Tutorial

A self-contained, minimal walkthrough is available in the tutorial/ directory of the repository. It generates a small synthetic sensor dataset, extracts features, evaluates rule diagnostics, and produces an interval event log — without needing any external data files.

Running it

python3 tutorial/toy_walkthrough.py

This is also available as a Jupyter notebook, tutorial/toy_walkthrough.ipynb, which mirrors the script and includes a repo-root bootstrap cell for reliable imports when launched from tutorial/. To run it, make sure ipykernel is installed in your environment:

python -m pip install ipykernel

What it produces

Running the walkthrough writes the following to tutorial/output/:

• toy_sensor_data.csv — the synthetic raw sensor dataset.

• toy_features.csv — the engineered feature table.

• toy_event_log.csv — the resulting interval event log.

It also prints rule-diagnostic recommendations to the console and (if matplotlib is installed) renders sensor time-series plots and a simple process graph.

Further tutorials

A tiered set of tutorials — from core concepts through advanced process-mining integration and eventization-quality evaluation — is in progress in the repository’s tutorials/ directory. See the tutorials table in the README for current status.