chebyshev_nodes — MATH numerics op

• Data kinds: none → signal (an op determined by its arguments alone — it takes no image or data input)

• Call: import fullseye as fs; fs.ledger.chebyshev_nodes(n: 'int', a: 'float' = -1.0, b: 'float' = 1.0, kind: 'int' = 2) -> 'np.ndarray' (to call the implementation directly, import mathnumerics; mathnumerics.chebyshev_nodes(n: 'int', a: 'float' = -1.0, b: 'float' = 1.0, kind: 'int' = 2) -> 'np.ndarray'; from the registry, opsmath.get("chebyshev_nodes"))

Usage

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

区間 [a, b] の Chebyshev 点 n 個(昇順)。

`kind=2(既定)は端点を含む Chebyshev–Lobatto 点 x_k = cos(kπ/(n−1))、kind=1` は端点を含まない

Chebyshev–Gauss 点 cos((2k+1)π/(2n))。端に向かって密になり、多項式補間の暴れ(Runge 現象)を抑える。

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)

• numerics_tour — py -3.11 examples/numerics_tour.py

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

mat_solve · mat_lstsq · stat_describe · stat_histogram · stat_zscore · interp_linear · interp_cubic · interp_scattered

Same category (numerics)

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


*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.