esprit_doa — MATH spectral op

• Data kinds: matrix → table

• Call: import fullseye as fs; fs.ledger.esprit_doa(X, n_sources: 'int | None' = None, *, spacing: 'float' = 0.5) -> 'dict' (to call the implementation directly, import mathspectral; mathspectral.esprit_doa(X, n_sources: 'int | None' = None, *, spacing: 'float' = 0.5) -> 'dict'; from the registry, opsmath.get("esprit_doa"))

Usage

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

ESPRIT(Roy & Kailath 1989): アレイの「1 素子ずらし」の不変性から、格子を使わずに向きを解く。

信号部分空間 E_s の上 M−1 行と下 M−1 行を最小二乗で結ぶ Φ の固有値 λ_k = exp(−2πi d sin θ_k) から

θ_k = arcsin(−arg λ_k / (2π d))。雑音なし・無相関なら厳密(格子の分解能に縛られない)。

`n_sources=None なら MDL で推定する。返り値 {"doa_deg", "eigenvalues", "n_sources", "n_sources_estimated"}`。

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)

• spectral_tour — py -3.11 examples/spectral_tour.py

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

dynsys_poincare_section · dwt_inverse · chebyshev_eval_nd

Same category (spectral)

lomb_scargle · ula_snapshots · music_doa · n_sources_mdl · hilbert_analytic


*Provenance: mathspectral.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.