image_analysis: compute ROI statistics in the non-FPGA path

MXAnalysisWithoutFPGA never filled DataMessage.roi, so ROI integrals were
only available on the FPGA path. Add a software ROI engine that mirrors the
FPGA roi_calc kernel: per-ROI sum, sum of squares, good-pixel count, max and
intensity-weighted centre of mass, with each pixel carrying a 16-bit mask so
it can contribute to any subset of up to 16 ROIs.

New image_analysis/roi/ library (JFJochROIIntegration), structured like azint:
a base that precomputes the per-pixel mask and names, a templated CPU engine
(generic over pixel type for a future 16-bit path), and a GPU kernel using
per-block shared-memory atomics for the STXM case (half-detector ROIs).

Masked pixels are excluded entirely; saturated pixels are excluded from the
sums but still count towards the max, matching roi_calc exactly. The engine is
only constructed when at least one ROI is defined. Downstream CBOR/HDF5 already
consume message.roi, so no further changes are needed.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

image_analysis/MXAnalysisWithoutFPGA.cpp

@@ -11,9 +11,11 @@
 #include "image_preprocessing/ImagePreprocessorCPU.h"
 
 #include "azint/AzIntEngineCPU.h"
+#include "roi/ROIIntegrationCPU.h"
 #include "spot_finding/ImageSpotFinderCPU.h"
 #ifdef JFJOCH_USE_CUDA
 #include "azint/AzIntEngineGPU.h"
+#include "roi/ROIIntegrationGPU.h"
 #include "spot_finding/ImageSpotFinderGPU.h"
 #include "image_preprocessing/ImagePreprocessorGPU.h"
 #include "image_preprocessing/ImagePreprocessorBufferGPU.h"
@@ -42,6 +44,8 @@ MXAnalysisWithoutFPGA::MXAnalysisWithoutFPGA(const DiffractionExperiment &in_exp
         spotFinder = std::make_unique<ImageSpotFinderCPU>(experiment.GetXPixelsNum(), experiment.GetYPixelsNum());
         azint = std::make_unique<AzIntEngineCPU>(integration);
         preprocessor = std::make_unique<ImagePreprocessorCPU>(in_experiment, in_mask);
+        if (experiment.ROI().size() >= 1)
+            roi = std::make_unique<ROIIntegrationCPU>(experiment);
 #ifdef JFJOCH_USE_CUDA
     } else {
         auto stream = std::make_shared<CudaStream>();
@@ -49,6 +53,8 @@ MXAnalysisWithoutFPGA::MXAnalysisWithoutFPGA(const DiffractionExperiment &in_exp
         preprocessor = std::make_unique<ImagePreprocessorGPU>(in_experiment, in_mask, stream);
         spotFinder = std::make_unique<ImageSpotFinderGPU>(experiment.GetXPixelsNum(), experiment.GetYPixelsNum(), stream);
         azint = std::make_unique<AzIntEngineGPU>(integration, stream);
+        if (experiment.ROI().size() >= 1)
+            roi = std::make_unique<ROIIntegrationGPU>(experiment, stream);
     }
 #endif
 }
@@ -77,6 +83,9 @@ void MXAnalysisWithoutFPGA::Analyze(DataMessage &output,
     const auto azint_end_time = std::chrono::steady_clock::now();
     output.azint_time_s = std::chrono::duration<float>(azint_end_time - azint_start_time).count();
 
+    if (roi)
+        roi->Run(*preprocessor_buffer, output.roi);
+
     if (spot_finding_settings.enable) {
         // Update resolution mask
         if (mask_high_res != spot_finding_settings.high_resolution_limit