level op• Data kinds: signal → measurement
• Call: import fullseye as fs; fs.ledger.equivalent_level(x, rate, weighting='A', ref=1.0, floor_db=-200.0, window='none') (implementation को सीधे call करना हो तो import acoustics; acoustics.equivalent_level(x, rate, weighting='A', ref=1.0, floor_db=-200.0, window='none'), registry से लेना हो तो opsacoustics.get("equivalent_level"))
record का energy-equivalent level, ref के सापेक्ष dB में।
> नीचे का विस्तृत विवरण मूल text में है — सारांश और headings का अनुवाद हो चुका है।
L_eq = 10 log10(mean(x_w**2) / ref**2) where x_w is the signal after the chosen weighting. Returns a plain float.
The reference is yours to supply. The default ref=1.0 means dB relative to one unit of the signal's own units; it is not dB SPL, because this library never sees your calibration. Pass ref=20e-6 for pascals.
Measured: a 1 kHz sine of amplitude 1.0 at 16 kHz over exactly 1000 periods gives L_eq = -3.010300 dB with Z weighting, against the closed form 10*log10(1/2) = -3.010300 (difference 2.2e-15 dB), and the same value under A weighting (difference 8.9e-16 dB), because A is 0 dB at 1 kHz. Doubling the amplitude adds 6.020600 dB. Silence returns -200.0.
Silence returns floor_db (default -200) rather than -inf; an -inf in a list of levels destroys every average taken over it afterwards.
A weighted level is only as good as the weighting, and the weighting has a leakage limit this operator inherits in full. A pure tone that is not a whole number of periods in the record comes back too loud — measured +7.7986 dB at 31.5 Hz (a nominal one-third-octave centre) over 0.5 s at 48 kHz, and up to +17.2116 dB at 20.5 Hz — with no exception, no NaN and no warning. weighting="Z" is exempt (it does no filtering) and "C" is nearly so (+0.0493 dB on the same tone); it is "A", whose curve spans about 40 dB across the audio band, that is exposed.
window="hann" is the opt-in remedy: the record is multiplied by a Hann window and the mean square divided by the window's own mean square, which suppresses the leakage almost entirely — the 31.5 Hz error goes from +7.7986 to +0.0534 dB and the 20.5 Hz error from +17.2116 to +0.1841 — while costing about 0.15 dB on records that were exact before. It is not the default, and must not be used when a transient's level is the point: a window makes the answer depend on *where in the record the sound happened*. Measured on a 50 ms burst inside a 0.5 s record (Z weighting, so only the window acts; unwindowed all three are -13.0103 dB as they must be): at the start -36.0587, at the centre -8.8218, at the end -36.0587 — a 27 dB spread produced by nothing but position. Use "hann" for a stationary tonal record, which is exactly the case the leakage ruins, and "none" (the default, an honest energy average) for everything else. The full measurement is in apply_weighting.
Raises ValueError: everything _as_signal refuses, an unknown weighting or window, ref <= 0 (a decibel needs a positive reference; a zero reference makes every level +inf and a negative one makes the ratio negative), rate <= 0.
• acoustic_condition_monitoring family guide
• Sample data catalog (DL URL / license) — 2-D के लिए skimage.data (BSD/public) + synthetic, 3-D के लिए real data sources (Stanford/PDS आदि) के DL URL।
• Operators का स्रोत और संदर्भ — इस op family के मूल research/methods के स्रोत।
• Algorithm का मानक स्रोत (लेखक, वर्ष) और उपयोग ऊपर की family usage guide में दिए गए हैं।
• acoustic_condition_monitoring — py -3.11 examples/acoustic_condition_monitoring.py
measurement को input के रूप में लेते हैं)—
level)octave_bands · octave_spectrum · weighting_response · apply_weighting · percentile_level
*Provenance: acoustics.py — ACOUSTICS operator registry. यह per-op note tools/opdocs.py md से अपने-आप generate होता है (हाथ से edit न करें)।*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.