tcspc op• Data kinds: none → counts (an op determined by its arguments alone — it takes no image or data input)
• Call: import photoncount; photoncount.tcspc_simulate(distance_m=3.0, bins=256, bin_ps=100.0, signal_photons=50.0, ambient_photons=20.0, irf_fwhm_ps=200.0, seed=0, noise=True) (or opsphoton.get("tcspc_simulate"))
Synthesise a single-pixel photon arrival-time histogram with a known answer.
The generative model of a direct time-of-flight (dToF) / TCSPC measurement::
lambda_k = signal_photons * P(pulse in bin k) + ambient_photons / bins
N_k ~ Poisson(lambda_k)
where the pulse is a Gaussian of full width at half maximum *irf_fwhm_ps*
centred at the round-trip time `t0 = 2*distance_m/c, and `P(pulse in bin
k)`` is its exact integral over the bin (an erf difference, not a
midpoint sample) — so with `noise=False` the returned histogram is an
analytic ground truth, not an approximation of one. *ambient_photons* is the
total background (sunlight, dark counts) spread uniformly over the window.
`noise=False returns lambda_k itself (no sampling); noise=True`
draws one Poisson realisation from `numpy.random.default_rng(seed)`.
Returns a float64 1-D histogram of length *bins*. The unambiguous range is
`c * bins * bin_ps / 2` — 3.84 m at the defaults (256 bins x 100 ps), with
a bin resolution of 1.50 cm.
The pulse is not renormalised to the window: a target near the far edge
genuinely loses the tail of its pulse, exactly as a real sensor does, and the
total signal comes back slightly below *signal_photons*. Renormalising would
have made the truncated pulse asymmetric and biased its centroid.
Raises `ValueError`: a non-positive *distance_m*, a *bins* outside
`[2, MAX_BINS]`, a non-positive *bin_ps* / *irf_fwhm_ps*, negative photon
budgets, a non-integer or negative *seed*, a non-bool *noise*, and — instead
of wrapping the pulse silently to a short distance — a *distance_m* whose
round-trip time falls outside the `bins * bin_ps` window.
• 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_dtof_ranging — py -3.11 examples/poc_dtof_ranging.py
counts as input)tcspc_coates_correct · tcspc_irf_convolve · tcspc_background_subtract · tcspc_stats · dtof_depth · lifetime_fit · lifetime_phasor
tcspc)tcspc_irf_convolve · tcspc_background_subtract · tcspc_stats
*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.