typed op• 資料種類:counts → counts
• 呼叫:fullseye.apply(img, "tb_tcspc_irf_convolve", 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_tcspc_irf_convolve: knob a sweep (docs site)
掃描旋鈕 b(0.1 / 0.5 / 0.9，另一旋鈕取預設):
▸ tb_tcspc_irf_convolve: knob b sweep (docs site)
階段(前置運算子 → 本運算子，由左至右):
▸ tb_tcspc_irf_convolve: 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_tcspc_irf_convolve: other inputs (docs site)
用儀器響應（時序抖動）對到達時間直方圖進行模糊處理。
> 以下的詳細說明為原文 —— 摘要與標題已翻譯。
The temporal analogue of a PSF convolution: a detector's timing uncertainty
(SPAD jitter + TDC quantisation + laser pulse width) smears every arrival
time by the instrument response function, here a Gaussian of full width at
half maximum *irf_fwhm_ps*. The kernel is the exact bin integral of that
Gaussian (erf differences), normalised to sum 1, truncated at
`+-truncate*sigma` and forced to odd length so the convolution is centred.
Ground truth: convolving a unit spike in the middle of a 256-bin window with
`irf_fwhm_ps = 500 at bin_ps = 50` leaves the centroid exactly
where it was (measured shift 0.0 ps — the kernel is symmetric) and gives a
profile whose measured FWHM is 501.22 ps. That 0.24% excess over 500 is the
*measurement*, not the kernel: :func:tcspc_stats finds the half-maximum
crossings by linear interpolation between bins, which slightly overestimates
the width of a Gaussian.
Total counts are preserved *except* at the window edges, where
`mode='same'` discards the tail that falls outside — measured loss exactly
0 for that centred spike, but a genuine loss for a pulse within a few sigma
of either end.
Returns a float64 1-D histogram of the same length as *hist*.
Raises `ValueError`: negative, non-finite or non-1-D *hist*, a
non-positive *bin_ps* / *irf_fwhm_ps* / *truncate*, an IRF sigma below
1e-3 bins (the kernel would be a delta and the op a no-op — say so instead
of pretending to blur), and a kernel that would be longer than the
:data:MAX_BINS cap.
Typed bridge of the photon op `tcspc_irf_convolve into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. a drives bin_ps (default 100) and b drives irf_fwhm_ps` (default 200).
• 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_tcspc_irf_convolve 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 tcspc_irf_convolve。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_spad_deadtime_correct · tb_tcspc_coates_correct · 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.