DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 2.1.1.9222
-Date: 2025-03-20
+Version: 2.1.1.9220
+Date: 2025-03-19
 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 2.1.1.9222
+# AMR 2.1.1.9220
 
 *(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).)*
 
@@ -46,7 +46,6 @@ This package now supports not only tools for AMR data analysis in clinical setti
   * It is now possible to use column names for argument `ab`, `mo`, and `uti`: `as.sir(..., ab = "column1", mo = "column2", uti = "column3")`. This greatly improves the flexibility for users.
   * Users can now set their own criteria (using regular expressions) as to what should be considered S, I, R, SDD, and NI.
   * To get quantitative values, `as.double()` on a `sir` object will return 1 for S, 2 for SDD/I, and 3 for R (NI will become `NA`). Other functions using `sir` classes (e.g., `summary()`) are updated to reflect the change to contain NI and SDD.
-  * Combined MIC values (e.g., from CLSI) are now supported
   * The argument `conserve_capped_values` in `as.sir()` has been replaced with `capped_mic_handling`, which allows greater flexibility in handling capped MIC values (`<`, `<=`, `>`, `>=`). The four available options (`"standard"`, `"strict"`, `"relaxed"`, `"inverse"`) provide full control over whether these values should be interpreted conservatively or ignored. Using `conserve_capped_values` is now deprecated and returns a warning.
 * `antibiogram()` function
   * Argument `antibiotics` has been renamed to `antimicrobials`. Using `antibiotics` will still work, but now returns a warning.

R/mic.R

@@ -201,10 +201,6 @@ as.mic <- function(x, na.rm = FALSE, keep_operators = "all") {
   # transform Unicode for >= and <=
   x <- gsub("\u2264", "<=", x, fixed = TRUE)
   x <- gsub("\u2265", ">=", x, fixed = TRUE)
-  if (any(x %like% "[0-9]/.*[0-9]", na.rm = TRUE)) {
-    warning_("Some MICs were combined values, only the first values are kept")
-    x[x %like% "[0-9]/.*[0-9]"] <- gsub("/.*", "", x[x %like% "[0-9]/.*[0-9]"])
-  }
   # remove other invalid characters
   x <- gsub("[^a-zA-Z0-9.><= -]+", "", x, perl = TRUE)
   # transform => to >= and =< to <=

data-raw/_generate_python_wrapper.sh

@@ -44,44 +44,46 @@ description_file="../DESCRIPTION"
 cat <<EOL > "$datasets_file"
 import os
 import sys
+from rpy2 import robjects
+from rpy2.robjects import pandas2ri
+from rpy2.robjects.packages import importr, isinstalled
 import pandas as pd
 import importlib.metadata as metadata
 
 # Get the path to the virtual environment
 venv_path = sys.prefix
+
+# Define R library path within the venv
 r_lib_path = os.path.join(venv_path, "R_libs")
+# Ensure the R library path exists
 os.makedirs(r_lib_path, exist_ok=True)
 
-# Set environment variable before importing rpy2
-os.environ['R_LIBS_SITE'] = r_lib_path
-
-from rpy2 import robjects
-from rpy2.robjects import pandas2ri
-from rpy2.robjects.packages import importr, isinstalled
-
 # Import base and utils
 base = importr('base')
 utils = importr('utils')
 
-base.options(warn=-1)
+base.options(warn = -1)
 
-# Ensure library paths explicitly
-base._libPaths(r_lib_path)
+# Override R library paths globally for the session
+robjects.r(f'.Library.site <- "{r_lib_path}"')  # Replace site-specific library
+base._libPaths(r_lib_path)  # Override .libPaths() as well
+
+# Get the effective library path
+r_amr_lib_path = base._libPaths()[0]
 
 # Check if the AMR package is installed in R
-if not isinstalled('AMR', lib_loc=r_lib_path):
-    print(f"AMR: Installing latest AMR R package to {r_lib_path}...", flush=True)
+if not isinstalled('AMR', lib_loc=r_amr_lib_path):
+    print(f"AMR: Installing latest AMR R package to {r_amr_lib_path}...", flush=True)
     utils.install_packages('AMR', repos='https://msberends.r-universe.dev', quiet=True)
 
-# Retrieve Python AMR version
+# Python package version of AMR
 try:
     python_amr_version = metadata.version('AMR')
 except metadata.PackageNotFoundError:
     python_amr_version = ''
 
-# Retrieve R AMR version
-r_amr_version = robjects.r(f'as.character(packageVersion("AMR", lib.loc = "{r_lib_path}"))')
-r_amr_version = str(r_amr_version[0])
+# R package version of AMR
+r_amr_version = robjects.r(f'as.character(packageVersion("AMR", lib.loc = "{r_amr_lib_path}"))')
 
 print(python_amr_version)
 print(r_amr_version)
@@ -89,7 +91,7 @@ print(r_amr_version)
 # Compare R and Python package versions
 if r_amr_version != python_amr_version:
     try:
-        print(f"AMR: Updating AMR package in {r_lib_path}...", flush=True)
+        print(f"AMR: Updating AMR package in {r_amr_lib_path}...", flush=True)
         utils.install_packages('AMR', repos='https://msberends.r-universe.dev', quiet=True)
     except Exception as e:
         print(f"AMR: Could not update: {e}", flush=True)

data-raw/gpt_training_text_v2.1.1.9220.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 2.1.1.9222. Remember this whenever someone asks which AMR package version you’re at.
+First and foremost, you are trained on version 2.1.1.9220. Remember this whenever someone asks which AMR package version you’re at.
 
 Below are the contents of the NAMESPACE file, the index.md file, and all the man/*.Rd files (documentation) in the package. Every file content is split using 100 hypens.
 ----------------------------------------------------------------------------------------------------