psd_welch — ONED matched op

• Data kinds: signal → pairs

• Call: import fullseye as fs; fs.ledger.psd_welch(x, rate: 'float' = 4096.0, segment_s: 'float | None' = None, *, overlap: 'float' = 0.5, window: 'str' = 'hann', average: 'str' = 'mean') -> 'np.ndarray' (to call the implementation directly, import gwsearch; gwsearch.psd_welch(x, rate: 'float' = 4096.0, segment_s: 'float | None' = None, *, overlap: 'float' = 0.5, window: 'str' = 'hann', average: 'str' = 'mean') -> 'np.ndarray'; from the registry, ops1d.get("psd_welch"))

Usage

One-sided Welch PSD as pairs (frequency [Hz], S [1/Hz]).

> The detailed description below is the original text — the summary and the headings are translated.

Parameters

x : array_like

時系列(1-D)。

rate : float

標本化周波数 fs [Hz]。

segment_s : float or None

1 区間の長さ [s] (周波数分解能 = 1/segment_s)。None なら 4 s と信号長の 1/8 の短い方

(重力波の慣例 4 s、短い信号でも 8 区間は取る)。信号より長ければ信号全長に切り詰める。

overlap : float

区間の重なり(0 ≤ overlap < 1)。

window : str

窓("hann" / "hamming" / "blackman" / "boxcar"、scipy の名前)。

average : str

区間の平均 "mean" か "median"(グリッチに強い。scipy は median の偏り補正つき)。

Returns

numpy.ndarray

(n_freq, 2)。白色ガウス雑音(分散 σ²)で S = 2σ²/fs(片側)。

Notes

重力波の標準手順(GWOSC の例題)と同じ scaling="density"。分解能 1/segment_s より細い線(60 Hz の電源線など)は幅がこの分解能に広がる。

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_gw_detector_pseudo_simulation — py -3.11 examples/poc_gw_detector_pseudo_simulation.py

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

whiten_by_psd · chirp_mass_from_track · matched_filter_snr · optimal_snr

Same category (matched)

whiten_by_psd · chirp_newtonian · chirp_mass_from_track · matched_filter_snr · optimal_snr · coincidence_delay


*Provenance: gwsearch.py — ONED 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.