Panel layout stage 3: per-panel spot finding (CPU+GPU, CCL) and raster algorithms on the plane raster

Spot finding works panel by panel, as the FPGA path does per JUNGFRAU module. PanelBoxes (common/) gives
one box per DetectorModule; an empty table gives one box, the whole image, so every clamp reduces to the
old image bounds in the same evaluation order (rotation sets, EIGER, CCDs, our JUNGFRAU unchanged).
- ImageSpotFinder::SetPanels: the CPU local-box pass (dense, count-threshold and the DetectAt/candidate
  path of the adaptive finder) slides its windows inside each panel box; host CCL labels panel by panel;
  pixels on no panel are folded into the resolution mask.
- GPU: analyze_pixel tiles each panel (warps numbered panel after panel), analyze_candidates and
  union_neighbours clip to the pixel's panel, the device spot carries its panel; the GPU list is put in
  panel order so it equals the host's.
- DiffractionSpot carries its panel; SpotAnalyze maps by ImageToPlane(panel, ...) (d_A on the plane).
- ImagePreprocessorBuffer::GatherTiles (CPU+GPU) clips each square to the panel of its centre.
- MXAnalysisWithoutFPGA and the pre-scan workers hand the module table to finders and buffers.

Raster algorithms: new common/AssembleToPlane.h (PlaneRasterOf, AssembleToPlane nearest-pixel gather with
gaps, GatherFromPlane back to stored pixels; empty table = copy). With panels, ShadowFinder::GetMask runs on
the projection assembled to the plane raster and gathers the mask back per stored pixel (CPU route);
FindBeamCenterFFT scores the assembled projection and reports plane coordinates; the detector diagnostic
JPEG shows the assembled plane. Without panels all three take their old path.

Harness: PanelLayout_SpotsNeverCrossPanels enabled (count threshold and SNR on the edge scene), new
PanelLayout_SpotFinderParity (CPU vs GPU, local box and adaptive, on the stacked layout),
PanelLayout_AssembleToPlane, PanelLayout_ShadowFinder, PanelLayout_BeamCenterFFT,
PanelLayout_DetectorDiagnostic (stacked vs assembled image cut to the raster).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu

image_analysis/spot_finding/SpotUtils.cpp

@@ -372,12 +372,12 @@ void SpotAnalyze(const DiffractionExperiment &experiment,
 
     std::vector<SpotToSave> spots_out;
 
-    // A spot is found on the image; from here on it is where its module puts it on the detector plane.
+    // A spot is found on the image; from here on it is where its panel puts it on the detector plane.
     const auto &modules = experiment.GetModules();
     for (const auto &spot: spots) {
         if (auto s = spot.Export(geom, output.number); s.has_value()) {
             if (!modules.empty()) {
-                const auto [px, py] = modules.ImageToPlane(s->x, s->y);
+                const auto [px, py] = modules.ImageToPlane(spot.Panel(), s->x, s->y);
                 s->x = static_cast<float>(px);
                 s->y = static_cast<float>(py);
                 s->d_A = geom.PxlToRes(s->x, s->y);