japan_stats — DRIVE japan op

• Data kinds: table → table

• Call: import fullseye as fs; fs.ledger.japan_stats(graph: 'dict') -> 'Dict[str, object]' (to call the implementation directly, import drivejapan; drivejapan.japan_stats(graph: 'dict') -> 'Dict[str, object]'; from the registry, opsdrive.get("japan_stats"))

Usage

Breakdown table of the road network: number of edges, total length and mean width per type, breakdown of where widths come from, and the number of notable nodes.

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• poc_driving_japan_town — py -3.11 examples/poc_driving_japan_town.py

Ops the type connects to (they accept table as input)

course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same

Same category (japan)

osm_synthetic · osm_parse · osm_road_graph · osm_road_mask · osm_road_loops · osm_route · japan_world · latlon_to_local

*Provenance: drivejapan.py — DRIVE operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.