dual op• 데이터 종류: signal × signal → table
• 호출: import fullseye as fs; fs.ledger.transfer_function(x, y, rate, win=None, hop=None, window='hann', estimator='h1', ref=1.0, floor_db=-200.0)(구현을 직접 호출하려면 import acoustics; acoustics.transfer_function(x, y, rate, win=None, hop=None, window='hann', estimator='h1', ref=1.0, floor_db=-200.0), 원장에서 가져오려면 opsacoustics.get("transfer_function"))
x 를 입력, y 를 출력으로 H(f) 를 추정하고 결맞음도 함께.
> 아래 상세 설명은 원문입니다 —— 요약과 제목은 번역되어 있습니다.
estimator:
• "h1" — Pxy / Pxx. Unbiased when the noise is on the output. The usual default and the right one for a driven test.
• "h2" — Pyy / conj(Pxy). Unbiased when the noise is on the input. It over-estimates the magnitude wherever H1 under-estimates it, so the two together bracket the truth, and |H1/H2| = gamma**2 exactly — an identity worth checking rather than a coincidence.
Returns a dict: freqs, response (complex), magnitude, magnitude_db (relative to ref), phase_rad, coherence, estimator, n_frames, win, hop, rate.
Measured at 16 kHz over 16384 samples, win = 1024, 31 frames, white input:
• y = 2.5 * x: mean |H| = 2.5000000000, max deviation from 2.5 over all bins 1.78e-15, mean |phase| 2.7e-17, mean coherence 1.0000000000.
• y = 0.8 * x[n-37]: the phase is a straight line in frequency of slope -2 pi * 37 / 16000 s. A least-squares fit to the unwrapped phase over 200-7000 Hz gives a group delay of 37.000004 samples against a true 37 (error 4.3e-06 samples), and mean |H| = 0.792220 over the same bins against a true 0.8 (max deviation 0.050).
• y = 2.5 * x + n with output noise at 0 dB SNR: H1 gives mean |H| = 2.523390 — 0.94 % from the truth — while H2 gives 5.043020, a factor of 2.0 too large, exactly as the theory predicts when the noise sits on the output. And |H1/H2| equals the coherence pointwise to 5.6e-16 (both mean 0.509143), which is the identity worth
knowing: the ratio of the two estimators *is* the coherence.
That third row is why the coherence is returned with the response. The H2 number is off by 100 % and there is nothing about 5.04 that looks wrong.
Raises ValueError: everything coherence refuses, plus an unknown estimator and ref <= 0.
• acoustic_condition_monitoring 패밀리 가이드
• 샘플 데이터 카탈로그(DL URL / 라이선스) —— 2-D 는 skimage.data(BSD/public)+ 합성, 3-D 는 실데이터 소스(Stanford/PDS 등)의 DL URL.
• 연산자의 내력·참고문헌 —— 이 연산자 족의 바탕이 된 연구/기법의 출처.
• 알고리즘의 정전(저자·연도)과 용도는 위의 패밀리 사용 가이드에 적혀 있습니다.
• acoustic_condition_monitoring — py -3.11 examples/acoustic_condition_monitoring.py
• poc_leak_localization — py -3.11 examples/poc_leak_localization.py
table 를 입력으로 받는 것)dual)*Provenance: acoustics.py — ACOUSTICS 연산자 레지스트리. 이 op 노트는 tools/opdocs.py md 가 자동 생성합니다(직접 편집하지 마세요).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.