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11b1dc2b02 | |||
b1399259e7 |
6
.github/workflows/publish-to-pypi.yml
vendored
6
.github/workflows/publish-to-pypi.yml
vendored
@ -59,9 +59,9 @@ jobs:
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bash _generate_python_wrapper.sh
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- name: Publish to PyPI
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env:
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TWINE_USERNAME: "__token__"
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TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
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# env:
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# TWINE_USERNAME: "__token__"
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# TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
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run: |
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cd data-raw/python_wrapper/AMR
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python -m twine upload dist/*
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@ -1,5 +1,5 @@
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Package: AMR
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Version: 2.1.1.9099
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Version: 2.1.1.9100
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Date: 2024-10-17
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Title: Antimicrobial Resistance Data Analysis
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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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2
NEWS.md
2
NEWS.md
@ -1,4 +1,4 @@
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# AMR 2.1.1.9099
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# AMR 2.1.1.9100
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*(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).)*
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54
R/sir.R
54
R/sir.R
@ -319,11 +319,23 @@ as.sir <- function(x, ...) {
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UseMethod("as.sir")
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}
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as_sir_structure <- function(x) {
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structure(factor(as.character(unlist(unname(x))),
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levels = c("S", "SDD", "I", "R", "NI"),
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ordered = TRUE),
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class = c("sir", "ordered", "factor"))
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as_sir_structure <- function(x,
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guideline = NULL,
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mo = NULL,
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ab = NULL,
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method = NULL,
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ref_tbl = NULL,
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ref_breakpoints = NULL) {
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out <- structure(factor(as.character(unlist(unname(x))),
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levels = c("S", "SDD", "I", "R", "NI"),
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ordered = TRUE),
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guideline = guideline,
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mo = mo,
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ab = ab,
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method = method,
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ref_tbl = ref_tbl,
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ref_breakpoints = ref_breakpoints,
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class = c("sir", "ordered", "factor"))
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}
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#' @rdname as.sir
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@ -1634,7 +1646,17 @@ get_skimmers.sir <- function(column) {
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#' @export
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#' @noRd
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print.sir <- function(x, ...) {
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x_name <- deparse(substitute(x))
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cat("Class 'sir'\n")
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if (!is.null(attributes(x)$guideline) && !all(is.na(attributes(x)$guideline))) {
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cat(font_blue(word_wrap("These values were interpreted using ",
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font_bold(vector_and(attributes(x)$guideline, quotes = FALSE)),
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" based on ",
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vector_and(attributes(x)$method, quotes = FALSE),
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" values. ",
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"Use `sir_interpretation_history(", x_name, ")` to return a full logbook.")))
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cat("\n")
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}
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print(as.character(x), quote = FALSE)
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}
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@ -1715,7 +1737,27 @@ summary.sir <- function(object, ...) {
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#' @export
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#' @noRd
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c.sir <- function(...) {
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as.sir(unlist(lapply(list(...), as.character)))
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lst <- list(...)
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guideline <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$guideline %||% NA_character_)
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mo <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$mo %||% NA_character_)
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ab <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ab %||% NA_character_)
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method <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$method %||% NA_character_)
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ref_tbl <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_tbl %||% NA_character_)
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ref_breakpoints <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_breakpoints %||% NA_character_)
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out <- as.sir(unlist(lapply(list(...), as.character)))
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if (!all(is.na(guideline))) {
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attributes(out)$guideline <- guideline
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attributes(out)$mo <- mo
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attributes(out)$ab <- ab
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attributes(out)$method <- method
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attributes(out)$ref_tbl <- ref_tbl
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attributes(out)$ref_breakpoints <- ref_breakpoints
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}
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out
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}
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#' @method unique sir
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@ -21728,11 +21728,23 @@ as.sir <- function(x, ...) {
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UseMethod("as.sir")
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}
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as_sir_structure <- function(x) {
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structure(factor(as.character(unlist(unname(x))),
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levels = c("S", "SDD", "I", "R", "NI"),
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ordered = TRUE),
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class = c("sir", "ordered", "factor"))
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as_sir_structure <- function(x,
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guideline = NULL,
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mo = NULL,
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ab = NULL,
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method = NULL,
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ref_tbl = NULL,
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ref_breakpoints = NULL) {
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out <- structure(factor(as.character(unlist(unname(x))),
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levels = c("S", "SDD", "I", "R", "NI"),
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ordered = TRUE),
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guideline = guideline,
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mo = mo,
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ab = ab,
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method = method,
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ref_tbl = ref_tbl,
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ref_breakpoints = ref_breakpoints,
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class = c("sir", "ordered", "factor"))
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}
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#' @rdname as.sir
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@ -23043,7 +23055,17 @@ get_skimmers.sir <- function(column) {
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#' @export
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#' @noRd
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print.sir <- function(x, ...) {
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x_name <- deparse(substitute(x))
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cat("Class 'sir'\n")
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if (!is.null(attributes(x)$guideline) && !all(is.na(attributes(x)$guideline))) {
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cat(font_blue(word_wrap("These values were interpreted using ",
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font_bold(vector_and(attributes(x)$guideline, quotes = FALSE)),
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" based on ",
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vector_and(attributes(x)$method, quotes = FALSE),
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" values. ",
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"Use `sir_interpretation_history(", x_name, ")` to return a full logbook.")))
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cat("\n")
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}
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print(as.character(x), quote = FALSE)
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}
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@ -23124,7 +23146,27 @@ summary.sir <- function(object, ...) {
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#' @export
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#' @noRd
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c.sir <- function(...) {
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as.sir(unlist(lapply(list(...), as.character)))
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lst <- list(...)
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guideline <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$guideline %||% NA_character_)
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mo <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$mo %||% NA_character_)
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ab <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ab %||% NA_character_)
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method <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$method %||% NA_character_)
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ref_tbl <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_tbl %||% NA_character_)
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ref_breakpoints <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_breakpoints %||% NA_character_)
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out <- as.sir(unlist(lapply(list(...), as.character)))
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if (!all(is.na(guideline))) {
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attributes(out)$guideline <- guideline
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attributes(out)$mo <- mo
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attributes(out)$ab <- ab
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attributes(out)$method <- method
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attributes(out)$ref_tbl <- ref_tbl
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attributes(out)$ref_breakpoints <- ref_breakpoints
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}
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out
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}
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#' @method unique sir
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@ -24740,7 +24782,13 @@ This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` p
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# Install
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1. First make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
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1. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
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```bash
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pip install AMR
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```
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2. Make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
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For Linux:
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@ -24761,12 +24809,6 @@ This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` p
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For Windows, visit the [CRAN download page](https://cran.r-project.org) to download and install R.
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2. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
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```bash
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pip install AMR
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```
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# Examples of Usage
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## Cleaning Taxonomy
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@ -25982,7 +26024,7 @@ THE NEXT PART CONTAINS CONTENTS FROM FILE DESCRIPTION
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Package: AMR
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Version: 2.1.1.9098
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Version: 2.1.1.9099
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Date: 2024-10-17
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Title: Antimicrobial Resistance Data Analysis
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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
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# Install
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1. First make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
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1. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
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```bash
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pip install AMR
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```
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2. Make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
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For Linux:
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@ -51,12 +57,6 @@ This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` p
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For Windows, visit the [CRAN download page](https://cran.r-project.org) to download and install R.
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2. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
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```bash
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pip install AMR
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```
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# Examples of Usage
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## Cleaning Taxonomy
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|
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