signal op• 데이터 종류: signal → signal
• 호출: import fullseye as fs; fs.ledger.quantize(x, bits=8, mode='round', dither=None, seed=0)(구현을 직접 호출하려면 import dsp; dsp.quantize(x, bits=8, mode='round', dither=None, seed=0), 원장에서 가져오려면 ops1d.get("quantize"))
오차 모델을 명시한 스칼라 양자화기(디더 선택 가능).
> 아래 상세 설명은 원문입니다 —— 요약과 제목은 번역되어 있습니다.
*bits* sets the number of levels L = 2**bits over the signal's own min..max range. *mode* is "round" (mid-tread, unbiased) or "truncate" (floor, the convention PIL's posterize and most fixed-point casts use).
The two differ by more than a rounding convention. With step Delta = range/(L-1) both have error variance Delta**2/12, but truncation also carries a mean of -Delta/2, so its mean square error is
truncate: Delta**2/12 + (Delta/2)**2 = Delta**2/3
round: Delta**2/12
— a factor of 4. Anything that measures a level (not just displays it) must round.
*dither* adds noise before quantising so the error stops being a function of the signal: "tpdf" (triangular, the audio standard — two uniform draws summed, so the error's variance no longer depends on the sample value) or "rpdf" (one uniform draw). Dither raises the total error power but removes the correlation that makes quantisation audible as distortion rather than as hiss. seed fixes the draw so the op stays deterministic.
Applicability. (1) The range is taken from *this* signal, so two signals quantised separately do not share a scale. (2) bits=1 with no dither is a comparator, not a quantiser — the error model does not apply. (3) The error model assumes the signal moves by more than a step between samples; on a flat stretch the error is a constant offset, not noise.
• 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.
• poc_cold_chain_excursion — py -3.11 examples/poc_cold_chain_excursion.py
signal 를 입력으로 받는 것)create_funct_1d_array · create_funct_1d_pairs · smooth_funct_1d_gauss · smooth_funct_1d_mean · derivate_funct_1d · integrate_funct_1d · zero_crossings_funct_1d · local_min_max_funct_1d
signal)lowpass · highpass · bandpass · envelope · rms · local_std · companding_mu_law · resample
*Provenance: dsp.py — ONED 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.