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dr. M.S. (Matthijs) Berends 2024-11-21 10:06:26 +01:00
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^vignettes/WHONET\.Rmd$ ^vignettes/WHONET\.Rmd$
^logo.svg$ ^logo.svg$
^CRAN-SUBMISSION$ ^CRAN-SUBMISSION$
^PythonPackage$

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data-raw/country_analysis2.R data-raw/country_analysis2.R
data-raw/taxonomy.csv data-raw/taxonomy.csv
data-raw/WHONET/* data-raw/WHONET/*
data-raw/python_wrapper/*

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Metadata-Version: 2.1
Name: AMR
Version: 2.1.1.9103
Summary: A Python wrapper for the AMR R package
Home-page: https://github.com/msberends/AMR
Author: Dr. Matthijs Berends
Author-email: m.s.berends@umcg.nl
License: GPL 2
Project-URL: Bug Tracker, https://github.com/msberends/AMR/issues
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: rpy2
Requires-Dist: numpy
Requires-Dist: pandas
---
title: "AMR for Python"
output:
rmarkdown::html_vignette:
toc: true
toc_depth: 3
vignette: >
%\VignetteIndexEntry{AMR for Python}
%\VignetteEncoding{UTF-8}
%\VignetteEngine{knitr::rmarkdown}
editor_options:
chunk_output_type: console
---
```{r setup, include = FALSE, results = 'markup'}
knitr::opts_chunk$set(
warning = FALSE,
collapse = TRUE,
comment = "#>",
fig.width = 7.5,
fig.height = 5
)
```
# Introduction
The `AMR` package for R is a powerful tool for antimicrobial resistance (AMR) analysis. It provides extensive features for handling microbial and antimicrobial data. However, for those who work primarily in Python, we now have a more intuitive option available: the [`AMR` Python Package Index](https://pypi.org/project/AMR/).
This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` package internally. Despite the need to have R installed, Python users can now easily work with AMR data directly through Python code.
# Install
1. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
```bash
pip install AMR
```
2. Make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
For Linux:
```bash
# Ubuntu / Debian
sudo apt install r-base
# Fedora:
sudo dnf install R
# CentOS/RHEL
sudo yum install R
```
For macOS (using [Homebrew](https://brew.sh)):
```bash
brew install r
```
For Windows, visit the [CRAN download page](https://cran.r-project.org) to download and install R.
# Examples of Usage
## Cleaning Taxonomy
Here’s an example that demonstrates how to clean microorganism and drug names using the `AMR` Python package:
```python
import pandas as pd
import AMR
# Sample data
data = {
"MOs": ['E. coli', 'ESCCOL', 'esco', 'Esche coli'],
"Drug": ['Cipro', 'CIP', 'J01MA02', 'Ciproxin']
}
df = pd.DataFrame(data)
# Use AMR functions to clean microorganism and drug names
df['MO_clean'] = AMR.mo_name(df['MOs'])
df['Drug_clean'] = AMR.ab_name(df['Drug'])
# Display the results
print(df)
```
| MOs | Drug | MO_clean | Drug_clean |
|-------------|-----------|--------------------|---------------|
| E. coli | Cipro | Escherichia coli | Ciprofloxacin |
| ESCCOL | CIP | Escherichia coli | Ciprofloxacin |
| esco | J01MA02 | Escherichia coli | Ciprofloxacin |
| Esche coli | Ciproxin | Escherichia coli | Ciprofloxacin |
### Explanation
* **mo_name:** This function standardises microorganism names. Here, different variations of *Escherichia coli* (such as "E. coli", "ESCCOL", "esco", and "Esche coli") are all converted into the correct, standardised form, "Escherichia coli".
* **ab_name**: Similarly, this function standardises antimicrobial names. The different representations of ciprofloxacin (e.g., "Cipro", "CIP", "J01MA02", and "Ciproxin") are all converted to the standard name, "Ciprofloxacin".
## Taxonomic Data Sets Now in Python!
As a Python user, you might like that the most important data sets of the `AMR` R package, `microorganisms`, `antibiotics`, `clinical_breakpoints`, and `example_isolates`, are now available as regular Python data frames:
```python
AMR.microorganisms
```
| mo | fullname | status | kingdom | gbif | gbif_parent | gbif_renamed_to | prevalence |
|--------------|------------------------------------|----------|----------|-----------|-------------|-----------------|------------|
| B_GRAMN | (unknown Gram-negatives) | unknown | Bacteria | None | None | None | 2.0 |
| B_GRAMP | (unknown Gram-positives) | unknown | Bacteria | None | None | None | 2.0 |
| B_ANAER-NEG | (unknown anaerobic Gram-negatives) | unknown | Bacteria | None | None | None | 2.0 |
| B_ANAER-POS | (unknown anaerobic Gram-positives) | unknown | Bacteria | None | None | None | 2.0 |
| B_ANAER | (unknown anaerobic bacteria) | unknown | Bacteria | None | None | None | 2.0 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| B_ZYMMN_POMC | Zymomonas pomaceae | accepted | Bacteria | 10744418 | 3221412 | None | 2.0 |
| B_ZYMPH | Zymophilus | synonym | Bacteria | None | 9475166 | None | 2.0 |
| B_ZYMPH_PCVR | Zymophilus paucivorans | synonym | Bacteria | None | None | None | 2.0 |
| B_ZYMPH_RFFN | Zymophilus raffinosivorans | synonym | Bacteria | None | None | None | 2.0 |
| F_ZYZYG | Zyzygomyces | unknown | Fungi | None | 7581 | None | 2.0 |
```python
AMR.antibiotics
```
| ab | cid | name | group | oral_ddd | oral_units | iv_ddd | iv_units |
|-----|-------------|----------------------|----------------------------|----------|------------|--------|----------|
| AMA | 4649.0 | 4-aminosalicylic acid| Antimycobacterials | 12.00 | g | NaN | None |
| ACM | 6450012.0 | Acetylmidecamycin | Macrolides/lincosamides | NaN | None | NaN | None |
| ASP | 49787020.0 | Acetylspiramycin | Macrolides/lincosamides | NaN | None | NaN | None |
| ALS | 8954.0 | Aldesulfone sodium | Other antibacterials | 0.33 | g | NaN | None |
| AMK | 37768.0 | Amikacin | Aminoglycosides | NaN | None | 1.0 | g |
| ... | ... | ... | ... | ... | ... | ... | ... |
| VIR | 11979535.0 | Virginiamycine | Other antibacterials | NaN | None | NaN | None |
| VOR | 71616.0 | Voriconazole | Antifungals/antimycotics | 0.40 | g | 0.4 | g |
| XBR | 72144.0 | Xibornol | Other antibacterials | NaN | None | NaN | None |
| ZID | 77846445.0 | Zidebactam | Other antibacterials | NaN | None | NaN | None |
| ZFD | NaN | Zoliflodacin | None | NaN | None | NaN | None |
## Calculating AMR
```python
import AMR
import pandas as pd
df = AMR.example_isolates
result = AMR.resistance(df["AMX"])
print(result)
```
```
[0.59555556]
```
## Generating Antibiograms
One of the core functions of the `AMR` package is generating an antibiogram, a table that summarises the antimicrobial susceptibility of bacterial isolates. Here’s how you can generate an antibiogram from Python:
```python
result2a = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]])
print(result2a)
```
| Pathogen | Amoxicillin | Ciprofloxacin | Piperacillin/tazobactam |
|-----------------|-----------------|-----------------|--------------------------|
| CoNS | 7% (10/142) | 73% (183/252) | 30% (10/33) |
| E. coli | 50% (196/392) | 88% (399/456) | 94% (393/416) |
| K. pneumoniae | 0% (0/58) | 96% (53/55) | 89% (47/53) |
| P. aeruginosa | 0% (0/30) | 100% (30/30) | None |
| P. mirabilis | None | 94% (34/36) | None |
| S. aureus | 6% (8/131) | 90% (171/191) | None |
| S. epidermidis | 1% (1/91) | 64% (87/136) | None |
| S. hominis | None | 80% (56/70) | None |
| S. pneumoniae | 100% (112/112) | None | 100% (112/112) |
```python
result2b = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]], mo_transform = "gramstain")
print(result2b)
```
| Pathogen | Amoxicillin | Ciprofloxacin | Piperacillin/tazobactam |
|----------------|-----------------|------------------|--------------------------|
| Gram-negative | 36% (226/631) | 91% (621/684) | 88% (565/641) |
| Gram-positive | 43% (305/703) | 77% (560/724) | 86% (296/345) |
In this example, we generate an antibiogram by selecting various antibiotics.
# Conclusion
With the `AMR` Python package, Python users can now effortlessly call R functions from the `AMR` R package. This eliminates the need for complex `rpy2` configurations and provides a clean, easy-to-use interface for antimicrobial resistance analysis. The examples provided above demonstrate how this can be applied to typical workflows, such as standardising microorganism and antimicrobial names or calculating resistance.
By just running `import AMR`, users can seamlessly integrate the robust features of the R `AMR` package into Python workflows.
Whether you're cleaning data or analysing resistance patterns, the `AMR` Python package makes it easy to work with AMR data in Python.

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README.md
setup.py
AMR/__init__.py
AMR/datasets.py
AMR/functions.py
AMR.egg-info/PKG-INFO
AMR.egg-info/SOURCES.txt
AMR.egg-info/dependency_links.txt
AMR.egg-info/requires.txt
AMR.egg-info/top_level.txt

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rpy2
numpy
pandas

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AMR

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from .datasets import example_isolates
from .datasets import microorganisms
from .datasets import antibiotics
from .datasets import clinical_breakpoints
from .functions import ab_from_text
from .functions import ab_name
from .functions import ab_cid
from .functions import ab_synonyms
from .functions import ab_tradenames
from .functions import ab_group
from .functions import ab_atc
from .functions import ab_atc_group1
from .functions import ab_atc_group2
from .functions import ab_loinc
from .functions import ab_ddd
from .functions import ab_ddd_units
from .functions import ab_info
from .functions import ab_url
from .functions import ab_property
from .functions import add_custom_antimicrobials
from .functions import clear_custom_antimicrobials
from .functions import add_custom_microorganisms
from .functions import clear_custom_microorganisms
from .functions import age
from .functions import age_groups
from .functions import antibiogram
from .functions import ab_class
from .functions import ab_selector
from .functions import aminoglycosides
from .functions import aminopenicillins
from .functions import antifungals
from .functions import antimycobacterials
from .functions import betalactams
from .functions import carbapenems
from .functions import cephalosporins
from .functions import cephalosporins_1st
from .functions import cephalosporins_2nd
from .functions import cephalosporins_3rd
from .functions import cephalosporins_4th
from .functions import cephalosporins_5th
from .functions import fluoroquinolones
from .functions import glycopeptides
from .functions import lincosamides
from .functions import lipoglycopeptides
from .functions import macrolides
from .functions import nitrofurans
from .functions import oxazolidinones
from .functions import penicillins
from .functions import polymyxins
from .functions import quinolones
from .functions import rifamycins
from .functions import streptogramins
from .functions import tetracyclines
from .functions import trimethoprims
from .functions import ureidopenicillins
from .functions import administrable_per_os
from .functions import administrable_iv
from .functions import not_intrinsic_resistant
from .functions import as_ab
from .functions import is_ab
from .functions import as_av
from .functions import is_av
from .functions import as_disk
from .functions import is_disk
from .functions import as_mic
from .functions import is_mic
from .functions import rescale_mic
from .functions import as_mo
from .functions import is_mo
from .functions import mo_uncertainties
from .functions import mo_renamed
from .functions import mo_failures
from .functions import mo_reset_session
from .functions import mo_cleaning_regex
from .functions import as_sir
from .functions import is_sir
from .functions import is_sir_eligible
from .functions import sir_interpretation_history
from .functions import atc_online_property
from .functions import atc_online_groups
from .functions import atc_online_ddd
from .functions import atc_online_ddd_units
from .functions import av_from_text
from .functions import av_name
from .functions import av_cid
from .functions import av_synonyms
from .functions import av_tradenames
from .functions import av_group
from .functions import av_atc
from .functions import av_loinc
from .functions import av_ddd
from .functions import av_ddd_units
from .functions import av_info
from .functions import av_url
from .functions import av_property
from .functions import availability
from .functions import bug_drug_combinations
from .functions import count_resistant
from .functions import count_susceptible
from .functions import count_S
from .functions import count_SI
from .functions import count_I
from .functions import count_IR
from .functions import count_R
from .functions import count_all
from .functions import n_sir
from .functions import count_df
from .functions import custom_eucast_rules
from .functions import eucast_rules
from .functions import eucast_dosage
from .functions import export_ncbi_biosample
from .functions import first_isolate
from .functions import filter_first_isolate
from .functions import g_test
from .functions import is_new_episode
from .functions import ggplot_pca
from .functions import ggplot_sir
from .functions import geom_sir
from .functions import theme_sir
from .functions import labels_sir_count
from .functions import guess_ab_col
from .functions import italicise_taxonomy
from .functions import italicize_taxonomy
from .functions import inner_join_microorganisms
from .functions import left_join_microorganisms
from .functions import right_join_microorganisms
from .functions import full_join_microorganisms
from .functions import semi_join_microorganisms
from .functions import anti_join_microorganisms
from .functions import key_antimicrobials
from .functions import all_antimicrobials
from .functions import antimicrobials_equal
from .functions import kurtosis
from .functions import like
from .functions import mdro
from .functions import custom_mdro_guideline
from .functions import brmo
from .functions import mrgn
from .functions import mdr_tb
from .functions import mdr_cmi2012
from .functions import eucast_exceptional_phenotypes
from .functions import mean_amr_distance
from .functions import amr_distance_from_row
from .functions import mo_matching_score
from .functions import mo_name
from .functions import mo_fullname
from .functions import mo_shortname
from .functions import mo_subspecies
from .functions import mo_species
from .functions import mo_genus
from .functions import mo_family
from .functions import mo_order
from .functions import mo_class
from .functions import mo_phylum
from .functions import mo_kingdom
from .functions import mo_domain
from .functions import mo_type
from .functions import mo_status
from .functions import mo_pathogenicity
from .functions import mo_gramstain
from .functions import mo_is_gram_negative
from .functions import mo_is_gram_positive
from .functions import mo_is_yeast
from .functions import mo_is_intrinsic_resistant
from .functions import mo_oxygen_tolerance
from .functions import mo_is_anaerobic
from .functions import mo_snomed
from .functions import mo_ref
from .functions import mo_authors
from .functions import mo_year
from .functions import mo_lpsn
from .functions import mo_mycobank
from .functions import mo_gbif
from .functions import mo_rank
from .functions import mo_taxonomy
from .functions import mo_synonyms
from .functions import mo_current
from .functions import mo_group_members
from .functions import mo_info
from .functions import mo_url
from .functions import mo_property
from .functions import pca
from .functions import resistance
from .functions import susceptibility
from .functions import sir_confidence_interval
from .functions import proportion_R
from .functions import proportion_IR
from .functions import proportion_I
from .functions import proportion_SI
from .functions import proportion_S
from .functions import proportion_df
from .functions import sir_df
from .functions import random_mic
from .functions import random_disk
from .functions import random_sir
from .functions import resistance_predict
from .functions import sir_predict
from .functions import ggplot_sir_predict
from .functions import skewness
from .functions import reset_AMR_locale
from .functions import translate_AMR

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BLUE = '\033[94m'
GREEN = '\033[32m'
RESET = '\033[0m'
print(f"{BLUE}AMR:{RESET} Setting up R environment and AMR datasets...", flush=True)
import os
from rpy2 import robjects
from rpy2.robjects import pandas2ri
from rpy2.robjects.packages import importr, isinstalled
import pandas as pd
import importlib.metadata as metadata
# Get the path to the virtual environment
venv_path = os.getenv('VIRTUAL_ENV') # Path to the active virtual environment
if not venv_path:
raise EnvironmentError("No virtual environment detected. Please activate your Python virtual environment.")
# Define R library path within the venv
r_lib_path = os.path.join(venv_path, "R_libs")
# Ensure the R library path exists
os.makedirs(r_lib_path, exist_ok=True)
# Set the R library path in .libPaths
base = importr('base')
base._libPaths(r_lib_path)
# Check if the AMR package is installed in R
if not isinstalled('AMR'):
utils = importr('utils')
utils.install_packages('AMR', repos='https://msberends.r-universe.dev', quiet=True)
# Python package version of AMR
try:
python_amr_version = metadata.version('AMR')
except metadata.PackageNotFoundError:
python_amr_version = None
# R package version of AMR
r_amr_version = robjects.r(f'as.character(packageVersion("AMR", lib.loc = "{r_lib_path}"))')[0]
# Compare R and Python package versions
if python_amr_version and r_amr_version != python_amr_version:
try:
utils = importr('utils')
utils.install_packages('AMR', repos='https://msberends.r-universe.dev', quiet=True)
except Exception as e:
print(f"{BLUE}AMR:{RESET} Could not update: {e}{RESET}", flush=True)
# Activate the automatic conversion between R and pandas DataFrames
pandas2ri.activate()
# example_isolates
example_isolates = pandas2ri.rpy2py(robjects.r('''
df <- AMR::example_isolates
df[] <- lapply(df, function(x) {
if (inherits(x, c("Date", "POSIXt", "factor"))) {
as.character(x)
} else {
x
}
})
df <- df[, !sapply(df, is.list)]
df
'''))
example_isolates['date'] = pd.to_datetime(example_isolates['date'])
# microorganisms
microorganisms = pandas2ri.rpy2py(robjects.r('AMR::microorganisms[, !sapply(AMR::microorganisms, is.list)]'))
antibiotics = pandas2ri.rpy2py(robjects.r('AMR::antibiotics[, !sapply(AMR::antibiotics, is.list)]'))
clinical_breakpoints = pandas2ri.rpy2py(robjects.r('AMR::clinical_breakpoints[, !sapply(AMR::clinical_breakpoints, is.list)]'))
print(f"{BLUE}AMR:{RESET} {GREEN}Done.{RESET}", flush=True)

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import rpy2.robjects as robjects
from rpy2.robjects.packages import importr
from rpy2.robjects.vectors import StrVector, FactorVector, IntVector, FloatVector, DataFrame
from rpy2.robjects import pandas2ri
import pandas as pd
import numpy as np
# Activate automatic conversion between R data frames and pandas data frames
pandas2ri.activate()
# Import the AMR R package
amr_r = importr('AMR')
def convert_to_python(r_output):
# Check if it's a StrVector (R character vector)
if isinstance(r_output, StrVector):
return list(r_output) # Convert to a Python list of strings
# Check if it's a FactorVector (R factor)
elif isinstance(r_output, FactorVector):
return list(r_output) # Convert to a list of integers (factor levels)
# Check if it's an IntVector or FloatVector (numeric R vectors)
elif isinstance(r_output, (IntVector, FloatVector)):
return list(r_output) # Convert to a Python list of integers or floats
# Check if it's a pandas-compatible R data frame
elif isinstance(r_output, pd.DataFrame):
return r_output # Return as pandas DataFrame (already converted by pandas2ri)
elif isinstance(r_output, DataFrame):
return pandas2ri.rpy2py(r_output) # Return as pandas DataFrame
# Check if the input is a NumPy array and has a string data type
if isinstance(r_output, np.ndarray) and np.issubdtype(r_output.dtype, np.str_):
return r_output.tolist() # Convert to a regular Python list
# Fall-back
return r_output
def ab_from_text(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_from_text(*args, **kwargs))
def ab_name(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_name(x, *args, **kwargs))
def ab_cid(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_cid(x, *args, **kwargs))
def ab_synonyms(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_synonyms(x, *args, **kwargs))
def ab_tradenames(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_tradenames(x, *args, **kwargs))
def ab_group(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_group(x, *args, **kwargs))
def ab_atc(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_atc(x, *args, **kwargs))
def ab_atc_group1(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_atc_group1(x, *args, **kwargs))
def ab_atc_group2(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_atc_group2(x, *args, **kwargs))
def ab_loinc(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_loinc(x, *args, **kwargs))
def ab_ddd(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_ddd(x, *args, **kwargs))
def ab_ddd_units(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_ddd_units(x, *args, **kwargs))
def ab_info(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_info(x, *args, **kwargs))
def ab_url(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_url(x, *args, **kwargs))
def ab_property(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_property(x, *args, **kwargs))
def add_custom_antimicrobials(x):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.add_custom_antimicrobials(x))
def clear_custom_antimicrobials(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.clear_custom_antimicrobials(*args, **kwargs))
def add_custom_microorganisms(x):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.add_custom_microorganisms(x))
def clear_custom_microorganisms(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.clear_custom_microorganisms(*args, **kwargs))
def age(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.age(x, *args, **kwargs))
def age_groups(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.age_groups(x, *args, **kwargs))
def antibiogram(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.antibiogram(*args, **kwargs))
def ab_class(ab_class, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_class(ab_class, *args, **kwargs))
def ab_selector(filter, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ab_selector(filter, *args, **kwargs))
def aminoglycosides(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.aminoglycosides(only_sir_columns = False, *args, **kwargs))
def aminopenicillins(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.aminopenicillins(only_sir_columns = False, *args, **kwargs))
def antifungals(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.antifungals(only_sir_columns = False, *args, **kwargs))
def antimycobacterials(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.antimycobacterials(only_sir_columns = False, *args, **kwargs))
def betalactams(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.betalactams(only_sir_columns = False, *args, **kwargs))
def carbapenems(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.carbapenems(only_sir_columns = False, *args, **kwargs))
def cephalosporins(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.cephalosporins(only_sir_columns = False, *args, **kwargs))
def cephalosporins_1st(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.cephalosporins_1st(only_sir_columns = False, *args, **kwargs))
def cephalosporins_2nd(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.cephalosporins_2nd(only_sir_columns = False, *args, **kwargs))
def cephalosporins_3rd(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.cephalosporins_3rd(only_sir_columns = False, *args, **kwargs))
def cephalosporins_4th(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.cephalosporins_4th(only_sir_columns = False, *args, **kwargs))
def cephalosporins_5th(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.cephalosporins_5th(only_sir_columns = False, *args, **kwargs))
def fluoroquinolones(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.fluoroquinolones(only_sir_columns = False, *args, **kwargs))
def glycopeptides(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.glycopeptides(only_sir_columns = False, *args, **kwargs))
def lincosamides(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.lincosamides(only_sir_columns = False, *args, **kwargs))
def lipoglycopeptides(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.lipoglycopeptides(only_sir_columns = False, *args, **kwargs))
def macrolides(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.macrolides(only_sir_columns = False, *args, **kwargs))
def nitrofurans(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.nitrofurans(only_sir_columns = False, *args, **kwargs))
def oxazolidinones(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.oxazolidinones(only_sir_columns = False, *args, **kwargs))
def penicillins(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.penicillins(only_sir_columns = False, *args, **kwargs))
def polymyxins(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.polymyxins(only_sir_columns = False, *args, **kwargs))
def quinolones(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.quinolones(only_sir_columns = False, *args, **kwargs))
def rifamycins(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.rifamycins(only_sir_columns = False, *args, **kwargs))
def streptogramins(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.streptogramins(only_sir_columns = False, *args, **kwargs))
def tetracyclines(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.tetracyclines(only_sir_columns = False, *args, **kwargs))
def trimethoprims(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.trimethoprims(only_sir_columns = False, *args, **kwargs))
def ureidopenicillins(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ureidopenicillins(only_sir_columns = False, *args, **kwargs))
def administrable_per_os(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.administrable_per_os(only_sir_columns = False, *args, **kwargs))
def administrable_iv(only_sir_columns = False, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.administrable_iv(only_sir_columns = False, *args, **kwargs))
def not_intrinsic_resistant(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.not_intrinsic_resistant(*args, **kwargs))
def as_ab(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.as_ab(x, *args, **kwargs))
def is_ab(x):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.is_ab(x))
def as_av(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.as_av(x, *args, **kwargs))
def is_av(x):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.is_av(x))
def as_disk(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.as_disk(x, *args, **kwargs))
def is_disk(x):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.is_disk(x))
def as_mic(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.as_mic(x, *args, **kwargs))
def is_mic(x):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.is_mic(x))
def rescale_mic(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.rescale_mic(x, *args, **kwargs))
def as_mo(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.as_mo(*args, **kwargs))
def is_mo(x):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.is_mo(x))
def mo_uncertainties(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_uncertainties(*args, **kwargs))
def mo_renamed(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_renamed(*args, **kwargs))
def mo_failures(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_failures(*args, **kwargs))
def mo_reset_session(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_reset_session(*args, **kwargs))
def mo_cleaning_regex(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_cleaning_regex(*args, **kwargs))
def as_sir(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.as_sir(x, *args, **kwargs))
def is_sir(x):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.is_sir(x))
def is_sir_eligible(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.is_sir_eligible(x, *args, **kwargs))
def sir_interpretation_history(clean):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.sir_interpretation_history(clean))
def atc_online_property(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.atc_online_property(*args, **kwargs))
def atc_online_groups(atc_code, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.atc_online_groups(atc_code, *args, **kwargs))
def atc_online_ddd(atc_code, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.atc_online_ddd(atc_code, *args, **kwargs))
def atc_online_ddd_units(atc_code, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.atc_online_ddd_units(atc_code, *args, **kwargs))
def av_from_text(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_from_text(*args, **kwargs))
def av_name(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_name(x, *args, **kwargs))
def av_cid(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_cid(x, *args, **kwargs))
def av_synonyms(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_synonyms(x, *args, **kwargs))
def av_tradenames(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_tradenames(x, *args, **kwargs))
def av_group(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_group(x, *args, **kwargs))
def av_atc(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_atc(x, *args, **kwargs))
def av_loinc(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_loinc(x, *args, **kwargs))
def av_ddd(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_ddd(x, *args, **kwargs))
def av_ddd_units(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_ddd_units(x, *args, **kwargs))
def av_info(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_info(x, *args, **kwargs))
def av_url(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_url(x, *args, **kwargs))
def av_property(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.av_property(x, *args, **kwargs))
def availability(tbl, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.availability(tbl, *args, **kwargs))
def bug_drug_combinations(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.bug_drug_combinations(x, *args, **kwargs))
def count_resistant(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.count_resistant(*args, **kwargs))
def count_susceptible(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.count_susceptible(*args, **kwargs))
def count_S(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.count_S(*args, **kwargs))
def count_SI(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.count_SI(*args, **kwargs))
def count_I(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.count_I(*args, **kwargs))
def count_IR(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.count_IR(*args, **kwargs))
def count_R(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.count_R(*args, **kwargs))
def count_all(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.count_all(*args, **kwargs))
def n_sir(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.n_sir(*args, **kwargs))
def count_df(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.count_df(*args, **kwargs))
def custom_eucast_rules(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.custom_eucast_rules(*args, **kwargs))
def eucast_rules(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.eucast_rules(*args, **kwargs))
def eucast_dosage(ab, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.eucast_dosage(ab, *args, **kwargs))
def export_ncbi_biosample(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.export_ncbi_biosample(*args, **kwargs))
def first_isolate(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.first_isolate(*args, **kwargs))
def filter_first_isolate(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.filter_first_isolate(*args, **kwargs))
def g_test(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.g_test(x, *args, **kwargs))
def is_new_episode(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.is_new_episode(x, *args, **kwargs))
def ggplot_pca(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ggplot_pca(*args, **kwargs))
def ggplot_sir(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ggplot_sir(*args, **kwargs))
def geom_sir(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.geom_sir(*args, **kwargs))
def theme_sir(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.theme_sir(*args, **kwargs))
def labels_sir_count(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.labels_sir_count(*args, **kwargs))
def guess_ab_col(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.guess_ab_col(*args, **kwargs))
def italicise_taxonomy(string, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.italicise_taxonomy(string, *args, **kwargs))
def italicize_taxonomy(string, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.italicize_taxonomy(string, *args, **kwargs))
def inner_join_microorganisms(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.inner_join_microorganisms(x, *args, **kwargs))
def left_join_microorganisms(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.left_join_microorganisms(x, *args, **kwargs))
def right_join_microorganisms(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.right_join_microorganisms(x, *args, **kwargs))
def full_join_microorganisms(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.full_join_microorganisms(x, *args, **kwargs))
def semi_join_microorganisms(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.semi_join_microorganisms(x, *args, **kwargs))
def anti_join_microorganisms(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.anti_join_microorganisms(x, *args, **kwargs))
def key_antimicrobials(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.key_antimicrobials(*args, **kwargs))
def all_antimicrobials(x = None, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.all_antimicrobials(x = None, *args, **kwargs))
def antimicrobials_equal(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.antimicrobials_equal(*args, **kwargs))
def kurtosis(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.kurtosis(x, *args, **kwargs))
def like(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.like(x, *args, **kwargs))
def mdro(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mdro(*args, **kwargs))
def custom_mdro_guideline(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.custom_mdro_guideline(*args, **kwargs))
def brmo(x = None, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.brmo(x = None, *args, **kwargs))
def mrgn(x = None, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mrgn(x = None, *args, **kwargs))
def mdr_tb(x = None, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mdr_tb(x = None, *args, **kwargs))
def mdr_cmi2012(x = None, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mdr_cmi2012(x = None, *args, **kwargs))
def eucast_exceptional_phenotypes(x = None, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.eucast_exceptional_phenotypes(x = None, *args, **kwargs))
def mean_amr_distance(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mean_amr_distance(x, *args, **kwargs))
def amr_distance_from_row(amr_distance, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.amr_distance_from_row(amr_distance, *args, **kwargs))
def mo_matching_score(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_matching_score(x, *args, **kwargs))
def mo_name(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_name(*args, **kwargs))
def mo_fullname(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_fullname(*args, **kwargs))
def mo_shortname(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_shortname(*args, **kwargs))
def mo_subspecies(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_subspecies(*args, **kwargs))
def mo_species(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_species(*args, **kwargs))
def mo_genus(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_genus(*args, **kwargs))
def mo_family(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_family(*args, **kwargs))
def mo_order(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_order(*args, **kwargs))
def mo_class(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_class(*args, **kwargs))
def mo_phylum(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_phylum(*args, **kwargs))
def mo_kingdom(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_kingdom(*args, **kwargs))
def mo_domain(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_domain(*args, **kwargs))
def mo_type(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_type(*args, **kwargs))
def mo_status(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_status(*args, **kwargs))
def mo_pathogenicity(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_pathogenicity(*args, **kwargs))
def mo_gramstain(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_gramstain(*args, **kwargs))
def mo_is_gram_negative(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_is_gram_negative(*args, **kwargs))
def mo_is_gram_positive(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_is_gram_positive(*args, **kwargs))
def mo_is_yeast(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_is_yeast(*args, **kwargs))
def mo_is_intrinsic_resistant(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_is_intrinsic_resistant(*args, **kwargs))
def mo_oxygen_tolerance(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_oxygen_tolerance(*args, **kwargs))
def mo_is_anaerobic(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_is_anaerobic(*args, **kwargs))
def mo_snomed(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_snomed(*args, **kwargs))
def mo_ref(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_ref(*args, **kwargs))
def mo_authors(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_authors(*args, **kwargs))
def mo_year(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_year(*args, **kwargs))
def mo_lpsn(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_lpsn(*args, **kwargs))
def mo_mycobank(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_mycobank(*args, **kwargs))
def mo_gbif(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_gbif(*args, **kwargs))
def mo_rank(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_rank(*args, **kwargs))
def mo_taxonomy(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_taxonomy(*args, **kwargs))
def mo_synonyms(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_synonyms(*args, **kwargs))
def mo_current(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_current(x, *args, **kwargs))
def mo_group_members(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_group_members(*args, **kwargs))
def mo_info(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_info(*args, **kwargs))
def mo_url(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_url(*args, **kwargs))
def mo_property(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.mo_property(*args, **kwargs))
def pca(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.pca(*args, **kwargs))
def resistance(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.resistance(*args, **kwargs))
def susceptibility(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.susceptibility(*args, **kwargs))
def sir_confidence_interval(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.sir_confidence_interval(*args, **kwargs))
def proportion_R(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.proportion_R(*args, **kwargs))
def proportion_IR(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.proportion_IR(*args, **kwargs))
def proportion_I(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.proportion_I(*args, **kwargs))
def proportion_SI(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.proportion_SI(*args, **kwargs))
def proportion_S(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.proportion_S(*args, **kwargs))
def proportion_df(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.proportion_df(*args, **kwargs))
def sir_df(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.sir_df(*args, **kwargs))
def random_mic(size = None, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.random_mic(size = None, *args, **kwargs))
def random_disk(size = None, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.random_disk(size = None, *args, **kwargs))
def random_sir(size = None, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.random_sir(size = None, *args, **kwargs))
def resistance_predict(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.resistance_predict(*args, **kwargs))
def sir_predict(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.sir_predict(*args, **kwargs))
def ggplot_sir_predict(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.ggplot_sir_predict(*args, **kwargs))
def skewness(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.skewness(x, *args, **kwargs))
def reset_AMR_locale(*args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.reset_AMR_locale(*args, **kwargs))
def translate_AMR(x, *args, **kwargs):
"""See our website of the R package for the manual: https://msberends.github.io/AMR/index.html"""
return convert_to_python(amr_r.translate_AMR(x, *args, **kwargs))

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---
title: "AMR for Python"
output:
rmarkdown::html_vignette:
toc: true
toc_depth: 3
vignette: >
%\VignetteIndexEntry{AMR for Python}
%\VignetteEncoding{UTF-8}
%\VignetteEngine{knitr::rmarkdown}
editor_options:
chunk_output_type: console
---
```{r setup, include = FALSE, results = 'markup'}
knitr::opts_chunk$set(
warning = FALSE,
collapse = TRUE,
comment = "#>",
fig.width = 7.5,
fig.height = 5
)
```
# Introduction
The `AMR` package for R is a powerful tool for antimicrobial resistance (AMR) analysis. It provides extensive features for handling microbial and antimicrobial data. However, for those who work primarily in Python, we now have a more intuitive option available: the [`AMR` Python Package Index](https://pypi.org/project/AMR/).
This Python package is a wrapper round the `AMR` R package. It uses the `rpy2` package internally. Despite the need to have R installed, Python users can now easily work with AMR data directly through Python code.
# Install
1. Since the Python package is available on the official [Python Package Index](https://pypi.org/project/AMR/), you can just run:
```bash
pip install AMR
```
2. Make sure you have R installed. There is **no need to install the `AMR` R package**, as it will be installed automatically.
For Linux:
```bash
# Ubuntu / Debian
sudo apt install r-base
# Fedora:
sudo dnf install R
# CentOS/RHEL
sudo yum install R
```
For macOS (using [Homebrew](https://brew.sh)):
```bash
brew install r
```
For Windows, visit the [CRAN download page](https://cran.r-project.org) to download and install R.
# Examples of Usage
## Cleaning Taxonomy
Here’s an example that demonstrates how to clean microorganism and drug names using the `AMR` Python package:
```python
import pandas as pd
import AMR
# Sample data
data = {
"MOs": ['E. coli', 'ESCCOL', 'esco', 'Esche coli'],
"Drug": ['Cipro', 'CIP', 'J01MA02', 'Ciproxin']
}
df = pd.DataFrame(data)
# Use AMR functions to clean microorganism and drug names
df['MO_clean'] = AMR.mo_name(df['MOs'])
df['Drug_clean'] = AMR.ab_name(df['Drug'])
# Display the results
print(df)
```
| MOs | Drug | MO_clean | Drug_clean |
|-------------|-----------|--------------------|---------------|
| E. coli | Cipro | Escherichia coli | Ciprofloxacin |
| ESCCOL | CIP | Escherichia coli | Ciprofloxacin |
| esco | J01MA02 | Escherichia coli | Ciprofloxacin |
| Esche coli | Ciproxin | Escherichia coli | Ciprofloxacin |
### Explanation
* **mo_name:** This function standardises microorganism names. Here, different variations of *Escherichia coli* (such as "E. coli", "ESCCOL", "esco", and "Esche coli") are all converted into the correct, standardised form, "Escherichia coli".
* **ab_name**: Similarly, this function standardises antimicrobial names. The different representations of ciprofloxacin (e.g., "Cipro", "CIP", "J01MA02", and "Ciproxin") are all converted to the standard name, "Ciprofloxacin".
## Taxonomic Data Sets Now in Python!
As a Python user, you might like that the most important data sets of the `AMR` R package, `microorganisms`, `antibiotics`, `clinical_breakpoints`, and `example_isolates`, are now available as regular Python data frames:
```python
AMR.microorganisms
```
| mo | fullname | status | kingdom | gbif | gbif_parent | gbif_renamed_to | prevalence |
|--------------|------------------------------------|----------|----------|-----------|-------------|-----------------|------------|
| B_GRAMN | (unknown Gram-negatives) | unknown | Bacteria | None | None | None | 2.0 |
| B_GRAMP | (unknown Gram-positives) | unknown | Bacteria | None | None | None | 2.0 |
| B_ANAER-NEG | (unknown anaerobic Gram-negatives) | unknown | Bacteria | None | None | None | 2.0 |
| B_ANAER-POS | (unknown anaerobic Gram-positives) | unknown | Bacteria | None | None | None | 2.0 |
| B_ANAER | (unknown anaerobic bacteria) | unknown | Bacteria | None | None | None | 2.0 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| B_ZYMMN_POMC | Zymomonas pomaceae | accepted | Bacteria | 10744418 | 3221412 | None | 2.0 |
| B_ZYMPH | Zymophilus | synonym | Bacteria | None | 9475166 | None | 2.0 |
| B_ZYMPH_PCVR | Zymophilus paucivorans | synonym | Bacteria | None | None | None | 2.0 |
| B_ZYMPH_RFFN | Zymophilus raffinosivorans | synonym | Bacteria | None | None | None | 2.0 |
| F_ZYZYG | Zyzygomyces | unknown | Fungi | None | 7581 | None | 2.0 |
```python
AMR.antibiotics
```
| ab | cid | name | group | oral_ddd | oral_units | iv_ddd | iv_units |
|-----|-------------|----------------------|----------------------------|----------|------------|--------|----------|
| AMA | 4649.0 | 4-aminosalicylic acid| Antimycobacterials | 12.00 | g | NaN | None |
| ACM | 6450012.0 | Acetylmidecamycin | Macrolides/lincosamides | NaN | None | NaN | None |
| ASP | 49787020.0 | Acetylspiramycin | Macrolides/lincosamides | NaN | None | NaN | None |
| ALS | 8954.0 | Aldesulfone sodium | Other antibacterials | 0.33 | g | NaN | None |
| AMK | 37768.0 | Amikacin | Aminoglycosides | NaN | None | 1.0 | g |
| ... | ... | ... | ... | ... | ... | ... | ... |
| VIR | 11979535.0 | Virginiamycine | Other antibacterials | NaN | None | NaN | None |
| VOR | 71616.0 | Voriconazole | Antifungals/antimycotics | 0.40 | g | 0.4 | g |
| XBR | 72144.0 | Xibornol | Other antibacterials | NaN | None | NaN | None |
| ZID | 77846445.0 | Zidebactam | Other antibacterials | NaN | None | NaN | None |
| ZFD | NaN | Zoliflodacin | None | NaN | None | NaN | None |
## Calculating AMR
```python
import AMR
import pandas as pd
df = AMR.example_isolates
result = AMR.resistance(df["AMX"])
print(result)
```
```
[0.59555556]
```
## Generating Antibiograms
One of the core functions of the `AMR` package is generating an antibiogram, a table that summarises the antimicrobial susceptibility of bacterial isolates. Here’s how you can generate an antibiogram from Python:
```python
result2a = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]])
print(result2a)
```
| Pathogen | Amoxicillin | Ciprofloxacin | Piperacillin/tazobactam |
|-----------------|-----------------|-----------------|--------------------------|
| CoNS | 7% (10/142) | 73% (183/252) | 30% (10/33) |
| E. coli | 50% (196/392) | 88% (399/456) | 94% (393/416) |
| K. pneumoniae | 0% (0/58) | 96% (53/55) | 89% (47/53) |
| P. aeruginosa | 0% (0/30) | 100% (30/30) | None |
| P. mirabilis | None | 94% (34/36) | None |
| S. aureus | 6% (8/131) | 90% (171/191) | None |
| S. epidermidis | 1% (1/91) | 64% (87/136) | None |
| S. hominis | None | 80% (56/70) | None |
| S. pneumoniae | 100% (112/112) | None | 100% (112/112) |
```python
result2b = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]], mo_transform = "gramstain")
print(result2b)
```
| Pathogen | Amoxicillin | Ciprofloxacin | Piperacillin/tazobactam |
|----------------|-----------------|------------------|--------------------------|
| Gram-negative | 36% (226/631) | 91% (621/684) | 88% (565/641) |
| Gram-positive | 43% (305/703) | 77% (560/724) | 86% (296/345) |
In this example, we generate an antibiogram by selecting various antibiotics.
# Conclusion
With the `AMR` Python package, Python users can now effortlessly call R functions from the `AMR` R package. This eliminates the need for complex `rpy2` configurations and provides a clean, easy-to-use interface for antimicrobial resistance analysis. The examples provided above demonstrate how this can be applied to typical workflows, such as standardising microorganism and antimicrobial names or calculating resistance.
By just running `import AMR`, users can seamlessly integrate the robust features of the R `AMR` package into Python workflows.
Whether you're cleaning data or analysing resistance patterns, the `AMR` Python package makes it easy to work with AMR data in Python.

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from setuptools import setup, find_packages
setup(
name='AMR',
version='2.1.1.9103',
packages=find_packages(),
install_requires=[
'rpy2',
'numpy',
'pandas',
],
author='Dr. Matthijs Berends',
author_email='m.s.berends@umcg.nl',
description='A Python wrapper for the AMR R package',
long_description=open('README.md').read(),
long_description_content_type='text/markdown',
url='https://github.com/msberends/AMR',
project_urls={
'Bug Tracker': 'https://github.com/msberends/AMR/issues',
},
license='GPL 2',
classifiers=[
'Programming Language :: Python :: 3',
'Operating System :: OS Independent',
],
python_requires='>=3.6',
)

24
R/sir.R
View File

@ -970,6 +970,7 @@ as_sir_method <- function(method_short,
warning_("The following animal host(s) could not be coerced: ", vector_and(host.bak[is.na(host) & !is.na(host.bak)]), immediate = TRUE) warning_("The following animal host(s) could not be coerced: ", vector_and(host.bak[is.na(host) & !is.na(host.bak)]), immediate = TRUE)
message() # new line message() # new line
} }
# TODO add a switch to turn this off? In interactive sessions perhaps ask the user. Default should be On.
if (breakpoint_type == "animal" && message_not_thrown_before("as.sir", "host_missing_breakpoints")) { if (breakpoint_type == "animal" && message_not_thrown_before("as.sir", "host_missing_breakpoints")) {
if (guideline_coerced %like% "CLSI") { if (guideline_coerced %like% "CLSI") {
message_("Please note that in the absence of specific veterinary breakpoints for certain animal hosts, the CLSI guideline VET09 will be applied where possible.\n\n") message_("Please note that in the absence of specific veterinary breakpoints for certain animal hosts, the CLSI guideline VET09 will be applied where possible.\n\n")
@ -1053,6 +1054,8 @@ as_sir_method <- function(method_short,
) )
} }
} }
# TODO set uti to specimen column here
if (length(ab) == 1 && ab %like% paste0("as.", method_short)) { if (length(ab) == 1 && ab %like% paste0("as.", method_short)) {
stop_("No unambiguous name was supplied about the antibiotic (argument `ab`). See ?as.sir.", call = FALSE) stop_("No unambiguous name was supplied about the antibiotic (argument `ab`). See ?as.sir.", call = FALSE)
@ -1238,6 +1241,8 @@ as_sir_method <- function(method_short,
new_sir <- rep(NA_sir_, length(rows)) new_sir <- rep(NA_sir_, length(rows))
# find different mo properties, as fast as possible # find different mo properties, as fast as possible
# TODO in case of VET09, we need to keep E. coli, also when users have Proteus in their data set
# TODO look up which species, at least E. coli - also Staph or Strep?
mo_current_genus <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$genus[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$fullname)] mo_current_genus <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$genus[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$fullname)]
mo_current_family <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$family[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$fullname)] mo_current_family <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$family[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$fullname)]
mo_current_order <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$order[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$fullname)] mo_current_order <- AMR_env$MO_lookup$mo[match(AMR_env$MO_lookup$order[match(mo_current, AMR_env$MO_lookup$mo)], AMR_env$MO_lookup$fullname)]
@ -1262,6 +1267,7 @@ as_sir_method <- function(method_short,
) )
# gather all available breakpoints for current MO # gather all available breakpoints for current MO
# TODO for VET09 do not filter out E. coli and such
breakpoints_current <- breakpoints %pm>% breakpoints_current <- breakpoints %pm>%
subset(ab == ab_current) %pm>% subset(ab == ab_current) %pm>%
subset(mo %in% c( subset(mo %in% c(
@ -1271,14 +1277,17 @@ as_sir_method <- function(method_short,
mo_current_other mo_current_other
)) ))
# TODO are operators considered??
# This seems to not work well: as.sir(as.mic(c(4, ">4", ">=4", 8, ">8", ">=8")), ab = "AMC", mo = "E. coli", breakpoint_type = "animal", host = "dogs", guideline = "CLSI 2024")
## fall-back methods for veterinary guidelines ---- ## fall-back methods for veterinary guidelines ----
if (breakpoint_type == "animal" && !host_current %in% breakpoints_current$host) { if (breakpoint_type == "animal" && !host_current %in% breakpoints_current$host) {
if (guideline_coerced %like% "CLSI") { if (guideline_coerced %like% "CLSI") {
# VET09 says that staph/strep/enterococcus BP can be extrapolated to all Gr+ cocci except for intrinsic resistance, so take all Gr+ cocci: # VET09 says that staph/strep/enterococcus BP can be extrapolated to all Gr+ cocci except for intrinsic resistance, so take all Gr+ cocci:
all_gram_pos_genera <- c("B_STPHY", "B_STRPT", "B_PPTST", "B_AERCC", "B_MCRCCC", "B_TRPRL") gram_plus_cocci_vet09 <- microorganisms$mo[microorganisms$genus %in% c("Staphylococcus", "Streptococcus", "Peptostreptococcus", "Aerococcus", "Micrococcus") & microorganisms$rank == "genus"] # TODO should probably include genera that were either of these before
# HUMAN SUBSTITUTES # HUMAN SUBSTITUTES
if (ab_current == "AZM" && mo_current_genus %in% all_gram_pos_genera && host_current %in% c("dogs", "cats", "horse")) { if (ab_current == "AZM" && mo_current_genus %in% gram_plus_cocci_vet09 && host_current %in% c("dogs", "cats", "horse")) {
# azithro can take human breakpoints for these agents # azithro can take human breakpoints for these agents
breakpoints_current <- breakpoints_current %pm>% subset(host == "human") breakpoints_current <- breakpoints_current %pm>% subset(host == "human")
notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in Gram-positive cocci based on CLSI VET09.")) notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in Gram-positive cocci based on CLSI VET09."))
@ -1290,7 +1299,7 @@ as_sir_method <- function(method_short,
# cefta can take human breakpoints for these agents # cefta can take human breakpoints for these agents
breakpoints_current <- breakpoints_current %pm>% subset(host == "human") breakpoints_current <- breakpoints_current %pm>% subset(host == "human")
notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in Enterobacterales and ", font_italic("P. aeruginosa"), " based on CLSI VET09.")) notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in Enterobacterales and ", font_italic("P. aeruginosa"), " based on CLSI VET09."))
} else if (ab_current == "ERY" && mo_current_genus %in% all_gram_pos_genera && host_current %in% c("dogs", "cats", "horse")) { } else if (ab_current == "ERY" && mo_current_genus %in% gram_plus_cocci_vet09 && host_current %in% c("dogs", "cats", "horse")) {
# erythro can take human breakpoints for these agents # erythro can take human breakpoints for these agents
breakpoints_current <- breakpoints_current %pm>% subset(host == "human") breakpoints_current <- breakpoints_current %pm>% subset(host == "human")
notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in Gram-positive cocci based on CLSI VET09.")) notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in Gram-positive cocci based on CLSI VET09."))
@ -1298,7 +1307,7 @@ as_sir_method <- function(method_short,
# imipenem can take human breakpoints for these agents # imipenem can take human breakpoints for these agents
breakpoints_current <- breakpoints_current %pm>% subset(host == "human") breakpoints_current <- breakpoints_current %pm>% subset(host == "human")
notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in Enterobacterales and ", font_italic("P. aeruginosa"), " based on CLSI VET09.")) notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in Enterobacterales and ", font_italic("P. aeruginosa"), " based on CLSI VET09."))
} else if (ab_current == "LNZ" && mo_current_genus %in% all_gram_pos_genera && host_current %in% c("dogs", "cats")) { } else if (ab_current == "LNZ" && mo_current_genus %in% gram_plus_cocci_vet09 && host_current %in% c("dogs", "cats")) {
# linezolid can take human breakpoints for these agents # linezolid can take human breakpoints for these agents
breakpoints_current <- breakpoints_current %pm>% subset(host == "human") breakpoints_current <- breakpoints_current %pm>% subset(host == "human")
notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in staphylococci/enterococci based on CLSI VET09.")) notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in staphylococci/enterococci based on CLSI VET09."))
@ -1306,11 +1315,11 @@ as_sir_method <- function(method_short,
# nitro can take human breakpoints for these agents # nitro can take human breakpoints for these agents
breakpoints_current <- breakpoints_current %pm>% subset(host == "human") breakpoints_current <- breakpoints_current %pm>% subset(host == "human")
notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " based on CLSI VET09.")) notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " based on CLSI VET09."))
} else if (ab_current == "PEN" && mo_current_genus %in% all_gram_pos_genera && host_current %in% c("dogs", "cats")) { } else if (ab_current == "PEN" && mo_current_genus %in% gram_plus_cocci_vet09 && host_current %in% c("dogs", "cats")) {
# penicillin can take human breakpoints for these agents # penicillin can take human breakpoints for these agents
breakpoints_current <- breakpoints_current %pm>% subset(host == "human") breakpoints_current <- breakpoints_current %pm>% subset(host == "human")
notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in Gram-positive cocci based on CLSI VET09.")) notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in Gram-positive cocci based on CLSI VET09."))
} else if (ab_current == "RIF" && mo_current_genus %in% all_gram_pos_genera && host_current %in% c("dogs", "cats")) { } else if (ab_current == "RIF" && mo_current_genus %in% gram_plus_cocci_vet09 && host_current %in% c("dogs", "cats")) {
# rifampicin can take human breakpoints for staphylococci # rifampicin can take human breakpoints for staphylococci
breakpoints_current <- breakpoints_current %pm>% subset(host == "human") breakpoints_current <- breakpoints_current %pm>% subset(host == "human")
notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in staphylococci based on CLSI VET09.")) notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", ab_formatted, " in staphylococci based on CLSI VET09."))
@ -1325,7 +1334,8 @@ as_sir_method <- function(method_short,
} else if (host_current %in% c("dogs", "cats") && (mo_current_genus %in% c("B_AMYCS", "B_NOCRD", "B_CMPYL", "B_CRYNB", "B_ENTRC", "B_MYCBC", "B_PSDMN", "B_AERMN") | mo_current_class == "B_[CLS]_BTPRTBCT" | mo_current == "B_LISTR_MNCY")) { } else if (host_current %in% c("dogs", "cats") && (mo_current_genus %in% c("B_AMYCS", "B_NOCRD", "B_CMPYL", "B_CRYNB", "B_ENTRC", "B_MYCBC", "B_PSDMN", "B_AERMN") | mo_current_class == "B_[CLS]_BTPRTBCT" | mo_current == "B_LISTR_MNCY")) {
# dog breakpoints if no canine/feline # dog breakpoints if no canine/feline
breakpoints_current <- breakpoints_current %pm>% subset(host == "human") # TODO do we still have dogs breakpoints at this point???
breakpoints_current <- breakpoints_current %pm>% subset(host == "human") # WRONG
notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", mo_formatted, " based on CLSI VET09.")) notes_current <- c(notes_current, paste0("Using ", font_bold("human"), " breakpoints for ", mo_formatted, " based on CLSI VET09."))
} else { } else {

69
data-raw/_generate_python_wrapper.sh
View File

@ -30,13 +30,15 @@
# ==================================================================== # # ==================================================================== #
# Clean up # Clean up
rm -rf python_wrapper/AMR/* rm -rf ../PythonPackage/AMR/*
mkdir -p python_wrapper/AMR/AMR mkdir -p ../PythonPackage/AMR/AMR
# Output Python file # Output Python file
functions_file="python_wrapper/AMR/AMR/functions.py" setup_file="../PythonPackage/AMR/setup.py"
datasets_file="python_wrapper/AMR/AMR/datasets.py" functions_file="../PythonPackage/AMR/AMR/functions.py"
init_file="python_wrapper/AMR/AMR/__init__.py" datasets_file="../PythonPackage/AMR/AMR/datasets.py"
init_file="../PythonPackage/AMR/AMR/__init__.py"
# Write header to the datasets Python file, including the convert_to_python function # Write header to the datasets Python file, including the convert_to_python function
cat <<EOL > "$datasets_file" cat <<EOL > "$datasets_file"
@ -46,31 +48,48 @@ RESET = '\033[0m'
print(f"{BLUE}AMR:{RESET} Setting up R environment and AMR datasets...", flush=True) print(f"{BLUE}AMR:{RESET} Setting up R environment and AMR datasets...", flush=True)
import os
from rpy2 import robjects from rpy2 import robjects
from rpy2.robjects import pandas2ri from rpy2.robjects import pandas2ri
from rpy2.robjects.packages import importr, isinstalled from rpy2.robjects.packages import importr, isinstalled
import pandas as pd import pandas as pd
# import importlib.metadata as metadata import importlib.metadata as metadata
# Check if AMR package is installed in R # Get the path to the virtual environment
venv_path = os.getenv('VIRTUAL_ENV') # Path to the active virtual environment
if not venv_path:
raise EnvironmentError("No virtual environment detected. Please activate your Python virtual environment.")
# Define R library path within the venv
r_lib_path = os.path.join(venv_path, "R_libs")
# Ensure the R library path exists
os.makedirs(r_lib_path, exist_ok=True)
# Set the R library path in .libPaths
base = importr('base')
base._libPaths(r_lib_path)
# Check if the AMR package is installed in R
if not isinstalled('AMR'): if not isinstalled('AMR'):
utils = importr('utils') utils = importr('utils')
utils.install_packages('AMR', repos='https://msberends.r-universe.dev') utils.install_packages('AMR', repos='https://msberends.r-universe.dev', quiet=True)
# Python package version of AMR # Python package version of AMR
try:
python_amr_version = metadata.version('AMR') python_amr_version = metadata.version('AMR')
except metadata.PackageNotFoundError:
python_amr_version = None
# R package version of AMR # R package version of AMR
# r_amr_version = robjects.r('packageVersion("AMR")')[0] r_amr_version = robjects.r(f'as.character(packageVersion("AMR", lib.loc = "{r_lib_path}"))')[0]
# Compare R and Python package versions # Compare R and Python package versions
# if r_amr_version != python_amr_version: if python_amr_version and r_amr_version != python_amr_version:
# print(f"{BLUE}AMR:{RESET} Version mismatch detected. Updating AMR R package version to {python_amr_version}...", flush=True) try:
# try: utils = importr('utils')
# # Re-install the specific version of AMR in R utils.install_packages('AMR', repos='https://msberends.r-universe.dev', quiet=True)
# utils = importr('utils') except Exception as e:
# utils.install_packages('AMR', repos='https://msberends.r-universe.dev') print(f"{BLUE}AMR:{RESET} Could not update: {e}{RESET}", flush=True)
# except Exception as e:
# print(f"{BLUE}AMR:{RESET} Could not update: {e}{RESET}", flush=True)
# Activate the automatic conversion between R and pandas DataFrames # Activate the automatic conversion between R and pandas DataFrames
pandas2ri.activate() pandas2ri.activate()
@ -237,22 +256,20 @@ done
echo "Python wrapper functions generated in $functions_file." echo "Python wrapper functions generated in $functions_file."
echo "Python wrapper functions listed in $init_file." echo "Python wrapper functions listed in $init_file."
cp ../vignettes/AMR_for_Python.Rmd python_wrapper/AMR/README.md cp ../vignettes/AMR_for_Python.Rmd ../PythonPackage/AMR/README.md
sed -i '1,/^# Introduction$/d' python_wrapper/AMR/README.md sed -i '1,/^# Introduction$/d' ../PythonPackage/AMR/README.md
echo "README copied" echo "README copied"
# Path to your DESCRIPTION file # Path to your DESCRIPTION file
description_file="../DESCRIPTION" description_file="../DESCRIPTION"
# Output setup.py file
functions_file="python_wrapper/AMR/setup.py"
# Extract the relevant fields from DESCRIPTION # Extract the relevant fields from DESCRIPTION
version=$(grep "^Version:" "$description_file" | awk '{print $2}') version=$(grep "^Version:" "$description_file" | awk '{print $2}')
# Write the setup.py file # Write the setup.py file
cat <<EOL > "$functions_file" cat <<EOL > "$setup_file"
from setuptools import setup, find_packages from setuptools import setup, find_packages
setup( setup(
@ -283,8 +300,10 @@ setup(
EOL EOL
# Output completion message # Output completion message
echo "setup.py has been generated in $functions_file." echo "setup.py has been generated in $setup_file."
cd python_wrapper/AMR cd ../PythonPackage/AMR
python3 setup.py sdist bdist_wheel pip3 install build
python3 -m build
# python3 setup.py sdist bdist_wheel