transform op• 数据种类:table → signal
• 调用: import fullseye as fs; fs.ledger.istft(transform)(要直接调用实现,import acoustics; acoustics.istft(transform);从台账取用则 opsacoustics.get("istft"))
用加权重叠相加精确地逆 stft。
> 以下的详细说明为原文 —— 摘要与标题已翻译。
Weighted overlap-add divides the synthesised sum by the overlap sum of the *squared* window, which makes the reconstruction exact for any window and hop satisfying NOLA, not only for the COLA pairs. stft refuses the NOLA violation up front, so if the transform was produced by it the inverse cannot be lossy.
Measured round-trip error, max |x - istft(stft(x))| on 4096 samples of white noise (float64, so 2.2e-16 is one ulp of the largest sample):
=============== ==== ==== ========= =========
window win hop max error nola_min
=============== ==== ==== ========= =========
hann 256 128 1.33e-15 0.5
hann 256 64 1.33e-15 1.5
hann 256 255 2.73e-12 2.27e-08
hamming 256 128 1.33e-15 0.5832
blackman 512 128 1.33e-15 1.206
flattop 256 64 1.33e-15 0.396
boxcar 256 128 8.88e-16 2.0
hann (nfft 512) 256 128 1.33e-15 0.5
=============== ==== ==== ========= =========
Read the third row's two columns together. hop = 255 on a 256-sample window overlaps by one sample, which breaks plain (unweighted) overlap-add completely; weighted overlap-add still inverts it, but only to 2.7e-12 rather than 1.3e-15, because the squared-window overlap sum falls to 2.3e-08 and the reconstruction divides by it. NOLA is satisfied and the result is four orders of magnitude less accurate than every other row — which is why nola_min is *returned* and not merely checked. A NOLA minimum that is small but positive is a conditioning warning, and there is no threshold at which it stops being one, so no threshold is invented here.
Raises ValueError: a dict missing any key stft writes, a spectra whose shape disagrees with the recorded nfft / frame count, or a non-complex spectra.
• acoustic_condition_monitoring 族使用指南
• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。
• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。
• 算法的正典(作者、年份)与用途见上面的族使用指南。
• acoustic_condition_monitoring — py -3.11 examples/acoustic_condition_monitoring.py
signal 作为输入)stft · envelope_spectrum · spectral_kurtosis · cepstrum · angular_resample · order_spectrum · octave_spectrum · weighting_response
transform)*Provenance: acoustics.py — ACOUSTICS 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.