dipole_torque_resolution — DRIVE tactorque op

• Data kinds: matrix × matrix × scalar × scalar × scalar × scalar × scalar → table

• Call: import fullseye as fs; fs.ledger.dipole_torque_resolution(pts, u, sigma_px: 'float', pitch: 'float', coef: 'float', area: 'float', radius: 'float', trials: 'int' = 100, window=None, seed: 'int' = 0, form: 'str' = 'divergence') -> 'dict' (to call the implementation directly, import tactorque; tactorque.dipole_torque_resolution(pts, u, sigma_px: 'float', pitch: 'float', coef: 'float', area: 'float', radius: 'float', trials: 'int' = 100, window=None, seed: 'int' = 0, form: 'str' = 'divergence') -> 'dict'; from the registry, opsdrive.get("dipole_torque_resolution"))

Usage

Adds marker-centroid noise σ [px] to the displacements, recomputes the dipole trials times and measures the torque resolution σ_M = σ_D/|coef| [N·m]. Returns sigma_D (2,), sigma_M (2,), D0 (noise-free), snr = |D0|/σ_D, trials. σ_M ∝ σ (measured). Raises ValueError: σ < 0, trials < 2, coef = 0.

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_tactile_dipole_torque — py -3.11 examples/poc_tactile_dipole_torque.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 (tactorque)

punch_pressure · punch_surface_uz · hertz_pressure_shifted · ellipse_pressure_shifted · pressure_first_moment · boussinesq_kernel · boussinesq_surface_displacement · surface_divergence_closed_form


*Provenance: tactorque.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.