(v2.1.1.9100) PyPI update

.github/workflows/publish-to-pypi.yml

@@ -60,8 +60,8 @@ jobs:
       
       - name: Publish to PyPI
         env:
-          TWINE_USERNAME: "__token__"
+          # TWINE_USERNAME: "__token__"
-          TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
+          # TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
         run: |
           cd data-raw/python_wrapper/AMR
           python -m twine upload dist/*

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: AMR
-Version: 2.1.1.9099
+Version: 2.1.1.9100
 Date: 2024-10-17
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 2.1.1.9099
+# AMR 2.1.1.9100
 
 *(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).)*
 

data-raw/gpt_training_text.txt

@@ -21728,11 +21728,23 @@ as.sir <- function(x, ...) {
   UseMethod("as.sir")
 }
 
-as_sir_structure <- function(x) {
+as_sir_structure <- function(x,
-  structure(factor(as.character(unlist(unname(x))),
+                             guideline = NULL,
-                   levels = c("S", "SDD", "I", "R", "NI"),
+                             mo = NULL,
-                   ordered = TRUE),
+                             ab = NULL,
-            class = c("sir", "ordered", "factor"))
+                             method = NULL,
+                             ref_tbl = NULL,
+                             ref_breakpoints = NULL) {
+  out <- structure(factor(as.character(unlist(unname(x))),
+                          levels = c("S", "SDD", "I", "R", "NI"),
+                          ordered = TRUE),
+                   guideline = guideline,
+                   mo = mo,
+                   ab = ab,
+                   method = method,
+                   ref_tbl = ref_tbl,
+                   ref_breakpoints = ref_breakpoints,
+                   class = c("sir", "ordered", "factor"))
 }
 
 #' @rdname as.sir
@@ -23043,7 +23055,17 @@ get_skimmers.sir <- function(column) {
 #' @export
 #' @noRd
 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")
+  }
   print(as.character(x), quote = FALSE)
 }
 
@@ -23124,7 +23146,27 @@ summary.sir <- function(object, ...) {
 #' @export
 #' @noRd
 c.sir <- function(...) {
-  as.sir(unlist(lapply(list(...), as.character)))
+  lst <- list(...)
+  
+  guideline <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$guideline %||% NA_character_)
+  mo <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$mo %||% NA_character_)
+  ab <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ab %||% NA_character_)
+  method <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$method %||% NA_character_)
+  ref_tbl <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_tbl %||% NA_character_)
+  ref_breakpoints <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_breakpoints %||% 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
+  }
+  
+  out
 }
 
 #' @method unique sir
@@ -24740,7 +24782,13 @@ This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` p
 
 # Install
 
-1. First make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
+1. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
+
+    ```bash
+    pip install AMR
+    ```
+
+2. Make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
 
     For Linux:
 
@@ -24761,12 +24809,6 @@ This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` p
     
     For Windows, visit the [CRAN download page](https://cran.r-project.org) to download and install R.
 
-2. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
-
-    ```bash
-    pip install AMR
-    ```
-
 # Examples of Usage
 
 ## Cleaning Taxonomy
@@ -25982,7 +26024,7 @@ THE NEXT PART CONTAINS CONTENTS FROM FILE DESCRIPTION
 
 
 Package: AMR
-Version: 2.1.1.9098
+Version: 2.1.1.9099
 Date: 2024-10-17
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)

vignettes/AMR_for_Python.Rmd

@@ -30,7 +30,13 @@ This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` p
 
 # Install
 
-1. First make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
+1. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
+
+    ```bash
+    pip install AMR
+    ```
+
+2. Make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
 
     For Linux:
 
@@ -51,12 +57,6 @@ This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` p
     
     For Windows, visit the [CRAN download page](https://cran.r-project.org) to download and install R.
 
-2. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
-
-    ```bash
-    pip install AMR
-    ```
-
 # Examples of Usage
 
 ## Cleaning Taxonomy