typed op• 資料種類:counts → counts
• 呼叫:fullseye.apply(img, "tb_spad_deadtime_correct", 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。*
掃描旋鈕 a(0.1 / 0.5 / 0.9，另一旋鈕取預設):
▸ tb_spad_deadtime_correct: knob a sweep (docs site)
*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_spad_deadtime_correct: 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_spad_deadtime_correct: other inputs (docs site)
從受死時間影響而失真的量測速率中還原真實光子速率。
> 以下的詳細說明為原文 —— 摘要與標題已翻譯。
The exact inverse of the non-paralysable law of
:func:spad_deadtime_apply::
n = m / (1 - m*tau)
A round trip `apply -> correct` is exact to machine precision (measured max
elementwise relative error 6.0e-16 over 2000 rates spanning 1e3 to 5e7 Hz at
`tau = 50 ns`, where the measured rate reaches 71.4% of the 20 MHz
saturation rate).
There is deliberately no paralysable inverse. `m = n*exp(-n*tau)` is not
injective — every measured rate below the maximum `1/(e*tau)` corresponds to
*two* true rates, one below and one above `1/tau` — so returning one of them
would be a fabrication dressed as a correction. Resolve the branch with an
independent measurement (e.g. an attenuator step) and invert it yourself.
*measured_hz* is a 1-D array of measured rates in counts per second;
*dead_time_ns* the dead time in nanoseconds (default 50, the same
placeholder :func:spad_deadtime_apply uses — replace it with the
datasheet value). Returns the corrected true rates as a float64 1-D array.
Raises `ValueError`: negative, non-finite or non-1-D *measured_hz*, a
non-positive *dead_time_ns*, and — instead of returning `inf` or a negative
rate — any measured rate at or above the saturation rate `1/tau`, which no
non-paralysable detector can ever produce.
Typed bridge of the photon op `spad_deadtime_correct into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. a drives dead_time_ns (default 50); b` is 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_counts 0.50 0.50 tb_spad_deadtime_correct 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 spad_deadtime_correct。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)。
• photon_timeresolved — py -3.11 examples/photon_timeresolved.py
counts 作為輸入)identity · tb_spad_deadtime_apply · tb_tcspc_coates_correct · tb_tcspc_irf_convolve · tb_tcspc_background_subtract · tb_dtof_depth · tb_countrate_to_counts · tb_counts_to_countrate
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.