typed op• 데이터 종류: counts → counts
• 호출: fullseye.apply(img, "tb_spad_deadtime_apply", a=0.5, b=0.5)(2-D 는 이미지 1 장 + 스칼라 노브 2 개 a,b∈[0,1] 모델)
*그림 없음: 이 연산자는 counts를 입력으로 받습니다. 이미지에서 시작하는 Studio 프로그램으로는 그 타입에 닿지 않으므로 아래의 실행 가능한 예제를 보세요.*
검출기의 데드타임으로 실제 광자율을 왜곡시킴(계수 손실).
> 아래 상세 설명은 원문입니다 —— 요약과 제목은 번역되어 있습니다.
After every detection a SPAD is blind for a recharge (dead) time `tau`, so
the *measured* rate `m is always below the *true* incident rate n`.
Two classical laws, and this op implements both:
• non-paralysable (default) — an arriving photon during the dead time is
simply lost: `m = n / (1 + n*tau). Monotonic, saturating at 1/tau`.
• paralysable (`paralyzable=True`) — an arriving photon *restarts* the
dead time: `m = n * exp(-n*tau). This law **peaks** at n = 1/tau`
(where `m = 1/(e*tau)`) and then falls, so a bright scene can read
*darker* than a dim one. That is why no inverse op exists for it (see
:func:spad_deadtime_correct).
*rate_hz* is a 1-D array of true rates in counts per second; *dead_time_ns*
is the dead time in nanoseconds, defaulting to 50 — the middle of the
10-100 ns range a passively quenched SPAD occupies, and a placeholder to be
replaced by the datasheet value, never a measurement of your detector.
Returns the measured rates as a float64 1-D array of the same length.
Ground truth (pinned in the tests): at `n = 1/tau` the non-paralysable law
gives exactly `n/2`; the paralysable law's maximum is exactly
`1/(e*tau) at n = 1/tau; both reduce to m = n as n*tau -> 0`.
Raises `ValueError`: negative, non-finite or non-1-D *rate_hz*, a
non-positive *dead_time_ns*, and a non-bool *paralyzable*.
Typed bridge of the photon op `spad_deadtime_apply 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.
• 샘플 데이터 카탈로그(DL URL / 라이선스) —— 2-D 는 skimage.data(BSD/public)+ 합성, 3-D 는 실데이터 소스(Stanford/PDS 등)의 DL URL.
• 연산자의 내력·참고문헌 —— 이 연산자 족의 바탕이 된 연구/기법의 출처.
• (아직 없음)
counts 를 입력으로 받는 것)identity · tb_spad_deadtime_correct · 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_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal
*Provenance: ops.py — 2D 연산자 레지스트리. 이 op 노트는 tools/opdocs.py md 가 자동 생성합니다(직접 편집하지 마세요).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.