tacscalib op• Data kinds: matrix × signal × any → table
• Call: import fullseye as fs; fs.ledger.field_position_sweep(centres, errors, image_shape) -> 'dict' (to call the implementation directly, import tacscalib; tacscalib.field_position_sweep(centres, errors, image_shape) -> 'dict'; from the registry, opsdrive.get("field_position_sweep"))
Position dependence of the error: arranges each image's contact center (row, column) and error (e.g. the median) against the distance from the image center, and returns the least-squares slope [error / 100 px] and Spearman's rank correlation (ties get average ranks) (numpy only). Returns: dist_px, err, slope_per_100px, intercept, spearman, n. Raises ValueError: fewer than 3 pairs / shape mismatch / non-finite / shape of image_shape.
• 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.
• poc_tacscalib_sphere_lut — py -3.11 examples/poc_tacscalib_sphere_lut.py
table as input)course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same
tacscalib)calib_pack_load · sphere_normals_known · lights_fit_from_sphere · membrane_predict_rgb · gradient_lut_build · gradient_lut_invert · normal_error_map · sphere_cap_height
*Provenance: tacscalib.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.