parabola_fit_g — DRIVE `kendama` op

• Data kinds: none → table (an op determined by its arguments alone — it takes no image or data input)

• Call: import fullseye as fs; fs.ledger.parabola_fit_g(t, P, *, g: 'float' = 9.81, t_ref: 'float' = None) -> 'dict' (to call the implementation directly, import kendama; kendama.parabola_fit_g(t, P, *, g: 'float' = 9.81, t_ref: 'float' = None) -> 'dict'; from the registry, opsdrive.get("parabola_fit_g"))

Usage

Fits the parabola p(t) = p_r + v_r (t − t_ref) − ½ g (t − t_ref)² ẑ by least squares with gravity g (−z) known (6 unknowns = position and velocity).

> The detailed description below is the original text — the summary and the headings are translated.

t (N,)、P (N, 3)(NaN の行は飛ばす)。t_ref 既定 = 使った最後の時刻(= その瞬間の状態を返す)。各軸は [1, t − t_ref] の線形最小二乗(z は ½ g (t − t_ref)² を足してから)。返り値 {"p", "v", "t_ref", "rms" (残差の RMS [m]), "n"}。有効な点が 2 未満・時刻が全部同じ・g ≤ 0 は ValueError。真空の正確な標本なら (p, v) を丸め誤差で戻す(門)。

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)

• (none yet)

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 (`kendama`)

kendama_params · elliptic_k_agm · pendulum_period_exact · pendulum_launch_speed · pendulum_rod_simulate · tether_tension_fixed · tether_slack_angle · swing_up_plan

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

parabola_fit_g — DRIVE kendama op