v1.0.0-rc.173 (#83)

* jfjoch_broker: Optional per-dataset authentication - statistics, images and plots can require a bearer token, which jfjoch_viewer supports.
* jfjoch_viewer: Dark mode and a theme-matched colour scheme, a magnifier panel, and simpler contrast and background controls.
* Rugnux: Multiple performance improvements on GPU and CPU (CPU-only processing up to 40% faster, faster image decoding on ARM), with unchanged results.
* Rugnux: `--model` rigid-body refinement runs on the GPU, and the model-validation check is faster and more reliable.
* Rugnux: Improved scaling and merging - error model, outlier rejection, absorption correction and French-Wilson amplitudes now agree more closely with XDS and ctruncate.
* Rugnux: Improved integration - radial background on powder and ice rings, crowded rotation data keep their reflections, and CPU-only builds integrate large unit cells as GPU builds do.
* Rugnux: More robust detector geometry - measured beam centre, X-ray bandwidth and goniometer rate, and geometry refinement accepted only on significant evidence.
* Rugnux: Merged files are written in the standard setting, or in the setting of a reference MTZ, structure-factor mmCIF or model, with its free-R flags.
* Rugnux: Richer report - ice and powder rings, further lattices, superstructure candidates and mosaicity, with warnings worded as prompts to check.
* Rugnux: Clear error messages when a data set needs more GPU or host memory than is available.

Reviewed-on: #83
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>

image_analysis/bragg_integration/BraggIntegrationEngine.cpp

@@ -27,15 +27,7 @@ double parallax_var_px2(const std::string &material, double thickness_um, double
     if (!(thickness_um > 0.0) || !(pixel_um > 0.0) || !(lambda_A > 0.0))
         return 0.0;
     const double L = sensor_absorption::AttenuationLength_um(material, lambda_A);
-    if (!(L > 0.0))
-        return 0.0;
-    const double a = thickness_um / L, e = std::exp(-a);
-    if (1.0 - e <= 0.0)
-        return 0.0;
-    const double mean = L * (1.0 - (1.0 + a) * e) / (1.0 - e);
-    const double ez2 = L * L * (2.0 - (a * a + 2.0 * a + 2.0) * e) / (1.0 - e);
-    const double var = std::max(0.0, ez2 - mean * mean);     // um^2
-    return var / (pixel_um * pixel_um);
+    return sensor_absorption::ConversionDepthVariance_um2(L, thickness_um) / (pixel_um * pixel_um);
 }
 
 // The radial-offset kernels below are a pure function of these six numbers, and one engine is built
@@ -236,6 +228,8 @@ std::vector<Reflection> BraggIntegrationEngine::Finalize(const std::vector<Refle
             refl.observed_x = fr.observed_x;
             refl.observed_y = fr.observed_y;
         }
+        // has_observed is set only for a signal disk every pixel of which was readable.
+        refl.clipped = !fr.has_observed;
         refl.observed = true;
         if (polarization)
             refl.prescaling_corr /= geom.CalcAzIntPolarizationCorr(refl.predicted_x, refl.predicted_y, polarization.value());