counting op• Data kinds: image2d → image2d
• Call: import fullseye as fs; fs.ledger.photon_uncertainty(counts, relative=False, zero_floor=0.0) (to call the implementation directly, import photoncount; photoncount.photon_uncertainty(counts, relative=False, zero_floor=0.0); from the registry, 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).
• photon_timeresolved family guide
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• photon_timeresolved — py -3.11 examples/photon_timeresolved.py
• poc_thermal_radiometry — py -3.11 examples/poc_thermal_radiometry.py
image2d as input)photon_sample · photon_statistics · anscombe_transform · anscombe_inverse
counting)photon_sample · photon_statistics
*Provenance: photoncount.py — PHOTON operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.