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.

Empty input (graph an empty dict) raises ValueError.

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.