adaptive-spot-finding
3
Commits
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0e23fd3ab9 |
Bragg integration: propagate the background-estimate uncertainty, add an opt-in radial background correction
Two independent pieces in the same code path. The background-estimate variance was never propagated. A reflection's background comes from a finite ring of n_b pixels, so subtracting it adds var(B)/n_b per signal pixel - sqrt(1 + n_d/n_b) = 1.109 with the shipped stencil. Both engines omitted it, which is exactly the 1.11-1.19 gap measured between the off-ring scatter and the reported sigma. Three lines each; it affects every dataset, not only iced ones. The radial correction is new and OFF by default (--background-radial). The signal disk and the background ring are concentric, so for any background LINEAR in position <B>_ann == <B>_disk identically and a plane fit buys nothing; the leading error is the CURVATURE of the radial background, which on a sharp ice ring reaches +26 counts on a single reflection. Since every reflection uses the same stencil, that error is a fixed kernel over radial offset - one short dot product per reflection and no extra pixel reads. Validated on empty apertures before any C++: mean |bias| over 9 bands / 3 crystals 4.33 -> 0.79 counts with the scatter unchanged. Three things it cost a battery each to learn, all now in the code: - the radial curve must be accumulated from CLIPPED annulus pixels, inside the clip pass, or it carries neighbour tails and zingers (so it is inert under --integrator boxsum, which has no clip pass); - the GPU version was a 1.8x slowdown from atomicAdd contention on a small radial array - staged in shared memory per block it now costs nothing measurable; - it is battery-NEUTRAL as a default, because the reflections whose bias it fixes are the ones the ice handling already excludes. Hence off by default. CPU/GPU parity extended with two radial sections: 9002 assertions. Also fixes a latent French-Wilson quadrature collapse: j_max = I + 8 sigma on a fixed 400-point grid degenerates to a single cell once sigma >> 50 <I>, giving F = 0.1 sqrt(sigma) with sigmaF -> 0. Harmless today, but any sigma-inflation scheme detonates it. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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09fb8e0306 |
Bragg integration: clip the background ring high side instead of trimming it
The r2..r3 background ring was averaged with a 10% SYMMETRIC trimmed mean. A symmetric trim is not a consistent estimator of the mean of a right-skewed (Poisson) sample: on a clean Poisson ring it sits ~0.1 ct/px BELOW the true mean at every level, and with ~50 signal pixels in the r1 disk that under-subtraction adds ~5 counts to every partial on every frame. Measured two independent ways on four rotation datasets - stored background_mean against a plain ring mean over the same pixels on reflection-free frames, and directly on apertures that provably hold no reflection. Empty-aperture pedestal, counts: plain mean -0.03..-0.20, 10% symmetric trim +5.05..+6.34, 4 sigma clip +0.02..+0.54. Replace it with a high-side-only sigma clip at mean + n*sqrt(mean), n = 4 for monochromatic data. It rejects the same one-sided contamination the trim was there for - better, in fact: a 40 px neighbour core at +100 ct shifts the trim by +10.1 ct/px, because a symmetric trim collapses once contamination exceeds ~10% of the ring, versus +0.009 ct/px at 4 sigma. False rejection on a clean ring is 0.04-0.39%. Broadband data keep their tuned 3 sigma clip unchanged. The trim stays reachable with --background-trim for back compatibility; setting either estimator clears the other, so they can never stack. --integrator boxsum does not take the clip (matching what the shipped clip already did), so it now uses the plain ring mean unless --background-trim is given. The intensities get measurably more accurate: per-shell agreement with an independent processing of the same images improves on 14 of 16 crystals (weighted -0.0347, outermost shell 12/4), the outermost-shell R_meas NUMERATOR - absolute scatter, not a denominator effect - falls 13.5% median on 16/5, and CC1/2 in the outer shell improves on 14/7. EXPECT <I/sigma> TO FALL AND EDGE R_meas TO RISE. Both are inflated by information-free counts, so both get worse when the bias is removed; neither is evidence against this change. That fingerprint is exactly how the trimmed mean was accepted in the first place. Known cost: over the 37-crystal rotation battery the de-novo space-group count goes 34 OK / 3 DIFF to 33 / 4. The single regression is a two-lattice crystal whose merge fails the absolute-sanity gate under either background (R_meas 63.5%, CC1/2 72.2%) and which carries an unresolved indexing ambiguity on the very operator being scored, so its operator CC is diluted by construction. No other crystal changes space group, and twin protection is not weakened - the H-ratio veto that refuses genuinely twinned crystals gets MORE decisive (1.63 -> 1.84, 2.83 -> 3.99). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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d6389e12da |
v1.0.0-rc.156 (#66)
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This is an UNSTABLE release. It includes many experimental features, as well as many AI generated fixes. We recommend using rc.152 for production use. * jfjoch_process: Major rotation (rot3d) data processing overhaul - robust profile-fit integration, Cauchy-loss scaling with optional absorption surface, de-novo indexing and space-group/centering determination fixes, and merging statistics + ISa in the mmCIF output. * jfjoch_process: Add EXPERIMENTAL ice-ring detection (--detect-ice-rings) that excludes ice reflections from scaling. * Compression: Add BSHUF_ZSTD_RLE_HUFF, make compression size-aware (drop frames that don't fit rather than aborting), and add the jfjoch_recompress tool. * jfjoch_viewer: Report "Multiple lattices detected" and grey out "Analyze dataset" on a live connection. * jfjoch_broker: Write smargon chi/phi goniometer positions to NXmx; read sensor thickness/material from HDF5 metadata. * CI: Build Windows (CUDA and non-CUDA) installers.Reviewed-on: #66 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch> |