v1.0.0-rc.166 (#76)

* `rugnux --mode calibration` writes `<prefix>.json` beside the `.poni`, whose `dataset_settings` member is a `jfjoch_broker` `dataset_settings` body as it stands.
* `rugnux` and `jfjoch_viewer` read PILATUS miniCBF sweeps natively, without conversion.
* Masters written by other facilities open, including Eiger 1.x and third-party NXmx variants.
* `rugnux` measures the beam centre on every run, and indexes with it when the file's value indexes nothing.
* A detector swung out on a 2theta arm is placed where the file says it stands, and the calibration can hold the tilt fixed.
* `rugnux` writes the unmerged MTZ by default, and a P1 merge beside it, so a wrong space group can be re-merged without reprocessing.
* Significant improvements to symmetry handling in `rugnux`: the lattice, the point group, the setting and the systematic absences.
* The `rugnux` report gives the resolution the CC1/2 fit reached, beside the range the reflections were written to.
* The `rugnux` report gives the twinning statistics measured before the space group was decided, beside the ones measured after.
* The `rugnux` report gives the strong-direction diffraction limit, and warns when CC1/2 is not monotone with resolution.
* `rugnux` ranks screw axes on the evidence their absences carry, rather than on how many control reflections a candidate happens to have.
* Twinning is no longer reported when the L-test contradicts it.
* The `rugnux` report gives the detector tilt, the measured tilt and the direct beam beside the beam centre, and a post-refined beam centre is judged against the run's own measurement rather than the file's.
* `--no-refine-tilt` holds the detector tilt at the value in the file, instead of zeroing it, when the calibration starts from the spots.
* The `jfjoch_viewer` grid scan view draws the cells in the proportion of the scan steps, so the map has the shape of the scanned area.

Reviewed-on: #76
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>

tests/AdaptiveThresholdTest.cpp

@@ -51,7 +51,7 @@ TEST_CASE("AdaptiveThreshold_PoissonThreshold", "[SpotFinding]") {
     const float z = static_cast<float>(NormalQuantile(1.0 - p));
 
     // The defining property: the returned count is the SMALLEST whose upper tail is within p.
-    for (const double mu: {1e-6, 0.1, 1.0, 3.0, 10.0, 40.0}) {
+    for (const double mu: {1e-6, 0.1, 1.0, 3.0, 10.0, 40.0, 60.0, 120.0}) {
         const int thr = static_cast<int>(PoissonThreshold(mu, p, z));
         CHECK(PoissonUpperTail(mu, thr) <= p);
         CHECK(PoissonUpperTail(mu, thr - 1) > p);
@@ -65,8 +65,19 @@ TEST_CASE("AdaptiveThreshold_PoissonThreshold", "[SpotFinding]") {
         prev = thr;
     }
 
-    // Above mu = 50 it short-circuits to the Gaussian form mu + z sqrt(mu).
-    CHECK(PoissonThreshold(100.0, p, z) == Catch::Approx(100.0 + z * 10.0).epsilon(1e-5));
+    // Above the summation limit the Cornish-Fisher form takes over, and it has to stay a POISSON
+    // quantile: the skewness term (z^2-1)/6 is what a plain mu + z*sqrt(mu) leaves out, and at this
+    // z the Gaussian form alone lets through several times the tail asked for.
+    for (const double mu: {250.0, 400.0}) {
+        const float thr = PoissonThreshold(mu, p, z);
+        CHECK(thr > mu + z * std::sqrt(mu));
+        CHECK(PoissonUpperTail(mu, static_cast<int>(thr)) <= 2 * p);
+        CHECK(PoissonUpperTail(mu, static_cast<int>(mu + z * std::sqrt(mu))) > 2 * p);
+    }
+
+    // And it joins the exact quantile smoothly at the switch - no step for a ring whose background
+    // drifts across it from frame to frame.
+    CHECK(std::fabs(PoissonThreshold(200.5, p, z) - PoissonThreshold(199.5, p, z)) < 2.0f);
 
     // A tighter operating point (smaller p) can only raise the threshold.
     CHECK(PoissonThreshold(5.0, 1e-8, static_cast<float>(NormalQuantile(1.0 - 1e-8)))