Python wrapper update

.Rbuildignore

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-^.*\.Rproj$
-^\.Rproj\.user$

.gitignore

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-.Rproj.user
-.Rhistory
-.RData
-.Ruserdata
-AMR.Rproj

AMR.egg-info/PKG-INFO

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+Metadata-Version: 2.4
+Name: AMR
+Version: 3.0.1.9091
+Summary: A Python wrapper for the AMR R package
+Home-page: https://github.com/msberends/AMR
+Author: 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
+Dynamic: author
+Dynamic: author-email
+Dynamic: classifier
+Dynamic: description
+Dynamic: description-content-type
+Dynamic: home-page
+Dynamic: license
+Dynamic: project-url
+Dynamic: requires-dist
+Dynamic: requires-python
+Dynamic: summary
+
+
+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](https://pypi.org/project/AMR/).
+
+This Python package is a wrapper around 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.
+
+# Prerequisites
+
+This package was only tested with a [virtual environment (venv)](https://docs.python.org/3/library/venv.html). You can set up such an environment by running:
+
+```python
+# linux and macOS:
+python -m venv /path/to/new/virtual/environment
+
+# Windows:
+python -m venv C:\path\to\new\virtual\environment
+```
+
+Then you can [activate the environment](https://docs.python.org/3/library/venv.html#how-venvs-work), after which the venv is ready to work with.
+
+# Install AMR
+
+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".
+
+## 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.
+
+## 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`, `antimicrobials`, `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.antimicrobials
+```
+
+| 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     |
+
+
+# Installation Channels
+
+## Stable Release (CRAN)
+
+The default `AMR` Python package uses the latest stable version of the `AMR` R package, published on CRAN. After running `pip install AMR`, import it as usual:
+
+```python
+import AMR
+
+AMR.example_isolates
+```
+
+## Development Version (GitHub)
+
+To use the latest development version of the `AMR` R package (sourced directly from GitHub), import the `beta` sub-package and alias it as `AMR`:
+
+```python
+import AMR.beta as AMR
+
+AMR.example_isolates
+```
+
+Aliasing with `as AMR` keeps all downstream code identical to the stable import. Switching between the stable release and the development version requires changing only the import line — nothing else in your script needs to change.
+
+# SIR Classification with `as_sir()`
+
+## Using `enforce_method`
+
+The `as_sir()` function in R uses S3 method dispatch to select the correct calculation method based on the input class: `<mic>` for MIC values and `<disk>` for disk diffusion values. Because Python objects do not carry R class attributes through the `rpy2` bridge, this automatic dispatch may not resolve correctly.
+
+To explicitly specify the input type, use the `enforce_method` argument:
+
+```python
+# Treat the column as MIC values — maps to R's as.sir.mic()
+AMR.as_sir(df["MIC_col"], mo="E. coli", ab="AMX", guideline="EUCAST", enforce_method="mic")
+
+# Treat the column as disk diffusion values — maps to R's as.sir.disk()
+AMR.as_sir(df["disk_col"], mo="E. coli", ab="AMX", guideline="EUCAST", enforce_method="disk")
+```
+
+Without `enforce_method`, R falls back to class-based dispatch on the raw Python input, which may fail or return unexpected results. Always supply `enforce_method` when calling `as_sir()` from Python.
+
+# 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.

AMR.egg-info/SOURCES.txt

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+README.md
+setup.py
+AMR/__init__.py
+AMR/_engine.py
+AMR/beta.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

AMR.egg-info/dependency_links.txt

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+

AMR.egg-info/requires.txt

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+rpy2
+numpy
+pandas

AMR.egg-info/top_level.txt

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+AMR

AMR/__init__.py

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+import sys
+
+_DATASETS = frozenset({
+    'example_isolates', 'microorganisms',
+    'antimicrobials', 'clinical_breakpoints'
+})
+
+class _AMRModule(type(sys.modules[__name__])):
+    """Lazy-loading module: nothing runs until an attribute is accessed."""
+    
+    def __getattr__(self, name):
+        if name in _DATASETS:
+            from .datasets import get
+            return get(name, source="cran")
+        try:
+            from . import functions
+            return getattr(functions, name)
+        except AttributeError:
+            raise AttributeError(
+                f"module 'AMR' has no attribute '{name}'")
+
+sys.modules[__name__].__class__ = _AMRModule
+from .functions import custom_eucast_rules
+from .functions import ab_class
+from .functions import ab_selector
+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 all_sir
+from .functions import all_sir_predictors
+from .functions import all_mic
+from .functions import all_mic_predictors
+from .functions import all_disk
+from .functions import all_disk_predictors
+from .functions import step_mic_log2
+from .functions import step_sir_numeric
+from .functions import amr_course
+from .functions import wisca
+from .functions import antibiogram
+from .functions import retrieve_wisca_parameters
+from .functions import wisca_plot
+from .functions import aminoglycosides
+from .functions import aminopenicillins
+from .functions import antifungals
+from .functions import antimycobacterials
+from .functions import betalactams
+from .functions import betalactams_with_inhibitor
+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 ionophores
+from .functions import isoxazolylpenicillins
+from .functions import lincosamides
+from .functions import lipoglycopeptides
+from .functions import macrolides
+from .functions import monobactams
+from .functions import nitrofurans
+from .functions import oxazolidinones
+from .functions import penicillins
+from .functions import peptides
+from .functions import phenicols
+from .functions import phosphonics
+from .functions import polymyxins
+from .functions import quinolones
+from .functions import rifamycins
+from .functions import spiropyrimidinetriones
+from .functions import streptogramins
+from .functions import sulfonamides
+from .functions import tetracyclines
+from .functions import trimethoprims
+from .functions import ureidopenicillins
+from .functions import amr_class
+from .functions import amr_selector
+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 ab_reset_session
+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 mic_p50
+from .functions import mic_p90
+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_interpretive_rules
+from .functions import custom_mdro_guideline
+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 guess_ab_col
+from .functions import interpretive_rules
+from .functions import eucast_rules
+from .functions import clsi_rules
+from .functions import eucast_dosage
+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 kurtosis
+from .functions import like
+from .functions import mdro
+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_morphology
+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 theme_sir
+from .functions import labels_sir_count
+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 top_n_microorganisms
+from .functions import reset_AMR_locale
+from .functions import translate_AMR

AMR/_engine.py

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+import os
+import sys
+import importlib.metadata as metadata
+
+# Get the path to the virtual environment
+venv_path = sys.prefix
+r_lib_path = os.path.join(venv_path, "R_libs")
+os.makedirs(r_lib_path, exist_ok=True)
+
+# Set environment variable before importing rpy2
+os.environ['R_LIBS_SITE'] = r_lib_path
+
+from rpy2 import robjects
+from rpy2.robjects.vectors import StrVector
+from rpy2.robjects.packages import importr, isinstalled
+
+# Import base and utils once
+base = importr('base')
+utils = importr('utils')
+
+# Silence R console output entirely
+robjects.r('suppressMessages(suppressWarnings(sink(tempfile())))')
+base._libPaths(r_lib_path)
+
+_installed_source = None
+
+def _r_version():
+    """Return the currently installed AMR R package version, or None."""
+    try:
+        return str(robjects.r(
+            f'as.character(packageVersion("AMR", lib.loc = "{r_lib_path}"))')[0])
+    except Exception:
+        return None
+
+def _py_version():
+    """Return the Python AMR package version from metadata, or empty string."""
+    try:
+        return str(metadata.version('AMR'))
+    except metadata.PackageNotFoundError:
+        return ''
+
+def _install_cran():
+    """Install AMR from CRAN into the isolated library."""
+    print("AMR: Installing from CRAN...", flush=True)
+    utils.install_packages(
+        'AMR',
+        repos='https://cloud.r-project.org',
+        lib=r_lib_path,
+        quiet=True
+    )
+
+def _install_github():
+    """Install AMR development version from GitHub into the isolated library."""
+    print("AMR: Installing development version from GitHub...", flush=True)
+    utils.install_packages(
+        StrVector(['remotes', 'desc']),
+        repos='https://cloud.r-project.org',
+        lib=r_lib_path,
+        quiet=True
+    )
+    remotes = importr('remotes', lib_loc=r_lib_path)
+    remotes.install_github('msberends/AMR', lib=r_lib_path, quiet=True)
+
+def ensure_amr(source="cran"):
+    """Ensure AMR is installed from the requested source. Idempotent per source."""
+    global _installed_source
+    
+    if _installed_source == source:
+        return
+    
+    install_fn = _install_github if source == "github" else _install_cran
+    
+    if not isinstalled('AMR', lib_loc=r_lib_path):
+        install_fn()
+    else:
+        # Check for version mismatch and update if needed
+        r_ver = _r_version()
+        py_ver = _py_version()
+        if r_ver != py_ver:
+            try:
+                install_fn()
+            except Exception as e:
+                print(f"AMR: Could not update ({e})", flush=True)
+    
+    print(f"AMR: R package version {_r_version()} ready.", flush=True)
+    _installed_source = source
+
+def restore_sink():
+    """Restore R console output after setup is complete."""
+    try:
+        robjects.r('sink()')
+    except Exception:
+        pass

AMR/beta.py

@@ -0,0 +1,22 @@
+import sys
+
+_DATASETS = frozenset({
+    'example_isolates', 'microorganisms',
+    'antimicrobials', 'clinical_breakpoints'
+})
+
+class _BetaModule(type(sys.modules[__name__])):
+    """Lazy-loading module: installs AMR from GitHub on first access."""
+    
+    def __getattr__(self, name):
+        if name in _DATASETS:
+            from .datasets import get
+            return get(name, source="github")
+        try:
+            from . import functions
+            return getattr(functions, name)
+        except AttributeError:
+            raise AttributeError(
+                f"module 'AMR.beta' has no attribute '{name}'")
+
+sys.modules[__name__].__class__ = _BetaModule

AMR/datasets.py

@@ -0,0 +1,54 @@
+import pandas as pd
+from rpy2 import robjects
+from rpy2.robjects.conversion import localconverter
+from rpy2.robjects import default_converter, numpy2ri, pandas2ri
+
+from ._engine import ensure_amr, restore_sink
+
+_cache = {}
+_loaded_source = None
+
+def _load_datasets(source="cran"):
+    """Load all AMR datasets into the module cache."""
+    global _loaded_source
+    
+    if _cache and _loaded_source == source:
+        return
+    
+    if _cache and _loaded_source != source:
+        _cache.clear()
+    
+    ensure_amr(source)
+    
+    with localconverter(default_converter + numpy2ri.converter + pandas2ri.converter):
+        _cache['example_isolates'] = _load_example_isolates()
+        _cache['microorganisms'] = robjects.r(
+            'AMR::microorganisms[, !sapply(AMR::microorganisms, is.list)]')
+        _cache['antimicrobials'] = robjects.r(
+            'AMR::antimicrobials[, !sapply(AMR::antimicrobials, is.list)]')
+        _cache['clinical_breakpoints'] = robjects.r(
+            'AMR::clinical_breakpoints[, !sapply(AMR::clinical_breakpoints, is.list)]')
+    
+    restore_sink()
+    _loaded_source = source
+
+def _load_example_isolates():
+    df = 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
+    ''')
+    df['date'] = pd.to_datetime(df['date'])
+    return df
+
+def get(name, source="cran"):
+    """Retrieve a dataset by name, installing AMR if needed."""
+    _load_datasets(source)
+    return _cache[name]

AMR/functions.py

@@ -0,0 +1,984 @@
+import functools
+import rpy2.robjects as robjects
+from rpy2.robjects.packages import importr
+from rpy2.robjects.vectors import StrVector, FactorVector, IntVector, FloatVector, DataFrame
+from rpy2.robjects.conversion import localconverter
+from rpy2.robjects import default_converter, numpy2ri, pandas2ri
+import pandas as pd
+import numpy as np
+
+from ._engine import ensure_amr
+
+# Ensure AMR is available before importing it in R
+ensure_amr("cran")
+amr_r = importr('AMR')
+
+def convert_to_r(value):
+    """Convert Python lists/tuples to typed R vectors.
+
+    rpy2's default_converter passes Python lists to R as R lists, not as
+    character/numeric vectors. This causes element-wise type-check functions
+    such as is.mic(), is.sir(), and is.disk() to return a logical vector
+    rather than a single logical, breaking R's scalar && operator.
+
+    This helper converts Python lists and tuples to the appropriate R vector
+    type based on the element types, so R always receives a proper vector."""
+    if isinstance(value, (list, tuple)):
+        if len(value) == 0:
+            return StrVector([])
+        # bool must be checked before int because bool is a subclass of int
+        if all(isinstance(v, bool) for v in value):
+            return robjects.vectors.BoolVector(value)
+        if all(isinstance(v, int) for v in value):
+            return IntVector(value)
+        if all(isinstance(v, float) for v in value):
+            return FloatVector(value)
+        if all(isinstance(v, str) for v in value):
+            return StrVector(value)
+        # Mixed types: coerce all to string
+        return StrVector([str(v) for v in value])
+    return value
+
+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, DataFrame)):
+        return r_output  # Return as pandas DataFrame (already converted by pandas2ri)
+
+    # 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 r_to_python(r_func):
+    """Decorator that converts Python list/tuple inputs to typed R vectors,
+    runs the rpy2 function under a localconverter, and converts the output
+    to a Python type."""
+    @functools.wraps(r_func)
+    def wrapper(*args, **kwargs):
+        args = tuple(convert_to_r(a) for a in args)
+        kwargs = {k: convert_to_r(v) for k, v in kwargs.items()}
+        with localconverter(default_converter + numpy2ri.converter + pandas2ri.converter):
+            return convert_to_python(r_func(*args, **kwargs))
+    return wrapper
+@r_to_python
+def custom_eucast_rules(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.custom_eucast_rules(*args, **kwargs)
+@r_to_python
+def ab_class(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_class(*args, **kwargs)
+@r_to_python
+def ab_selector(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_selector(*args, **kwargs)
+@r_to_python
+def ab_from_text(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_from_text(*args, **kwargs)
+@r_to_python
+def ab_name(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_name(x, *args, **kwargs)
+@r_to_python
+def ab_cid(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_cid(x, *args, **kwargs)
+@r_to_python
+def ab_synonyms(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_synonyms(x, *args, **kwargs)
+@r_to_python
+def ab_tradenames(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_tradenames(x, *args, **kwargs)
+@r_to_python
+def ab_group(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_group(x, *args, **kwargs)
+@r_to_python
+def ab_atc(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_atc(x, *args, **kwargs)
+@r_to_python
+def ab_atc_group1(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_atc_group1(x, *args, **kwargs)
+@r_to_python
+def ab_atc_group2(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_atc_group2(x, *args, **kwargs)
+@r_to_python
+def ab_loinc(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_loinc(x, *args, **kwargs)
+@r_to_python
+def ab_ddd(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_ddd(x, *args, **kwargs)
+@r_to_python
+def ab_ddd_units(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_ddd_units(x, *args, **kwargs)
+@r_to_python
+def ab_info(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_info(x, *args, **kwargs)
+@r_to_python
+def ab_url(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_url(x, *args, **kwargs)
+@r_to_python
+def ab_property(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_property(x, *args, **kwargs)
+@r_to_python
+def add_custom_antimicrobials(x):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.add_custom_antimicrobials(x)
+@r_to_python
+def clear_custom_antimicrobials(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.clear_custom_antimicrobials(*args, **kwargs)
+@r_to_python
+def add_custom_microorganisms(x):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.add_custom_microorganisms(x)
+@r_to_python
+def clear_custom_microorganisms(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.clear_custom_microorganisms(*args, **kwargs)
+@r_to_python
+def age(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.age(x, *args, **kwargs)
+@r_to_python
+def age_groups(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.age_groups(x, *args, **kwargs)
+@r_to_python
+def all_sir(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.all_sir(*args, **kwargs)
+@r_to_python
+def all_sir_predictors(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.all_sir_predictors(*args, **kwargs)
+@r_to_python
+def all_mic(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.all_mic(*args, **kwargs)
+@r_to_python
+def all_mic_predictors(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.all_mic_predictors(*args, **kwargs)
+@r_to_python
+def all_disk(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.all_disk(*args, **kwargs)
+@r_to_python
+def all_disk_predictors(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.all_disk_predictors(*args, **kwargs)
+@r_to_python
+def step_mic_log2(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.step_mic_log2(*args, **kwargs)
+@r_to_python
+def step_sir_numeric(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.step_sir_numeric(*args, **kwargs)
+@r_to_python
+def amr_course(github_repo, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.amr_course(github_repo, *args, **kwargs)
+@r_to_python
+def wisca(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.wisca(*args, **kwargs)
+@r_to_python
+def antibiogram(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.antibiogram(*args, **kwargs)
+@r_to_python
+def retrieve_wisca_parameters(wisca_model, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.retrieve_wisca_parameters(wisca_model, *args, **kwargs)
+@r_to_python
+def wisca_plot(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.wisca_plot(*args, **kwargs)
+@r_to_python
+def aminoglycosides(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.aminoglycosides(*args, **kwargs)
+@r_to_python
+def aminopenicillins(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.aminopenicillins(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def antifungals(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.antifungals(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def antimycobacterials(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.antimycobacterials(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def betalactams(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.betalactams(*args, **kwargs)
+@r_to_python
+def betalactams_with_inhibitor(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.betalactams_with_inhibitor(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def carbapenems(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.carbapenems(*args, **kwargs)
+@r_to_python
+def cephalosporins(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.cephalosporins(*args, **kwargs)
+@r_to_python
+def cephalosporins_1st(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.cephalosporins_1st(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def cephalosporins_2nd(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.cephalosporins_2nd(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def cephalosporins_3rd(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.cephalosporins_3rd(*args, **kwargs)
+@r_to_python
+def cephalosporins_4th(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.cephalosporins_4th(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def cephalosporins_5th(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.cephalosporins_5th(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def fluoroquinolones(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.fluoroquinolones(*args, **kwargs)
+@r_to_python
+def glycopeptides(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.glycopeptides(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def ionophores(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ionophores(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def isoxazolylpenicillins(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.isoxazolylpenicillins(*args, **kwargs)
+@r_to_python
+def lincosamides(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.lincosamides(*args, **kwargs)
+@r_to_python
+def lipoglycopeptides(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.lipoglycopeptides(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def macrolides(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.macrolides(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def monobactams(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.monobactams(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def nitrofurans(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.nitrofurans(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def oxazolidinones(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.oxazolidinones(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def penicillins(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.penicillins(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def peptides(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.peptides(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def phenicols(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.phenicols(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def phosphonics(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.phosphonics(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def polymyxins(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.polymyxins(*args, **kwargs)
+@r_to_python
+def quinolones(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.quinolones(*args, **kwargs)
+@r_to_python
+def rifamycins(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.rifamycins(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def spiropyrimidinetriones(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.spiropyrimidinetriones(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def streptogramins(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.streptogramins(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def sulfonamides(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.sulfonamides(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def tetracyclines(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.tetracyclines(*args, **kwargs)
+@r_to_python
+def trimethoprims(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.trimethoprims(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def ureidopenicillins(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ureidopenicillins(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def amr_class(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.amr_class(*args, **kwargs)
+@r_to_python
+def amr_selector(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.amr_selector(*args, **kwargs)
+@r_to_python
+def administrable_per_os(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.administrable_per_os(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def administrable_iv(only_sir_columns = False, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.administrable_iv(only_sir_columns = False, *args, **kwargs)
+@r_to_python
+def not_intrinsic_resistant(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.not_intrinsic_resistant(*args, **kwargs)
+@r_to_python
+def as_ab(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.as_ab(*args, **kwargs)
+@r_to_python
+def is_ab(x):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.is_ab(x)
+@r_to_python
+def ab_reset_session(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ab_reset_session(*args, **kwargs)
+@r_to_python
+def as_av(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.as_av(x, *args, **kwargs)
+@r_to_python
+def is_av(x):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.is_av(x)
+@r_to_python
+def as_disk(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.as_disk(x, *args, **kwargs)
+@r_to_python
+def is_disk(x):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.is_disk(x)
+@r_to_python
+def as_mic(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.as_mic(x, *args, **kwargs)
+@r_to_python
+def is_mic(x):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.is_mic(x)
+@r_to_python
+def rescale_mic(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.rescale_mic(*args, **kwargs)
+@r_to_python
+def mic_p50(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mic_p50(x, *args, **kwargs)
+@r_to_python
+def mic_p90(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mic_p90(x, *args, **kwargs)
+@r_to_python
+def as_mo(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.as_mo(*args, **kwargs)
+@r_to_python
+def is_mo(x):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.is_mo(x)
+@r_to_python
+def mo_uncertainties(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_uncertainties(*args, **kwargs)
+@r_to_python
+def mo_renamed(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_renamed(*args, **kwargs)
+@r_to_python
+def mo_failures(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_failures(*args, **kwargs)
+@r_to_python
+def mo_reset_session(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_reset_session(*args, **kwargs)
+@r_to_python
+def mo_cleaning_regex(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_cleaning_regex(*args, **kwargs)
+@r_to_python
+def as_sir(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.as_sir(x, *args, **kwargs)
+@r_to_python
+def is_sir(x):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.is_sir(x)
+@r_to_python
+def is_sir_eligible(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.is_sir_eligible(x, *args, **kwargs)
+@r_to_python
+def sir_interpretation_history(clean):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.sir_interpretation_history(clean)
+@r_to_python
+def atc_online_property(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.atc_online_property(*args, **kwargs)
+@r_to_python
+def atc_online_groups(atc_code, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.atc_online_groups(atc_code, *args, **kwargs)
+@r_to_python
+def atc_online_ddd(atc_code, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.atc_online_ddd(atc_code, *args, **kwargs)
+@r_to_python
+def atc_online_ddd_units(atc_code, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.atc_online_ddd_units(atc_code, *args, **kwargs)
+@r_to_python
+def av_from_text(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_from_text(*args, **kwargs)
+@r_to_python
+def av_name(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_name(x, *args, **kwargs)
+@r_to_python
+def av_cid(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_cid(x, *args, **kwargs)
+@r_to_python
+def av_synonyms(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_synonyms(x, *args, **kwargs)
+@r_to_python
+def av_tradenames(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_tradenames(x, *args, **kwargs)
+@r_to_python
+def av_group(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_group(x, *args, **kwargs)
+@r_to_python
+def av_atc(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_atc(x, *args, **kwargs)
+@r_to_python
+def av_loinc(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_loinc(x, *args, **kwargs)
+@r_to_python
+def av_ddd(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_ddd(x, *args, **kwargs)
+@r_to_python
+def av_ddd_units(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_ddd_units(x, *args, **kwargs)
+@r_to_python
+def av_info(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_info(x, *args, **kwargs)
+@r_to_python
+def av_url(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_url(x, *args, **kwargs)
+@r_to_python
+def av_property(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.av_property(x, *args, **kwargs)
+@r_to_python
+def availability(tbl, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.availability(tbl, *args, **kwargs)
+@r_to_python
+def bug_drug_combinations(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.bug_drug_combinations(*args, **kwargs)
+@r_to_python
+def count_resistant(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.count_resistant(*args, **kwargs)
+@r_to_python
+def count_susceptible(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.count_susceptible(*args, **kwargs)
+@r_to_python
+def count_S(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.count_S(*args, **kwargs)
+@r_to_python
+def count_SI(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.count_SI(*args, **kwargs)
+@r_to_python
+def count_I(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.count_I(*args, **kwargs)
+@r_to_python
+def count_IR(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.count_IR(*args, **kwargs)
+@r_to_python
+def count_R(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.count_R(*args, **kwargs)
+@r_to_python
+def count_all(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.count_all(*args, **kwargs)
+@r_to_python
+def n_sir(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.n_sir(*args, **kwargs)
+@r_to_python
+def count_df(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.count_df(*args, **kwargs)
+@r_to_python
+def custom_interpretive_rules(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.custom_interpretive_rules(*args, **kwargs)
+@r_to_python
+def custom_mdro_guideline(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.custom_mdro_guideline(*args, **kwargs)
+@r_to_python
+def export_ncbi_biosample(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.export_ncbi_biosample(*args, **kwargs)
+@r_to_python
+def first_isolate(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.first_isolate(*args, **kwargs)
+@r_to_python
+def filter_first_isolate(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.filter_first_isolate(*args, **kwargs)
+@r_to_python
+def g_test(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.g_test(x, *args, **kwargs)
+@r_to_python
+def is_new_episode(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.is_new_episode(x, *args, **kwargs)
+@r_to_python
+def ggplot_pca(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ggplot_pca(*args, **kwargs)
+@r_to_python
+def ggplot_sir(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ggplot_sir(*args, **kwargs)
+@r_to_python
+def geom_sir(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.geom_sir(*args, **kwargs)
+@r_to_python
+def guess_ab_col(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.guess_ab_col(*args, **kwargs)
+@r_to_python
+def interpretive_rules(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.interpretive_rules(*args, **kwargs)
+@r_to_python
+def eucast_rules(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.eucast_rules(*args, **kwargs)
+@r_to_python
+def clsi_rules(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.clsi_rules(*args, **kwargs)
+@r_to_python
+def eucast_dosage(ab, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.eucast_dosage(ab, *args, **kwargs)
+@r_to_python
+def italicise_taxonomy(string, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.italicise_taxonomy(string, *args, **kwargs)
+@r_to_python
+def italicize_taxonomy(string, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.italicize_taxonomy(string, *args, **kwargs)
+@r_to_python
+def inner_join_microorganisms(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.inner_join_microorganisms(x, *args, **kwargs)
+@r_to_python
+def left_join_microorganisms(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.left_join_microorganisms(x, *args, **kwargs)
+@r_to_python
+def right_join_microorganisms(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.right_join_microorganisms(x, *args, **kwargs)
+@r_to_python
+def full_join_microorganisms(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.full_join_microorganisms(x, *args, **kwargs)
+@r_to_python
+def semi_join_microorganisms(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.semi_join_microorganisms(x, *args, **kwargs)
+@r_to_python
+def anti_join_microorganisms(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.anti_join_microorganisms(x, *args, **kwargs)
+@r_to_python
+def key_antimicrobials(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.key_antimicrobials(*args, **kwargs)
+@r_to_python
+def all_antimicrobials(x = None, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.all_antimicrobials(x = None, *args, **kwargs)
+@r_to_python
+def kurtosis(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.kurtosis(x, *args, **kwargs)
+@r_to_python
+def like(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.like(x, *args, **kwargs)
+@r_to_python
+def mdro(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mdro(*args, **kwargs)
+@r_to_python
+def brmo(x = None, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.brmo(x = None, *args, **kwargs)
+@r_to_python
+def mrgn(x = None, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mrgn(x = None, *args, **kwargs)
+@r_to_python
+def mdr_tb(x = None, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mdr_tb(x = None, *args, **kwargs)
+@r_to_python
+def mdr_cmi2012(x = None, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mdr_cmi2012(x = None, *args, **kwargs)
+@r_to_python
+def eucast_exceptional_phenotypes(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.eucast_exceptional_phenotypes(*args, **kwargs)
+@r_to_python
+def mean_amr_distance(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mean_amr_distance(x, *args, **kwargs)
+@r_to_python
+def amr_distance_from_row(amr_distance, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.amr_distance_from_row(amr_distance, *args, **kwargs)
+@r_to_python
+def mo_matching_score(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_matching_score(x, *args, **kwargs)
+@r_to_python
+def mo_name(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_name(*args, **kwargs)
+@r_to_python
+def mo_fullname(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_fullname(*args, **kwargs)
+@r_to_python
+def mo_shortname(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_shortname(*args, **kwargs)
+@r_to_python
+def mo_subspecies(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_subspecies(*args, **kwargs)
+@r_to_python
+def mo_species(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_species(*args, **kwargs)
+@r_to_python
+def mo_genus(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_genus(*args, **kwargs)
+@r_to_python
+def mo_family(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_family(*args, **kwargs)
+@r_to_python
+def mo_order(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_order(*args, **kwargs)
+@r_to_python
+def mo_class(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_class(*args, **kwargs)
+@r_to_python
+def mo_phylum(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_phylum(*args, **kwargs)
+@r_to_python
+def mo_kingdom(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_kingdom(*args, **kwargs)
+@r_to_python
+def mo_domain(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_domain(*args, **kwargs)
+@r_to_python
+def mo_type(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_type(*args, **kwargs)
+@r_to_python
+def mo_status(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_status(*args, **kwargs)
+@r_to_python
+def mo_pathogenicity(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_pathogenicity(*args, **kwargs)
+@r_to_python
+def mo_gramstain(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_gramstain(*args, **kwargs)
+@r_to_python
+def mo_is_gram_negative(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_is_gram_negative(*args, **kwargs)
+@r_to_python
+def mo_is_gram_positive(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_is_gram_positive(*args, **kwargs)
+@r_to_python
+def mo_is_yeast(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_is_yeast(*args, **kwargs)
+@r_to_python
+def mo_is_intrinsic_resistant(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_is_intrinsic_resistant(*args, **kwargs)
+@r_to_python
+def mo_oxygen_tolerance(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_oxygen_tolerance(*args, **kwargs)
+@r_to_python
+def mo_is_anaerobic(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_is_anaerobic(*args, **kwargs)
+@r_to_python
+def mo_morphology(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_morphology(*args, **kwargs)
+@r_to_python
+def mo_snomed(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_snomed(*args, **kwargs)
+@r_to_python
+def mo_ref(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_ref(*args, **kwargs)
+@r_to_python
+def mo_authors(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_authors(*args, **kwargs)
+@r_to_python
+def mo_year(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_year(*args, **kwargs)
+@r_to_python
+def mo_lpsn(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_lpsn(*args, **kwargs)
+@r_to_python
+def mo_mycobank(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_mycobank(*args, **kwargs)
+@r_to_python
+def mo_gbif(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_gbif(*args, **kwargs)
+@r_to_python
+def mo_rank(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_rank(*args, **kwargs)
+@r_to_python
+def mo_taxonomy(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_taxonomy(*args, **kwargs)
+@r_to_python
+def mo_synonyms(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_synonyms(*args, **kwargs)
+@r_to_python
+def mo_current(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_current(x, *args, **kwargs)
+@r_to_python
+def mo_group_members(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_group_members(*args, **kwargs)
+@r_to_python
+def mo_info(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_info(*args, **kwargs)
+@r_to_python
+def mo_url(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_url(*args, **kwargs)
+@r_to_python
+def mo_property(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.mo_property(*args, **kwargs)
+@r_to_python
+def pca(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.pca(*args, **kwargs)
+@r_to_python
+def theme_sir(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.theme_sir(*args, **kwargs)
+@r_to_python
+def labels_sir_count(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.labels_sir_count(*args, **kwargs)
+@r_to_python
+def resistance(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.resistance(*args, **kwargs)
+@r_to_python
+def susceptibility(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.susceptibility(*args, **kwargs)
+@r_to_python
+def sir_confidence_interval(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.sir_confidence_interval(*args, **kwargs)
+@r_to_python
+def proportion_R(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.proportion_R(*args, **kwargs)
+@r_to_python
+def proportion_IR(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.proportion_IR(*args, **kwargs)
+@r_to_python
+def proportion_I(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.proportion_I(*args, **kwargs)
+@r_to_python
+def proportion_SI(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.proportion_SI(*args, **kwargs)
+@r_to_python
+def proportion_S(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.proportion_S(*args, **kwargs)
+@r_to_python
+def proportion_df(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.proportion_df(*args, **kwargs)
+@r_to_python
+def sir_df(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.sir_df(*args, **kwargs)
+@r_to_python
+def random_mic(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.random_mic(*args, **kwargs)
+@r_to_python
+def random_disk(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.random_disk(*args, **kwargs)
+@r_to_python
+def random_sir(size = None, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.random_sir(size = None, *args, **kwargs)
+@r_to_python
+def resistance_predict(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.resistance_predict(*args, **kwargs)
+@r_to_python
+def sir_predict(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.sir_predict(*args, **kwargs)
+@r_to_python
+def ggplot_sir_predict(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.ggplot_sir_predict(*args, **kwargs)
+@r_to_python
+def skewness(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.skewness(x, *args, **kwargs)
+@r_to_python
+def top_n_microorganisms(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.top_n_microorganisms(*args, **kwargs)
+@r_to_python
+def reset_AMR_locale(*args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.reset_AMR_locale(*args, **kwargs)
+@r_to_python
+def translate_AMR(x, *args, **kwargs):
+    """Please see our website of the R package for the full manual: https://amr-for-r.org"""
+    return amr_r.translate_AMR(x, *args, **kwargs)

DESCRIPTION

@@ -1,32 +0,0 @@
-Package: AMR
-Version: 0.1.1
-Date: 2018-02-22
-Title: Antimicrobial Resistance Analysis
-Authors@R: c(
-    person(
-        given = c("Matthijs", "S."),
-        family = "Berends",
-        email = "m.s.berends@umcg.nl",
-        role = c("aut", "cre")),
-    person(
-        given = c("Christian", "F."),
-        family = "Luz",
-        email = "c.f.luz@umcg.nl",
-        role = c("aut", "ctb")),
-    person(
-        given = c("Erwin", "E.A."),
-        family = "Hassing",
-        email = "e.hassing@certe.nl",
-        role = "ctb"))
-Description: Functions to simplify the analysis of Antimicrobial Resistance (AMR)
-    of microbial isolates, by using new S3 classes and applying EUCAST expert rules
-    on antibiograms according to Leclercq (2013)
-    <doi:10.1111/j.1469-0691.2011.03703.x>.
-Depends: R (>= 3.0)
-Imports: dplyr (>= 0.7.0), reshape2 (>= 1.4.0), xml2, rvest
-URL: https://github.com/msberends/AMR
-BugReports: https://github.com/msberends/AMR/issues
-License: GPL-2 | file LICENSE
-Encoding: UTF-8
-LazyData: true
-RoxygenNote: 6.0.1.9000

LICENSE

@@ -1,339 +0,0 @@
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-    Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
-    This is free software, and you are welcome to redistribute it
-    under certain conditions; type `show c' for details.
-
-The hypothetical commands `show w' and `show c' should show the appropriate
-parts of the General Public License.  Of course, the commands you use may
-be called something other than `show w' and `show c'; they could even be
-mouse-clicks or menu items--whatever suits your program.
-
-You should also get your employer (if you work as a programmer) or your
-school, if any, to sign a "copyright disclaimer" for the program, if
-necessary.  Here is a sample; alter the names:
-
-  Yoyodyne, Inc., hereby disclaims all copyright interest in the program
-  `Gnomovision' (which makes passes at compilers) written by James Hacker.
-
-  {signature of Ty Coon}, 1 April 1989
-  Ty Coon, President of Vice
-
-This General Public License does not permit incorporating your program into
-proprietary programs.  If your program is a subroutine library, you may
-consider it more useful to permit linking proprietary applications with the
-library.  If this is what you want to do, use the GNU Lesser General
-Public License instead of this License.

NAMESPACE

@@ -1,68 +0,0 @@
-# Generated by roxygen2: do not edit by hand
-
-S3method(as.double,mic)
-S3method(as.integer,mic)
-S3method(as.numeric,mic)
-S3method(plot,mic)
-S3method(plot,rsi)
-S3method(print,mic)
-S3method(print,rsi)
-S3method(summary,mic)
-S3method(summary,rsi)
-export(EUCAST_rules)
-export(abname)
-export(anti_join_bactlist)
-export(as.mic)
-export(as.rsi)
-export(atc_property)
-export(full_join_bactlist)
-export(inner_join_bactlist)
-export(interpretive_reading)
-export(is.mic)
-export(is.rsi)
-export(key_antibiotics)
-export(left_join_bactlist)
-export(mo_property)
-export(right_join_bactlist)
-export(rsi)
-export(rsi_df)
-export(rsi_predict)
-export(semi_join_bactlist)
-exportMethods(as.double.mic)
-exportMethods(as.integer.mic)
-exportMethods(as.numeric.mic)
-exportMethods(plot.mic)
-exportMethods(plot.rsi)
-exportMethods(print.mic)
-exportMethods(print.rsi)
-exportMethods(summary.mic)
-exportMethods(summary.rsi)
-importFrom(dplyr,"%>%")
-importFrom(dplyr,all_vars)
-importFrom(dplyr,any_vars)
-importFrom(dplyr,arrange)
-importFrom(dplyr,arrange_at)
-importFrom(dplyr,between)
-importFrom(dplyr,filter)
-importFrom(dplyr,filter_at)
-importFrom(dplyr,group_by)
-importFrom(dplyr,group_by_at)
-importFrom(dplyr,if_else)
-importFrom(dplyr,lag)
-importFrom(dplyr,left_join)
-importFrom(dplyr,mutate)
-importFrom(dplyr,n_distinct)
-importFrom(dplyr,progress_estimated)
-importFrom(dplyr,pull)
-importFrom(dplyr,row_number)
-importFrom(dplyr,select)
-importFrom(dplyr,slice)
-importFrom(dplyr,summarise)
-importFrom(dplyr,tibble)
-importFrom(dplyr,vars)
-importFrom(graphics,plot)
-importFrom(graphics,text)
-importFrom(reshape2,dcast)
-importFrom(rvest,html_nodes)
-importFrom(rvest,html_table)
-importFrom(xml2,read_html)

R/EUCAST.R

@@ -1,638 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Analysis                              #
-#                                                                      #
-# AUTHORS                                                              #
-# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)           #
-#                                                                      #
-# LICENCE                                                              #
-# This program is free software; you can redistribute it and/or modify #
-# it under the terms of the GNU General Public License version 2.0,    #
-# as published by the Free Software Foundation.                        #
-#                                                                      #
-# This program is distributed in the hope that it will be useful,      #
-# but WITHOUT ANY WARRANTY; without even the implied warranty of       #
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the        #
-# GNU General Public License for more details.                         #
-# ==================================================================== #
-
-#' EUCAST expert rules
-#'
-#' Apply expert rules (like intrinsic resistance), as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{http://eucast.org}), see \emph{Source}.
-#' @param tbl table with antibiotic columns, like e.g. \code{amox} and \code{amcl}
-#' @param col_bactcode column name of the bacteria ID in \code{tbl} - should also be present in \code{bactlist$bactid}, see \code{\link{bactlist}}.
-#' @param info print progress
-#' @param amcl,amik,amox,ampi,azit,aztr,cefa,cfra,cfep,cfot,cfox,cfta,cftr,cfur,chlo,cipr,clar,clin,clox,coli,czol,dapt,doxy,erta,eryt,fosf,fusi,gent,imip,kana,levo,linc,line,mero,mino,moxi,nali,neom,neti,nitr,novo,norf,oflo,peni,pita,poly,qida,rifa,roxi,siso,teic,tetr,tica,tige,tobr,trim,trsu,vanc column names of antibiotics. Use \code{NA} to skip a column, like \code{tica = NA}. Non-existing column will be skipped.
-#' @param ... parameters that are passed on to \code{EUCAST_rules}
-#' @name EUCAST
-#' @rdname EUCAST
-#' @export
-#' @importFrom dplyr %>% left_join select
-#' @return table with edited variables of antibiotics.
-#' @source
-#'   EUCAST Expert Rules Version 2.0: \cr
-#'   Leclercq et al. \strong{EUCAST expert rules in antimicrobial susceptibility testing.} \emph{Clin Microbiol Infect.} 2013;19(2):141-60. \cr
-#'   \url{https://doi.org/10.1111/j.1469-0691.2011.03703.x} \cr
-#'   \cr
-#'   EUCAST Expert Rules Version 3.1: \cr
-#'   \url{http://www.eucast.org/expert_rules_and_intrinsic_resistance}
-#' @examples
-#' \dontrun{
-#' tbl <- EUCAST_rules(tbl)
-#' }
-EUCAST_rules <- function(tbl,
-                         col_bactcode = 'bacteriecode',
-                         info = TRUE,
-                         amcl = 'amcl',
-                         amik = 'amik',
-                         amox = 'amox',
-                         ampi = 'ampi',
-                         azit = 'azit',
-                         aztr = 'aztr',
-                         cefa = 'cefa',
-                         cfra = 'cfra',
-                         cfep = 'cfep',
-                         cfot = 'cfot',
-                         cfox = 'cfox',
-                         cfta = 'cfta',
-                         cftr = 'cftr',
-                         cfur = 'cfur',
-                         chlo = 'chlo',
-                         cipr = 'cipr',
-                         clar = 'clar',
-                         clin = 'clin',
-                         clox = 'clox',
-                         coli = 'coli',
-                         czol = 'czol',
-                         dapt = 'dapt',
-                         doxy = 'doxy',
-                         erta = 'erta',
-                         eryt = 'eryt',
-                         fosf = 'fosf',
-                         fusi = 'fusi',
-                         gent = 'gent',
-                         imip = 'imip',
-                         kana = 'kana',
-                         levo = 'levo',
-                         linc = 'linc',
-                         line = 'line',
-                         mero = 'mero',
-                         mino = 'mino',
-                         moxi = 'moxi',
-                         nali = 'nali',
-                         neom = 'neom',
-                         neti = 'neti',
-                         nitr = 'nitr',
-                         novo = 'novo',
-                         norf = 'norf',
-                         oflo = 'oflo',
-                         peni = 'peni',
-                         pita = 'pita',
-                         poly = 'poly',
-                         qida = 'qida',
-                         rifa = 'rifa',
-                         roxi = 'roxi',
-                         siso = 'siso',
-                         teic = 'teic',
-                         tetr = 'tetr',
-                         tica = 'tica',
-                         tige = 'tige',
-                         tobr = 'tobr',
-                         trim = 'trim',
-                         trsu = 'trsu',
-                         vanc = 'vanc') {
-  
-  if (!col_bactcode %in% colnames(tbl)) {
-    stop('Column ', col_bactcode, ' not found.')
-  }
-  
-  # kolommen controleren
-  col.list <- c(amcl, amik, amox, ampi, azit, aztr, cefa, cfra, cfep,
-                cfot, cfox, cfta, cftr, cfur, cipr, clar, clin, clox, coli, czol,
-                dapt, doxy, erta, eryt, fusi, gent, imip, kana, levo, linc, line,
-                mero, mino, moxi, nali, neom, neti, nitr, novo, norf, oflo, peni,
-                pita, poly, qida, rifa, roxi, siso, teic, tetr, tica, tige, tobr,
-                trim, trsu, vanc)
-  col.list <- col.list[!is.na(col.list)]
-  if (!all(col.list %in% colnames(tbl))) {
-    if (info == TRUE) {
-      cat('\n')
-    }
-    if (info == TRUE) {
-      warning('These columns do not exist and will be ignored:\n',
-              col.list[!(col.list %in% colnames(tbl))] %>% toString(),
-              immediate. = TRUE,
-              call. = FALSE)
-    }
-    if (!amcl %in% colnames(tbl)) { amcl <- NA }
-    if (!amik %in% colnames(tbl)) { amik <- NA }
-    if (!amox %in% colnames(tbl)) { amox <- NA }
-    if (!ampi %in% colnames(tbl)) { ampi <- NA }
-    if (!azit %in% colnames(tbl)) { azit <- NA }
-    if (!aztr %in% colnames(tbl)) { aztr <- NA }
-    if (!cefa %in% colnames(tbl)) { cefa <- NA }
-    if (!cfra %in% colnames(tbl)) { cfra <- NA }
-    if (!cfep %in% colnames(tbl)) { cfep <- NA }
-    if (!cfot %in% colnames(tbl)) { cfot <- NA }
-    if (!cfox %in% colnames(tbl)) { cfox <- NA }
-    if (!cfta %in% colnames(tbl)) { cfta <- NA }
-    if (!cftr %in% colnames(tbl)) { cftr <- NA }
-    if (!cfur %in% colnames(tbl)) { cfur <- NA }
-    if (!chlo %in% colnames(tbl)) { chlo <- NA }
-    if (!cipr %in% colnames(tbl)) { cipr <- NA }
-    if (!clar %in% colnames(tbl)) { clar <- NA }
-    if (!clin %in% colnames(tbl)) { clin <- NA }
-    if (!clox %in% colnames(tbl)) { clox <- NA }
-    if (!coli %in% colnames(tbl)) { coli <- NA }
-    if (!czol %in% colnames(tbl)) { czol <- NA }
-    if (!dapt %in% colnames(tbl)) { dapt <- NA }
-    if (!doxy %in% colnames(tbl)) { doxy <- NA }
-    if (!erta %in% colnames(tbl)) { erta <- NA }
-    if (!eryt %in% colnames(tbl)) { eryt <- NA }
-    if (!fosf %in% colnames(tbl)) { fosf <- NA }
-    if (!fusi %in% colnames(tbl)) { fusi <- NA }
-    if (!gent %in% colnames(tbl)) { gent <- NA }
-    if (!imip %in% colnames(tbl)) { imip <- NA }
-    if (!kana %in% colnames(tbl)) { kana <- NA }
-    if (!levo %in% colnames(tbl)) { levo <- NA }
-    if (!linc %in% colnames(tbl)) { linc <- NA }
-    if (!line %in% colnames(tbl)) { line <- NA }
-    if (!mero %in% colnames(tbl)) { mero <- NA }
-    if (!mino %in% colnames(tbl)) { mino <- NA }
-    if (!moxi %in% colnames(tbl)) { moxi <- NA }
-    if (!nali %in% colnames(tbl)) { nali <- NA }
-    if (!neom %in% colnames(tbl)) { neom <- NA }
-    if (!neti %in% colnames(tbl)) { neti <- NA }
-    if (!nitr %in% colnames(tbl)) { nitr <- NA }
-    if (!novo %in% colnames(tbl)) { novo <- NA }
-    if (!norf %in% colnames(tbl)) { norf <- NA }
-    if (!oflo %in% colnames(tbl)) { oflo <- NA }
-    if (!peni %in% colnames(tbl)) { peni <- NA }
-    if (!pita %in% colnames(tbl)) { pita <- NA }
-    if (!poly %in% colnames(tbl)) { poly <- NA }
-    if (!qida %in% colnames(tbl)) { qida <- NA }
-    if (!rifa %in% colnames(tbl)) { rifa <- NA }
-    if (!roxi %in% colnames(tbl)) { roxi <- NA }
-    if (!siso %in% colnames(tbl)) { siso <- NA }
-    if (!teic %in% colnames(tbl)) { teic <- NA }
-    if (!tetr %in% colnames(tbl)) { tetr <- NA }
-    if (!tica %in% colnames(tbl)) { tica <- NA }
-    if (!tige %in% colnames(tbl)) { tige <- NA }
-    if (!tobr %in% colnames(tbl)) { tobr <- NA }
-    if (!trim %in% colnames(tbl)) { trim <- NA }
-    if (!trsu %in% colnames(tbl)) { trsu <- NA }
-    if (!vanc %in% colnames(tbl)) { vanc <- NA }
-  }
-  
-  total <- 0
-  
-  # functie voor uitvoeren
-  edit_rsi <- function(to, rows, cols) {
-    #voortgang$tick()$print()
-    cols <- cols[!is.na(cols)]
-    if (length(rows) > 0 & length(cols) > 0) {
-      tbl[rows, cols] <<- to
-      total <<- total + (length(rows) * length(cols))
-    }
-  }
-  
-  # bactlist aan vastknopen (bestaande kolommen krijgen extra suffix)
-  joinby <- colnames(AMR::bactlist)[1]
-  names(joinby) <- col_bactcode
-  tbl <- tbl %>% left_join(y = AMR::bactlist, by = joinby, suffix = c("_tempbactlist", ""))
-  
-  # antibioticagroepen
-  aminoglycosiden <- c(tobr, gent, kana, neom, neti, siso)
-  tetracyclines <- c(doxy, mino, tetr) # sinds EUCAST v3.1 is tige(cycline) apart
-  polymyxines <- c(poly, coli)
-  macroliden <- c(eryt, azit, roxi, clar) # sinds EUCAST v3.1 is clinda apart
-  glycopeptiden <- c(vanc, teic)
-  streptogramines <- qida # eigenlijk pristinamycine en quinupristine/dalfopristine
-  cefalosporines <- c(cfep, cfot, cfox, cfra, cfta, cftr, cfur, czol)
-  carbapenems <- c(erta, imip, mero)
-  aminopenicillines <- c(ampi, amox)
-  ureidopenicillines <- pita # eigenlijk ook azlo en mezlo
-  fluorochinolonen <- c(oflo, cipr, norf, levo, moxi)
-  
-  if (info == TRUE) {
-    cat('\nApplying EUCAST expert rules on',
-        tbl[!is.na(tbl$genus),] %>% nrow(),
-        'isolates according to "EUCAST Expert Rules Version 3.1"\n\n')
-  }
-  
-  # Table 1: Intrinsic resistance in Enterobacteriaceae ----
-  if (info == TRUE) {
-    cat('...Table 1: Intrinsic resistance in Enterobacteriaceae\n')
-  }
-  #voortgang <- progress_estimated(17)
-  # Intrisiek R voor groep
-  edit_rsi(to = 'R',
-           rows = which(tbl$family == 'Enterobacteriaceae'),
-           cols = c(peni, glycopeptiden, fusi, macroliden, linc, streptogramines, rifa, dapt, line))
-  # Citrobacter
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Citrobacter (koseri|amalonaticus|sedlakii|farmeri|rodentium)'),
-           cols = c(ampi, tica))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Citrobacter (freundii|braakii|murliniae|werkmanii|youngae)'),
-           cols = c(ampi, amcl, czol, cfox))
-  # Enterobacter
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Enterobacter cloacae'),
-           cols = c(ampi, amcl, czol, cfox))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Enterobacter aerogenes'),
-           cols = c(ampi, amcl, czol, cfox))
-  # Escherichia
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Escherichia hermanni'),
-           cols = c(ampi, tica))
-  # Hafnia
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Hafnia alvei'),
-           cols = c(ampi, amcl, czol, cfox))
-  # Klebsiella
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Klebsiella'),
-           cols = c(ampi, tica))
-  # Morganella / Proteus
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Morganella morganii'),
-           cols = c(ampi, amcl, czol, tetracyclines, polymyxines, nitr))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Proteus mirabilis'),
-           cols = c(tetracyclines, tige, polymyxines, nitr))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Proteus penneri'),
-           cols = c(ampi, czol, cfur, tetracyclines, tige, polymyxines, nitr))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Proteus vulgaris'),
-           cols = c(ampi, czol, cfur, tetracyclines, tige, polymyxines, nitr))
-  # Providencia
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Providencia rettgeri'),
-           cols = c(ampi, amcl, czol, cfur, tetracyclines, tige, polymyxines, nitr))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Providencia stuartii'),
-           cols = c(ampi, amcl, czol, cfur, tetracyclines, tige, polymyxines, nitr))
-  # Raoultella
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Raoultella'),
-           cols = c(ampi, tica))
-  # Serratia
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Serratia marcescens'),
-           cols = c(ampi, amcl, czol, cfox, cfur, tetracyclines[tetracyclines != 'mino'], polymyxines, nitr))
-  # Yersinia
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Yersinia enterocolitica'),
-           cols = c(ampi, amcl, tica, czol, cfox))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Yersinia pseudotuberculosis'),
-           cols = c(poly, coli))
-  
-  
-  # Table 2: Intrinsic resistance in non-fermentative Gram-negative bacteria ----
-  if (info == TRUE) {
-    cat('...Table 2: Intrinsic resistance in non-fermentative Gram-negative bacteria\n')
-  }
-  #voortgang <- progress_estimated(8)
-  # Intrisiek R voor groep
-  edit_rsi(to = 'R',
-           rows = which(tbl$genus %in% c('Achromobacter',
-                                         'Acinetobacter',
-                                         'Alcaligenes',
-                                         'Bordatella',
-                                         'Burkholderia',
-                                         'Elizabethkingia',
-                                         'Flavobacterium',
-                                         'Ochrobactrum',
-                                         'Pseudomonas',
-                                         'Stenotrophomonas')),
-           cols = c(peni, cfox, cfur, glycopeptiden, fusi, macroliden, linc, streptogramines, rifa, dapt, line))
-  # Acinetobacter
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Acinetobacter (baumannii|pittii|nosocomialis|calcoaceticus)'),
-           cols = c(ampi, amcl, czol, cfot, cftr, aztr, erta, trim, fosf, tetracyclines[tetracyclines != 'mino']))
-  # Achromobacter
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Achromobacter (xylosoxydans|xylosoxidans)'),
-           cols = c(ampi, czol, cfot, cftr, erta))
-  # Burkholderia
-  edit_rsi(to = 'R',
-           # onder 'Burkholderia cepacia complex' vallen deze species allemaal: PMID 16217180.
-           rows = which(tbl$fullname %like% '^Burkholderia (cepacia|multivorans|cenocepacia|stabilis|vietnamiensis|dolosa|ambifaria|anthina|pyrrocinia|ubonensis)'),
-           cols = c(ampi, amcl, tica, pita, czol, cfot, cftr, aztr, erta, cipr, chlo, aminoglycosiden, trim, fosf, polymyxines))
-  # Elizabethkingia
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Elizabethkingia meningoseptic(a|um)'),
-           cols = c(ampi, amcl, tica, czol, cfot, cftr, cfta, cfep, aztr, erta, imip, mero, polymyxines))
-  # Ochrobactrum
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Ochrobactrum anthropi'),
-           cols = c(ampi, amcl, tica, pita, czol, cfot, cftr, cfta, cfep, aztr, erta))
-  # Pseudomonas
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Pseudomonas aeruginosa'),
-           cols = c(ampi, amcl, czol, cfot, cftr, erta, chlo, kana, neom, trim, trsu, tetracyclines, tige))
-  # Stenotrophomonas
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Stenotrophomonas maltophilia'),
-           cols = c(ampi, amcl, tica, pita, czol, cfot, cftr, cfta, aztr, erta, imip, mero, aminoglycosiden, trim, fosf, tetr))
-  
-  
-  # Table 3: Intrinsic resistance in other Gram-negative bacteria ----
-  if (info == TRUE) {
-    cat('...Table 3: Intrinsic resistance in other Gram-negative bacteria\n')
-  }
-  #voortgang <- progress_estimated(7)
-  # Intrisiek R voor groep
-  edit_rsi(to = 'R',
-           rows = which(tbl$genus %in% c('Haemophilus',
-                                         'Moraxella',
-                                         'Neisseria',
-                                         'Campylobacter')),
-           cols = c(glycopeptiden, linc, dapt, line))
-  # Haemophilus
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Haemophilus influenzae'),
-           cols = c(fusi, streptogramines))
-  # Moraxella
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Moraxella catarrhalis'),
-           cols = trim)
-  # Neisseria
-  edit_rsi(to = 'R',
-           rows = which(tbl$genus == 'Neisseria'),
-           cols = trim)
-  # Campylobacter
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Campylobacter fetus'),
-           cols = c(fusi, streptogramines, trim, nali))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Campylobacter (jejuni|coli)'),
-           cols = c(fusi, streptogramines, trim))
-  
-  
-  # Table 4: Intrinsic resistance in Gram-positive bacteria ----
-  if (info == TRUE) {
-    cat('...Table 4: Intrinsic resistance in Gram-positive bacteria\n')
-  }
-  #voortgang <- progress_estimated(14)
-  # Intrisiek R voor groep
-  edit_rsi(to = 'R',
-           rows = which(tbl$gramstain %like% 'Positi(e|)(v|f)'),
-           cols = c(aztr, polymyxines, nali))
-  # Staphylococcus
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Staphylococcus saprophyticus'),
-           cols = c(fusi, cfta, fosf, novo))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Staphylococcus (cohnii|xylosus)'),
-           cols = c(cfta, novo))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Staphylococcus capitis'),
-           cols = c(cfta, fosf))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Staphylococcus (aureus|epidermidis|coagulase negatief|hominis|haemolyticus|intermedius|pseudointermedius)'),
-           cols = cfta)
-  # Streptococcus
-  edit_rsi(to = 'R',
-           rows = which(tbl$genus == 'Streptococcus'),
-           cols = c(fusi, cfta, aminoglycosiden))
-  # Enterococcus
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Enterococcus faecalis'),
-           cols = c(fusi, cfta, cefalosporines[cefalosporines != cfta], aminoglycosiden, macroliden, clin, qida, trim, trsu))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Enterococcus (gallinarum|casseliflavus)'),
-           cols = c(fusi, cfta, cefalosporines[cefalosporines != cfta], aminoglycosiden, macroliden, clin, qida, vanc, trim, trsu))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Enterococcus faecium'),
-           cols = c(fusi, cfta, cefalosporines[cefalosporines != cfta], aminoglycosiden, macroliden, trim, trsu))
-  # Corynebacterium
-  edit_rsi(to = 'R',
-           rows = which(tbl$genus == 'Corynebacterium'),
-           cols = fosf)
-  # Listeria
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Listeria monocytogenes'),
-           cols = c(cfta, cefalosporines[cefalosporines != cfta]))
-  # overig
-  edit_rsi(to = 'R',
-           rows = which(tbl$genus %in% c('Leuconostoc', 'Pediococcus')),
-           cols = c(vanc, teic))
-  edit_rsi(to = 'R',
-           rows = which(tbl$genus == 'Lactobacillus'),
-           cols = c(vanc, teic))
-  edit_rsi(to = 'R',
-           rows = which(tbl$fullname %like% '^Clostridium (ramosum|innocuum)'),
-           cols = vanc)
-  
-  # Table 8: Interpretive rules for B-lactam agents and Gram-positive cocci ----
-  if (info == TRUE) {
-    cat('...Table 8: Interpretive rules for B-lactam agents and Gram-positive cocci\n')
-  }
-  #voortgang <- progress_estimated(2)
-  # regel 8.3
-  if (!is.na(peni)) {
-    edit_rsi(to = 'S',
-             rows = which(tbl$fullname %like% '^Streptococcus (pyogenes|agalactiae|dysgalactiae|groep A|groep B|groep C|groep G)'
-                          & tbl[, peni] == 'S'),
-             cols = c(aminopenicillines, cefalosporines, carbapenems))
-  }
-  # regel 8.6
-  if (!is.na(ampi)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl$genus == 'Enterococcus'
-                          & tbl[, ampi] == 'R'),
-             cols = c(ureidopenicillines, carbapenems))
-  }
-  
-  # Table 9: Interpretive rules for B-lactam agents and Gram-negative rods ----
-  if (info == TRUE) {
-    cat('...Table 9: Interpretive rules for B-lactam agents and Gram-negative rods\n')
-  }
-  #voortgang <- progress_estimated(1)
-  # regel 9.3
-  if (!is.na(tica) & !is.na(pita)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl$family == 'Enterobacteriaceae'
-                          & tbl[, tica] == 'R'
-                          & tbl[, pita] == 'S'),
-             cols = pita)
-  }
-  
-  # Table 10: Interpretive rules for B-lactam agents and other Gram-negative bacteria ----
-  if (info == TRUE) {
-    cat('...Table 10: Interpretive rules for B-lactam agents and other Gram-negative bacteria\n')
-  }
-  #voortgang <- progress_estimated(1)
-  # regel 10.2
-  if (!is.na(ampi)) {
-    # hiervoor moeten we eerst weten of ze B-lactamase-positief zijn
-    # edit_rsi(to = 'R',
-    #          rows = which(tbl$fullname %like% '^Haemophilus influenza'
-    #                       & tbl[, ampi] == 'R'),
-    #          cols = c(ampi, amox, amcl, pita, cfur))
-  }
-  
-  # Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins ----
-  if (info == TRUE) {
-    cat('...Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins\n')
-  }
-  # regel 11.1
-  if (!is.na(eryt)) {
-    if (!is.na(azit)) {
-      tbl[, azit] <- tbl[, eryt]
-    }
-    if (!is.na(clar)) {
-      tbl[, clar] <- tbl[, eryt]
-    }
-  }
-  
-  # Table 12: Interpretive rules for aminoglycosides ----
-  if (info == TRUE) {
-    cat('...Table 12: Interpretive rules for aminoglycosides\n')
-  }
-  #voortgang <- progress_estimated(4)
-  # regel 12.2
-  if (!is.na(tobr)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl$genus == 'Staphylococcus'
-                          & tbl[, tobr] == 'R'),
-             cols = c(kana, amik))
-  }
-  # regel 12.3
-  if (!is.na(gent)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl$genus == 'Staphylococcus'
-                          & tbl[, gent] == 'R'),
-             cols = aminoglycosiden)
-  }
-  # regel 12.8
-  if (!is.na(gent) & !is.na(tobr)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl$family == 'Enterobacteriaceae'
-                          & tbl[, gent] == 'I'
-                          & tbl[, tobr] == 'S'),
-             cols = gent)
-  }
-  # regel 12.9
-  if (!is.na(gent) & !is.na(tobr)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl$family == 'Enterobacteriaceae'
-                          & tbl[, tobr] == 'I'
-                          & tbl[, gent] == 'R'),
-             cols = tobr)
-  }
-  
-  
-  # Table 13: Interpretive rules for quinolones ----
-  if (info == TRUE) {
-    cat('...Table 13: Interpretive rules for quinolones\n')
-  }
-  #voortgang <- progress_estimated(4)
-  # regel 13.2
-  if (!is.na(moxi)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl$genus == 'Staphylococcus'
-                          & tbl[, moxi] == 'R'),
-             cols = fluorochinolonen)
-  }
-  # regel 13.4
-  if (!is.na(moxi)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl$fullname %like% '^Streptococcus pneumoniae'
-                          & tbl[, moxi] == 'R'),
-             cols = fluorochinolonen)
-  }
-  # regel 13.5
-  if (!is.na(cipr)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl$family == 'Enterobacteriaceae'
-                          & tbl[, cipr] == 'R'),
-             cols = fluorochinolonen)
-  }
-  # regel 13.8
-  if (!is.na(cipr)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl$fullname %like% '^Neisseria gonorrhoeae'
-                          & tbl[, cipr] == 'R'),
-             cols = fluorochinolonen)
-  }
-  
-  
-  # Other ----
-  if (info == TRUE) {
-    cat('...Other\n')
-  }
-  #voortgang <- progress_estimated(2)
-  if (!is.na(amcl)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl[, amcl] == 'R'),
-             cols = ampi)
-  }
-  if (!is.na(trsu)) {
-    edit_rsi(to = 'R',
-             rows = which(tbl[, trsu] == 'R'),
-             cols = trim)
-  }
-  if (!is.na(ampi) & !is.na(amox)) {
-    tbl[, amox] <- tbl[, ampi]
-  }
-  
-  # Toegevoegde kolommen weer verwijderen
-  bactlist.ncol <- ncol(AMR::bactlist) - 2
-  tbl.ncol <- ncol(tbl)
-  tbl <- tbl %>% select(-c((tbl.ncol - bactlist.ncol):tbl.ncol))
-  # en eventueel toegevoegde suffix aan bestaande kolommen weer verwijderen
-  colnames(tbl) <- gsub("_tempbactlist", "", colnames(tbl))
-  
-  if (info == TRUE) {
-    cat('\nDone.\nExpert rules applied to', total, 'test results.\n')
-  }
-  
-  tbl
-}
-
-#' @rdname EUCAST
-#' @export
-interpretive_reading <- function(...) {
-  EUCAST_rules(...)
-}
-
-#' Poperties of a microorganism
-#'
-#' @param bactcode ID of a microorganisme, like \code{"STAAUR} and \code{"ESCCOL}
-#' @param property One of the values \code{bactid}, \code{bactsys}, \code{family}, \code{genus}, \code{species}, \code{subspecies}, \code{fullname}, \code{type}, \code{gramstain}, \code{aerobic}
-#' @export
-#' @importFrom dplyr %>% filter select
-#' @seealso \code{\link{bactlist}}
-mo_property <- function(bactcode, property = 'fullname') {
-  
-  mocode <- as.character(bactcode)
-  
-  for (i in 1:length(mocode)) {
-    bug <- mocode[i]
-    
-    if (!is.na(bug)) {
-      result = tryCatch({
-        mocode[i] <-
-          AMR::bactlist %>%
-          filter(bactid == bactcode) %>%
-          select(property) %>%
-          unlist() %>%
-          as.character()
-      }, error = function(error_condition) {
-        warning('Code ', bug, ' not found in bacteria list.')
-      }, finally = {
-        if (mocode[i] == bug & !property %in% c('bactid', 'bactsys')) {
-          mocode[i] <- NA
-        }
-      })
-    }
-    
-  }
-  mocode
-}

R/atc.R

@@ -1,226 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Analysis                              #
-#                                                                      #
-# AUTHORS                                                              #
-# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)           #
-#                                                                      #
-# LICENCE                                                              #
-# This program is free software; you can redistribute it and/or modify #
-# it under the terms of the GNU General Public License version 2.0,    #
-# as published by the Free Software Foundation.                        #
-#                                                                      #
-# This program is distributed in the hope that it will be useful,      #
-# but WITHOUT ANY WARRANTY; without even the implied warranty of       #
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the        #
-# GNU General Public License for more details.                         #
-# ==================================================================== #
-
-#' Properties of an ATC code
-#'
-#' Gets data from the WHO to determine properties of an ATC of e.g. an antibiotic. \strong{This function requires an internet connection.}
-#' @param atc_code a character or character vector with ATC code(s) of antibiotic(s)
-#' @param property property of an ATC code. Valid values are \code{"ATC code"}, \code{"Name"}, \code{"DDD"}, \code{"U"} (\code{"unit"}), \code{"Adm.R"} en \code{"Note"}.
-#' @param administration type of administration, see \emph{Details}
-#' @param url url of website of the WHO. The sign \code{\%s} can be used as a placeholder for ATC codes.
-#' @details
-#' Abbreviations for the property \code{"Adm.R"} (parameter \code{administration}):
-#' \itemize{
-#'   \item{\code{"Implant"}}{ = Implant}
-#'   \item{\code{"Inhal"}}{ = Inhalation}
-#'   \item{\code{"Instill"}}{ = Instillation}
-#'   \item{\code{"N"}}{ = nasal}
-#'   \item{\code{"O"}}{ = oral}
-#'   \item{\code{"P"}}{ = parenteral}
-#'   \item{\code{"R"}}{ = rectal}
-#'   \item{\code{"SL"}}{ = sublingual/buccal}
-#'   \item{\code{"TD"}}{ = transdermal}
-#'   \item{\code{"V"}}{ = vaginal}
-#' }
-#'
-#' Abbreviations for the property \code{"U"} (unit):
-#' \itemize{
-#'   \item{\code{"g"}}{ = gram}
-#'   \item{\code{"mg"}}{ = milligram}
-#'   \item{\code{"mcg"}}{ = microgram}
-#'   \item{\code{"U"}}{ = unit}
-#'   \item{\code{"TU"}}{ = thousand units}
-#'   \item{\code{"MU"}}{ = million units}
-#'   \item{\code{"mmol"}}{ = millimole}
-#'   \item{\code{"ml"}}{ = milliliter (e.g. eyedrops)}
-#' }
-#' @export
-#' @importFrom dplyr %>% progress_estimated
-#' @importFrom xml2 read_html
-#' @importFrom rvest html_nodes html_table
-#' @source \url{https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/}
-#' @examples 
-#' \donttest{
-#' atc_property("J01CA04", "DDD", "O") # oral DDD of amoxicillin
-#' atc_property("J01CA04", "DDD", "P") # parenteral DDD of amoxicillin
-#' }
-atc_property <- function(atc_code,
-                         property,
-                         administration = 'O',
-                         url = 'https://www.whocc.no/atc_ddd_index/?code=%s&showdescription=no') {
-  
-  # property <- property %>% tolower()
-  #
-  if (property %like% 'unit') {
-    property <- 'U'
-  }
-  
-  # validation of properties
-  valid_properties.bak <- c("ATC code", "Name", "DDD", "U", "Adm.R", "Note")
-  valid_properties <- valid_properties.bak #%>% tolower()
-  if (!property %in% valid_properties) {
-    stop('Invalid `property`, use one of ', paste(valid_properties, collapse = ", "), '.')
-  }
-  
-  returnvalue <- rep(NA_character_, length(atc_code))
-  if (property == 'DDD') {
-    returnvalue <- rep(NA_real_, length(atc_code))
-  }
-  
-  progress <- progress_estimated(n = length(atc_code))
-  
-  for (i in 1:length(atc_code)) {
-    
-    progress$tick()$print()
-    
-    atc_url <- sub('%s', atc_code[i], url, fixed = TRUE)
-    tbl <- xml2::read_html(atc_url) %>%
-      rvest::html_nodes('table') %>%
-      rvest::html_table(header = TRUE)
-    
-    if (length(tbl) == 0) {
-      warning('ATC not found: ', atc_code[i], '. Please check ', atc_url, '.', call. = FALSE)
-      returnvalue[i] <- NA
-      next
-    }
-    
-    tbl <- tbl[[1]]
-    
-    if (property == 'Name') {
-      returnvalue[i] <- tbl[1, 2]
-    } else {
-      
-      names(returnvalue)[i] <- tbl[1, 2] %>% as.character()
-      
-      if (!'Adm.R' %in% colnames(tbl) | is.na(tbl[1, 'Adm.R'])) {
-        returnvalue[i] <- NA
-        next
-      } else {
-        for (j in 1:nrow(tbl)) {
-          if (tbl[j, 'Adm.R'] == administration) {
-            returnvalue[i] <- tbl[j, property]
-          }
-        }
-      }
-    }
-  }
-  
-  cat('\n')
-  returnvalue
-  
-}
-
-#' Name of an antibiotic
-#'
-#' Convert antibiotic codes (from a laboratory information system like MOLIS or GLIMS) to a (trivial) antibiotic name or ATC code, or vice versa. This uses the data from \code{\link{ablist}}.
-#' @param abcode a code or name, like \code{"amox"}, \code{"cftr"} or \code{"J01CA04"}
-#' @param from,to type to transform from and to. See \code{\link{ablist}} for its column names.
-#' @param textbetween text to put between multiple returned texts
-#' @param tolower return output as lower case with function \code{\link{tolower}}.
-#' @keywords ab antibiotics
-#' @source \code{\link{ablist}}
-#' @export
-#' @importFrom dplyr %>% filter select slice 
-#' @examples
-#' abname("AMCL")
-#' # "amoxicillin and enzyme inhibitor"
-#'
-#' abname("AMCL+GENT")
-#' # "amoxicillin and enzyme inhibitor + gentamicin"
-#'
-#' abname(c("AMCL", "GENT"))
-#' # "amoxicillin and enzyme inhibitor" "gentamicin" 
-#'
-#' abname("AMCL", to = "trivial")
-#' # "Amoxicilline/clavulaanzuur"
-#'
-#' abname("AMCL", to = "atc")
-#' # "J01CR02"
-#'
-#' abname("J01CR02", from = "atc", to = "umcg")
-#' # "AMCL"
-abname <- function(abcode, from = 'umcg', to = 'official', textbetween = ' + ', tolower = FALSE) {
-  
-  ablist <- AMR::ablist
-  colnames(ablist) <- colnames(ablist) %>% tolower()
-  from <- from %>% tolower()
-  to <- to %>% tolower()
-  
-  if (!from %in% colnames(ablist) |
-      !to %in% colnames(ablist)) {
-    stop(paste0('Invalid `from` or `to`. Choose one of ', 
-                colnames(ablist) %>% paste(collapse = ","), '.'), call. = FALSE)
-  }
-  
-  abcode <- as.character(abcode)
-  
-  for (i in 1:length(abcode)) {
-    drug <- abcode[i]
-    if (!grepl('+', drug, fixed = TRUE) & !grepl(' en ', drug, fixed = TRUE)) {
-      # bestaat maar uit 1 middel
-      if (any(ablist[, from] == drug)) {
-        abcode[i] <-
-          ablist %>%
-          filter(.[, from] == drug) %>%
-          select(to) %>%
-          slice(1) %>%
-          as.character()
-      } else {
-        # niet gevonden
-        warning('Code "', drug, '" not found in antibiotics list.', call. = FALSE)
-        abcode[i] <- NA
-      }
-    } else {
-      # meerdere middelen
-      if (grepl('+', drug, fixed = TRUE)) {
-        drug.group <-
-          strsplit(drug, '+', fixed = TRUE) %>%
-          unlist() %>%
-          trimws('both')
-      } else if (grepl(' en ', drug, fixed = TRUE)) {
-        drug.group <-
-          strsplit(drug, ' en ', fixed = TRUE) %>%
-          unlist() %>%
-          trimws('both')
-      } else {
-        warning('Invalid concat.')
-        abcode[i] <- NA
-        next
-      }
-      
-      for (j in 1:length(drug.group)) {
-        drug.group[j] <-
-          ablist %>%
-          filter(.[, from] == drug.group[j]) %>%
-          select(to) %>%
-          slice(1) %>%
-          as.character()
-        if (j > 1 & to %in% c('official', 'trivial')) {
-          drug.group[j] <- drug.group[j] %>% tolower()
-        }
-      }
-      abcode[i] <- paste(drug.group, collapse = textbetween)
-    }
-  }
-  
-  if (tolower == TRUE) {
-    abcode <- abcode %>% tolower()
-  }
-  
-  abcode
-}

R/classes.R

@@ -1,375 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Analysis                              #
-#                                                                      #
-# AUTHORS                                                              #
-# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)           #
-#                                                                      #
-# LICENCE                                                              #
-# This program is free software; you can redistribute it and/or modify #
-# it under the terms of the GNU General Public License version 2.0,    #
-# as published by the Free Software Foundation.                        #
-#                                                                      #
-# This program is distributed in the hope that it will be useful,      #
-# but WITHOUT ANY WARRANTY; without even the implied warranty of       #
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the        #
-# GNU General Public License for more details.                         #
-# ==================================================================== #
-
-#' Class 'rsi'
-#'
-#' This transforms a vector to a new class \code{rsi}, which is an ordered factor with levels \code{S < I < R}. Invalid antimicrobial interpretations will be translated as \code{NA} with a warning.
-#' @rdname as.rsi
-#' @param x vector
-#' @return New class \code{rsi}
-#' @export
-#' @importFrom dplyr %>%
-#' @examples
-#' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
-#' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370), "A", "B", "C"))
-#' is.rsi(rsi_data)
-#' plot(rsi_data)
-#' 
-#' \donttest{
-#' library(dplyr)
-#' tbl %>%
-#'   mutate_at(vars(ends_with("_rsi")), as.rsi)
-#' sapply(mic_data, is.rsi)
-#' }
-as.rsi <- function(x) {
-  if (is.rsi(x)) {
-    x
-  } else {
-    
-    x <- x %>% unlist()
-    x.bak <- x
-    
-    na_before <- x[is.na(x) | x == ''] %>% length()
-    x <- gsub('[^RSI]+', '', x %>% toupper())
-    # needed for UMCG in cases of "S;S" but also "S;I"; the latter will be NA:
-    x <- gsub('^S+$', 'S', x)
-    x <- gsub('^I+$', 'I', x)
-    x <- gsub('^R+$', 'R', x)
-    x[!x %in% c('S', 'I', 'R')] <- NA
-    na_after <- x[is.na(x) | x == ''] %>% length()
-    
-    if (na_before != na_after) {
-      list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ''] %>%
-        unique() %>%
-        sort()
-      list_missing <- paste0('"', list_missing , '"', collapse = ", ")
-      warning(na_after - na_before, ' results truncated (',
-              round(((na_after - na_before) / length(x)) / 100),
-              '%) that were invalid antimicrobial interpretations: ',
-              list_missing, call. = FALSE)
-    }
-    
-    x <- x %>% toupper() %>% factor(levels = c("S", "I", "R"), ordered = TRUE)
-    class(x) <- c('rsi', 'ordered', 'factor')
-    x
-  }
-}
-
-#' @rdname as.rsi
-#' @export
-#' @importFrom dplyr %>%
-is.rsi <- function(x) {
-  class(x) %>% identical(c('rsi', 'ordered', 'factor'))
-}
-
-#' @exportMethod print.rsi
-#' @export
-#' @importFrom dplyr %>%
-#' @noRd
-print.rsi <- function(x, ...) {
-  n_total <- x %>% length()
-  x <- x[!is.na(x)]
-  n <- x %>% length()
-  S <- x[x == 'S'] %>% length()
-  I <- x[x == 'I'] %>% length()
-  R <- x[x == 'R'] %>% length()
-  IR <- x[x %in% c('I', 'R')] %>% length()
-  cat("Class 'rsi': ", n, " isolates\n", sep = '')
-  cat('\n')
-  cat('<NA>:      ', n_total - n, '\n')
-  cat('Sum of S:  ', S, '\n')
-  cat('Sum of IR: ', IR, '\n')
-  cat('- Sum of R:', R, '\n')
-  cat('- Sum of I:', I, '\n')
-  cat('\n')
-  print(c(
-    `%S` = round((S / n) * 100, 1),
-    `%IR` = round((IR / n) * 100, 1),
-    `%I` = round((I / n) * 100, 1),
-    `%R` = round((R / n) * 100, 1)
-  ))
-}
-
-#' @exportMethod summary.rsi
-#' @export
-#' @importFrom dplyr %>%
-#' @noRd
-summary.rsi <- function(object, ...) {
-  x <- object
-  n_total <- x %>% length()
-  x <- x[!is.na(x)]
-  n <- x %>% length()
-  S <- x[x == 'S'] %>% length()
-  I <- x[x == 'I'] %>% length()
-  R <- x[x == 'R'] %>% length()
-  IR <- x[x %in% c('I', 'R')] %>% length()
-  lst <- c('rsi', n_total - n, S, IR, R, I)
-  names(lst) <- c("Mode", "<NA>", "Sum S", "Sum IR", "Sum R", "Sum I")
-  lst
-}
-
-#' @exportMethod plot.rsi
-#' @export
-#' @importFrom dplyr %>% group_by summarise filter mutate if_else
-#' @importFrom graphics plot text
-#' @noRd
-plot.rsi <- function(x, ...) {
-  x_name <- deparse(substitute(x))
-  
-  data <- data.frame(x = x,
-                     y = 1,
-                     stringsAsFactors = TRUE) %>%
-    group_by(x) %>%
-    summarise(n = sum(y)) %>%
-    filter(!is.na(x)) %>%
-    mutate(s = round((n / sum(n)) * 100, 1))
-  data$x <- factor(data$x, levels = c('S', 'I', 'R'), ordered = TRUE)
-  
-  ymax <- if_else(max(data$s) > 95, 105, 100)
-
-  plot(x = data$x,
-       y = data$s,
-       lwd = 2,
-       col = c('green', 'orange', 'red'),
-       ylim = c(0, ymax),
-       ylab = 'Percentage',
-       xlab = 'Antimicrobial Interpretation',
-       main = paste('Susceptibilty Analysis of', x_name),
-       ...)
-  text(x = data$x,
-       y = data$s + 5,
-       labels = paste0(data$s, '% (n = ', data$n, ')'))
-}
-
-#' Class 'mic'
-#'
-#' This transforms a vector to a new class\code{mic}, which is an ordered factor valid MIC values as levels. Invalid MIC values will be translated as \code{NA} with a warning.
-#' @rdname as.mic
-#' @param x vector
-#' @param na.rm a logical indicating whether missing values should be removed
-#' @return New class \code{mic}
-#' @export
-#' @importFrom dplyr %>%
-#' @examples
-#' mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
-#' is.mic(mic_data)
-#' plot(mic_data)
-#' 
-#' \donttest{
-#' library(dplyr)
-#' tbl %>%
-#'   mutate_at(vars(ends_with("_mic")), as.mic)
-#' sapply(mic_data, is.mic)
-#' }
-as.mic <- function(x, na.rm = FALSE) {
-  if (is.mic(x)) {
-    x
-  } else {
-    x <- x %>% unlist()
-    if (na.rm == TRUE) {
-      x <- x[!is.na(x)]
-    }
-    x.bak <- x
-    
-    # comma to dot
-    x <- gsub(',', '.', x, fixed = TRUE)
-    # starting dots must start with 0
-    x <- gsub('^[.]', '0.', x)
-    # <=0.2560.512 should be 0.512
-    x <- gsub('.*[.].*[.]', '0.', x)
-    # remove ending .0
-    x <- gsub('[.]0$', '', x)
-    # remove all after last digit
-    x <- gsub('[^0-9]$', '', x)
-    # remove last zeroes
-    x <- gsub('[.]?0+$', '', x)
-    
-    lvls <- c("<0.002", "<=0.002", "0.002", ">=0.002", ">0.002",
-              "<0.003", "<=0.003", "0.003", ">=0.003", ">0.003",
-              "<0.004", "<=0.004", "0.004", ">=0.004", ">0.004",
-              "<0.006", "<=0.006", "0.006", ">=0.006", ">0.006",
-              "<0.008", "<=0.008", "0.008", ">=0.008", ">0.008",
-              "<0.012", "<=0.012", "0.012", ">=0.012", ">0.012",
-              "<0.016", "<=0.016", "0.016", ">=0.016", ">0.016",
-              "<0.023", "<=0.023", "0.023", ">=0.023", ">0.023",
-              "<0.03", "<=0.03", "0.03", ">=0.03", ">0.03",
-              "<0.032", "<=0.032", "0.032", ">=0.032", ">0.032",
-              "<0.047", "<=0.047", "0.047", ">=0.047", ">0.047",
-              "<0.05", "<=0.05", "0.05", ">=0.05", ">0.05",
-              "<0.06", "<=0.06", "0.06", ">=0.06", ">0.06",
-              "<0.0625", "<=0.0625", "0.0625", ">=0.0625", ">0.0625",
-              "<0.064", "<=0.064", "0.064", ">=0.064", ">0.064",
-              "<0.09", "<=0.09", "0.09", ">=0.09", ">0.09",
-              "<0.094", "<=0.094", "0.094", ">=0.094", ">0.094",
-              "<0.12", "<=0.12", "0.12", ">=0.12", ">0.12",
-              "<0.125", "<=0.125", "0.125", ">=0.125", ">0.125",
-              "<0.128", "<=0.128", "0.128", ">=0.128", ">0.128",
-              "<0.19", "<=0.19", "0.19", ">=0.19", ">0.19",
-              "<0.25", "<=0.25", "0.25", ">=0.25", ">0.25",
-              "<0.256", "<=0.256", "0.256", ">=0.256", ">0.256",
-              "<0.38", "<=0.38", "0.38", ">=0.38", ">0.38",
-              "<0.5", "<=0.5", "0.5", ">=0.5", ">0.5",
-              "<0.512", "<=0.512", "0.512", ">=0.512", ">0.512",
-              "<0.75", "<=0.75", "0.75", ">=0.75", ">0.75",
-              "<1", "<=1", "1", ">=1", ">1",
-              "<1.5", "<=1.5", "1.5", ">=1.5", ">1.5",
-              "<2", "<=2", "2", ">=2", ">2",
-              "<3", "<=3", "3", ">=3", ">3",
-              "<4", "<=4", "4", ">=4", ">4",
-              "<6", "<=6", "6", ">=6", ">6",
-              "<8", "<=8", "8", ">=8", ">8",
-              "<10", "<=10", "10", ">=10", ">10",
-              "<12", "<=12", "12", ">=12", ">12",
-              "<16", "<=16", "16", ">=16", ">16",
-              "<20", "<=20", "20", ">=20", ">20",
-              "<24", "<=24", "24", ">=24", ">24",
-              "<32", "<=32", "32", ">=32", ">32",
-              "<40", "<=40", "40", ">=40", ">40",
-              "<48", "<=48", "48", ">=48", ">48",
-              "<64", "<=64", "64", ">=64", ">64",
-              "<80", "<=80", "80", ">=80", ">80",
-              "<96", "<=96", "96", ">=96", ">96",
-              "<128", "<=128", "128", ">=128", ">128",
-              "<160", "<=160", "160", ">=160", ">160",
-              "<256", "<=256", "256", ">=256", ">256",
-              "<320", "<=320", "320", ">=320", ">320",
-              "<512", "<=512", "512", ">=512", ">512",
-              "<1024", "<=1024", "1024", ">=1024", ">1024")
-    x <- x %>% as.character()
-    
-    na_before <- x[is.na(x) | x == ''] %>% length()
-    x[!x %in% lvls] <- NA
-    na_after <- x[is.na(x) | x == ''] %>% length()
-    
-    if (na_before != na_after) {
-      list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ''] %>%
-        unique() %>%
-        sort()
-      list_missing <- paste0('"', list_missing , '"', collapse = ", ")
-      warning(na_after - na_before, ' results truncated (',
-              round(((na_after - na_before) / length(x)) / 100),
-              '%) that were invalid MICs: ',
-              list_missing, call. = FALSE)
-    }
-    
-    x <- factor(x = x,
-                levels = lvls,
-                ordered = TRUE)
-    class(x) <- c('mic', 'ordered', 'factor')
-    x
-  }
-}
-
-#' @rdname as.mic
-#' @export
-#' @importFrom dplyr %>%
-is.mic <- function(x) {
-  class(x) %>% identical(c('mic', 'ordered', 'factor'))
-}
-
-#' @exportMethod as.double.mic
-#' @export
-#' @importFrom dplyr %>%
-#' @noRd
-as.double.mic <- function(x, ...) {
-  as.double(gsub('(<=)|(>=)', '', as.character(x)))
-}
-
-#' @exportMethod as.integer.mic
-#' @export
-#' @importFrom dplyr %>%
-#' @noRd
-as.integer.mic <- function(x, ...) {
-  as.integer(gsub('(<=)|(>=)', '', as.character(x)))
-}
-
-#' @exportMethod as.numeric.mic
-#' @export
-#' @importFrom dplyr %>%
-#' @noRd
-as.numeric.mic <- function(x, ...) {
-  as.numeric(gsub('(<=)|(>=)', '', as.character(x)))
-}
-
-#' @exportMethod print.mic
-#' @export
-#' @importFrom dplyr %>% tibble group_by summarise pull
-#' @noRd
-print.mic <- function(x, ...) {
-  n_total <- x %>% length()
-  x <- x[!is.na(x)]
-  n <- x %>% length()
-  cat("Class 'mic': ", n, " isolates\n", sep = '')
-  cat('\n')
-  cat('<NA> ', n_total - n, '\n')
-  cat('\n')
-  tbl <- tibble(x = x, y = 1) %>% group_by(x) %>% summarise(y = sum(y))
-  cnt <- tbl %>% pull(y)
-  names(cnt) <- tbl %>% pull(x)
-  print(cnt)
-}
-
-#' @exportMethod summary.mic
-#' @export
-#' @importFrom dplyr %>% tibble group_by summarise pull
-#' @noRd
-summary.mic <- function(object, ...) {
-  x <- object
-  n_total <- x %>% length()
-  x <- x[!is.na(x)]
-  n <- x %>% length()
-  return(c("Mode" = 'mic',
-           "NA" = n_total - n,
-           "Min." = sort(x)[1] %>% as.character(),
-           "Max." = sort(x)[n] %>% as.character()
-  ))
-  cat("Class 'mic': ", n, " isolates\n", sep = '')
-  cat('\n')
-  cat('<NA> ', n_total - n, '\n')
-  cat('\n')
-  tbl <- tibble(x = x, y = 1) %>% group_by(x) %>% summarise(y = sum(y))
-  cnt <- tbl %>% pull(y)
-  names(cnt) <- tbl %>% pull(x)
-  print(cnt)
-}
-
-#' @exportMethod plot.mic
-#' @export
-#' @importFrom dplyr %>% group_by summarise
-#' @importFrom graphics plot text
-#' @noRd
-plot.mic <- function(x, ...) {
-  x_name <- deparse(substitute(x))
-  
-  data <- data.frame(mic = x, cnt = 1) %>%
-    group_by(mic) %>%
-    summarise(cnt = sum(cnt)) %>%
-    droplevels()
-
-  plot(x = data$mic,
-       y = data$cnt,
-       lwd = 2,
-       ylim = c(-0.5, max(5, max(data$cnt))),
-       ylab = 'Frequency',
-       xlab = 'MIC value',
-       main = paste('MIC values of', x_name),
-       ...)
-  text(x = data$mic,
-       y = -0.5,
-       labels = paste('n =', data$cnt))
-}

R/data.R

@@ -1,77 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Analysis                              #
-#                                                                      #
-# AUTHORS                                                              #
-# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)           #
-#                                                                      #
-# LICENCE                                                              #
-# This program is free software; you can redistribute it and/or modify #
-# it under the terms of the GNU General Public License version 2.0,    #
-# as published by the Free Software Foundation.                        #
-#                                                                      #
-# This program is distributed in the hope that it will be useful,      #
-# but WITHOUT ANY WARRANTY; without even the implied warranty of       #
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the        #
-# GNU General Public License for more details.                         #
-# ==================================================================== #
-
-#' Dataset with 420 antibiotics
-#'
-#' A dataset containing all antibiotics with a J0 code, with their DDD's.
-#' @format A data.frame with 420 observations and 12 variables:
-#' \describe{
-#'   \item{\code{atc}}{ATC code, like \code{J01CR02}}
-#'   \item{\code{molis}}{MOLIS code, like \code{amcl}}
-#'   \item{\code{umcg}}{UMCG code, like \code{AMCL}}
-#'   \item{\code{official}}{Official name by the WHO, like \code{"amoxicillin and enzyme inhibitor"}}
-#'   \item{\code{official_nl}}{Official name in the Netherlands, like \code{"Amoxicilline met enzymremmer"}}
-#'   \item{\code{trivial}}{Trivial name in Dutch, like \code{"Amoxicilline/clavulaanzuur"}}
-#'   \item{\code{oral_ddd}}{Daily Defined Dose (DDD) according to the WHO, oral treatment}
-#'   \item{\code{oral_units}}{Units of \code{ddd_units}}
-#'   \item{\code{iv_ddd}}{Daily Defined Dose (DDD) according to the WHO, bij parenteral treatment}
-#'   \item{\code{iv_units}}{Units of \code{iv_ddd}}
-#'   \item{\code{atc_group1}}{ATC group in Dutch, like \code{"Macroliden, lincosamiden en streptograminen"}}
-#'   \item{\code{atc_group2}}{Subgroup of \code{atc_group1} in Dutch, like \code{"Macroliden"}}
-#' }
-#' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) - \url{https://www.umcg.nl} \cr \cr World Health Organization - \url{https://www.whocc.no/atc_ddd_index/}
-#' @seealso \code{\link{bactlist}}
-# todo:
-# ablist <- ablist %>% mutate(useful_gramnegative = if_else(atc_group2 == 'Tetracyclines', FALSE, TRUE))
-# ablist <- ablist %>% mutate(useful_gramnegative = if_else(atc_group2 %like% 'Glycopept', FALSE, useful_gramnegative))
-# Tbl1 Enterobacteriaceae are also intrinsically resistant to benzylpenicillin, glycopeptides, fusidic acid, macrolides (with some exceptions1), lincosamides, streptogramins, rifampicin, daptomycin and linezolid.
-# Tbl2 Non-fermentative Gram-negative bacteria are also generally intrinsically resistant to benzylpenicillin, first and second generation cephalosporins, glycopeptides, fusidic acid, macrolides, lincosamides, streptogramins, rifampicin, daptomycin and linezolid
-# Tbl3 Gram-negative bacteria other than Enterobacteriaceae and non-fermentative Gram-negative bacteria listed are also intrinsically resistant to glycopeptides, lincosamides, daptomycin and linezolid.
-"ablist"
-
-#' Dataset with ~2500 microorganisms
-#'
-#' A dataset containing all microorganisms of MOLIS. MO codes of the UMCG can be looked up using \code{\link{bactlist.umcg}}.
-#' @format A data.frame with 2507 observations and 10 variables:
-#' \describe{
-#'   \item{\code{bactid}}{ID of microorganism}
-#'   \item{\code{bactsys}}{Bactsyscode of microorganism}
-#'   \item{\code{family}}{Family name of microorganism}
-#'   \item{\code{genus}}{Genus name of microorganism, like \code{"Echerichia"}}
-#'   \item{\code{species}}{Species name of microorganism, like \code{"coli"}}
-#'   \item{\code{subspecies}}{Subspecies name of bio-/serovar of microorganism, like \code{"EHEC"}}
-#'   \item{\code{fullname}}{Full name, like \code{"Echerichia coli (EHEC)"}}
-#'   \item{\code{type}}{Type of microorganism, like \code{"Bacterie"} en \code{"Schimmel/gist"} (these are Dutch)}
-#'   \item{\code{gramstain}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
-#'   \item{\code{aerobic}}{Type aerobe/anaerobe of bacteria}
-#' }
-#' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
-#' @seealso \code{\link{ablist}} \code{\link{bactlist.umcg}}
-"bactlist"
-
-#' Translation table for UMCG with ~1100 microorganisms
-#'
-#' A dataset containing all bacteria codes of UMCG MMB. These codes can be joined to data with an ID from \code{\link{bactlist}$bactid}, using \code{\link{left_join_bactlist}}.
-#' @format A data.frame with 1090 observations and 2 variables:
-#' \describe{
-#'   \item{\code{mocode}}{Code of microorganism according to UMCG MMB}
-#'   \item{\code{bactid}}{Code of microorganism in \code{\link{bactlist}}}
-#' }
-#' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) - \url{https://www.umcg.nl}
-#' @seealso \code{\link{bactlist}}
-"bactlist.umcg"

R/first_isolates.R

@@ -1,516 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Analysis                              #
-#                                                                      #
-# AUTHORS                                                              #
-# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)           #
-#                                                                      #
-# LICENCE                                                              #
-# This program is free software; you can redistribute it and/or modify #
-# it under the terms of the GNU General Public License version 2.0,    #
-# as published by the Free Software Foundation.                        #
-#                                                                      #
-# This program is distributed in the hope that it will be useful,      #
-# but WITHOUT ANY WARRANTY; without even the implied warranty of       #
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the        #
-# GNU General Public License for more details.                         #
-# ==================================================================== #
-
-#' Determine first (weighted) isolates
-#'
-#' Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type.
-#' @param tbl a \code{data.frame} containing isolates.
-#' @param col_date column name of the result date (or date that is was received on the lab)
-#' @param col_patid column name of the unique IDs of the patients
-#' @param col_genus column name of the genus of the microorganisms
-#' @param col_species column name of the species of the microorganisms
-#' @param col_testcode column name of the test codes, see Details
-#' @param col_specimen column name of the specimen type or group
-#' @param col_icu column name of the logicals (\code{TRUE}/\code{FALSE}) whether a ward or department is an Intensive Care Unit (ICU)
-#' @param col_keyantibiotics column name of the key antibiotics to determine first \emph{weighted} isolates, see \code{\link{key_antibiotics}}.
-#' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again
-#' @param testcodes_exclude character vector with test codes that should be excluded (caseINsensitive)
-#' @param icu_exclude logical whether ICU isolates should be excluded
-#' @param filter_specimen specimen group or type that should be excluded
-#' @param output_logical return output as \code{logical} (will else the values \code{0} or \code{1})
-#' @param ignore_I ignore \code{"I"} as antimicrobial interpretation of key antibiotics (with \code{FALSE}, changes in antibiograms from S to I and I to R will be interpreted as difference)
-#' @param info print progress
-# @param ... parameters to pass through to \code{first_isolate}.
-#' @rdname first_isolate
-#' @details To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode. If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that is was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all \emph{S. aureus} isolates would be overestimated, because you included this MRSA more than once. It would be selection bias.
-#'
-#'     Use \code{col_testcode = NA} to \strong{not} exclude certain test codes (like test codes for screening). In that case \code{testcodes_exclude} will be ignored.
-#' @keywords isolate isolates first
-#' @importFrom dplyr arrange_at lag between row_number filter mutate arrange
-#' @return A vector to add to table, see Examples.
-#' @examples
-#' \dontrun{
-#'
-#' # set key antibiotics to a new variable
-#' tbl$keyab <- key_antibiotics(tbl)
-#'
-#' tbl$first_isolate <-
-#'   first_isolate(tbl)
-#'
-#' tbl$first_isolate_weighed <-
-#'   first_isolate(tbl,
-#'                 col_keyantibiotics = 'keyab')
-#'
-#' tbl$first_blood_isolate <-
-#'   first_isolate(tbl,
-#'                 filter_specimen = 'Blood')
-#'
-#' tbl$first_blood_isolate_weighed <-
-#'   first_isolate(tbl,
-#'                 filter_specimen = 'Blood',
-#'                 col_keyantibiotics = 'keyab')
-#'
-#' tbl$first_urine_isolate <-
-#'   first_isolate(tbl,
-#'                 filter_specimen = 'Urine')
-#'
-#' tbl$first_urine_isolate_weighed <-
-#'   first_isolate(tbl,
-#'                 filter_specimen = 'Urine',
-#'                 col_keyantibiotics = 'keyab')
-#'
-#' tbl$first_resp_isolate <-
-#'   first_isolate(tbl,
-#'                 filter_specimen = 'Respiratory')
-#'
-#' tbl$first_resp_isolate_weighed <-
-#'   first_isolate(tbl,
-#'                 filter_specimen = 'Respiratory',
-#'                 col_keyantibiotics = 'keyab')
-#' }
-first_isolate <- function(tbl,
-                          col_date,
-                          col_patid,
-                          col_genus,
-                          col_species,
-                          col_testcode = NA,
-                          col_specimen,
-                          col_icu,
-                          col_keyantibiotics = NA,
-                          episode_days = 365,
-                          testcodes_exclude = '',
-                          icu_exclude = FALSE,
-                          filter_specimen = NA,
-                          output_logical = TRUE,
-                          ignore_I = TRUE,
-                          info = TRUE) {
-  
-  # controleren of kolommen wel bestaan
-  check_columns_existance <- function(column, tblname = tbl) {
-    if (NROW(tblname) <= 1 | NCOL(tblname) <= 1) {
-      stop('Please check tbl for existance.')
-    }
-    
-    if (!is.na(column)) {
-      if (!(column %in% colnames(tblname))) {
-        stop('Column ', column, ' not found.')
-      }
-    }
-  }
-  
-  check_columns_existance(col_date)
-  check_columns_existance(col_patid)
-  check_columns_existance(col_genus)
-  check_columns_existance(col_species)
-  check_columns_existance(col_testcode)
-  check_columns_existance(col_icu)
-  check_columns_existance(col_keyantibiotics)
-  
-  if (is.na(col_testcode)) {
-    testcodes_exclude <- NA
-  }
-  # testcodes verwijderen die ingevuld zijn
-  if (!is.na(testcodes_exclude[1]) & testcodes_exclude[1] != '' & info == TRUE) {
-    cat('Isolates from these test codes will be ignored:\n', toString(testcodes_exclude), '\n')
-  }
-  
-  if (is.na(col_icu)) {
-    icu_exclude <- FALSE
-  } else {
-    tbl <- tbl %>%
-      mutate(col_icu = tbl %>% pull(col_icu) %>% as.logical())
-  }
-  
-  specgroup.notice <- ''
-  weighted.notice <- ''
-  # filteren op materiaalgroep en sleutelantibiotica gebruiken wanneer deze ingevuld zijn
-  if (!is.na(filter_specimen) & filter_specimen != '') {
-    check_columns_existance(col_specimen, tbl)
-    if (info == TRUE) {
-      cat('Isolates other than of specimen group \'', filter_specimen, '\' will be ignored. ', sep = '')
-    }
-  } else {
-    filter_specimen <- ''
-  }
-  if (col_keyantibiotics %in% c(NA, '')) {
-    col_keyantibiotics <- ''
-  } else {
-    tbl <- tbl %>% mutate(key_ab = tbl %>% pull(col_keyantibiotics))
-  }
-  
-  if (is.na(testcodes_exclude[1])) {
-    testcodes_exclude <- ''
-  }
-  
-  # nieuwe dataframe maken met de oorspronkelijke rij-index, 0-bepaling en juiste sortering
-  #cat('Sorting table...')
-  tbl <- tbl %>%
-    mutate(first_isolate_row_index = 1:nrow(tbl),
-           eersteisolaatbepaling = 0,
-           date_lab = tbl %>% pull(col_date),
-           species = if_else(is.na(species), '', species),
-           genus = if_else(is.na(genus), '', genus))
-  
-  if (filter_specimen == '') {
-    
-    if (icu_exclude == FALSE) {
-      if (info == TRUE) {
-        cat('Isolates from ICU will *NOT* be ignored.\n')
-      }
-      tbl <- tbl %>%
-        arrange_at(c(col_patid,
-                     col_genus,
-                     col_species,
-                     col_date))
-      row.start <- 1
-      row.end <- nrow(tbl)
-    } else {
-      if (info == TRUE) {
-        cat('Isolates from ICU will be ignored.\n')
-      }
-      tbl <- tbl %>%
-        arrange_at(c(col_icu,
-                     col_patid,
-                     col_genus,
-                     col_species,
-                     col_date))
-      
-      suppressWarnings(
-        row.start <- which(tbl %>% pull(col_icu) == FALSE) %>% min(na.rm = TRUE)
-      )
-      suppressWarnings(
-        row.end <- which(tbl %>% pull(col_icu) == FALSE) %>% max(na.rm = TRUE)
-      )
-    }
-    
-  } else {
-    # sorteren op materiaal en alleen die rijen analyseren om tijd te besparen
-    if (icu_exclude == FALSE) {
-      if (info == TRUE) {
-        cat('Isolates from ICU will *NOT* be ignored.\n')
-      }
-      tbl <- tbl %>%
-        arrange_at(c(col_specimen,
-                     col_patid,
-                     col_genus,
-                     col_species,
-                     col_date))
-      suppressWarnings(
-        row.start <- which(tbl %>% pull(col_specimen) == filter_specimen) %>% min(na.rm = TRUE)
-      )
-      suppressWarnings(
-        row.end <- which(tbl %>% pull(col_specimen) == filter_specimen) %>% max(na.rm = TRUE)
-      )
-    } else {
-      if (info == TRUE) {
-        cat('Isolates from ICU will be ignored.\n')
-      }
-      tbl <- tbl %>%
-        arrange_at(c(col_icu,
-                     col_specimen,
-                     col_patid,
-                     col_genus,
-                     col_species,
-                     col_date))
-      suppressWarnings(
-        row.start <- which(tbl %>% pull(col_specimen) == filter_specimen
-                           & tbl %>% pull(col_icu) == FALSE) %>% min(na.rm = TRUE)
-      )
-      suppressWarnings(
-        row.end <- which(tbl %>% pull(col_specimen) == filter_specimen
-                         & tbl %>% pull(col_icu) == FALSE) %>% max(na.rm = TRUE)
-      )
-    }
-    
-  }
-  
-  if (abs(row.start) == Inf | abs(row.end) == Inf) {
-    if (info == TRUE) {
-      cat('No isolates found.\n')
-    }
-    # NA's maken waar genus niet beschikbaar is
-    tbl <- tbl %>%
-      mutate(real_first_isolate = if_else(genus == '', NA, FALSE))
-    if (output_logical == FALSE) {
-      tbl$real_first_isolate <- tbl %>% pull(real_first_isolate) %>% as.integer()
-    }
-    return(tbl %>% pull(real_first_isolate))
-  }
-  
-  scope.size <- tbl %>%
-    filter(row_number() %>%
-             between(row.start,
-                     row.end),
-           genus != '') %>%
-    nrow()
-  
-  # Analyse van eerste isolaat ----
-  all_first <- tbl %>%
-    mutate(other_pat_or_mo = if_else(patient_id == lag(patient_id)
-                                     & genus == lag(genus)
-                                     & species == lag(species),
-                                     FALSE,
-                                     TRUE),
-           days_diff = 0) %>%
-    mutate(days_diff = if_else(other_pat_or_mo == FALSE,
-                               (date_lab - lag(date_lab)) + lag(days_diff),
-                               0))
-  
-  if (col_keyantibiotics != '') {
-    # dit duurt 2 min bij 120.000 isolaten
-    if (info == TRUE) {
-      cat('Comparing key antibiotics for first weighted isolates')
-      if (ignore_I == TRUE) {
-        cat(' (ignoring I)')
-      }
-      cat('...\n')
-    }
-    all_first <- all_first %>%
-      mutate(key_ab_lag = lag(key_ab)) %>%
-      mutate(key_ab_other = !key_antibiotics_equal(key_ab,
-                                                  key_ab_lag,
-                                                  ignore_I = ignore_I,
-                                                  info = info)) %>%
-      mutate(
-        real_first_isolate =
-          if_else(
-            between(row_number(), row.start, row.end)
-            & genus != ''
-            & (other_pat_or_mo
-               | days_diff >= episode_days
-               | key_ab_other),
-            TRUE,
-            FALSE))
-    if (info == TRUE) {
-      cat('\n')
-    }
-  } else {
-    all_first <- all_first %>%
-      mutate(
-        real_first_isolate =
-          if_else(
-            between(row_number(), row.start, row.end)
-            & genus != ''
-            & (other_pat_or_mo
-               | days_diff >= episode_days),
-            TRUE,
-            FALSE))
-  }
-  
-  # allereerst isolaat als TRUE
-  all_first[row.start, 'real_first_isolate'] <- TRUE
-  # geen testen die uitgesloten moeten worden, of ICU
-  if (!is.na(col_testcode)) {
-    all_first[which(all_first[, col_testcode] %in% tolower(testcodes_exclude)), 'real_first_isolate'] <- FALSE
-  }
-  if (icu_exclude == TRUE) {
-    all_first[which(all_first[, col_icu] == TRUE), 'real_first_isolate'] <- FALSE
-  }
-  
-  # NA's maken waar genus niet beschikbaar is
-  all_first <- all_first %>%
-    mutate(real_first_isolate = if_else(genus == '', NA, real_first_isolate))
-  
-  all_first <- all_first %>%
-    arrange(first_isolate_row_index) %>%
-    pull(real_first_isolate)
-  
-  if (info == TRUE) {
-    cat(paste0('\nFound ',
-               all_first %>% sum(na.rm = TRUE),
-               ' first ', weighted.notice, 'isolates (',
-               (all_first %>% sum(na.rm = TRUE) / scope.size) %>% percent(),
-               ' of isolates in scope [where genus was not empty] and ',
-               (all_first %>% sum(na.rm = TRUE) / tbl %>% nrow()) %>% percent(),
-               ' of total)\n'))
-  }
-  
-  if (output_logical == FALSE) {
-    all_first <- all_first %>% as.integer()
-  }
-  
-  all_first
-  
-}
-
-#' Key antibiotics based on bacteria ID
-#'
-#' @param tbl table with antibiotics coloms, like \code{amox} and \code{amcl}.
-#' @param col_bactcode column of bacteria IDs in \code{tbl}; these should occur in \code{bactlist$bactid}, see \code{\link{bactlist}}
-#' @param info print warnings
-#' @param amcl,amox,cfot,cfta,cftr,cfur,cipr,clar,clin,clox,doxy,gent,line,mero,peni,pita,rifa,teic,trsu,vanc column names of antibiotics.
-#' @export
-#' @importFrom dplyr %>% mutate if_else 
-#' @return Character of length 1.
-#' @seealso \code{\link{mo_property}} \code{\link{ablist}}
-#' @examples 
-#' \donttest{
-#' #' # set key antibiotics to a new variable
-#' tbl$keyab <- key_antibiotics(tbl)
-#' }
-key_antibiotics <- function(tbl,
-                            col_bactcode = 'bacteriecode',
-                            info = TRUE,
-                            amcl = 'amcl',
-                            amox = 'amox',
-                            cfot = 'cfot',
-                            cfta = 'cfta',
-                            cftr = 'cftr',
-                            cfur = 'cfur',
-                            cipr = 'cipr',
-                            clar = 'clar',
-                            clin = 'clin',
-                            clox = 'clox',
-                            doxy = 'doxy',
-                            gent = 'gent',
-                            line = 'line',
-                            mero = 'mero',
-                            peni = 'peni',
-                            pita = 'pita',
-                            rifa = 'rifa',
-                            teic = 'teic',
-                            trsu = 'trsu',
-                            vanc = 'vanc') {
-  
-  keylist <- character(length = nrow(tbl))
-  
-  # check columns
-  col.list <- c(amox, cfot, cfta, cftr, cfur, cipr, clar,
-                clin, clox, doxy, gent, line, mero, peni,
-                pita, rifa, teic, trsu, vanc)
-  col.list <- col.list[!is.na(col.list)]
-  if (!all(col.list %in% colnames(tbl))) {
-    if (info == TRUE) {
-      warning('These columns do not exist and will be ignored:\n',
-              col.list[!(col.list %in% colnames(tbl))] %>% toString(),
-              immediate. = TRUE,
-              call. = FALSE)
-    }
-  }
-  
-  # bactlist aan vastknopen
-  tbl <- tbl %>% left_join_bactlist(col_bactcode)
-  
-  tbl$key_ab <- NA_character_
-  
-  # Staphylococcus
-  list_ab <- c(clox, trsu, teic, vanc, doxy, line, clar, rifa)
-  list_ab <- list_ab[list_ab %in% colnames(tbl)]
-  tbl <- tbl %>% mutate(key_ab =
-                          if_else(genus == 'Staphylococcus',
-                                  apply(X = tbl[, list_ab],
-                                        MARGIN = 1,
-                                        FUN = function(x) paste(x, collapse = "")),
-                                  key_ab))
-  
-  # Rest of Gram +
-  list_ab <- c(peni, amox, teic, vanc, clin, line, clar, trsu)
-  list_ab <- list_ab[list_ab %in% colnames(tbl)]
-  tbl <- tbl %>% mutate(key_ab =
-                          if_else(gramstain %like% '^Positi[e]?ve',
-                                  apply(X = tbl[, list_ab],
-                                        MARGIN = 1,
-                                        FUN = function(x) paste(x, collapse = "")),
-                                  key_ab))
-  
-  # Gram -
-  list_ab <- c(amox, amcl, pita, cfur, cfot, cfta, cftr, mero, cipr, trsu, gent)
-  list_ab <- list_ab[list_ab %in% colnames(tbl)]
-  tbl <- tbl %>% mutate(key_ab =
-                          if_else(gramstain %like% '^Negati[e]?ve',
-                                  apply(X = tbl[, list_ab],
-                                        MARGIN = 1,
-                                        FUN = function(x) paste(x, collapse = "")),
-                                  key_ab))
-  
-  # format
-  tbl <- tbl %>%
-    mutate(key_ab = gsub('(NA|NULL)', '-', key_ab) %>% toupper())
-  
-  tbl$key_ab
-  
-}
-
-# Compare key antibiotics
-#
-# Check whether two text values with key antibiotics match. Supports vectors.
-# @param x,y tekst (or multiple text vectors) with antimicrobial interpretations
-# @param ignore_I ignore \code{"I"} as antimicrobial interpretation of key antibiotics (with \code{FALSE}, changes in antibiograms from S to I and I to R will be interpreted as difference)
-# @param info print progress
-# @return logical
-# @export
-# @seealso \code{\link{key_antibiotics}}
-
-# only internal use
-key_antibiotics_equal <- function(x, y, ignore_I = TRUE, info = FALSE) {
-  if (length(x) != length(y)) {
-    stop('Length of `x` and `y` must be equal.')
-  }
-  
-  result <- logical(length(x))
-  
-  if (info == TRUE) {
-    voortgang <- dplyr::progress_estimated(length(x))
-  }
-  
-  for (i in 1:length(x)) {
-    
-    if (info == TRUE) {
-      voortgang$tick()$print()
-    }
-    
-    if (is.na(x[i])) {
-      x[i] <- ''
-    }
-    if (is.na(y[i])) {
-      y[i] <- ''
-    }
-    
-    if (nchar(x[i]) != nchar(y[i])) {
-      
-      result[i] <- FALSE
-      
-    } else if (x[i] == '' & y[i] == '') {
-      
-      result[i] <- TRUE
-      
-    } else {
-      
-      x2 <- strsplit(x[i], "")[[1]]
-      y2 <- strsplit(y[i], "")[[1]]
-      
-      if (ignore_I == TRUE) {
-        valid_chars <- c('S', 's', 'R', 'r')
-      } else {
-        valid_chars <- c('S', 's', 'I', 'i', 'R', 'r')
-      }
-      
-      # Ongeldige waarden (zoals "-", NA) op beide locaties verwijderen
-      x2[which(!x2 %in% valid_chars)] <- '?'
-      x2[which(!y2 %in% valid_chars)] <- '?'
-      y2[which(!x2 %in% valid_chars)] <- '?'
-      y2[which(!y2 %in% valid_chars)] <- '?'
-      
-      result[i] <- all(x2 == y2)
-    }
-  }
-  if (info == TRUE) {
-    cat('\n')
-  }
-  result
-}

R/globals.R

@@ -1,37 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Analysis                              #
-#                                                                      #
-# AUTHORS                                                              #
-# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)           #
-#                                                                      #
-# LICENCE                                                              #
-# This program is free software; you can redistribute it and/or modify #
-# it under the terms of the GNU General Public License version 2.0,    #
-# as published by the Free Software Foundation.                        #
-#                                                                      #
-# This program is distributed in the hope that it will be useful,      #
-# but WITHOUT ANY WARRANTY; without even the implied warranty of       #
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the        #
-# GNU General Public License for more details.                         #
-# ==================================================================== #
-
-globalVariables(c('.',
-                  'abname',
-                  'bactid',
-                  'cnt',
-                  'date_lab',
-                  'days_diff',
-                  'first_isolate_row_index',
-                  'genus',
-                  'gramstain',
-                  'key_ab',
-                  'key_ab_lag',
-                  'key_ab_other',
-                  'mic',
-                  'n',
-                  'other_pat_or_mo',
-                  'patient_id',
-                  'real_first_isolate',
-                  'species',
-                  'y'))

R/join.R

@@ -1,109 +0,0 @@
-#' Join a table with \code{bactlist}
-#'
-#' Join the list of microorganisms \code{\link{bactlist}} easily to an existing table.
-#' @rdname join
-#' @name join
-#' @aliases join inner_join
-#' @param x existing table to join
-#' @param by a variable to join by - could be a column name of \code{x} with values that exist in \code{bactlist$bactid} (like \code{by = "bacteria_id"}), or another column in \code{\link{bactlist}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})
-#' @param ... other parameters to pass trhough to \code{dplyr::\link[dplyr]{join}}.
-#' @details As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
-#' @export
-#' @examples 
-#' df <- data.frame(date = seq(from = as.Date("2018-01-01"),
-#'                             to = as.Date("2018-01-07"),
-#'                             by = 1),
-#'                  bacteria_id = c("STAAUR", "STAAUR", "STAAUR", "STAAUR",
-#'                                  "ESCCOL", "ESCCOL", "ESCCOL"),
-#'                  stringsAsFactors = FALSE)
-#'                  
-#' colnames(df)
-#' df2 <- left_join_bactlist(df, "bacteria_id")
-#' colnames(df2)
-inner_join_bactlist <- function(x, by = 'bactid', ...) {
-  # no name set to `by` parameter
-  if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
-    names(joinby) <- by
-  } else {
-    joinby <- by
-  }
-  join <- dplyr::inner_join(x = x, y = AMR::bactlist, by = joinby, suffix = c("2", ""), ...)
-  if (nrow(join) > nrow(x)) {
-    warning('the newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original')
-  }
-  join
-}
-
-#' @rdname join
-#' @export
-left_join_bactlist <- function(x, by = 'bacteriecode', ...) {
-  # no name set to `by` parameter
-  if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
-    names(joinby) <- by
-  } else {
-    joinby <- by
-  }
-  join <- dplyr::left_join(x = x, y = AMR::bactlist, by = joinby, suffix = c("2", ""), ...)
-  if (nrow(join) > nrow(x)) {
-    warning('the newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original')
-  }
-  join
-}
-
-#' @rdname join
-#' @export
-right_join_bactlist <- function(x, by = 'bacteriecode', ...) {
-  # no name set to `by` parameter
-  if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
-    names(joinby) <- by
-  } else {
-    joinby <- by
-  }
-  join <- dplyr::right_join(x = x, y = AMR::bactlist, by = joinby, suffix = c("2", ""), ...)
-  if (nrow(join) > nrow(x)) {
-    warning('the newly joined tbl contains ', nrow(join) - nrow(x), ' rows more that its original')
-  }
-  join
-}
-
-#' @rdname join
-#' @export
-full_join_bactlist <- function(x, by = 'bacteriecode', ...) {
-  # no name set to `by` parameter
-  if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
-    names(joinby) <- by
-  } else {
-    joinby <- by
-  }
-  dplyr::full_join(x = x, y = AMR::bactlist, by = joinby, suffix = c("2", ""), ...)
-}
-
-#' @rdname join
-#' @export
-semi_join_bactlist <- function(x, by = 'bacteriecode', ...) {
-  # no name set to `by` parameter
-  if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
-    names(joinby) <- by
-  } else {
-    joinby <- by
-  }
-  dplyr::semi_join(x = x, y = AMR::bactlist, by = joinby, ...)
-}
-
-#' @rdname join
-#' @export
-anti_join_bactlist <- function(x, by = 'bacteriecode', ...) {
-  # no name set to `by` parameter
-  if (is.null(names(by))) {
-    joinby <- colnames(AMR::bactlist)[1]
-    names(joinby) <- by
-  } else {
-    joinby <- by
-  }
-  dplyr::anti_join(x = x, y = AMR::bactlist, by = joinby, ...)
-}

R/misc.R

@@ -1,31 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Analysis                              #
-#                                                                      #
-# AUTHORS                                                              #
-# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)           #
-#                                                                      #
-# LICENCE                                                              #
-# This program is free software; you can redistribute it and/or modify #
-# it under the terms of the GNU General Public License version 2.0,    #
-# as published by the Free Software Foundation.                        #
-#                                                                      #
-# This program is distributed in the hope that it will be useful,      #
-# but WITHOUT ANY WARRANTY; without even the implied warranty of       #
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the        #
-# GNU General Public License for more details.                         #
-# ==================================================================== #
-
-# No export, no Rd
-"%like%" <- function(vector, pattern) {
-  # Source: https://github.com/Rdatatable/data.table/blob/master/R/like.R
-  if (is.factor(vector)) {
-    as.integer(vector) %in% grep(pattern, levels(vector))
-  } else {
-    grepl(pattern, vector)
-  }
-}
-
-percent <- function(x, round = 1, ...) {
-  base::paste0(base::round(x * 100, digits = round), "%")
-}

R/rsi_analysis.R

@@ -1,386 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# Antimicrobial Resistance (AMR) Analysis                              #
-#                                                                      #
-# AUTHORS                                                              #
-# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)           #
-#                                                                      #
-# LICENCE                                                              #
-# This program is free software; you can redistribute it and/or modify #
-# it under the terms of the GNU General Public License version 2.0,    #
-# as published by the Free Software Foundation.                        #
-#                                                                      #
-# This program is distributed in the hope that it will be useful,      #
-# but WITHOUT ANY WARRANTY; without even the implied warranty of       #
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the        #
-# GNU General Public License for more details.                         #
-# ==================================================================== #
-
-#' Resistance of isolates in data.frame
-#'
-#' \strong{NOTE: use \code{\link{rsi}} in dplyr functions like \code{\link[dplyr]{summarise}}.} \cr Calculate the percentage of S, SI, I, IR or R of a \code{data.frame} containing isolates.
-#' @param tbl \code{data.frame} containing columns with antibiotic interpretations.
-#' @param antibiotics character vector with 1, 2 or 3 antibiotics that occur as column names in \code{tbl}, like \code{antibiotics = c("amox", "amcl")}
-#' @param interpretation antimicrobial interpretation of which the portion must be calculated. Valid values are \code{"S"}, \code{"SI"}, \code{"I"}, \code{"IR"} or \code{"R"}.
-#' @param minimum minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA} with a warning (when \code{warning = TRUE}).
-#' @param percent return output as percent (text), will else (at default) be a double
-#' @param info calculate the amount of available isolates and print it, like \code{n = 423}
-#' @param warning show a warning when the available amount of isolates is below \code{minimum}
-#' @details Remember that you should filter your table to let it contain \strong{only first isolates}!
-#' @keywords rsi antibiotics isolate isolates
-#' @return Double or, when \code{percent = TRUE}, a character.
-#' @export
-#' @importFrom dplyr %>% n_distinct filter filter_at pull vars all_vars any_vars
-#' @seealso \code{\link{rsi}} for the function that can be used with \code{\link[dplyr]{summarise}} directly.
-#' @examples
-#' \dontrun{
-#' rsi_df(tbl_with_bloodcultures, 'amcl')
-#'
-#' rsi_df(tbl_with_bloodcultures, c('amcl', 'gent'), interpretation = 'IR')
-#'
-#' library(dplyr)
-#' # calculate current empiric therapy of Helicobacter gastritis:
-#' my_table %>%
-#'   filter(first_isolate == TRUE, 
-#'          genus == "Helicobacter") %>%
-#'   rsi_df(antibiotics = c("amox", "metr"))
-#' }
-rsi_df <- function(tbl,
-                   antibiotics,
-                   interpretation = 'IR',
-                   minimum = 30,
-                   percent = FALSE,
-                   info = TRUE,
-                   warning = TRUE) {
-  
-  # we willen niet dat tbl$interpretation toevallig ook bestaat, dus:
-  te_testen_uitslag_ab <- interpretation
-  
-  # validatie:
-  if (min(grepl('^[a-z]{3,4}$', antibiotics)) == 0 &
-      min(grepl('^rsi[1-2]$', antibiotics)) == 0) {
-    for (i in 1:length(antibiotics)) {
-      antibiotics[i] <- paste0('rsi', i)
-    }
-  }
-  if (!grepl('^(S|SI|IS|I|IR|RI|R){1}$', te_testen_uitslag_ab)) {
-    stop('Invalid `interpretation`; must be "S", "SI", "I", "IR", or "R".')
-  }
-  if ('is_ic' %in% colnames(tbl)) {
-    if (n_distinct(tbl$is_ic) > 1) {
-      warning('Dataset contains isolates from the Intensive Care. Exclude them from proper epidemiological analysis.')
-    }
-  }
-  
-  # transformeren wanneer gezocht wordt op verschillende uitslagen
-  if (te_testen_uitslag_ab %in% c('SI', 'IS')) {
-    for (i in 1:length(antibiotics)) {
-      lijst <- tbl[, antibiotics[i]]
-      if ('I' %in% lijst) {
-        tbl[which(tbl[antibiotics[i]] == 'I'), ][antibiotics[i]] <- 'S'
-      }
-    }
-    te_testen_uitslag_ab <- 'S'
-  }
-  if (te_testen_uitslag_ab %in% c('RI', 'IR')) {
-    for (i in 1:length(antibiotics)) {
-      lijst <- tbl[, antibiotics[i]]
-      if ('I' %in% lijst) {
-        tbl[which(tbl[antibiotics[i]] == 'I'), ][antibiotics[i]] <- 'R'
-      }
-    }
-    te_testen_uitslag_ab <- 'R'
-  }
-  
-  # breuk samenstellen
-  if (length(antibiotics) == 1) {
-    numerator <- tbl %>%
-      filter(pull(., antibiotics[1]) == te_testen_uitslag_ab) %>%
-      nrow()
-    
-    denominator <- tbl %>%
-      filter(pull(., antibiotics[1]) %in% c("S", "I", "R")) %>%
-      nrow()
-    
-  } else if (length(antibiotics) == 2) {
-    numerator <- tbl %>%
-      filter_at(vars(antibiotics[1], antibiotics[2]),
-                any_vars(. == te_testen_uitslag_ab)) %>%
-      filter_at(vars(antibiotics[1], antibiotics[2]),
-                all_vars(. %in% c("S", "R", "I"))) %>%
-      nrow()
-    
-    denominator <- tbl %>%
-      filter_at(vars(antibiotics[1], antibiotics[2]),
-                all_vars(. %in% c("S", "R", "I"))) %>%
-      nrow()
-    
-  } else if (length(antibiotics) == 3) {
-    numerator <- tbl %>%
-      filter_at(vars(antibiotics[1], antibiotics[2], antibiotics[3]),
-                any_vars(. == te_testen_uitslag_ab)) %>%
-      filter_at(vars(antibiotics[1], antibiotics[2], antibiotics[3]),
-                all_vars(. %in% c("S", "R", "I"))) %>%
-      nrow()
-    
-    denominator <- tbl %>%
-      filter_at(vars(antibiotics[1], antibiotics[2], antibiotics[3]),
-                all_vars(. %in% c("S", "R", "I"))) %>%
-      nrow()
-    
-  } else {
-    stop('Maximum of 3 drugs allowed.')
-  }
-  
-  # tekstdeel opbouwen
-  if (info == TRUE) {
-    cat('n =', denominator)
-    info.txt1 <- percent(denominator / nrow(tbl))
-    if (denominator == 0) {
-      info.txt1 <- 'none'
-    }
-    info.txt2 <- gsub(',', ' and',
-                      antibiotics %>%
-                        abname(to = 'trivial',
-                               tolower = TRUE) %>%
-                        toString(), fixed = TRUE)
-    info.txt2 <- gsub('rsi1 and rsi2', 'these two drugs', info.txt2, fixed = TRUE)
-    info.txt2 <- gsub('rsi1', 'this drug', info.txt2, fixed = TRUE)
-    cat(paste0(' (of ', nrow(tbl), ' in total; ', info.txt1, ' tested on ', info.txt2, ')\n'))
-  }
-  
-  # rekenen en opmaken
-  y <- numerator / denominator
-  if (percent == TRUE) {
-    y <- percent(y)
-  }
-  if (denominator < minimum) {
-    if (warning == TRUE) {
-      warning(paste0('TOO FEW ISOLATES OF ', toString(antibiotics), ' (n = ', denominator, ', n < ', minimum, '); NO RESULT.'))
-    }
-    y <- NA
-  }
-  
-  # output
-  y
-}
-
-#' Resistance of isolates
-#'
-#' This function can be used in \code{dplyr}s \code{\link[dplyr]{summarise}}, see \emph{Examples}. Calculate the percentage S, SI, I, IR or R of a vector of isolates.
-#' @param ab1,ab2 list with interpretations of an antibiotic
-#' @inheritParams rsi_df
-#' @details This function uses the \code{\link{rsi_df}} function internally.
-#' @keywords rsi antibiotics isolate isolates
-#' @return Double or, when \code{percent = TRUE}, a character.
-#' @export
-#' @examples
-#' \dontrun{
-#' tbl %>%
-#'   group_by(hospital) %>%
-#'   summarise(cipr = rsi(cipr))
-#'   
-#' tbl %>%
-#'   group_by(year, hospital) %>%
-#'   summarise(
-#'     isolates = n(),
-#'     cipro = rsi(cipr %>% as.rsi(), percent = TRUE),
-#'     amoxi = rsi(amox %>% as.rsi(), percent = TRUE))
-#'     
-#' rsi(as.rsi(isolates$amox))
-#'
-#' rsi(as.rsi(isolates$amcl), interpretation = "S")
-#' }
-rsi <- function(ab1, ab2 = NA, interpretation = 'IR', minimum = 30, percent = FALSE, info = FALSE, warning = FALSE) {
-  functietekst <- as.character(match.call())
-  # param 1 = functienaam
-  # param 2 = ab1
-  # param 3 = ab2
-  ab1.naam <- functietekst[2]
-  if (!grepl('^[a-z]{3,4}$', ab1.naam)) {
-    ab1.naam <- 'rsi1'
-  }
-  ab2.naam <- functietekst[3]
-  if (!grepl('^[a-z]{3,4}$', ab2.naam)) {
-    ab2.naam <- 'rsi2'
-  }
-  
-  tbl <- tibble(rsi1 = ab1, rsi2 = ab2)
-  
-  colnames(tbl) <- c(ab1.naam, ab2.naam)
-  
-  if (length(ab2) == 1) {
-    return(rsi_df(tbl = tbl,
-                  antibiotics = ab1.naam,
-                  interpretation = interpretation,
-                  minimum = minimum,
-                  percent = percent,
-                  info = info,
-                  warning = warning))
-  } else {
-    if (length(ab1) != length(ab2)) {
-      stop('`ab1` (n = ', length(ab1), ') and `ab2` (n = ', length(ab2), ') must be of same length.', call. = FALSE)
-    }
-    if (interpretation != 'S') {
-      warning('`interpretation` is not set to S, albeit analysing a combination therapy.')
-    }
-    return(rsi_df(tbl = tbl,
-                  antibiotics = c(ab1.naam, ab2.naam),
-                  interpretation = interpretation,
-                  minimum = minimum,
-                  percent = percent,
-                  info = info,
-                  warning = warning))
-  }
-}
-
-#' Predict antimicrobial resistance
-#'
-#' Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns \code{se_min} and \code{se_max}.
-#' @param tbl table that contains columns \code{col_ab} and \code{col_date}
-#' @param col_ab column name of \code{tbl} with antimicrobial interpretations (\code{R}, \code{I} and \code{S})
-#' @param col_date column name of the date, will be used to calculate years
-#' @param year_max highest year to use in the prediction model, deafults to 15 years after today
-#' @param year_every unit of sequence between lowest year found in the data and \code{year_max}
-#' @param model the statistical model of choice. Valid values are \code{"binomial"} (or \code{"binom"} or \code{"logit"}) or \code{"loglin"} or \code{"linear"} (or \code{"lin"}).
-#' @param I_as_R treat \code{I} as \code{R}
-#' @param preserve_measurements overwrite predictions of years that are actually available in the data, with the original data. The standard errors of those years will be \code{NA}.
-#' @param info print textual analysis with the name and \code{\link{summary}} of the model.
-#' @return \code{data.frame} with columns \code{year}, \code{probR}, \code{se_min} and \code{se_max}.
-#' @seealso \code{\link{lm}} \cr \code{\link{glm}}
-#' @export
-#' @importFrom dplyr %>% pull mutate group_by_at summarise filter
-#' @importFrom reshape2 dcast
-#' @examples
-#' \dontrun{
-#' # use it directly:
-#' rsi_predict(tbl[which(first_isolate == TRUE & genus == "Haemophilus"),], "amcl")
-#'   
-#' # or with dplyr so you can actually read it:
-#' library(dplyr)
-#' tbl %>%
-#'   filter(first_isolate == TRUE,
-#'          genus == "Haemophilus") %>%
-#'   rsi_predict("amcl")
-#'
-#' tbl %>%
-#'   filter(first_isolate_weighted == TRUE,
-#'          genus == "Haemophilus") %>%
-#'   rsi_predict(col_ab = "amcl",
-#'               year_max = 2050,
-#'               year_every = 5)
-#'
-#' }
-rsi_predict <- function(tbl,
-                        col_ab,
-                        col_date = 'ontvangstdatum',
-                        year_max = as.integer(format(as.Date(Sys.Date()), '%Y')) + 15,
-                        year_every = 1,
-                        model = 'binomial',
-                        I_as_R = TRUE,
-                        preserve_measurements = TRUE,
-                        info = TRUE) {
-  
-  if (I_as_R == TRUE) {
-    tbl[, col_ab] <- gsub('I', 'R', tbl %>% pull(col_ab))
-  }
-  
-  year <- function(x) {
-    as.integer(format(as.Date(x), '%Y'))
-  }
-  
-  years_predict <- seq(from = min(year(tbl %>% pull(col_date))), to = year_max, by = year_every)
-  
-  df <- tbl %>%
-    mutate(year = year(tbl %>% pull(col_date))) %>%
-    group_by_at(c('year', col_ab)) %>%
-    summarise(n())
-  colnames(df) <- c('year', 'antibiotic', 'count')
-  df <- df %>%
-    reshape2::dcast(year ~ antibiotic, value.var = 'count')
-  
-  if (model %in% c('binomial', 'binom', 'logit')) {
-    logitmodel <- with(df, glm(cbind(R, S) ~ year, family = binomial))
-    if (info == TRUE) {
-      cat('\nLogistic regression model (logit) with binomial distribution')
-      cat('\n------------------------------------------------------------\n')
-      print(summary(logitmodel))
-    }
-    
-    predictmodel <- stats::predict(logitmodel, newdata = with(df, list(year = years_predict)), type = "response", se.fit = TRUE)
-    prediction <- predictmodel$fit
-    se <- predictmodel$se.fit
-    
-  } else if (model == 'loglin') {
-    loglinmodel <- with(df, glm(R ~ year, family = poisson))
-    if (info == TRUE) {
-      cat('\nLog-linear regression model (loglin) with poisson distribution')
-      cat('\n--------------------------------------------------------------\n')
-      print(summary(loglinmodel))
-    }
-    
-    predictmodel <- stats::predict(loglinmodel, newdata = with(df, list(year = years_predict)), type = "response", se.fit = TRUE)
-    prediction <- predictmodel$fit
-    se <- predictmodel$se.fit
-    
-  } else if (model %in% c('lin', 'linear')) {
-    linmodel <- with(df, lm((R / (R + S)) ~ year))
-    if (info == TRUE) {
-      cat('\nLinear regression model')
-      cat('\n-----------------------\n')
-      print(summary(linmodel))
-    }
-    
-    predictmodel <- stats::predict(linmodel, newdata = with(df, list(year = years_predict)), se.fit = TRUE)
-    prediction <- predictmodel$fit
-    se <- predictmodel$se.fit
-    
-  } else {
-    stop('No valid model selected.')
-  }
-  
-  # prepare the output dataframe
-  prediction <- data.frame(year = years_predict, probR = prediction, stringsAsFactors = FALSE)
-  
-  prediction$se_min <- prediction$probR - se
-  prediction$se_max <- prediction$probR + se
-  
-  if (model == 'loglin') {
-    prediction$probR <- prediction$probR %>%
-      format(scientific = FALSE) %>%
-      as.integer()
-    prediction$se_min <- prediction$se_min %>% as.integer()
-    prediction$se_max <- prediction$se_max %>% as.integer()
-    
-    colnames(prediction) <- c('year', 'amountR', 'se_max', 'se_min')
-  } else {
-    prediction$se_max[which(prediction$se_max > 1)] <- 1
-  }
-  prediction$se_min[which(prediction$se_min < 0)] <- 0
-  
-  total <- prediction
-  
-  if (preserve_measurements == TRUE) {
-    # geschatte data vervangen door gemeten data
-    if (I_as_R == TRUE) {
-      if (!'I' %in% colnames(df)) {
-        df$I <- 0
-      }
-      df$probR <- df$R / rowSums(df[, c('R', 'S', 'I')])
-    } else {
-      df$probR <- df$R / rowSums(df[, c('R', 'S')])
-    }
-    measurements <- data.frame(year = df$year,
-                           probR = df$probR,
-                           se_min = NA,
-                           se_max = NA,
-                           stringsAsFactors = FALSE)
-    colnames(measurements) <- colnames(prediction)
-    prediction <- prediction %>% filter(!year %in% df$year)
-    
-    total <- rbind(measurements, prediction)
-  }
-  
-  total
-  
-}

README.md

@@ -1,147 +1,226 @@
-# `AMR`
-This is an [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR).
 
-![logo_uni](man/figures/logo_en.png)![logo_umcg](man/figures/logo_umcg.png)
+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](https://pypi.org/project/AMR/).
 
-This R package was created for academic research by PhD students of the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl/) and the Medical Microbiology & Infection Prevention department of the University Medical Center Groningen (UMCG). They also maintain this package, see [Authors](#authors).
+This Python package is a wrapper around 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.
 
-## Why this package?
+# Prerequisites
-This R package contains functions to make microbiological, epidemiological data analysis easier. It allows the use of some new S3 classes to work with MIC values and antimicrobial interpretations (i.e. values S, I and R).
 
-AMR can also be predicted for the forthcoming years with the `rsi_predict` function. For use with the `dplyr` package, the `rsi` function can be used in conjunction with `summarise` to calculate the resistance percentages of different antibiotic columns of a table.
+This package was only tested with a [virtual environment (venv)](https://docs.python.org/3/library/venv.html). You can set up such an environment by running:
 
-It also contains functions to translate antibiotic codes from the lab (like `"AMOX"`) or the [WHO](https://www.whocc.no/atc_ddd_index/?code=J01CA04&showdescription=no) (like `"J01CA04"`) to trivial names (like `"amoxicillin"`) and vice versa.
+```python
+# linux and macOS:
+python -m venv /path/to/new/virtual/environment
 
-## How to get it?
+# Windows:
-[![CRAN_Badge](http://www.r-pkg.org/badges/version/AMR)](http://cran.r-project.org/package=AMR)
+python -m venv C:\path\to\new\virtual\environment
-
-This package is available on CRAN (latest stable version) and also here on GitHub (latest development version).
-
-#### Latest stable version from CRAN (recommended)
-RStudio:
--  Click on `Tools` and then `Install Packages..`
--  Type in `AMR` and press <kbd>Install</kbd>
-
-Other:
-```r
-install.packages("AMR")
 ```
 
-#### Latest development version from GitHub
+Then you can [activate the environment](https://docs.python.org/3/library/venv.html#how-venvs-work), after which the venv is ready to work with.
-```r
+
-devtools::install_github("msberends/AMR")
+# Install AMR
+
+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)
 ```
 
-## How to use it?
+| MOs         | Drug      | MO_clean           | Drug_clean    |
-```r
+|-------------|-----------|--------------------|---------------|
-# Call it with:
+| E. coli     | Cipro     | Escherichia coli   | Ciprofloxacin |
-library(AMR)
+| ESCCOL      | CIP       | Escherichia coli   | Ciprofloxacin |
+| esco        | J01MA02   | Escherichia coli   | Ciprofloxacin |
+| Esche coli  | Ciproxin  | Escherichia coli   | Ciprofloxacin |
 
-# For a list of functions:
+### Explanation
-help(package = "AMR")
+
+* **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".
+
+## Calculating AMR
+
+```python
+import AMR
+import pandas as pd
+
+df = AMR.example_isolates
+result = AMR.resistance(df["AMX"])
+print(result)
 ```
 
-### Databases included in package
+```
-```r
+[0.59555556]
-# Dataset with ATC antibiotics codes, official names and DDD's (oral and parenteral)
-ablist        # A tibble: 420 x 12
-
-# Dataset with bacteria codes and properties like gram stain and aerobic/anaerobic
-bactlist      # A tibble: 2,507 x 10
 ```
 
-### New classes
+## Generating Antibiograms
-This package contains two new S3 classes: `mic` for MIC values (e.g. from Vitek or Phoenix) and `rsi` for antimicrobial drug interpretations (i.e. S, I and R). Both are actually ordered factors under the hood (an MIC of `2` being higher than `<=1` but lower than `>=32`, and for class `rsi` factors are ordered as `S < I < R`). 
-Both classes have extensions for existing generic functions like `print`, `summary` and `plot`.
 
-```r
+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:
-# Transform values to new classes
-mic_data <- as.mic(c(">=32", "1.0", "8", "<=0.128", "8", "16", "16"))
-rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
-```
-These functions also try to coerce valid values.
 
-Quick overviews when just printing objects:
+```python
-```r
+result2a = AMR.antibiogram(df[["mo", "AMX", "CIP", "TZP"]])
-mic_data
+print(result2a)
-# Class 'mic': 7 isolates
-# 
-# <NA>  0
-# 
-# <=0.128       1       8      16    >=32
-#       1       1       2       2       1
-
-rsi_data
-# Class 'rsi': 880 isolates
-# 
-# <NA>:       0 
-# Sum of S:   474 
-# Sum of IR:  406 
-# - Sum of R: 370 
-# - Sum of I: 36 
-# 
-#   %S  %IR   %I   %R 
-# 53.9 46.1  4.1 42.0 
 ```
 
-A plot of `rsi_data`:
+| Pathogen        | Amoxicillin     | Ciprofloxacin   | Piperacillin/tazobactam  |
-```r
+|-----------------|-----------------|-----------------|--------------------------|
-plot(rsi_data)
+| 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)
 ```
 
-![example](man/figures/rsi_example.png)
+| 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)            |
 
-Other epidemiological functions:
 
-```r
+In this example, we generate an antibiogram by selecting various antibiotics.
-# Apply EUCAST Expert Rules v3.1 (latest) to antibiotic columns
-EUCAST_rules(...)
 
-# Determine key antibiotic based on bacteria ID
+## Taxonomic Data Sets Now in Python!
-key_antibiotics(...)
-# Check if key antibiotics are equal
-key_antibiotics_equal(...)
 
-# Selection of first isolates of any patient
+As a Python user, you might like that the most important data sets of the `AMR` R package, `microorganisms`, `antimicrobials`, `clinical_breakpoints`, and `example_isolates`, are now available as regular Python data frames:
-first_isolate(...)
 
-# Calculate resistance levels of antibiotics
+```python
-rsi(...)
+AMR.microorganisms
-# Predict resistance levels of antibiotics
-rsi_predict(...)
-
-# Get name of antibiotic by ATC code
-abname(...)
-abname("J01CR02", from = "atc", to = "umcg") # "AMCL"
 ```
 
-## Authors
+| 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        |
 
-  - [Berends MS](https://github.com/msberends)<sup>1,2</sup>, PhD Student
+```python
-  - [Luz CF](https://github.com/ceefluz)<sup>1</sup>, PhD Student
+AMR.antimicrobials
-  - [Hassing EEA](https://github.com/erwinhassing)<sup>2</sup>, Data Analyst (contributor)
+```
-  
-<sup>1</sup> Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
 
-<sup>2</sup> Department of Medical, Market and Innovation (MMI), Certe Medische diagnostiek & advies, Groningen, the Netherlands
+| 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     |
 
-## Copyright
-This R package is licensed under the [GNU General Public License (GPL) v2.0](https://github.com/msberends/AMR/blob/master/LICENSE). In a nutshell, this means that this package:
 
-- May be used for commercial purposes
+# Installation Channels
 
-- May be used for private purposes
+## Stable Release (CRAN)
 
-- May be modified, although:
+The default `AMR` Python package uses the latest stable version of the `AMR` R package, published on CRAN. After running `pip install AMR`, import it as usual:
 
-  - Modifications **must** be released under the same license when distributing the package
+```python
-  - Changes made to the code **must** be documented
+import AMR
 
-- May be distributed, although:
+AMR.example_isolates
+```
 
-  - Source code **must** be made available when the package is distributed
+## Development Version (GitHub)
-  - A copy of the license and copyright notice **must** be included with the package.
 
-- Comes with a LIMITATION of liability
+To use the latest development version of the `AMR` R package (sourced directly from GitHub), import the `beta` sub-package and alias it as `AMR`:
 
-- Comes with NO warranty
+```python
+import AMR.beta as AMR
+
+AMR.example_isolates
+```
+
+Aliasing with `as AMR` keeps all downstream code identical to the stable import. Switching between the stable release and the development version requires changing only the import line — nothing else in your script needs to change.
+
+# SIR Classification with `as_sir()`
+
+## Using `enforce_method`
+
+The `as_sir()` function in R uses S3 method dispatch to select the correct calculation method based on the input class: `<mic>` for MIC values and `<disk>` for disk diffusion values. Because Python objects do not carry R class attributes through the `rpy2` bridge, this automatic dispatch may not resolve correctly.
+
+To explicitly specify the input type, use the `enforce_method` argument:
+
+```python
+# Treat the column as MIC values — maps to R's as.sir.mic()
+AMR.as_sir(df["MIC_col"], mo="E. coli", ab="AMX", guideline="EUCAST", enforce_method="mic")
+
+# Treat the column as disk diffusion values — maps to R's as.sir.disk()
+AMR.as_sir(df["disk_col"], mo="E. coli", ab="AMX", guideline="EUCAST", enforce_method="disk")
+```
+
+Without `enforce_method`, R falls back to class-based dispatch on the raw Python input, which may fail or return unexpected results. Always supply `enforce_method` when calling `as_sir()` from Python.
+
+# 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.

man/EUCAST.Rd

@@ -1,57 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/EUCAST.R
-\name{EUCAST}
-\alias{EUCAST}
-\alias{EUCAST_rules}
-\alias{interpretive_reading}
-\title{EUCAST expert rules}
-\source{
-EUCAST Expert Rules Version 2.0: \cr
-  Leclercq et al. \strong{EUCAST expert rules in antimicrobial susceptibility testing.} \emph{Clin Microbiol Infect.} 2013;19(2):141-60. \cr
-  \url{https://doi.org/10.1111/j.1469-0691.2011.03703.x} \cr
-  \cr
-  EUCAST Expert Rules Version 3.1: \cr
-  \url{http://www.eucast.org/expert_rules_and_intrinsic_resistance}
-}
-\usage{
-EUCAST_rules(tbl, col_bactcode = "bacteriecode", info = TRUE,
-  amcl = "amcl", amik = "amik", amox = "amox", ampi = "ampi",
-  azit = "azit", aztr = "aztr", cefa = "cefa", cfra = "cfra",
-  cfep = "cfep", cfot = "cfot", cfox = "cfox", cfta = "cfta",
-  cftr = "cftr", cfur = "cfur", chlo = "chlo", cipr = "cipr",
-  clar = "clar", clin = "clin", clox = "clox", coli = "coli",
-  czol = "czol", dapt = "dapt", doxy = "doxy", erta = "erta",
-  eryt = "eryt", fosf = "fosf", fusi = "fusi", gent = "gent",
-  imip = "imip", kana = "kana", levo = "levo", linc = "linc",
-  line = "line", mero = "mero", mino = "mino", moxi = "moxi",
-  nali = "nali", neom = "neom", neti = "neti", nitr = "nitr",
-  novo = "novo", norf = "norf", oflo = "oflo", peni = "peni",
-  pita = "pita", poly = "poly", qida = "qida", rifa = "rifa",
-  roxi = "roxi", siso = "siso", teic = "teic", tetr = "tetr",
-  tica = "tica", tige = "tige", tobr = "tobr", trim = "trim",
-  trsu = "trsu", vanc = "vanc")
-
-interpretive_reading(...)
-}
-\arguments{
-\item{tbl}{table with antibiotic columns, like e.g. \code{amox} and \code{amcl}}
-
-\item{col_bactcode}{column name of the bacteria ID in \code{tbl} - should also be present in \code{bactlist$bactid}, see \code{\link{bactlist}}.}
-
-\item{info}{print progress}
-
-\item{amcl, amik, amox, ampi, azit, aztr, cefa, cfra, cfep, cfot, cfox, cfta, cftr, cfur, chlo, cipr, clar, clin, clox, coli, czol, dapt, doxy, erta, eryt, fosf, fusi, gent, imip, kana, levo, linc, line, mero, mino, moxi, nali, neom, neti, nitr, novo, norf, oflo, peni, pita, poly, qida, rifa, roxi, siso, teic, tetr, tica, tige, tobr, trim, trsu, vanc}{column names of antibiotics. Use \code{NA} to skip a column, like \code{tica = NA}. Non-existing column will be skipped.}
-
-\item{...}{parameters that are passed on to \code{EUCAST_rules}}
-}
-\value{
-table with edited variables of antibiotics.
-}
-\description{
-Apply expert rules (like intrinsic resistance), as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{http://eucast.org}), see \emph{Source}.
-}
-\examples{
-\dontrun{
-tbl <- EUCAST_rules(tbl)
-}
-}

man/ablist.Rd

@@ -1,34 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/data.R
-\docType{data}
-\name{ablist}
-\alias{ablist}
-\title{Dataset with 420 antibiotics}
-\format{A data.frame with 420 observations and 12 variables:
-\describe{
-  \item{\code{atc}}{ATC code, like \code{J01CR02}}
-  \item{\code{molis}}{MOLIS code, like \code{amcl}}
-  \item{\code{umcg}}{UMCG code, like \code{AMCL}}
-  \item{\code{official}}{Official name by the WHO, like \code{"amoxicillin and enzyme inhibitor"}}
-  \item{\code{official_nl}}{Official name in the Netherlands, like \code{"Amoxicilline met enzymremmer"}}
-  \item{\code{trivial}}{Trivial name in Dutch, like \code{"Amoxicilline/clavulaanzuur"}}
-  \item{\code{oral_ddd}}{Daily Defined Dose (DDD) according to the WHO, oral treatment}
-  \item{\code{oral_units}}{Units of \code{ddd_units}}
-  \item{\code{iv_ddd}}{Daily Defined Dose (DDD) according to the WHO, bij parenteral treatment}
-  \item{\code{iv_units}}{Units of \code{iv_ddd}}
-  \item{\code{atc_group1}}{ATC group in Dutch, like \code{"Macroliden, lincosamiden en streptograminen"}}
-  \item{\code{atc_group2}}{Subgroup of \code{atc_group1} in Dutch, like \code{"Macroliden"}}
-}}
-\source{
-MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) - \url{https://www.umcg.nl} \cr \cr World Health Organization - \url{https://www.whocc.no/atc_ddd_index/}
-}
-\usage{
-ablist
-}
-\description{
-A dataset containing all antibiotics with a J0 code, with their DDD's.
-}
-\seealso{
-\code{\link{bactlist}}
-}
-\keyword{datasets}

man/abname.Rd

@@ -1,45 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/atc.R
-\name{abname}
-\alias{abname}
-\title{Name of an antibiotic}
-\source{
-\code{\link{ablist}}
-}
-\usage{
-abname(abcode, from = "umcg", to = "official", textbetween = " + ",
-  tolower = FALSE)
-}
-\arguments{
-\item{abcode}{a code or name, like \code{"amox"}, \code{"cftr"} or \code{"J01CA04"}}
-
-\item{from, to}{type to transform from and to. See \code{\link{ablist}} for its column names.}
-
-\item{textbetween}{text to put between multiple returned texts}
-
-\item{tolower}{return output as lower case with function \code{\link{tolower}}.}
-}
-\description{
-Convert antibiotic codes (from a laboratory information system like MOLIS or GLIMS) to a (trivial) antibiotic name or ATC code, or vice versa. This uses the data from \code{\link{ablist}}.
-}
-\examples{
-abname("AMCL")
-# "amoxicillin and enzyme inhibitor"
-
-abname("AMCL+GENT")
-# "amoxicillin and enzyme inhibitor + gentamicin"
-
-abname(c("AMCL", "GENT"))
-# "amoxicillin and enzyme inhibitor" "gentamicin" 
-
-abname("AMCL", to = "trivial")
-# "Amoxicilline/clavulaanzuur"
-
-abname("AMCL", to = "atc")
-# "J01CR02"
-
-abname("J01CR02", from = "atc", to = "umcg")
-# "AMCL"
-}
-\keyword{ab}
-\keyword{antibiotics}

man/as.mic.Rd

@@ -1,34 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/classes.R
-\name{as.mic}
-\alias{as.mic}
-\alias{is.mic}
-\title{Class 'mic'}
-\usage{
-as.mic(x, na.rm = FALSE)
-
-is.mic(x)
-}
-\arguments{
-\item{x}{vector}
-
-\item{na.rm}{a logical indicating whether missing values should be removed}
-}
-\value{
-New class \code{mic}
-}
-\description{
-This transforms a vector to a new class\code{mic}, which is an ordered factor valid MIC values as levels. Invalid MIC values will be translated as \code{NA} with a warning.
-}
-\examples{
-mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
-is.mic(mic_data)
-plot(mic_data)
-
-\donttest{
-library(dplyr)
-tbl \%>\%
-  mutate_at(vars(ends_with("_mic")), as.mic)
-sapply(mic_data, is.mic)
-}
-}

man/as.rsi.Rd

@@ -1,33 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/classes.R
-\name{as.rsi}
-\alias{as.rsi}
-\alias{is.rsi}
-\title{Class 'rsi'}
-\usage{
-as.rsi(x)
-
-is.rsi(x)
-}
-\arguments{
-\item{x}{vector}
-}
-\value{
-New class \code{rsi}
-}
-\description{
-This transforms a vector to a new class \code{rsi}, which is an ordered factor with levels \code{S < I < R}. Invalid antimicrobial interpretations will be translated as \code{NA} with a warning.
-}
-\examples{
-rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
-rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370), "A", "B", "C"))
-is.rsi(rsi_data)
-plot(rsi_data)
-
-\donttest{
-library(dplyr)
-tbl \%>\%
-  mutate_at(vars(ends_with("_rsi")), as.rsi)
-sapply(mic_data, is.rsi)
-}
-}

man/atc_property.Rd

@@ -1,57 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/atc.R
-\name{atc_property}
-\alias{atc_property}
-\title{Properties of an ATC code}
-\source{
-\url{https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/}
-}
-\usage{
-atc_property(atc_code, property, administration = "O",
-  url = "https://www.whocc.no/atc_ddd_index/?code=\%s&showdescription=no")
-}
-\arguments{
-\item{atc_code}{a character or character vector with ATC code(s) of antibiotic(s)}
-
-\item{property}{property of an ATC code. Valid values are \code{"ATC code"}, \code{"Name"}, \code{"DDD"}, \code{"U"} (\code{"unit"}), \code{"Adm.R"} en \code{"Note"}.}
-
-\item{administration}{type of administration, see \emph{Details}}
-
-\item{url}{url of website of the WHO. The sign \code{\%s} can be used as a placeholder for ATC codes.}
-}
-\description{
-Gets data from the WHO to determine properties of an ATC of e.g. an antibiotic. \strong{This function requires an internet connection.}
-}
-\details{
-Abbreviations for the property \code{"Adm.R"} (parameter \code{administration}):
-\itemize{
-  \item{\code{"Implant"}}{ = Implant}
-  \item{\code{"Inhal"}}{ = Inhalation}
-  \item{\code{"Instill"}}{ = Instillation}
-  \item{\code{"N"}}{ = nasal}
-  \item{\code{"O"}}{ = oral}
-  \item{\code{"P"}}{ = parenteral}
-  \item{\code{"R"}}{ = rectal}
-  \item{\code{"SL"}}{ = sublingual/buccal}
-  \item{\code{"TD"}}{ = transdermal}
-  \item{\code{"V"}}{ = vaginal}
-}
-
-Abbreviations for the property \code{"U"} (unit):
-\itemize{
-  \item{\code{"g"}}{ = gram}
-  \item{\code{"mg"}}{ = milligram}
-  \item{\code{"mcg"}}{ = microgram}
-  \item{\code{"U"}}{ = unit}
-  \item{\code{"TU"}}{ = thousand units}
-  \item{\code{"MU"}}{ = million units}
-  \item{\code{"mmol"}}{ = millimole}
-  \item{\code{"ml"}}{ = milliliter (e.g. eyedrops)}
-}
-}
-\examples{
-\donttest{
-atc_property("J01CA04", "DDD", "O") # oral DDD of amoxicillin
-atc_property("J01CA04", "DDD", "P") # parenteral DDD of amoxicillin
-}
-}

man/bactlist.Rd

@@ -1,32 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/data.R
-\docType{data}
-\name{bactlist}
-\alias{bactlist}
-\title{Dataset with ~2500 microorganisms}
-\format{A data.frame with 2507 observations and 10 variables:
-\describe{
-  \item{\code{bactid}}{ID of microorganism}
-  \item{\code{bactsys}}{Bactsyscode of microorganism}
-  \item{\code{family}}{Family name of microorganism}
-  \item{\code{genus}}{Genus name of microorganism, like \code{"Echerichia"}}
-  \item{\code{species}}{Species name of microorganism, like \code{"coli"}}
-  \item{\code{subspecies}}{Subspecies name of bio-/serovar of microorganism, like \code{"EHEC"}}
-  \item{\code{fullname}}{Full name, like \code{"Echerichia coli (EHEC)"}}
-  \item{\code{type}}{Type of microorganism, like \code{"Bacterie"} en \code{"Schimmel/gist"} (these are Dutch)}
-  \item{\code{gramstain}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
-  \item{\code{aerobic}}{Type aerobe/anaerobe of bacteria}
-}}
-\source{
-MOLIS (LIS of Certe) - \url{https://www.certe.nl}
-}
-\usage{
-bactlist
-}
-\description{
-A dataset containing all microorganisms of MOLIS. MO codes of the UMCG can be looked up using \code{\link{bactlist.umcg}}.
-}
-\seealso{
-\code{\link{ablist}} \code{\link{bactlist.umcg}}
-}
-\keyword{datasets}

man/bactlist.umcg.Rd

@@ -1,24 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/data.R
-\docType{data}
-\name{bactlist.umcg}
-\alias{bactlist.umcg}
-\title{Translation table for UMCG with ~1100 microorganisms}
-\format{A data.frame with 1090 observations and 2 variables:
-\describe{
-  \item{\code{mocode}}{Code of microorganism according to UMCG MMB}
-  \item{\code{bactid}}{Code of microorganism in \code{\link{bactlist}}}
-}}
-\source{
-MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) - \url{https://www.umcg.nl}
-}
-\usage{
-bactlist.umcg
-}
-\description{
-A dataset containing all bacteria codes of UMCG MMB. These codes can be joined to data with an ID from \code{\link{bactlist}$bactid}, using \code{\link{left_join_bactlist}}.
-}
-\seealso{
-\code{\link{bactlist}}
-}
-\keyword{datasets}

man/first_isolate.Rd

@@ -1,100 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/first_isolates.R
-\name{first_isolate}
-\alias{first_isolate}
-\title{Determine first (weighted) isolates}
-\usage{
-first_isolate(tbl, col_date, col_patid, col_genus, col_species,
-  col_testcode = NA, col_specimen, col_icu, col_keyantibiotics = NA,
-  episode_days = 365, testcodes_exclude = "", icu_exclude = FALSE,
-  filter_specimen = NA, output_logical = TRUE, ignore_I = TRUE,
-  info = TRUE)
-}
-\arguments{
-\item{tbl}{a \code{data.frame} containing isolates.}
-
-\item{col_date}{column name of the result date (or date that is was received on the lab)}
-
-\item{col_patid}{column name of the unique IDs of the patients}
-
-\item{col_genus}{column name of the genus of the microorganisms}
-
-\item{col_species}{column name of the species of the microorganisms}
-
-\item{col_testcode}{column name of the test codes, see Details}
-
-\item{col_specimen}{column name of the specimen type or group}
-
-\item{col_icu}{column name of the logicals (\code{TRUE}/\code{FALSE}) whether a ward or department is an Intensive Care Unit (ICU)}
-
-\item{col_keyantibiotics}{column name of the key antibiotics to determine first \emph{weighted} isolates, see \code{\link{key_antibiotics}}.}
-
-\item{episode_days}{episode in days after which a genus/species combination will be determined as 'first isolate' again}
-
-\item{testcodes_exclude}{character vector with test codes that should be excluded (caseINsensitive)}
-
-\item{icu_exclude}{logical whether ICU isolates should be excluded}
-
-\item{filter_specimen}{specimen group or type that should be excluded}
-
-\item{output_logical}{return output as \code{logical} (will else the values \code{0} or \code{1})}
-
-\item{ignore_I}{ignore \code{"I"} as antimicrobial interpretation of key antibiotics (with \code{FALSE}, changes in antibiograms from S to I and I to R will be interpreted as difference)}
-
-\item{info}{print progress}
-}
-\value{
-A vector to add to table, see Examples.
-}
-\description{
-Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type.
-}
-\details{
-To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode. If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that is was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all \emph{S. aureus} isolates would be overestimated, because you included this MRSA more than once. It would be selection bias.
-
-    Use \code{col_testcode = NA} to \strong{not} exclude certain test codes (like test codes for screening). In that case \code{testcodes_exclude} will be ignored.
-}
-\examples{
-\dontrun{
-
-# set key antibiotics to a new variable
-tbl$keyab <- key_antibiotics(tbl)
-
-tbl$first_isolate <-
-  first_isolate(tbl)
-
-tbl$first_isolate_weighed <-
-  first_isolate(tbl,
-                col_keyantibiotics = 'keyab')
-
-tbl$first_blood_isolate <-
-  first_isolate(tbl,
-                filter_specimen = 'Blood')
-
-tbl$first_blood_isolate_weighed <-
-  first_isolate(tbl,
-                filter_specimen = 'Blood',
-                col_keyantibiotics = 'keyab')
-
-tbl$first_urine_isolate <-
-  first_isolate(tbl,
-                filter_specimen = 'Urine')
-
-tbl$first_urine_isolate_weighed <-
-  first_isolate(tbl,
-                filter_specimen = 'Urine',
-                col_keyantibiotics = 'keyab')
-
-tbl$first_resp_isolate <-
-  first_isolate(tbl,
-                filter_specimen = 'Respiratory')
-
-tbl$first_resp_isolate_weighed <-
-  first_isolate(tbl,
-                filter_specimen = 'Respiratory',
-                col_keyantibiotics = 'keyab')
-}
-}
-\keyword{first}
-\keyword{isolate}
-\keyword{isolates}

man/join.Rd

@@ -1,50 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/join.R
-\name{join}
-\alias{join}
-\alias{inner_join_bactlist}
-\alias{inner_join}
-\alias{left_join_bactlist}
-\alias{right_join_bactlist}
-\alias{full_join_bactlist}
-\alias{semi_join_bactlist}
-\alias{anti_join_bactlist}
-\title{Join a table with \code{bactlist}}
-\usage{
-inner_join_bactlist(x, by = "bactid", ...)
-
-left_join_bactlist(x, by = "bacteriecode", ...)
-
-right_join_bactlist(x, by = "bacteriecode", ...)
-
-full_join_bactlist(x, by = "bacteriecode", ...)
-
-semi_join_bactlist(x, by = "bacteriecode", ...)
-
-anti_join_bactlist(x, by = "bacteriecode", ...)
-}
-\arguments{
-\item{x}{existing table to join}
-
-\item{by}{a variable to join by - could be a column name of \code{x} with values that exist in \code{bactlist$bactid} (like \code{by = "bacteria_id"}), or another column in \code{\link{bactlist}} (but then it should be named, like \code{by = c("my_genus_species" = "fullname")})}
-
-\item{...}{other parameters to pass trhough to \code{dplyr::\link[dplyr]{join}}.}
-}
-\description{
-Join the list of microorganisms \code{\link{bactlist}} easily to an existing table.
-}
-\details{
-As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
-}
-\examples{
-df <- data.frame(date = seq(from = as.Date("2018-01-01"),
-                            to = as.Date("2018-01-07"),
-                            by = 1),
-                 bacteria_id = c("STAAUR", "STAAUR", "STAAUR", "STAAUR",
-                                 "ESCCOL", "ESCCOL", "ESCCOL"),
-                 stringsAsFactors = FALSE)
-                 
-colnames(df)
-df2 <- left_join_bactlist(df, "bacteria_id")
-colnames(df2)
-}

man/key_antibiotics.Rd

@@ -1,37 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/first_isolates.R
-\name{key_antibiotics}
-\alias{key_antibiotics}
-\title{Key antibiotics based on bacteria ID}
-\usage{
-key_antibiotics(tbl, col_bactcode = "bacteriecode", info = TRUE,
-  amcl = "amcl", amox = "amox", cfot = "cfot", cfta = "cfta",
-  cftr = "cftr", cfur = "cfur", cipr = "cipr", clar = "clar",
-  clin = "clin", clox = "clox", doxy = "doxy", gent = "gent",
-  line = "line", mero = "mero", peni = "peni", pita = "pita",
-  rifa = "rifa", teic = "teic", trsu = "trsu", vanc = "vanc")
-}
-\arguments{
-\item{tbl}{table with antibiotics coloms, like \code{amox} and \code{amcl}.}
-
-\item{col_bactcode}{column of bacteria IDs in \code{tbl}; these should occur in \code{bactlist$bactid}, see \code{\link{bactlist}}}
-
-\item{info}{print warnings}
-
-\item{amcl, amox, cfot, cfta, cftr, cfur, cipr, clar, clin, clox, doxy, gent, line, mero, peni, pita, rifa, teic, trsu, vanc}{column names of antibiotics.}
-}
-\value{
-Character of length 1.
-}
-\description{
-Key antibiotics based on bacteria ID
-}
-\examples{
-\donttest{
-#' # set key antibiotics to a new variable
-tbl$keyab <- key_antibiotics(tbl)
-}
-}
-\seealso{
-\code{\link{mo_property}} \code{\link{ablist}}
-}

man/mo_property.Rd

@@ -1,19 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/EUCAST.R
-\name{mo_property}
-\alias{mo_property}
-\title{Poperties of a microorganism}
-\usage{
-mo_property(bactcode, property = "fullname")
-}
-\arguments{
-\item{bactcode}{ID of a microorganisme, like \code{"STAAUR} and \code{"ESCCOL}}
-
-\item{property}{One of the values \code{bactid}, \code{bactsys}, \code{family}, \code{genus}, \code{species}, \code{subspecies}, \code{fullname}, \code{type}, \code{gramstain}, \code{aerobic}}
-}
-\description{
-Poperties of a microorganism
-}
-\seealso{
-\code{\link{bactlist}}
-}

man/rsi.Rd

@@ -1,53 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/rsi_analysis.R
-\name{rsi}
-\alias{rsi}
-\title{Resistance of isolates}
-\usage{
-rsi(ab1, ab2 = NA, interpretation = "IR", minimum = 30, percent = FALSE,
-  info = FALSE, warning = FALSE)
-}
-\arguments{
-\item{ab1, ab2}{list with interpretations of an antibiotic}
-
-\item{interpretation}{antimicrobial interpretation of which the portion must be calculated. Valid values are \code{"S"}, \code{"SI"}, \code{"I"}, \code{"IR"} or \code{"R"}.}
-
-\item{minimum}{minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA} with a warning (when \code{warning = TRUE}).}
-
-\item{percent}{return output as percent (text), will else (at default) be a double}
-
-\item{info}{calculate the amount of available isolates and print it, like \code{n = 423}}
-
-\item{warning}{show a warning when the available amount of isolates is below \code{minimum}}
-}
-\value{
-Double or, when \code{percent = TRUE}, a character.
-}
-\description{
-This function can be used in \code{dplyr}s \code{\link[dplyr]{summarise}}, see \emph{Examples}. Calculate the percentage S, SI, I, IR or R of a vector of isolates.
-}
-\details{
-This function uses the \code{\link{rsi_df}} function internally.
-}
-\examples{
-\dontrun{
-tbl \%>\%
-  group_by(hospital) \%>\%
-  summarise(cipr = rsi(cipr))
-  
-tbl \%>\%
-  group_by(year, hospital) \%>\%
-  summarise(
-    isolates = n(),
-    cipro = rsi(cipr \%>\% as.rsi(), percent = TRUE),
-    amoxi = rsi(amox \%>\% as.rsi(), percent = TRUE))
-    
-rsi(as.rsi(isolates$amox))
-
-rsi(as.rsi(isolates$amcl), interpretation = "S")
-}
-}
-\keyword{antibiotics}
-\keyword{isolate}
-\keyword{isolates}
-\keyword{rsi}

man/rsi_df.Rd

@@ -1,54 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/rsi_analysis.R
-\name{rsi_df}
-\alias{rsi_df}
-\title{Resistance of isolates in data.frame}
-\usage{
-rsi_df(tbl, antibiotics, interpretation = "IR", minimum = 30,
-  percent = FALSE, info = TRUE, warning = TRUE)
-}
-\arguments{
-\item{tbl}{\code{data.frame} containing columns with antibiotic interpretations.}
-
-\item{antibiotics}{character vector with 1, 2 or 3 antibiotics that occur as column names in \code{tbl}, like \code{antibiotics = c("amox", "amcl")}}
-
-\item{interpretation}{antimicrobial interpretation of which the portion must be calculated. Valid values are \code{"S"}, \code{"SI"}, \code{"I"}, \code{"IR"} or \code{"R"}.}
-
-\item{minimum}{minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA} with a warning (when \code{warning = TRUE}).}
-
-\item{percent}{return output as percent (text), will else (at default) be a double}
-
-\item{info}{calculate the amount of available isolates and print it, like \code{n = 423}}
-
-\item{warning}{show a warning when the available amount of isolates is below \code{minimum}}
-}
-\value{
-Double or, when \code{percent = TRUE}, a character.
-}
-\description{
-\strong{NOTE: use \code{\link{rsi}} in dplyr functions like \code{\link[dplyr]{summarise}}.} \cr Calculate the percentage of S, SI, I, IR or R of a \code{data.frame} containing isolates.
-}
-\details{
-Remember that you should filter your table to let it contain \strong{only first isolates}!
-}
-\examples{
-\dontrun{
-rsi_df(tbl_with_bloodcultures, 'amcl')
-
-rsi_df(tbl_with_bloodcultures, c('amcl', 'gent'), interpretation = 'IR')
-
-library(dplyr)
-# calculate current empiric therapy of Helicobacter gastritis:
-my_table \%>\%
-  filter(first_isolate == TRUE, 
-         genus == "Helicobacter") \%>\%
-  rsi_df(antibiotics = c("amox", "metr"))
-}
-}
-\seealso{
-\code{\link{rsi}} for the function that can be used with \code{\link[dplyr]{summarise}} directly.
-}
-\keyword{antibiotics}
-\keyword{isolate}
-\keyword{isolates}
-\keyword{rsi}

man/rsi_predict.Rd

@@ -1,60 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/rsi_analysis.R
-\name{rsi_predict}
-\alias{rsi_predict}
-\title{Predict antimicrobial resistance}
-\usage{
-rsi_predict(tbl, col_ab, col_date = "ontvangstdatum",
-  year_max = as.integer(format(as.Date(Sys.Date()), "\%Y")) + 15,
-  year_every = 1, model = "binomial", I_as_R = TRUE,
-  preserve_measurements = TRUE, info = TRUE)
-}
-\arguments{
-\item{tbl}{table that contains columns \code{col_ab} and \code{col_date}}
-
-\item{col_ab}{column name of \code{tbl} with antimicrobial interpretations (\code{R}, \code{I} and \code{S})}
-
-\item{col_date}{column name of the date, will be used to calculate years}
-
-\item{year_max}{highest year to use in the prediction model, deafults to 15 years after today}
-
-\item{year_every}{unit of sequence between lowest year found in the data and \code{year_max}}
-
-\item{model}{the statistical model of choice. Valid values are \code{"binomial"} (or \code{"binom"} or \code{"logit"}) or \code{"loglin"} or \code{"linear"} (or \code{"lin"}).}
-
-\item{I_as_R}{treat \code{I} as \code{R}}
-
-\item{preserve_measurements}{overwrite predictions of years that are actually available in the data, with the original data. The standard errors of those years will be \code{NA}.}
-
-\item{info}{print textual analysis with the name and \code{\link{summary}} of the model.}
-}
-\value{
-\code{data.frame} with columns \code{year}, \code{probR}, \code{se_min} and \code{se_max}.
-}
-\description{
-Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns \code{se_min} and \code{se_max}.
-}
-\examples{
-\dontrun{
-# use it directly:
-rsi_predict(tbl[which(first_isolate == TRUE & genus == "Haemophilus"),], "amcl")
-  
-# or with dplyr so you can actually read it:
-library(dplyr)
-tbl \%>\%
-  filter(first_isolate == TRUE,
-         genus == "Haemophilus") \%>\%
-  rsi_predict("amcl")
-
-tbl \%>\%
-  filter(first_isolate_weighted == TRUE,
-         genus == "Haemophilus") \%>\%
-  rsi_predict(col_ab = "amcl",
-              year_max = 2050,
-              year_every = 5)
-
-}
-}
-\seealso{
-\code{\link{lm}} \cr \code{\link{glm}}
-}

setup.py

@@ -0,0 +1,27 @@
+from setuptools import setup, find_packages
+
+setup(
+    name='AMR',
+    version='3.0.1.9091',
+    packages=find_packages(),
+    install_requires=[
+        'rpy2',
+        'numpy',
+        'pandas',
+    ],
+    author='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',
+)