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: Delta2/12 + (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.