ford_circles — MATH construct 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.ford_circles(max_denominator=12, lo=0, hi=1) (to call the implementation directly, import mathops; mathops.ford_circles(max_denominator=12, lo=0, hi=1); from the registry, opsmath.get("ford_circles"))

Usage

Ford circles for the Farey fractions — tangency *is* an integer identity.

For a fraction `p/q` in lowest terms the Ford circle sits at

`(p/q, 1/(2q**2)) with radius 1/(2q**2)`. Two such circles are

tangent if and only if `|p*s - q*r| == 1` — the Farey-neighbour

condition — and otherwise strictly disjoint. They never overlap.

★Why this earns its place: the picture's correctness is an identity

between integers, not a tolerance. `|p*s - q*r|` is computed in exact

integer arithmetic and compared with the *geometric* tangency

`|c_i - c_j| == r_i + r_j` measured from the coordinates; the two must

agree on every pair. The number of fractions is the Farey length

`1 + sum(phi(q) for q in 1..n)`, another exact integer.

Returns a `table: x, y, radius, p, q`.

Raises `ValueError: max_denominator < 1; lo >= hi`; the

interval or denominator would exceed the cap.

HALCON: no operator.

Family-wide input contract (fail-closed)

Every mathops op validates its input before computing (nothing slips through silently):

• **complex input raises ValueError** — coercing to float64 silently discards the imaginary part (numpy only emits a ComplexWarning and returns a plausible-looking wrong real number). State .real/.imag/abs() explicitly, or use complexops, which handles complex data.

• **masked arrays with masked elements raise ValueError** — the implicit conversion that peels off the mask and uses the raw values underneath is refused. Say explicitly whether to fill or to drop.

• **NaN/Inf raises ValueError on every input** (refused with the count stated — it propagates through the whole result).

• Shapes are strict: 1-D and 2-D are never implicitly promoted or broadcast (a matrix in a vector slot, or a vector in a matrix slot, raises ValueError; reshape explicitly).

• Size cap: ops that take a matrix, and the stat_histogram bins, raise ValueError beyond mathops.MAX_ELEMENTS (2^26 ≈ 67 million elements).

Detailed usage guide

• math_metrology family guide

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_theorems_as_pictures — py -3.11 examples/poc_theorems_as_pictures.py

Ops the type connects to (they accept table as input)

dynsys_poincare_section

Same category (construct)

circle_packing_apollonian · phyllotaxis_pattern · neighbour_index_gaps · ifs_fractal · ifs_similarity_dimension · space_filling_curve · curve_locality


*Provenance: mathops.py — MATH 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.