Example notebooks

Three tiers of runnable example notebooks ship with aperta. Each is paired with a .py source file via Jupytext in the repository; the rendered versions below are the committed .ipynb outputs.

Tier	Notebook	Run time	What it covers
Minimal	minimal	~10 s	Every aperta primitive exercised exactly once, OSM data only (Cambridge MA). The “what does aperta do?” demo.
Walkthrough	walkthrough	~1 min	Guided tour of every primitive on real OSM data (Central Paris): tiered ODs, geo-keyed reindex, overheads, three accessibility metrics, path-first per-edge feature aggregation, cross-modal logsum.
Extended	extended_accessibility	~30 min	Production-scale Bern + 40 km cross-modal accessibility (walking, cycling, car at peak hours; three destination types). Generates the figures used in the toolkit paper.
Extended	extended_calibration	~30 min	Iterative edge-weight calibration against Google-Maps-derived car travel times.
Extended	extended_traffic_flows	~30 min	Per-edge AADT estimation via cost-decay-weighted nested-betweenness sampling, with counter-fit diagnostics.

The two extended-example calibration notebooks (extended_calibration and extended_traffic_flows) require ground-truth inputs (Google-Maps-derived car travel times and traffic-counter readings) whose source terms preclude redistribution. They render here from committed outputs, but re-running them locally requires the private inputs. A public-data version is planned.