typed op• 資料種類:signal → signal
• 呼叫:fullseye.apply(img, "tb_weighting_response", a=0.5, b=0.5)(2-D 的模型是一張圖 + 兩個純量旋鈕 a,b∈[0,1])
*圖為在 128×128 合成輸入上實際執行的輸出。左為輸入，右為輸出。點雲以俯視散點顯示(亮度 = z)，一維序列為折線，體資料為沿 z 的最大值投影，影片為中間影格，複數影像為振幅；無法成像的回傳值直接顯示數值。*
*旋鈕 a 不改變輸出(實測: 0.1 / 0.5 / 0.9 相同)。*
*旋鈕 b 不改變輸出(實測: 0.1 / 0.5 / 0.9 相同)。*
階段(前置運算子 → 本運算子，由左至右):
▸ tb_weighting_response: stages (docs site)
換別的影像(合成場景 / 照片 / 硬幣。上排為輸入，下排為對應輸出。旋鈕取預設):
▸ tb_weighting_response: other inputs (docs site)
在給定頻率下的 A / C / Z 頻率加權曲線，單位為 dB。
> 以下的詳細說明為原文 —— 摘要與標題已翻譯。
Computed from the four pole frequencies that *define* the networks and
normalised so that the response at 1 kHz is exactly 0 dB by construction
— the curve is divided by its own value at 1 kHz rather than having a
published offset constant added to it. That is why the tests can assert
equality at 1 kHz to 0.0 rather than to a tolerance, and why no standard's
table of attenuations appears anywhere in this repository.
The response depends on `f only through f**2`, so it is an even
function and negative frequencies are evaluated at `|f|` — that is the
definition, not a repair. `f = 0` has zero response (both curves have a
zero at DC) and is reported as `floor_db rather than -inf`.
Measured (computed, then printed — these are outputs, not transcriptions):
======== ========= =========
f (Hz) A (dB) C (dB)
======== ========= =========
10 -70.4304 -14.3300
31.5 -39.5250 -3.0305
100 -19.1428 -0.2996
1000 0.0000 0.0000
4000 0.9633 -0.8260
10000 -2.4918 -4.4055
20000 -9.3469 -11.2786
======== ========= =========
`A(1000) and C(1000) are exactly 0.0` — the Python float, not a
rounding — because of the construction. The low-frequency asymptote is a
closed form and is asserted in the tests: `A` falls at exactly
80 dB/decade as `f -> 0 (f**4 over three constants) and C` at
exactly 40 dB/decade (`f**2`). Measured between 0.001 and 0.01 Hz with the
floor lowered out of the way: 79.999998 and 39.999998 dB/decade.
That last caveat is real and is why the floor is an argument: with the
default `floor_db = -200` the A curve reaches the floor below about
0.35 Hz (unfloored, `A(0.1) = -228.55` dB), so the asymptote measured
against the default floor comes out as 0.0 dB/decade between 0.01 and
0.1 Hz — a clamp, correctly reported, that would look like a bug if the
floor were not visible.
Returns a float64 array the same shape as *freqs*.
Raises `ValueError`: a non-1-D / non-finite / complex / masked
`freqs, an unknown kind`.
Typed bridge of the acoustics op `weighting_response into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. This op has no tunable parameter; a and b` are unused.
• 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。
下面的程式已確認可以執行(與圖相同的輸入)。在 Studio 說明中，此區塊會變成按鈕，可當場載入並執行。
img_to_signal 0.50 0.50 tb_weighting_response 0.50 0.50
▸ Load this pipeline · Load & run
下面的範例呼叫的是底層帳本運算子 weighting_response。此橋接運算子只是把同一實作適配為 fn(v, a, b) 慣例，行為完全相同(只是呼叫形式不同)。
• acoustic_condition_monitoring — py -3.11 examples/acoustic_condition_monitoring.py
signal 作為輸入)identity · tb_create_funct_1d_array · tb_smooth_funct_1d_gauss · tb_smooth_funct_1d_mean · tb_derivate_funct_1d · tb_integrate_funct_1d · tb_zero_crossings_funct_1d · tb_abs_funct_1d
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 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.