Add --persistence-spots, a second parameter-free detector alongside --adaptive-spots.
Instead of a hard per-ring threshold it builds the noise-normalised image
z = (I - ring_mean) / sqrt(ring_sigma^2 + read^2) (same per-ring background as the
hard variant) and scores every intensity maximum by its 0-D topological persistence:
sweeping the height from high to low, each maximum is born and, when its basin meets
a taller one at a saddle, dies with persistence = birth - saddle, in sigma. A lone
noise spike merges into the background almost immediately (persistence ~1 sigma); a
real peak stands many sigma proud. Emitting maxima whose persistence clears the same
z(E) significance bar needs no photon threshold and no min-pix, and it deblends
touching peaks (each keeps its own maximum). Implemented with the same union-find
idiom as the connected-component labeller.
On serial stills this auto-adapts with no per-dataset tuning like --adaptive-spots,
finding fewer but cleaner (deblended) spots; the hard-threshold variant remains more
sensitive on the very weakest data. Both share the per-ring background and read-noise
floor. comp_of is allocated lazily so the default and hard-adaptive paths pay nothing.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The offline CPU spot finder marks a pixel strong when it clears a fixed photon
count AND a local-window SNR. The fixed photon floor forces per-dataset tuning:
its sweet spot tracks the background level (weak sets want a low threshold,
strong or high-background sets a high one) and the usable window is narrow, so
users hand-tune --spot-threshold/--spot-sigma per dataset.
Add an opt-in --adaptive-spots mode (AdaptiveSpotFinderCPU) that replaces the
fixed floor with a per-resolution-ring threshold derived from each image's own
noise. Per ring it computes a peak-excluded background mean and sigma (one plain
pass + two sigma-clip passes over the assembled photon image, binned by the
azimuthal-integration ring index) and sets
thr = max( PoissonTail(mean, p), mean + z * sqrt(sigma^2 + read^2) )
with p = false_pixels_per_frame / n_pixels the single portable knob (default
100) and z = Phi^-1(1 - p). The Poisson arm is the correct significance where
the background is countable (it carries the sqrt(mean) shot noise, so a bright
low-resolution ring gets a high threshold); the read-noise-floored Gaussian arm
keeps the threshold physical where the background vanishes (empty high-resolution
rings), without which those rings flood. read is a detector-level constant, not
a per-dataset knob. Both arms are needed: Poisson alone floods near-zero
background, Gaussian alone drops the shot-noise term and under-thresholds bright
rings.
One --adaptive-spots setting then adapts across a wide range of serial datasets
with no per-dataset threshold, matching or beating hand-tuned thresholds and the
peakfinder8/xgandalf reference on both weak large-cell and strong serial data,
with equal merged R-free.
The finder runs on the CPU (offline/viewer path) and reads the host image, which
the GPU pipeline already keeps in sync, so it works in either build. The default
(non-adaptive) path and the online/FPGA path are unchanged.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
leonarski_fandClaude Opus 4.8