dtof opcounts → measurementimport fullseye as fs; fs.ledger.dtof_depth(hist, bin_ps=100.0, mode='peak', offset_ps=0.0, subtract_background=False) (実装を直接呼ぶなら import photoncount; photoncount.dtof_depth(hist, bin_ps=100.0, mode='peak', offset_ps=0.0, subtract_background=False)、台帳から引くなら opsphoton.get("dtof_depth"))Distance from a photon arrival-time histogram: d = c*t/2.
Direct time-of-flight. The light travels to the target and back, so the one-way distance is half the round-trip time times the speed of light. bin_ps is the width of one time bin (a 100 ps bin is 1.50 cm of depth).
Four estimators, from crudest to sharpest:
"peak" — the centre of the fullest bin. Quantised to the bin grid;
the error is uniform in +-half a bin (+-0.75 cm at 100 ps)."centroid" — the first moment of the whole histogram. Exact for a
symmetric pulse with no background, and badly biased toward the middle
of the window with one — pass subtract_background=True."parabolic" — a parabola through the peak bin and its two neighbours.
Sub-bin, cheap, and biased for a Gaussian pulse."gaussian" — the same parabola fitted to the log of those three
samples, which is the exact vertex for a Gaussian pulse.Measured on a noiseless simulated return at 2.4371 m (256 bins x 100 ps,
500 ps IRF), absolute error: peak 1.29 mm, centroid 4.4e-16 m,
parabolic 0.067 mm, gaussian 9.4e-9 m — three orders of magnitude
between the crudest and the sharpest.
With Poisson noise (200 signal + 200 ambient photons, seed 0) the same
four give 13.7 mm, 146.5 mm (with subtract_background=True), 8.5 mm and
8.0 mm. Two honest readings of that: once shot noise dominates the sub-bin
estimators buy about 1.6x, not three orders of magnitude, and the centroid
collapses because a median-subtracted ambient floor still leaves noise
across the whole window that drags the first moment toward the centre. Use
"gaussian" or "parabolic" on noisy data; use "centroid" only when
the background is genuinely gone.
offset_ps is a system delay to remove: t_flight = t_measured -
offset_ps, so a positive offset makes the answer closer. Returns the
distance in metres as a float.
Raises ValueError: negative, non-finite, non-1-D or all-zero hist,
a non-positive bin_ps, an unknown mode, a non-finite offset_ps, a
flat histogram in a peak-based mode (argmax would silently pick bin 0
and report the first bin’s depth), a peak in the first or last bin with a
sub-bin mode (there is no neighbour to fit to — use "peak"), a
degenerate three-sample fit, and — instead of returning a negative distance —
an offset_ps larger than the measured arrival time.
py -3.11 examples/photon_timeresolved.pypy -3.11 examples/poc_dtof_ranging.pymeasurement を入力に取れる)—
dtof)dtof_cube_simulate · dtof_cube_depth
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.