transform op• 数据种类:table → signal
• 调用:import acoustics; acoustics.istft(transform)(或 opsacoustics.get("istft"))
用加权重叠相加精确地逆 :func: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. :func: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 :func: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.