sun_illuminance — DRIVE `env` op

• Data kinds: scalar → table

• Call: import fullseye as fs; fs.ledger.sun_illuminance(elevation: 'float', cloud: 'float' = 0.0) -> 'Dict[str, float]' (to call the implementation directly, import driveenv; driveenv.sun_illuminance(elevation: 'float', cloud: 'float' = 0.0) -> 'Dict[str, float]'; from the registry, opsdrive.get("sun_illuminance"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

晴天(雲量 `cloud ∈ [0, 1])の太陽の照度 [lx]: direct_normal(太陽に正対する面)・diffuse(水平面の散乱)・air_mass`。

直達 = 1361 W/m² × 0.7^{AM^0.678}(Meinel)× 105 lm/W × (1 − cloud)、AM = Kasten & Young 1989

1 / (sin h + 0.50572 (h + 6.07995°)^{−1.6364})。散乱 = 薄明の表(高度 ≤ 0)/ 400 + 16000 sin h(高度 > 0)に

雲で (1 + 0.5 cloud) を掛ける —— 仮定(モジュールの docstring)。

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_weather — py -3.11 examples/poc_driving_weather.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 (`env`)

julian_day · sun_at · sun_events · sun_vector · koschmieder · mor_from_beta · beta_from_mor · road_row_distance

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

sun_illuminance — DRIVE env op