typed op• 数据种类:signal → feature
• 调用:fullseye.apply(img, "tb_equivalent_level", a=0.5, b=0.5)(2-D 的模型是一张图 + 两个标量旋钮 a,b∈[0,1])
*图为在 128×128 合成输入上实际运行的输出。左为输入，右为输出。点云以俯视散点显示(亮度 = z)，一维序列为折线，体数据为沿 z 的最大值投影，视频为中间帧，复数图像为幅值；无法成像的返回值直接显示数值。*
扫描旋钮 a(0.1 / 0.5 / 0.9，另一旋钮取默认):
▸ tb_equivalent_level: 旋钮 a 扫描 (文档网站)
*旋钮 b 不改变输出(实测: 0.1 / 0.5 / 0.9 相同)。*
阶段(前置算子 → 本算子，从左到右):
▸ tb_equivalent_level: 处理阶段 (文档网站)
记录的能量等效级，单位为相对于 ref 的 dB。
> 以下的详细说明为原文 —— 摘要与标题已翻译。
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.
Typed bridge of the acoustics op equivalent_level into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. a drives ref (default 1); b is unused.
• 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。
下面的程序已确认可以运行(与图相同的输入)。在 Studio 帮助中，此块会变成按钮，可当场加载并运行。
img_to_signal 0.50 0.50 tb_equivalent_level 0.50 0.50
下面的示例调用的是底层账本算子 equivalent_level。此桥接算子只是把同一实现适配为 fn(v, a, b) 约定，行为完全相同(只是调用形式不同)。
• acoustic_condition_monitoring — py -3.11 examples/acoustic_condition_monitoring.py
feature 作为输入)typed)tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal · tb_voxel_grid_downsample
*Provenance: ops.py — 2D 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.