typed op• Data kinds: matrix → feature
• Call: fullseye.apply(img, "tb_mat_cond", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
Spectral (2-norm) condition number `s_max / s_min` — the numerical canary of the whole linalg family.
`cond == 1` for an orthogonal/orthonormal matrix (the best possible);
`inf` (returned, not raised — the question "how conditioned is it?" has
that honest answer) for an exactly singular one. A solve against *A* loses
roughly `log10(cond(A))` significant digits (Golub & Van Loan §2.6):
• `cond ~ 1e3` — comfortable, ~13 digits survive.
• `cond ~ 1e8` — half the digits are gone; residuals may still look
small while parameters are off.
• `cond > 1e12 — **do not trust** :func:mat_solve` here: at best ~3
digits remain. Rescale/centre the problem, or switch to
:func:mat_lstsq / :func:mat_pinv with an honest `rcond`.
Defined for any rectangular `(m, n)` matrix (via its singular values).
HALCON: no direct operator (combine `norm_matrix` of *A* and of its
inverse).
Typed bridge of the math op `mat_cond into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. This op has no tunable parameter; a and b` are unused.
• 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.
• (none yet)
feature as input)typed)tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal
*Provenance: ops.py — 2D 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.