fit op• Data kinds: keypoints → table
• Call: import fullseye as fs; fs.ledger.fit_circle_geometric(points, *, max_iterations: 'int' = 100, radius_limit_factor: 'float' = 1000000.0) -> 'dict' (to call the implementation directly, import measure; measure.fit_circle_geometric(points, *, max_iterations: 'int' = 100, radius_limit_factor: 'float' = 1000000.0) -> 'dict'; from the registry, opsfit.get("fit_circle_geometric"))
• GPU: none (CPU reference implementation only)
Fit a circle and radius to (row, col) points, including short arcs, by geometric least squares.
Kåsa's algebraic fit supplies the initial centre and radius, then a Levenberg--Marquardt solve minimises hypot(x-cx, y-cy) - r (Chernov & Lesort 2005). Returns cy, cx, r, geometric rms, iterations and converged. max_iterations is the maximum number of function evaluations. radius_limit_factor bounds the fitted radius relative to the point-cloud span; an exceeded bound is reported as ValueError instead of returning a line-like, effectively infinite circle. Non-finite, collinear, or fewer than three points are also rejected.
• 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.
• fit_ops_from_knowhow — py -3.11 examples/fit_ops_from_knowhow.py
table as input)—
fit)*Provenance: measure.py — FIT 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.