transform optable → signalimport fullseye as fs; fs.ledger.istft(transform) (実装を直接呼ぶなら import acoustics; acoustics.istft(transform)、台帳から引くなら opsacoustics.get("istft"))Invert :func:stft by weighted overlap-add — exactly.
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.
py -3.11 examples/acoustic_condition_monitoring.pysignal を入力に取れる)stft · envelope_spectrum · spectral_kurtosis · cepstrum · angular_resample · order_spectrum · octave_spectrum · weighting_response
transform)Provenance: acoustics.py — ACOUSTICS operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.