gauss_cubature — MATH numerics 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.gauss_cubature(n: 'int', dim: 'int' = 2, a=-1.0, b=1.0) -> 'dict' (to call the implementation directly, import mathnumerics; mathnumerics.gauss_cubature(n: 'int', dim: 'int' = 2, a=-1.0, b=1.0) -> 'dict'; from the registry, opsmath.get("gauss_cubature"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

Gauss–Legendre のテンソル積で、箱 [a, b]^dim(a, b は軸ごとでも可)の求積の節点 (n^dim, dim) と重み。

画像の画素平均・ボリュームの体積積分・PSF の積分に。各軸で 2n−1 次までの多項式の積を厳密に積分する

(門: x^p y^q で p, q <= 2n−1 は厳密、どれかが 2n で誤差)。点の数は n^dim なので高次元では急に増える

(dim > 6 では低食い違い列の方が向く)。

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)

• (none yet)

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

dynsys_poincare_section · dwt_inverse · chebyshev_eval_nd

Same category (numerics)

erf · erfc · bessel · gauss_quadrature · chebyshev_coeffs_nd · chebyshev_eval_nd · low_discrepancy · chebyshev_nodes


*Provenance: mathnumerics.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.