Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01D1G8gJVAy6gp1K5Dz3NE5C # Conflicts: # docs/CHANGELOG.md
436 lines
20 KiB
C++
436 lines
20 KiB
C++
// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
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// SPDX-License-Identifier: GPL-3.0-only
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#include <catch2/catch_all.hpp>
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#include <cmath>
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#include <filesystem>
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#include "../common/DiffractionExperiment.h"
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#include "../common/ScanResultGenerator.h"
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#include "../writer/FileWriter.h"
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#include "../reader/JFJochHDF5Reader.h"
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#include "../rugnux/Rugnux.h"
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#include "../rugnux/RugnuxCommandLine.h"
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#include "../rugnux/SpotWidth.h"
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#include "../image_analysis/geom_refinement/Calibrants.h"
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namespace {
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// Write a small VDS dataset of `n` flat images and return nothing (prefix_master.h5 +
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// prefix_data_000001.h5 land in the test working directory).
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void WriteTestDataset(const std::string &prefix, int n) {
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RegisterHDF5Filter();
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DiffractionExperiment x(DetJF(1));
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x.FilePrefix(prefix).ImagesPerTrigger(n).OverwriteExistingFiles(true);
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x.BitDepthImage(16).ImagesPerFile(n).SetFileWriterFormat(FileWriterFormat::NXmxVDS).PixelSigned(true);
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x.Compression(CompressionAlgorithm::NO_COMPRESSION);
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x.BeamX_pxl(512).BeamY_pxl(256).DetectorDistance_mm(150).IncidentEnergy_keV(WVL_1A_IN_KEV)
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.FrameTime(std::chrono::microseconds(500), std::chrono::microseconds(10));
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std::vector<int16_t> image(x.GetPixelsNum(), 5);
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StartMessage start_message;
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x.FillMessage(start_message);
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FileWriter file_set(start_message);
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ScanResultGenerator generator(x);
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for (int i = 0; i < n; i++) {
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DataMessage message{};
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message.image = CompressedImage(image, x.GetXPixelsNum(), x.GetYPixelsNum());
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message.number = i;
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REQUIRE_NOTHROW(file_set.WriteHDF5(message));
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generator.Add(message);
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}
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EndMessage end_message;
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end_message.max_image_number = n;
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generator.FillEndMessage(end_message);
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file_set.WriteHDF5(end_message);
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file_set.Finalize();
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}
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}
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TEST_CASE("Rugnux_AzInt", "[HDF5][Full]") {
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WriteTestDataset("process_azint_in", 8);
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JFJochHDF5Reader reader;
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REQUIRE_NOTHROW(reader.ReadFile("process_azint_in_master.h5"));
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auto dataset = reader.GetDataset();
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REQUIRE(dataset);
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ProcessConfig config;
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config.mode = ProcessMode::AzimuthalIntegration;
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config.nthreads = 2;
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config.output_prefix = "process_azint_out";
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Rugnux process(reader, dataset->experiment, *dataset->pixel_mask, config);
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ProcessResult result;
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REQUIRE_NOTHROW(result = process.Run());
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CHECK_FALSE(result.cancelled);
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CHECK(result.images_processed == 8);
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REQUIRE(result.written_master_path.has_value());
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{
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// The _process.h5 links back to the source images and carries an azimuthal profile per image.
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JFJochHDF5Reader out;
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REQUIRE_NOTHROW(out.ReadFile("process_azint_out_process.h5"));
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CHECK(out.GetNumberOfImages() == 8);
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std::shared_ptr<JFJochReaderImage> img;
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REQUIRE_NOTHROW(img = out.LoadImage(0));
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REQUIRE(img);
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CHECK_FALSE(img->ImageData().az_int_profile.empty());
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}
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reader.Close();
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remove("process_azint_in_master.h5");
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remove("process_azint_in_data_000001.h5");
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remove("process_azint_out_process.h5");
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REQUIRE(H5Fget_obj_count(H5F_OBJ_ALL, H5F_OBJ_ALL) == 0);
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}
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TEST_CASE("Rugnux_NoOutput", "[HDF5][Full]") {
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WriteTestDataset("process_noout_in", 6);
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JFJochHDF5Reader reader;
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REQUIRE_NOTHROW(reader.ReadFile("process_noout_in_master.h5"));
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auto dataset = reader.GetDataset();
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// Empty output prefix => process without writing any file.
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ProcessConfig config;
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config.mode = ProcessMode::AzimuthalIntegration;
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config.nthreads = 3;
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Rugnux process(reader, dataset->experiment, *dataset->pixel_mask, config);
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auto result = process.Run();
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CHECK_FALSE(result.cancelled);
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CHECK(result.images_processed == 6);
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CHECK_FALSE(result.written_master_path.has_value());
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reader.Close();
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remove("process_noout_in_master.h5");
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remove("process_noout_in_data_000001.h5");
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REQUIRE(H5Fget_obj_count(H5F_OBJ_ALL, H5F_OBJ_ALL) == 0);
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}
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TEST_CASE("Rugnux_Cancel", "[HDF5][Full]") {
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WriteTestDataset("process_cancel_in", 8);
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JFJochHDF5Reader reader;
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REQUIRE_NOTHROW(reader.ReadFile("process_cancel_in_master.h5"));
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auto dataset = reader.GetDataset();
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ProcessConfig config;
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config.mode = ProcessMode::AzimuthalIntegration;
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config.nthreads = 2;
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Rugnux process(reader, dataset->experiment, *dataset->pixel_mask, config);
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process.Cancel(); // cancel before running: the worker loop stops immediately
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auto result = process.Run();
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CHECK(result.cancelled);
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CHECK(result.images_processed == 0);
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CHECK_FALSE(result.written_master_path.has_value());
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reader.Close();
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remove("process_cancel_in_master.h5");
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remove("process_cancel_in_data_000001.h5");
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REQUIRE(H5Fget_obj_count(H5F_OBJ_ALL, H5F_OBJ_ALL) == 0);
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}
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// A calibration re-integrates its images binned about the geometry it fitted, and fits again. That
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// second profile must be the sum over every image: here each of six frames carries a different sixth
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// of the LaB6 rings, so a profile missing a frame is missing rings. The header's beam centre is 5 px
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// out, far enough that the first pass's smeared profile loses to the re-binned one - so the geometry
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// that comes out is the one fitted on the re-binned sum, and it must not depend on the thread count.
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TEST_CASE("Rugnux_CalibrationRebinsEveryImage", "[HDF5][DetGeomCalib]") {
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RegisterHDF5Filter();
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constexpr int n = 6;
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constexpr float true_beam_x = 1090.0f, true_beam_y = 1100.0f;
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const std::vector<float> rings_q = CalibrantRings("lab6");
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DiffractionExperiment x(DetJF4M());
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x.FilePrefix("process_calib_in").ImagesPerTrigger(n).OverwriteExistingFiles(true);
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x.BitDepthImage(16).ImagesPerFile(n).SetFileWriterFormat(FileWriterFormat::NXmxVDS).PixelSigned(true);
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x.Compression(CompressionAlgorithm::NO_COMPRESSION);
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x.BeamX_pxl(true_beam_x).BeamY_pxl(true_beam_y).DetectorDistance_mm(100).IncidentEnergy_keV(WVL_1A_IN_KEV)
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.FrameTime(std::chrono::microseconds(500), std::chrono::microseconds(10));
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const DiffractionGeometry geom_true = x.GetDiffractionGeometry();
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x.BeamX_pxl(true_beam_x + 5.0f); // what the header says
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// Radii of the rings the beam reaches, in pixels about the true centre.
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std::vector<float> ring_radius;
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for (const float q : rings_q) {
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const float d = static_cast<float>(2.0 * PI) / q;
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if (d > geom_true.GetWavelength_A() / 2.0f)
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ring_radius.push_back(geom_true.ResToPxl(d));
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}
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{
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StartMessage start_message;
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x.FillMessage(start_message);
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FileWriter file_set(start_message);
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ScanResultGenerator generator(x);
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std::vector<int16_t> image(x.GetPixelsNum());
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for (int i = 0; i < n; i++) {
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for (int64_t p = 0; p < x.GetPixelsNum(); p++) {
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const float px = static_cast<float>(p % x.GetXPixelsNum());
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const float py = static_cast<float>(p / x.GetXPixelsNum());
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const float r = std::hypot(px - true_beam_x, py - true_beam_y);
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float v = 5.0f;
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for (size_t k = i; k < ring_radius.size(); k += n) {
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const float dr = r - ring_radius[k];
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v += 400.0f * std::exp(-0.5f * dr * dr / (1.5f * 1.5f));
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}
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image[p] = static_cast<int16_t>(std::lround(v));
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}
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DataMessage message{};
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message.image = CompressedImage(image, x.GetXPixelsNum(), x.GetYPixelsNum());
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message.number = i;
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REQUIRE_NOTHROW(file_set.WriteHDF5(message));
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generator.Add(message);
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}
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EndMessage end_message;
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end_message.max_image_number = n;
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generator.FillEndMessage(end_message);
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file_set.WriteHDF5(end_message);
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file_set.Finalize();
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}
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JFJochHDF5Reader reader;
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REQUIRE_NOTHROW(reader.ReadFile("process_calib_in_master.h5"));
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auto dataset = reader.GetDataset();
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REQUIRE(dataset);
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DiffractionExperiment experiment(dataset->experiment);
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auto azint = experiment.GetAzimuthalIntegrationSettings();
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azint.AzimuthalBinCount(32);
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experiment.ImportAzimuthalIntegrationSettings(azint);
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std::vector<CalibrationResult> results;
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for (const int nthreads : {1, 4}) {
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ProcessConfig config;
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config.mode = ProcessMode::Calibration;
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config.calibrant_ring_q = rings_q;
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config.nthreads = nthreads;
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config.write_process_h5 = false;
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config.beam_center_check = false;
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config.spot_finding = DiffractionExperiment::DefaultDataProcessingSettings();
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config.spot_finding.indexing = false;
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Rugnux process(reader, experiment, *dataset->pixel_mask, config);
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ProcessResult result;
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REQUIRE_NOTHROW(result = process.Run());
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REQUIRE(result.calibration.has_value());
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results.push_back(*result.calibration);
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}
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for (const auto &cal : results) {
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CHECK(cal.converged);
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CHECK(cal.geometry.GetBeamX_pxl() == Catch::Approx(true_beam_x).margin(0.5));
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CHECK(cal.geometry.GetBeamY_pxl() == Catch::Approx(true_beam_y).margin(0.5));
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}
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CHECK(results[0].ring_points == results[1].ring_points);
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CHECK(results[0].rms_radial_pxl == results[1].rms_radial_pxl);
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CHECK(results[0].geometry.GetBeamX_pxl() == results[1].geometry.GetBeamX_pxl());
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CHECK(results[0].geometry.GetBeamY_pxl() == results[1].geometry.GetBeamY_pxl());
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CHECK(results[0].geometry.GetDetectorDistance_mm() == results[1].geometry.GetDetectorDistance_mm());
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reader.Close();
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remove("process_calib_in_master.h5");
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remove("process_calib_in_data_000001.h5");
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REQUIRE(H5Fget_obj_count(H5F_OBJ_ALL, H5F_OBJ_ALL) == 0);
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}
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TEST_CASE("RugnuxCommandLine_Full", "[process]") {
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DiffractionExperiment x(DetJF(1));
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IndexingSettings idx;
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idx.Algorithm(IndexingAlgorithmEnum::FFT);
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idx.GeomRefinementAlgorithm(GeomRefinementAlgorithmEnum::BeamCenter);
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x.ImportIndexingSettings(idx);
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x.SpaceGroupNumber(96);
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ProcessConfig config;
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config.mode = ProcessMode::FullAnalysis;
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config.nthreads = 8;
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config.output_prefix = "run1";
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config.end_image = 500;
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config.rotation_indexing = true;
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config.two_pass_rotation = true;
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config.rotation_indexing_image_count = 30;
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config.spot_finding = DiffractionExperiment::DefaultDataProcessingSettings();
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const std::string cmd = RugnuxCommandLine(config, x, "/data/test_master.h5");
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CHECK(cmd.rfind("rugnux", 0) == 0);
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CHECK(cmd.find("-N 8") != std::string::npos);
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CHECK(cmd.find("-e 500") != std::string::npos);
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CHECK(cmd.find("-o run1") != std::string::npos);
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CHECK(cmd.find("-X fft") != std::string::npos);
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CHECK(cmd.find("-S 96") != std::string::npos);
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// -R takes an optional argument, so its value must be attached (-R30); a separate "-R 30" token
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// would not re-parse (getopt would leave 30 as a positional and drop the count).
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CHECK(cmd.find("-R30") != std::string::npos);
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CHECK(cmd.find("-R 30") == std::string::npos);
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CHECK(cmd.find("/data/test_master.h5") != std::string::npos);
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}
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TEST_CASE("RugnuxCommandLine_AzInt", "[process]") {
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DiffractionExperiment x(DetJF(1));
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AzimuthalIntegrationSettings a;
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a.AzimuthalBinCount(4);
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x.ImportAzimuthalIntegrationSettings(a);
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ProcessConfig config;
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config.mode = ProcessMode::AzimuthalIntegration;
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config.nthreads = 2;
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config.output_prefix = "az";
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const std::string cmd = RugnuxCommandLine(config, x, "in.h5");
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CHECK(cmd.rfind("rugnux", 0) == 0);
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CHECK(cmd.find("--mode azint") != std::string::npos);
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CHECK(cmd.find("--azim-phi-bins 4") != std::string::npos);
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CHECK(cmd.find("--azim-min-q") != std::string::npos);
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CHECK(cmd.find("in.h5") != std::string::npos);
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}
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namespace {
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// A field of identical round Gaussian spots on three rings, so that the width estimator sees
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// several resolution bands with the same true width and its 1/d fit has to come back flat.
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void PaintGaussianSpots(ImagePreprocessorBuffer &image, int w, double sigma, double total_counts,
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std::vector<DiffractionSpot> &spots) {
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constexpr int BKG = 3;
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for (size_t i = 0; i < image.size(); i++) image[i] = BKG;
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const double amp = total_counts / (2.0 * M_PI * sigma * sigma);
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for (int radius : {150, 350, 550})
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for (int k = 0; k < 20; k++) {
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const double phi = 2.0 * M_PI * k / 20.0 + 0.1 * radius;
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const int cx = static_cast<int>(std::lround(600 + radius * std::cos(phi)));
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const int cy = static_cast<int>(std::lround(600 + radius * std::sin(phi)));
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for (int dy = -14; dy <= 14; dy++)
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for (int dx = -14; dx <= 14; dx++)
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image[static_cast<size_t>(cy + dy) * w + (cx + dx)] +=
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static_cast<int32_t>(std::lround(
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amp * std::exp(-(dx * dx + dy * dy) / (2.0 * sigma * sigma))));
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spots.emplace_back(static_cast<uint32_t>(cx), static_cast<uint32_t>(cy),
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static_cast<int64_t>(total_counts));
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}
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}
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}
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// The width the adaptive integration radius is set from. A round Gaussian of width sigma holds 80 %
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// of its flux inside sqrt(2 ln 5) * sigma = 1.794 * sigma, and that is what the estimator has to
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// return - over an aperture that owes nothing to the integrator's r1, which is the whole point of
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// measuring it here rather than reading the integrator's own second moment.
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TEST_CASE("SpotWidth_Gaussian", "[process]") {
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constexpr int W = 1200, H = 1200;
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DiffractionGeometry geometry;
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geometry.BeamX_pxl(600).BeamY_pxl(600).DetectorDistance_mm(200).PixelSize_mm(0.075)
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.Wavelength_A(1.0);
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for (double sigma : {1.0, 2.2}) {
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ImagePreprocessorBuffer image(static_cast<size_t>(W) * H);
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std::vector<DiffractionSpot> spots;
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PaintGaussianSpots(image, W, sigma, 20000.0, spots);
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std::vector<spot_width::FluxCurve> curves;
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MeasureSpotFluxCurves(image, W, H, geometry, spots, curves);
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REQUIRE(curves.size() >= 45);
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const auto r80 = spot_width::R80AtReference(curves);
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REQUIRE(r80.has_value());
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CHECK(*r80 == Catch::Approx(1.794 * sigma).margin(0.3));
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}
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// The rule the measurement drives: the shipped radius below the line, the capped one above it.
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CHECK(spot_width::R1ForWidth(1.0f) == 4.0f);
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CHECK(spot_width::R1ForWidth(1.794f) == 4.0f);
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CHECK(spot_width::R1ForWidth(2.4f) == 5.0f);
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CHECK(spot_width::R1ForWidth(3.947f) == 6.0f);
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CHECK(spot_width::R1ForWidth(9.0f) == 6.0f);
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}
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// The rotation two-pass quality guard. The refined pass is sent back to the header geometry only for
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// a decisive loss of signal - reflections at I/sigma >= 2 net of the noise tail at <= -2 - over no
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// more of reciprocal space.
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TEST_CASE("RefinedPassIsWorse", "[process]") {
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const auto pass = [](const UnitCell &cell, char centering, int64_t strong, int64_t negative,
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int64_t reflections) {
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ProcessResult r;
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r.has_merge_statistics = true;
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r.consensus_cell = cell;
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r.consensus_centering = centering;
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r.search_merge_strong_reflections = strong;
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r.search_merge_negative_reflections = negative;
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r.search_merge_reflections = reflections;
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return r;
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};
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const UnitCell cell{50.0f, 60.0f, 70.0f, 90.0f, 90.0f, 90.0f};
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// Same lattice: a loss of more than 10 % of the signal is decisive, a smaller one is not.
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const ProcessResult header = pass(cell, 'P', 50000, 1000, 200000);
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CHECK(!RefinedPassIsWorse(header, pass(cell, 'P', 40000, 1000, 200000)).empty());
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CHECK(RefinedPassIsWorse(header, pass(cell, 'P', 46000, 1000, 200000)).empty());
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// ... unless the refined pass reaches into more of reciprocal space: a dilution, not a loss.
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CHECK(RefinedPassIsWorse(header, pass(cell, 'P', 40000, 1000, 420000)).empty());
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// The header pass on a 7x supercell: seven times the reflections, six in seven of them empty,
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// and their noise tail alone reaches the strong count. Raw, 120k against 80k would read as a
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// decisive loss for the refined pass on the crystal's own lattice; net of the noise it is none.
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const UnitCell supercell{350.0f, 60.0f, 70.0f, 90.0f, 90.0f, 90.0f};
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const ProcessResult on_supercell = pass(supercell, 'P', 120000, 40000, 1400000);
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CHECK(RefinedPassIsWorse(on_supercell, pass(cell, 'P', 80000, 1500, 200000)).empty());
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// The rescue the guard is there for is kept: a refined pass that drops to a sub-cell of the
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// header's lattice loses the reflections the sub-cell cannot index. Half the volume, half the
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// reflections - the same coverage - and half the signal.
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const UnitCell subcell{25.0f, 60.0f, 70.0f, 90.0f, 90.0f, 90.0f};
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CHECK(!RefinedPassIsWorse(header, pass(subcell, 'P', 25500, 500, 100000)).empty());
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// A centred setting of the same lattice counts only the reflections its centring allows, so the
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// counts compare as they are; the primitive volume puts the coverage on the same footing.
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const UnitCell doubled{100.0f, 60.0f, 70.0f, 90.0f, 90.0f, 90.0f};
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CHECK(RefinedPassIsWorse(header, pass(doubled, 'C', 49000, 1000, 200000)).empty());
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CHECK(!RefinedPassIsWorse(header, pass(doubled, 'C', 40000, 1000, 200000)).empty());
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|
|
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// The axial arm: half of the low-order axial rows lost in the same setting, with no more signal.
|
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ProcessResult lost_rows = pass(cell, 'P', 50000, 1000, 200000);
|
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ProcessResult with_rows = header;
|
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with_rows.search_merge_axial_reflections = 16;
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|
lost_rows.search_merge_axial_reflections = 8;
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CHECK(!RefinedPassIsWorse(with_rows, lost_rows).empty());
|
|
}
|
|
|
|
// The beam-centre arbitration between a first pass at the file's centre and one at the measured
|
|
// centre. Two arms on the same lattice are two geometries of one hypothesis: they are judged on the
|
|
// signal each measured, not on a CC1/2 that reads the same on both.
|
|
TEST_CASE("MeasuredCentreWins", "[process]") {
|
|
const auto arm = [](const UnitCell &cell, gemmi::CrystalSystem system, double cc_half, int64_t strong) {
|
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ProcessResult r;
|
|
r.has_merge_statistics = true;
|
|
r.consensus_cell = cell;
|
|
r.consensus_centering = 'P';
|
|
r.rotation_lattice_type = LatticeMessage{'P', 0, system};
|
|
r.search_merge_cc_half = cc_half;
|
|
r.search_merge_strong_reflections = strong;
|
|
r.search_merge_reflections = 40000;
|
|
return r;
|
|
};
|
|
const UnitCell triclinic{40.0f, 41.0f, 100.0f, 86.0f, 84.0f, 72.0f};
|
|
// The same lattice in the setting with a and b exchanged, as a noisy a ~ b can come out.
|
|
const UnitCell swapped{41.02f, 39.98f, 100.1f, 84.0f, 86.0f, 72.0f};
|
|
const auto tri = gemmi::CrystalSystem::Triclinic;
|
|
|
|
const ProcessResult file = arm(triclinic, tri, 0.87, 9000);
|
|
REQUIRE(ArmsHoldSameLattice(file, arm(swapped, tri, 0.87, 9000)));
|
|
|
|
// Same lattice, same CC1/2: the arm that measured more signal wins, whichever centre it is...
|
|
CHECK(!MeasuredCentreWins(file, arm(swapped, tri, 0.87, 9500)).empty());
|
|
CHECK(MeasuredCentreWins(file, arm(swapped, tri, 0.87, 8500)).empty());
|
|
// ...a tie keeps the file's centre, and a higher CC1/2 alone does not move it.
|
|
CHECK(MeasuredCentreWins(file, arm(swapped, tri, 0.99, 9000)).empty());
|
|
|
|
// Different lattices: the metric question, decided on the search merges.
|
|
const UnitCell monoclinic{57.0f, 42.0f, 100.0f, 90.0f, 95.0f, 90.0f};
|
|
const auto mono = gemmi::CrystalSystem::Monoclinic;
|
|
REQUIRE(!ArmsHoldSameLattice(file, arm(monoclinic, mono, 0.87, 9000)));
|
|
CHECK(!MeasuredCentreWins(file, arm(monoclinic, mono, 0.95, 9000)).empty());
|
|
CHECK(MeasuredCentreWins(file, arm(monoclinic, mono, 0.88, 20000)).empty());
|
|
}
|