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(v2.1.1.9120) unit test fix

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dr. M.S. (Matthijs) Berends 2024-12-15 20:32:55 +01:00
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9 changed files with 19 additions and 11 deletions

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Package: AMR Package: AMR
Version: 2.1.1.9118 Version: 2.1.1.9120
Date: 2024-12-14 Date: 2024-12-15
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)
data analysis and to work with microbial and antimicrobial properties by data analysis and to work with microbial and antimicrobial properties by

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# AMR 2.1.1.9118 # AMR 2.1.1.9120
*(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).)*
@ -73,6 +73,7 @@ This package now supports not only tools for AMR data analysis in clinical setti
* Updated the prevalence calculation to include genera from the World Health Organization's (WHO) Priority Pathogen List * Updated the prevalence calculation to include genera from the World Health Organization's (WHO) Priority Pathogen List
* Improved algorithm of `first_isolate()` when using the phenotype-based method, to prioritise records with the highest availability of SIR values * Improved algorithm of `first_isolate()` when using the phenotype-based method, to prioritise records with the highest availability of SIR values
* `scale_y_percent()` can now cope with ranges outside the 0-100% range * `scale_y_percent()` can now cope with ranges outside the 0-100% range
* Support for new Dutch national MDRO guideline (SRI-richtlijn BRMO, Nov 2024)
## Other ## Other
* 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`. * 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 Metadata-Version: 2.1
Name: AMR Name: AMR
Version: 2.1.1.9118 Version: 2.1.1.9120
Summary: A Python wrapper for the AMR R package Summary: A Python wrapper for the AMR R package
Home-page: https://github.com/msberends/AMR Home-page: https://github.com/msberends/AMR
Author: Matthijs Berends Author: Matthijs Berends

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@ -2,7 +2,7 @@ from setuptools import setup, find_packages
setup( setup(
name='AMR', name='AMR',
version='2.1.1.9118', version='2.1.1.9120',
packages=find_packages(), packages=find_packages(),
install_requires=[ install_requires=[
'rpy2', 'rpy2',

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This files contains all context you must know about the AMR package for R. This files contains all context you must know about the AMR package for R.
First and foremost, you are trained on version 2.1.1.9118. Remember this whenever someone asks which AMR package version youre at. First and foremost, you are trained on version 2.1.1.9120. Remember this whenever someone asks which AMR package version youre at.
-------------------------------- --------------------------------
THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'NAMESPACE': THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'NAMESPACE':
@ -6140,7 +6140,7 @@ Ordered \link{factor} with levels \code{Negative} < \verb{Positive, unconfirmed}
} }
} }
\description{ \description{
Determine which isolates are multidrug-resistant organisms (MDRO) according to international, national and custom guidelines. Determine which isolates are multidrug-resistant organisms (MDRO) according to international, national, or custom guidelines.
} }
\details{ \details{
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}. 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}.
@ -6174,10 +6174,17 @@ The international guideline for multi-drug resistant tuberculosis - World Health
The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7; \doi{10.1186/s13756-015-0047-6} The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7; \doi{10.1186/s13756-015-0047-6}
\item \code{guideline = "BRMO"} \item \code{guideline = "BRMO"}
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}) The Dutch national guideline - Samenwerkingverband Richtlijnen Infectiepreventie (SRI) (2024) "Bijzonder Resistente Micro-Organismen (BRMO)" (\href{https://www.sri-richtlijnen.nl/brmo}{link})
Also:
\itemize{
\item \code{guideline = "BRMO 2017"}
The former Dutch national guideline - Werkgroep Infectiepreventie (WIP), RIVM, last revision as of 2017: "Bijzonder Resistente Micro-Organismen (BRMO)"
}
} }
Please suggest your own (country-specific) guidelines by letting us know: \url{https://github.com/msberends/AMR/issues/new}. Please suggest to implement guidelines by letting us know: \url{https://github.com/msberends/AMR/issues/new}.
} }
\section{Using Custom Guidelines}{ \section{Using Custom Guidelines}{

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@ -45,8 +45,8 @@ expect_identical(class(outcome), c("ordered", "factor"))
# example_isolates should have these finding using Dutch guidelines # example_isolates should have these finding using Dutch guidelines
expect_equal( expect_equal(
as.double(table(outcome)), as.double(table(outcome)),
c(1954, 24, 6) c(1994, 0, 6)
) # 1954 neg, 24 unconfirmed, 6 pos, rest is NA )
expect_equal( expect_equal(
brmo(example_isolates, info = FALSE), brmo(example_isolates, info = FALSE),