dtof opdepth → histcubeimport fullseye as fs; fs.ledger.dtof_cube_simulate(depth, bins=256, bin_ps=100.0, reflectivity=None, signal_photons=20.0, ambient_photons=5.0, irf_fwhm_ps=200.0, seed=0, noise=True) (実装を直接呼ぶなら import photoncount; photoncount.dtof_cube_simulate(depth, bins=256, bin_ps=100.0, reflectivity=None, signal_photons=20.0, ambient_photons=5.0, irf_fwhm_ps=200.0, seed=0, noise=True)、台帳から引くなら opsphoton.get("dtof_cube_simulate"))Synthesise the (H, W, T) photon histogram cube a SPAD array produces.
The per-pixel version of :func:tcspc_simulate: every pixel of the depth
map (metres, one-way distance) gets a Gaussian return at its own round-trip
time 2d/c, scaled by signal_photons times that pixel’s reflectivity,
on a uniform ambient pedestal of ambient_photons/bins per bin, Poisson
sampled with numpy.random.default_rng(seed).
The output is the cube that :func:dtof_cube_depth inverts, and the axis
order is (H, W, T) with time LAST — the same layout a SPAD array streams.
That is not the (D, H, W) of a :mod:volops voxel volume; the two are
both 3-D float arrays and swapping them silently produces a plausible-wrong
depth map, which is why :func:dtof_cube_depth checks and says so.
noise=False returns the exact expectation cube (no sampling).
Ground truth: with noise=False the per-pixel centroid of the cube returns
the input depth map to an RMS error of 3.2e-16 m (pinned in the tests) — the
pulse integral is analytic, so the only error is float round-off.
Raises ValueError: a non-2-D, non-finite or non-positive depth, a
reflectivity that is negative or not the same shape as depth, a bins
outside [2, MAX_BINS], non-positive bin_ps / irf_fwhm_ps, negative
photon budgets, a non-integer seed, a cube over
:data:MAX_CUBE_ELEMENTS (H*W*bins grows fast — 512x512x256 is 8x the
cap), and any depth whose round-trip time falls outside the time window
(which a real sensor would alias into a short distance).
py -3.11 examples/photon_timeresolved.pypy -3.11 examples/poc_dtof_ranging.pyhistcube を入力に取れる)dtof)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.