counting op• 数据种类:image2d → image2d
• 调用: import fullseye as fs; fs.ledger.photon_uncertainty(counts, relative=False, zero_floor=0.0)(要直接调用实现,import photoncount; photoncount.photon_uncertainty(counts, relative=False, zero_floor=0.0);从台账取用则 opsphoton.get("photon_uncertainty"))
光子计数帧逐像素的泊松误差棒。
> 以下的详细说明为原文 —— 摘要与标题已翻译。
For a Poisson variable the variance *equals* the mean, so the one-sigma uncertainty of a single measurement N is sqrt(N) — no calibration, no noise model to fit. With relative=True the returned map is the relative uncertainty 1/sqrt(N) instead (its reciprocal is the per-pixel SNR).
*zero_floor* replaces counts below it before the square root. It exists because N = 0 gives sqrt(0) = 0, i.e. "this pixel is exactly zero with no uncertainty", which is wrong: the 95% Poisson upper limit for a single observed zero is about 3 photons. Set zero_floor=1.0 for the common "one-count prior" convention. It is not applied silently — the default is 0.0 and the absolute map really does return 0 there.
Returns a float64 (H, W) image.
Raises ValueError: negative, non-finite or non-2-D *counts*, a negative *zero_floor*, and — instead of returning inf — relative=True with any pixel at 0 after the floor (that is the division 1/sqrt(0); pass zero_floor > 0 to say what a zero should mean).
• 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。
• 算法的正典(作者、年份)与用途见上面的族使用指南。
• photon_timeresolved — py -3.11 examples/photon_timeresolved.py
• poc_thermal_radiometry — py -3.11 examples/poc_thermal_radiometry.py
image2d 作为输入)photon_sample · photon_statistics · anscombe_transform · anscombe_inverse
counting)photon_sample · photon_statistics
*Provenance: photoncount.py — PHOTON 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.