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Author SHA1 Message Date
11b1dc2b02 Fix Py 2024-10-17 15:28:13 +02:00
b1399259e7 (v2.1.1.9100) PyPI update 2024-10-17 15:22:19 +02:00
6 changed files with 116 additions and 32 deletions

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@ -59,9 +59,9 @@ jobs:
bash _generate_python_wrapper.sh bash _generate_python_wrapper.sh
- name: Publish to PyPI - name: Publish to PyPI
env: # env:
TWINE_USERNAME: "__token__" # TWINE_USERNAME: "__token__"
TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }} # TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
run: | run: |
cd data-raw/python_wrapper/AMR cd data-raw/python_wrapper/AMR
python -m twine upload dist/* python -m twine upload dist/*

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

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@ -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).)* *(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).)*

54
R/sir.R
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@ -319,11 +319,23 @@ as.sir <- function(x, ...) {
UseMethod("as.sir") 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 #' @rdname as.sir
@ -1634,7 +1646,17 @@ get_skimmers.sir <- function(column) {
#' @export #' @export
#' @noRd #' @noRd
print.sir <- function(x, ...) { print.sir <- function(x, ...) {
x_name <- deparse(substitute(x))
cat("Class 'sir'\n") 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) print(as.character(x), quote = FALSE)
} }
@ -1715,7 +1737,27 @@ summary.sir <- function(object, ...) {
#' @export #' @export
#' @noRd #' @noRd
c.sir <- function(...) { 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 #' @method unique sir

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@ -21728,11 +21728,23 @@ as.sir <- function(x, ...) {
UseMethod("as.sir") 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 #' @rdname as.sir
@ -23043,7 +23055,17 @@ get_skimmers.sir <- function(column) {
#' @export #' @export
#' @noRd #' @noRd
print.sir <- function(x, ...) { print.sir <- function(x, ...) {
x_name <- deparse(substitute(x))
cat("Class 'sir'\n") 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) print(as.character(x), quote = FALSE)
} }
@ -23124,7 +23146,27 @@ summary.sir <- function(object, ...) {
#' @export #' @export
#' @noRd #' @noRd
c.sir <- function(...) { 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 #' @method unique sir
@ -24740,7 +24782,13 @@ This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` p
# Install # 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: 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. 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 # Examples of Usage
## Cleaning Taxonomy ## Cleaning Taxonomy
@ -25982,7 +26024,7 @@ THE NEXT PART CONTAINS CONTENTS FROM FILE DESCRIPTION
Package: AMR Package: AMR
Version: 2.1.1.9098 Version: 2.1.1.9099
Date: 2024-10-17 Date: 2024-10-17
Title: Antimicrobial Resistance Data Analysis Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR) Description: Functions to simplify and standardise antimicrobial resistance (AMR)

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@ -30,7 +30,13 @@ This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` p
# Install # 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: 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. 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 # Examples of Usage
## Cleaning Taxonomy ## Cleaning Taxonomy