(v3.0.1.9076) document Python installation channels and enforce_method in vignette (#296)

vignettes/AMR_for_Python.Rmd

@@ -200,6 +200,48 @@ AMR.antimicrobials
 | 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.