level op• 資料種類:signal → table
• 呼叫: import fullseye as fs; fs.ledger.percentile_level(x, rate, percentiles=(10.0, 50.0, 90.0), weighting='A', ref=1.0, window_s=0.125, floor_db=-200.0)(要直接呼叫實作,import acoustics; acoustics.percentile_level(x, rate, percentiles=(10.0, 50.0, 90.0), weighting='A', ref=1.0, window_s=0.125, floor_db=-200.0);從台帳取用則 opsacoustics.get("percentile_level"))
統計級:L_N 是有 N % 的時間被超過的級。
> 以下的詳細說明為原文 —— 摘要與標題已翻譯。
The record is cut into non-overlapping blocks of window_s seconds, each block's equivalent level is computed, and L_N is the (100-N)-th percentile of those levels. Non-overlapping rectangular blocks are used rather than an exponential time weighting because the block length is then exactly what the caller asked for and the statistic is exactly a percentile of the returned levels array — an exponential average would make the effective averaging time a function of the signal.
Returns a dict with one key per requested percentile ("L10", "L50", "L90", formatted with %g), plus levels (the per-block levels), times (block start times, s), n_blocks, block_samples, leq (the energy-equivalent level of the whole record), ref, weighting.
Note that L50 is the *median* level and leq is the *energy* level; they are different numbers whenever the signal is not stationary, and the gap between them is itself the usual measure of how fluctuating a record is.
Measured on a two-level test signal (1 s at 16 kHz, first half a 1 kHz sine of amplitude 1.0, second half the same at 0.1, Z-weighted, 0.125 s blocks, 8 blocks): L10 = -3.010300 and L90 = -23.010300 dB — exactly the two constituent levels, 20.000000 dB apart, as they must be for a 50/50 split. L50 = -13.010300 is the interpolated midpoint of the two clusters and leq = -5.977386, which is 17 dB above L90: the energy level sits near the loud half while the median sits between them. On a constant-amplitude signal all three percentiles and leq agree to 3.6e-15 dB.
Raises ValueError: everything _as_signal refuses, a percentile outside [0, 100], a non-positive window_s, a window_s longer than the record (which would give one block and make every percentile the same number while still looking like a statistic), ref <= 0.
• acoustic_condition_monitoring 族使用指南
• 範例資料目錄(下載 URL / 授權) —— 2-D 用 skimage.data(BSD/公有領域)加合成圖,3-D 給出真實資料源(Stanford/PDS 等)的下載 URL。
• 運算子來歷與參考文獻 —— 該運算子族所依據的研究/方法出處。
• 演算法的正典(作者、年份)與用途見上面的族使用指南。
• acoustic_condition_monitoring — py -3.11 examples/acoustic_condition_monitoring.py
table 作為輸入)level)octave_bands · octave_spectrum · weighting_response · apply_weighting · equivalent_level
*Provenance: acoustics.py — ACOUSTICS 運算子登記表。本條目由 tools/opdocs.py md 自動產生(請勿手動編輯)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.