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(v2.1.1.9120) unit test fix
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Package: AMR
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Version: 2.1.1.9118
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Date: 2024-12-14
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Version: 2.1.1.9120
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Date: 2024-12-15
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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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data analysis and to work with microbial and antimicrobial properties by
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3
NEWS.md
3
NEWS.md
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# AMR 2.1.1.9118
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# AMR 2.1.1.9120
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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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@ -73,6 +73,7 @@ This package now supports not only tools for AMR data analysis in clinical setti
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* Updated the prevalence calculation to include genera from the World Health Organization's (WHO) Priority Pathogen List
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* Improved algorithm of `first_isolate()` when using the phenotype-based method, to prioritise records with the highest availability of SIR values
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* `scale_y_percent()` can now cope with ranges outside the 0-100% range
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* Support for new Dutch national MDRO guideline (SRI-richtlijn BRMO, Nov 2024)
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## Other
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* Greatly improved `vctrs` integration, a Tidyverse package working in the background for many Tidyverse functions. For users, this means that functions such as `dplyr`'s `bind_rows()`, `rowwise()` and `c_across()` are now supported for e.g. columns of class `mic`. Despite this, this `AMR` package is still zero-dependent on any other package, including `dplyr` and `vctrs`.
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Metadata-Version: 2.1
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Name: AMR
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Version: 2.1.1.9118
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Version: 2.1.1.9120
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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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Author: Matthijs Berends
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@ -2,7 +2,7 @@ from setuptools import setup, find_packages
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setup(
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name='AMR',
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version='2.1.1.9118',
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version='2.1.1.9120',
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packages=find_packages(),
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install_requires=[
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'rpy2',
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@ -1,5 +1,5 @@
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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 2.1.1.9118. Remember this whenever someone asks which AMR package version you’re at.
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First and foremost, you are trained on version 2.1.1.9120. Remember this whenever someone asks which AMR package version you’re at.
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--------------------------------
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THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'NAMESPACE':
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@ -6140,7 +6140,7 @@ Ordered \link{factor} with levels \code{Negative} < \verb{Positive, unconfirmed}
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}
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}
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\description{
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Determine which isolates are multidrug-resistant organisms (MDRO) according to international, national and custom guidelines.
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Determine which isolates are multidrug-resistant organisms (MDRO) according to international, national, or custom guidelines.
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}
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\details{
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These functions are context-aware. This means that the \code{x} argument can be left blank if used inside a \link{data.frame} call, see \emph{Examples}.
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@ -6174,10 +6174,17 @@ The international guideline for multi-drug resistant tuberculosis - World Health
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The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7; \doi{10.1186/s13756-015-0047-6}
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\item \code{guideline = "BRMO"}
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The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)" (\href{https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh}{link})
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The Dutch national guideline - Samenwerkingverband Richtlijnen Infectiepreventie (SRI) (2024) "Bijzonder Resistente Micro-Organismen (BRMO)" (\href{https://www.sri-richtlijnen.nl/brmo}{link})
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Also:
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\itemize{
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\item \code{guideline = "BRMO 2017"}
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The former Dutch national guideline - Werkgroep Infectiepreventie (WIP), RIVM, last revision as of 2017: "Bijzonder Resistente Micro-Organismen (BRMO)"
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}
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}
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Please suggest your own (country-specific) guidelines by letting us know: \url{https://github.com/msberends/AMR/issues/new}.
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Please suggest to implement guidelines by letting us know: \url{https://github.com/msberends/AMR/issues/new}.
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}
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\section{Using Custom Guidelines}{
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@ -45,8 +45,8 @@ expect_identical(class(outcome), c("ordered", "factor"))
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# example_isolates should have these finding using Dutch guidelines
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expect_equal(
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as.double(table(outcome)),
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c(1954, 24, 6)
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) # 1954 neg, 24 unconfirmed, 6 pos, rest is NA
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c(1994, 0, 6)
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)
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expect_equal(
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brmo(example_isolates, info = FALSE),
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