counting opimage2d → image2dimport fullseye as fs; fs.ledger.photon_uncertainty(counts, relative=False, zero_floor=0.0) (実装を直接呼ぶなら import photoncount; photoncount.photon_uncertainty(counts, relative=False, zero_floor=0.0)、台帳から引くなら opsphoton.get("photon_uncertainty"))Per-pixel Poisson error bar of a photon-count frame.
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).
py -3.11 examples/photon_timeresolved.pypy -3.11 examples/poc_thermal_radiometry.pyimage2d を入力に取れる)photon_sample · photon_statistics · anscombe_transform · anscombe_inverse
counting)photon_sample · photon_statistics
Provenance: photoncount.py — PHOTON operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.