam", "Piperacillin/tazobactam + Gentamicin", "Piperacillin/tazobactam + Tobramycin"))
 
   # grouped tibbles
-
   if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) {
-    ab9 <- example_isolates %>%
+    expect_warning(
-      group_by(ward, gender) %>%
+      ab9 <- example_isolates %>%
-      wisca(antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
+        group_by(ward, gender) %>%
+        wisca(antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"))
+    )
     expect_equal(colnames(ab9), c("ward", "gender", "Piperacillin/tazobactam", "Piperacillin/tazobactam + Gentamicin", "Piperacillin/tazobactam + Tobramycin"))
   }