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mirror of https://github.com/msberends/AMR.git synced 2026-05-31 10:21:46 +02:00
Claude 060449e234 Optimise parallel as.sir(): row-batch mode when n_cols < n_cores
Previously parallel dispatch only parallelised by column, so a 6-column
dataset on a 16-core machine used at most 6 cores with the other 10 idle.
For large n this also caused memory-bandwidth saturation (each worker did
a full n-row scan of clinical_breakpoints simultaneously).

New row-batch mode (fork path, R >= 4.0, non-Windows):
  pieces_per_col = ceil(n_cores / n_cols)
  Jobs = n_cols × pieces_per_col  (≈ n_cores jobs total)
  Each job: one column × one row slice

Benefits:
  - All cores stay busy regardless of column count
  - Per-worker memory footprint shrinks by pieces_per_col ×
  - Breakpoints lookup cache pressure reduced per worker

PSOCK path (Windows / R < 4.0) is unchanged: per-job serialisation
overhead makes row batching unprofitable there.

run_as_sir_column() gains an optional `rows` parameter (NULL = all rows,
backward-compatible). Results are reassembled via as.sir(c(as.character(.)))
which is safe for already-clean SIR values.

https://claude.ai/code/session_012DXCXbZUC54Zij1z9bFiHR
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The AMR Package for R

Please visit our comprehensive package website https://amr-for-r.org to read more about this package, including many examples and tutorials.

Overview:

  • Provides an all-in-one solution for antimicrobial resistance (AMR) data analysis in a One Health approach
  • Peer-reviewed, used in over 175 countries, available in 28 languages
  • Generates antibiograms - traditional, combined, syndromic, and even WISCA
  • Provides the full microbiological taxonomy of ~79 000 distinct species and extensive info of ~620 antimicrobial drugs
  • Applies CLSI 2011-2026 and EUCAST 2011-2026 clinical and veterinary breakpoints, and ECOFFs, for MIC and disk zone interpretation
  • Corrects for duplicate isolates, calculates and predicts AMR per antimicrobial class
  • Integrates with WHONET, ATC, EARS-Net, PubChem, LOINC, SNOMED CT, and NCBI
  • 100% free of costs and dependencies, highly suitable for places with limited resources

The AMR package is a peer-reviewed, free and open-source R package with zero dependencies to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.

The AMR package supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen and the University Medical Center Groningen.


How to get this package

To install the latest release version from CRAN:

install.packages("AMR")

To install the latest beta version:

install.packages("AMR", repos = "beta.amr-for-r.org")

If this does not work, try to install directly from GitHub using the remotes package:

remotes::install_github("msberends/AMR")

This AMR package for R is free, open-source software and licensed under the GNU General Public License v2.0 (GPL-2). These requirements are consequently legally binding: modifications must be released under the same license when distributing the package, changes made to the code must be documented, source code must be made available when the package is distributed, and a copy of the license and copyright notice must be included with the package.

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