Skip to content

Coffee Machine with AALpy

This example learns a Mealy machine from recorded Coffee Machine traces using AALpy's passive RPNI algorithm. Training and prediction run locally in Python.

Run the example

From the repository root, retrieve the DVC-managed CSV traces and run the example:

uv run dvc pull --recursive examples/coffee_machine
just examples-coffee_machine

Each CSV is one synchronized trace. The example sorts its rows by time once and collects the aligned input and output columns into symbol words. It uses 80% of the traces for training and reports the fraction of test traces whose entire output word is predicted correctly.