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(v2.1.1.9112) unit test
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Package: AMR
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Package: AMR
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Version: 2.1.1.9111
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Version: 2.1.1.9112
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Date: 2024-12-06
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Date: 2024-12-06
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Title: Antimicrobial Resistance Data Analysis
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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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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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2
NEWS.md
2
NEWS.md
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# AMR 2.1.1.9111
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# AMR 2.1.1.9112
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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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*(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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Metadata-Version: 2.1
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Metadata-Version: 2.1
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Name: AMR
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Name: AMR
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Version: 2.1.1.9111
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Version: 2.1.1.9112
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Summary: A Python wrapper for the AMR R package
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Summary: A Python wrapper for the AMR R package
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Home-page: https://github.com/msberends/AMR
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Home-page: https://github.com/msberends/AMR
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Author: Dr. Matthijs Berends
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Author: Dr. Matthijs Berends
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PythonPackage/AMR/dist/amr-2.1.1.9111.tar.gz
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PythonPackage/AMR/dist/amr-2.1.1.9112.tar.gz
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@ -2,7 +2,7 @@ from setuptools import setup, find_packages
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setup(
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setup(
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name='AMR',
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name='AMR',
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version='2.1.1.9111',
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version='2.1.1.9112',
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packages=find_packages(),
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packages=find_packages(),
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install_requires=[
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install_requires=[
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'rpy2',
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'rpy2',
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#'
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#'
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#' # you can combine selectors like you are used with tidyverse
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#' # you can combine selectors like you are used with tidyverse
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#' # e.g., for betalactams, but not the ones with an enzyme inhibitor:
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#' # e.g., for betalactams, but not the ones with an enzyme inhibitor:
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#' example_isolates |> select(betalactams(), -betalactams_with_inhibitor())
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#' example_isolates %>% select(betalactams(), -betalactams_with_inhibitor())
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#'
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#'
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#' # select only antibiotic columns with DDDs for oral treatment
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#' # select only antibiotic columns with DDDs for oral treatment
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#' example_isolates %>% select(administrable_per_os())
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#' example_isolates %>% select(administrable_per_os())
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49
R/sir.R
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R/sir.R
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print.sir <- function(x, ...) {
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print.sir <- function(x, ...) {
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x_name <- deparse(substitute(x))
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x_name <- deparse(substitute(x))
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cat("Class 'sir'\n")
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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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# TODO for #170
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cat(font_blue(word_wrap("These values were interpreted using ",
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# if (!is.null(attributes(x)$guideline) && !all(is.na(attributes(x)$guideline))) {
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font_bold(vector_and(attributes(x)$guideline, quotes = FALSE)),
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# cat(font_blue(word_wrap("These values were interpreted using ",
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" based on ",
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# font_bold(vector_and(attributes(x)$guideline, quotes = FALSE)),
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vector_and(attributes(x)$method, quotes = FALSE),
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# " based on ",
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" values. ",
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# vector_and(attributes(x)$method, quotes = FALSE),
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"Use `sir_interpretation_history(", x_name, ")` to return a full logbook.")))
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# " values. ",
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cat("\n")
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# "Use `sir_interpretation_history(", x_name, ")` to return a full logbook.")))
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}
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# cat("\n")
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# }
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print(as.character(x), quote = FALSE)
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print(as.character(x), quote = FALSE)
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}
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}
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@ -1749,23 +1750,25 @@ summary.sir <- function(object, ...) {
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c.sir <- function(...) {
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c.sir <- function(...) {
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lst <- list(...)
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lst <- list(...)
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guideline <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$guideline %or% NA_character_)
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# TODO for #170
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mo <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$mo %or% NA_character_)
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# guideline <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$guideline %or% NA_character_)
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ab <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ab %or% NA_character_)
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# mo <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$mo %or% NA_character_)
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method <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$method %or% NA_character_)
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# ab <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ab %or% NA_character_)
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ref_tbl <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_tbl %or% NA_character_)
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# method <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$method %or% NA_character_)
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ref_breakpoints <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_breakpoints %or% NA_character_)
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# ref_tbl <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_tbl %or% NA_character_)
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# ref_breakpoints <- vapply(FUN.VALUE = character(1), lst, function(x) attributes(x)$ref_breakpoints %or% NA_character_)
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out <- as.sir(unlist(lapply(list(...), as.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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# TODO for #170
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attributes(out)$guideline <- guideline
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# if (!all(is.na(guideline))) {
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attributes(out)$mo <- mo
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# attributes(out)$guideline <- guideline
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attributes(out)$ab <- ab
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# attributes(out)$mo <- mo
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attributes(out)$method <- method
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# attributes(out)$ab <- ab
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attributes(out)$ref_tbl <- ref_tbl
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# attributes(out)$method <- method
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attributes(out)$ref_breakpoints <- ref_breakpoints
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# attributes(out)$ref_tbl <- ref_tbl
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}
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# attributes(out)$ref_breakpoints <- ref_breakpoints
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# }
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out
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out
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}
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}
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BIN
data-raw/AMR intro.jpg
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data-raw/AMR intro.jpg
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After Width: | Height: | Size: 578 KiB |
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This files contains all context you must know about the AMR package for R.
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This files contains all context you must know about the AMR package for R.
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First and foremost, you are trained on version 2.1.1.9111. Remember this whenever someone asks which AMR package version you’re at.
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First and foremost, you are trained on version 2.1.1.9112. Remember this whenever someone asks which AMR package version you’re at.
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--------------------------------
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--------------------------------
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THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'NAMESPACE':
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THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'NAMESPACE':
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@ -2130,7 +2130,7 @@ example_isolates \%>\% select(mo, aminoglycosides())
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# you can combine selectors like you are used with tidyverse
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# you can combine selectors like you are used with tidyverse
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# e.g., for betalactams, but not the ones with an enzyme inhibitor:
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# e.g., for betalactams, but not the ones with an enzyme inhibitor:
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example_isolates |> select(betalactams(), -betalactams_with_inhibitor())
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example_isolates \%>\% select(betalactams(), -betalactams_with_inhibitor())
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# select only antibiotic columns with DDDs for oral treatment
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# select only antibiotic columns with DDDs for oral treatment
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example_isolates \%>\% select(administrable_per_os())
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example_isolates \%>\% select(administrable_per_os())
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@ -203,7 +203,7 @@ example_isolates \%>\% select(mo, aminoglycosides())
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# you can combine selectors like you are used with tidyverse
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# you can combine selectors like you are used with tidyverse
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# e.g., for betalactams, but not the ones with an enzyme inhibitor:
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# e.g., for betalactams, but not the ones with an enzyme inhibitor:
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example_isolates |> select(betalactams(), -betalactams_with_inhibitor())
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example_isolates \%>\% select(betalactams(), -betalactams_with_inhibitor())
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# select only antibiotic columns with DDDs for oral treatment
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# select only antibiotic columns with DDDs for oral treatment
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example_isolates \%>\% select(administrable_per_os())
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example_isolates \%>\% select(administrable_per_os())
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