MDNormDirectSC.cpp

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// Mantid Repository : https://github.com/mantidproject/mantid
//
// Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
//   NScD Oak Ridge National Laboratory, European Spallation Source,
//   Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
// SPDX - License - Identifier: GPL - 3.0 +
#include "MantidMDAlgorithms/MDNormDirectSC.h"
 
#include "MantidAPI/CommonBinsValidator.h"
#include "MantidAPI/InstrumentValidator.h"
#include "MantidAPI/Run.h"
#include "MantidAPI/SpectrumInfo.h"
#include "MantidAPI/WorkspaceHistory.h"
#include "MantidDataObjects/EventWorkspace.h"
#include "MantidDataObjects/MDEventWorkspace.h"
#include "MantidDataObjects/MDHistoWorkspace.h"
#include "MantidGeometry/Instrument.h"
#include "MantidGeometry/Instrument/Goniometer.h"
#include "MantidKernel/CompositeValidator.h"
#include "MantidKernel/ConfigService.h"
#include "MantidKernel/PhysicalConstants.h"
#include "MantidKernel/Strings.h"
#include "MantidKernel/TimeSeriesProperty.h"
#include "MantidKernel/VectorHelper.h"
 
namespace Mantid::MDAlgorithms {
 
using Mantid::API::WorkspaceProperty;
using Mantid::Kernel::Direction;
using namespace Mantid::DataObjects;
using namespace Mantid::API;
using namespace Mantid::Kernel;
 
namespace {
// function to  compare two intersections (h,k,l,Momentum) by Momentum
bool compareMomentum(const std::array<double, 4> &v1, const std::array<double, 4> &v2) { return (v1[3] < v2[3]); }
const std::string LOG_CHARGE_NAME("proton_charge");
} // namespace
 
// Register the algorithm into the AlgorithmFactory
DECLARE_ALGORITHM(MDNormDirectSC)
 
 
MDNormDirectSC::MDNormDirectSC()
    : m_normWS(), m_inputWS(), m_hmin(0.0f), m_hmax(0.0f), m_kmin(0.0f), m_kmax(0.0f), m_lmin(0.0f), m_lmax(0.0f),
      m_dEmin(0.f), m_dEmax(0.f), m_Ei(0.), m_ki(0.), m_kfmin(0.), m_kfmax(0.), m_hIntegrated(true),
      m_kIntegrated(true), m_lIntegrated(true), m_dEIntegrated(true), m_rubw(3, 3), m_hIdx(-1), m_kIdx(-1), m_lIdx(-1),
      m_eIdx(-1), m_hX(), m_kX(), m_lX(), m_eX(), m_samplePos(), m_beamDir() {}
 
int MDNormDirectSC::version() const { return 1; }
 
const std::string MDNormDirectSC::category() const { return "MDAlgorithms\\Normalisation"; }
 
const std::string MDNormDirectSC::summary() const {
  return "Calculate normalization for an MDEvent workspace for single crystal "
         "direct geometry inelastic measurement.";
}
 
const std::string MDNormDirectSC::name() const { return "MDNormDirectSC"; }
 
void MDNormDirectSC::init() {
  declareProperty(std::make_unique<WorkspaceProperty<IMDEventWorkspace>>("InputWorkspace", "", Direction::Input),
                  "An input MDWorkspace.");
 
  std::string dimChars = getDimensionChars();
  // --------------- Axis-aligned properties
  // ---------------------------------------
  for (size_t i = 0; i < dimChars.size(); i++) {
    std::string dim(" ");
    dim[0] = dimChars[i];
    std::string propName = "AlignedDim" + dim;
    declareProperty(std::make_unique<PropertyWithValue<std::string>>(propName, "", Direction::Input),
                    "Binning parameters for the " + Strings::toString(i) +
                        "th dimension.\n"
                        "Enter it as a comma-separated list of values with the format: "
                        "'name,minimum,maximum,number_of_bins'. Leave blank for NONE.");
  }
 
  auto solidAngleValidator = std::make_shared<CompositeValidator>();
  solidAngleValidator->add<InstrumentValidator>();
  solidAngleValidator->add<CommonBinsValidator>();
 
  m_progress = std::make_unique<API::Progress>(this, 0, 1, 1);
 
  declareProperty(std::make_unique<WorkspaceProperty<>>("SolidAngleWorkspace", "", Direction::Input,
                                                        PropertyMode::Optional, solidAngleValidator),
                  "An input workspace containing integrated vanadium (a measure of the "
                  "solid angle).");
 
  declareProperty(std::make_unique<PropertyWithValue<bool>>("SkipSafetyCheck", false, Direction::Input),
                  "If set to true, the algorithm does "
                  "not check history if the workspace was modified since the"
                  "ConvertToMD algorithm was run, and assume that the direct "
                  "geometry inelastic mode is used.");
 
  declareProperty(std::make_unique<WorkspaceProperty<IMDHistoWorkspace>>("TemporaryNormalizationWorkspace", "",
                                                                         Direction::Input, PropertyMode::Optional),
                  "An input MDHistoWorkspace used to accumulate normalization "
                  "from multiple MDEventWorkspaces. If unspecified a blank "
                  "MDHistoWorkspace will be created.");
 
  declareProperty(std::make_unique<WorkspaceProperty<IMDHistoWorkspace>>("TemporaryDataWorkspace", "", Direction::Input,
                                                                         PropertyMode::Optional),
                  "An input MDHistoWorkspace used to accumulate data from "
                  "multiple MDEventWorkspaces. If unspecified a blank "
                  "MDHistoWorkspace will be created.");
 
  declareProperty(std::make_unique<WorkspaceProperty<Workspace>>("OutputWorkspace", "", Direction::Output),
                  "A name for the output data MDHistoWorkspace.");
  declareProperty(std::make_unique<WorkspaceProperty<Workspace>>("OutputNormalizationWorkspace", "", Direction::Output),
                  "A name for the output normalization MDHistoWorkspace.");
}
 
//----------------------------------------------------------------------------------------------
void MDNormDirectSC::exec() {
  cacheInputs();
  auto outputWS = binInputWS();
  convention = Kernel::ConfigService::Instance().getString("Q.convention");
  outputWS->setDisplayNormalization(Mantid::API::NoNormalization);
  setProperty<Workspace_sptr>("OutputWorkspace", outputWS);
  createNormalizationWS(*outputWS);
  m_normWS->setDisplayNormalization(Mantid::API::NoNormalization);
  setProperty("OutputNormalizationWorkspace", m_normWS);
 
  m_numExptInfos = outputWS->getNumExperimentInfo();
  m_signalArray = std::vector<std::atomic<signal_t>>(m_normWS->getNPoints());
  // loop over all experiment infos
  m_progress->resetNumSteps(m_numExptInfos, 0.3, 1.0);
  for (uint16_t expInfoIndex = 0; expInfoIndex < m_numExptInfos; expInfoIndex++) {
    const auto &currentExptInfo = *(m_inputWS->getExperimentInfo(expInfoIndex));
    if (!currentExptInfo.run().hasProperty("RUBW_MATRIX")) {
      throw std::runtime_error("Wokspace does not contain a log entry for the RUBW matrix."
                               "Cannot continue.");
    }
    // Check for other dimensions if we could measure anything in the original
    // data
    bool skipNormalization = false;
    const std::vector<coord_t> otherValues = getValuesFromOtherDimensions(skipNormalization, expInfoIndex);
    const auto affineTrans = findIntergratedDimensions(otherValues, skipNormalization);
    cacheDimensionXValues();
 
    if (!skipNormalization) {
      if (currentExptInfo.run().hasProperty("useLogTimes")) {
        calculateNormContinuous(otherValues, affineTrans, expInfoIndex);
      } else {
        calculateNormalization(otherValues, affineTrans, expInfoIndex);
      }
    } else {
      g_log.warning("Binning limits are outside the limits of the MDWorkspace. "
                    "Not applying normalization.");
    }
    m_progress->report();
  }
  std::copy(m_signalArray.cbegin(), m_signalArray.cend(), m_normWS->mutableSignalArray());
 
  // Set the display normalization based on the input workspace
  outputWS->setDisplayNormalization(m_inputWS->displayNormalizationHisto());
}
 
void MDNormDirectSC::cacheInputs() {
  m_inputWS = getProperty("InputWorkspace");
  bool skipCheck = getProperty("SkipSafetyCheck");
  if (!skipCheck && (inputEnergyMode() != "Direct")) {
    throw std::invalid_argument("Invalid energy transfer mode. Algorithm only "
                                "supports direct geometry spectrometers.");
  }
  // Min/max dimension values
  const auto hdim(m_inputWS->getDimension(0)), kdim(m_inputWS->getDimension(1)), ldim(m_inputWS->getDimension(2)),
      edim(m_inputWS->getDimension(3));
  m_hmin = hdim->getMinimum();
  m_kmin = kdim->getMinimum();
  m_lmin = ldim->getMinimum();
  m_dEmin = edim->getMinimum();
  m_hmax = hdim->getMaximum();
  m_kmax = kdim->getMaximum();
  m_lmax = ldim->getMaximum();
  m_dEmax = edim->getMaximum();
 
  const auto &exptInfoZero = *(m_inputWS->getExperimentInfo(0));
  auto source = exptInfoZero.getInstrument()->getSource();
  auto sample = exptInfoZero.getInstrument()->getSample();
  if (source == nullptr || sample == nullptr) {
    throw Kernel::Exception::InstrumentDefinitionError(
        "Instrument not sufficiently defined: failed to get source and/or "
        "sample");
  }
  m_samplePos = sample->getPos();
  m_beamDir = normalize(m_samplePos - source->getPos());
 
  double originaldEmin = exptInfoZero.run().getBinBoundaries().front();
  double originaldEmax = exptInfoZero.run().getBinBoundaries().back();
  if (exptInfoZero.run().hasProperty("Ei")) {
    m_Ei = exptInfoZero.run().getPropertyValueAsType<double>("Ei");
    if (m_Ei <= 0) {
      throw std::invalid_argument("Ei stored in the workspace is not positive");
    }
  } else {
    throw std::invalid_argument("Could not find Ei value in the workspace.");
  }
  double eps = 1e-7;
  if (m_Ei - originaldEmin < eps) {
    originaldEmin = m_Ei - eps;
  }
  if (m_Ei - originaldEmax < eps) {
    originaldEmax = m_Ei - 1e-7;
  }
  if (originaldEmin == originaldEmax) {
    throw std::runtime_error("The limits of the original workspace used in "
                             "ConvertToMD are incorrect");
  }
  const double energyToK = 8.0 * M_PI * M_PI * PhysicalConstants::NeutronMass * PhysicalConstants::meV * 1e-20 /
                           (PhysicalConstants::h * PhysicalConstants::h);
  m_ki = std::sqrt(energyToK * m_Ei);
  m_kfmin = std::sqrt(energyToK * (m_Ei - originaldEmin));
  m_kfmax = std::sqrt(energyToK * (m_Ei - originaldEmax));
}
 
std::string MDNormDirectSC::inputEnergyMode() const {
  const auto &hist = m_inputWS->getHistory();
  const size_t nalgs = hist.size();
  const auto &lastAlgHist = hist.getAlgorithmHistory(nalgs - 1);
 
  std::string emode;
  if (lastAlgHist->name() == "ConvertToMD") {
    // get dEAnalysisMode
    emode = lastAlgHist->getPropertyValue("dEAnalysisMode");
  } else {
    if ((lastAlgHist->name() == "Load" || lastAlgHist->name() == "LoadMD") && nalgs > 1) {
      const auto &penultimateAlgHist = hist.getAlgorithmHistory(nalgs - 2);
      if (penultimateAlgHist->name() == "ConvertToMD") {
        return penultimateAlgHist->getPropertyValue("dEAnalysisMode");
      }
    }
    throw std::invalid_argument("The last algorithm in the history of the "
                                "input workspace is not ConvertToMD");
  }
  return emode;
}
 
MDHistoWorkspace_sptr MDNormDirectSC::binInputWS() {
  const auto &props = getProperties();
  auto binMD = createChildAlgorithm("BinMD", 0.0, 0.3);
  binMD->setPropertyValue("AxisAligned", "1");
  for (auto prop : props) {
    const auto &propName = prop->name();
    if (propName != "SolidAngleWorkspace" && propName != "TemporaryNormalizationWorkspace" &&
        propName != "OutputNormalizationWorkspace" && propName != "SkipSafetyCheck") {
      binMD->setPropertyValue(propName, prop->value());
    }
  }
  binMD->executeAsChildAlg();
  Workspace_sptr outputWS = binMD->getProperty("OutputWorkspace");
  return std::dynamic_pointer_cast<MDHistoWorkspace>(outputWS);
}
 
void MDNormDirectSC::createNormalizationWS(const MDHistoWorkspace &dataWS) {
  // Copy the MDHisto workspace, and change signals and errors to 0.
  std::shared_ptr<IMDHistoWorkspace> tmp = this->getProperty("TemporaryNormalizationWorkspace");
  m_normWS = std::dynamic_pointer_cast<MDHistoWorkspace>(tmp);
  if (!m_normWS) {
    m_normWS = dataWS.clone();
    m_normWS->setTo(0., 0., 0.);
  }
}
 
std::vector<coord_t> MDNormDirectSC::getValuesFromOtherDimensions(bool &skipNormalization,
                                                                  uint16_t expInfoIndex) const {
  const auto &currentRun = m_inputWS->getExperimentInfo(expInfoIndex)->run();
 
  std::vector<coord_t> otherDimValues;
  for (size_t i = 4; i < m_inputWS->getNumDims(); i++) {
    const auto dimension = m_inputWS->getDimension(i);
    auto dimMin = static_cast<float>(dimension->getMinimum());
    auto dimMax = static_cast<float>(dimension->getMaximum());
    auto *dimProp = dynamic_cast<Kernel::TimeSeriesProperty<double> *>(currentRun.getProperty(dimension->getName()));
    if (dimProp) {
      auto value = static_cast<coord_t>(dimProp->firstValue());
      otherDimValues.emplace_back(value);
      // in the original MD data no time was spent measuring between dimMin and
      // dimMax
      if (value < dimMin || value > dimMax) {
        skipNormalization = true;
      }
    }
  }
  return otherDimValues;
}
 
Kernel::Matrix<coord_t> MDNormDirectSC::findIntergratedDimensions(const std::vector<coord_t> &otherDimValues,
                                                                  bool &skipNormalization) {
  // Get indices of the original dimensions in the output workspace,
  // and if not found, the corresponding dimension is integrated
  Kernel::Matrix<coord_t> affineMat = m_normWS->getTransformFromOriginal(0)->makeAffineMatrix();
 
  const size_t nrm1 = affineMat.numRows() - 1;
  const size_t ncm1 = affineMat.numCols() - 1;
  for (size_t row = 0; row < nrm1; row++) // affine matrix, ignore last row
  {
    const auto dimen = m_normWS->getDimension(row);
    const auto dimMin(dimen->getMinimum()), dimMax(dimen->getMaximum());
    if (affineMat[row][0] == 1.) {
      m_hIntegrated = false;
      m_hIdx = row;
      m_hmin = std::max(m_hmin, dimMin);
      m_hmax = std::min(m_hmax, dimMax);
      if (m_hmin > dimMax || m_hmax < dimMin) {
        skipNormalization = true;
      }
    }
    if (affineMat[row][1] == 1.) {
      m_kIntegrated = false;
      m_kIdx = row;
      m_kmin = std::max(m_kmin, dimMin);
      m_kmax = std::min(m_kmax, dimMax);
      if (m_kmin > dimMax || m_kmax < dimMin) {
        skipNormalization = true;
      }
    }
    if (affineMat[row][2] == 1.) {
      m_lIntegrated = false;
      m_lIdx = row;
      m_lmin = std::max(m_lmin, dimMin);
      m_lmax = std::min(m_lmax, dimMax);
      if (m_lmin > dimMax || m_lmax < dimMin) {
        skipNormalization = true;
      }
    }
 
    if (affineMat[row][3] == 1.) {
      m_dEIntegrated = false;
      m_eIdx = row;
      m_dEmin = std::max(m_dEmin, dimMin);
      m_dEmax = std::min(m_dEmax, dimMax);
      if (m_dEmin > dimMax || m_dEmax < dimMin) {
        skipNormalization = true;
      }
    }
    for (size_t col = 4; col < ncm1; col++) // affine matrix, ignore last column
    {
      if (affineMat[row][col] == 1.) {
        double val = otherDimValues.at(col - 3);
        if (val > dimMax || val < dimMin) {
          skipNormalization = true;
        }
      }
    }
  }
 
  return affineMat;
}
 
void MDNormDirectSC::cacheDimensionXValues() {
  constexpr double energyToK = 8.0 * M_PI * M_PI * PhysicalConstants::NeutronMass * PhysicalConstants::meV * 1e-20 /
                               (PhysicalConstants::h * PhysicalConstants::h);
  if (!m_hIntegrated) {
    auto &hDim = *m_normWS->getDimension(m_hIdx);
    m_hX.resize(hDim.getNBoundaries());
    for (size_t i = 0; i < m_hX.size(); ++i) {
      m_hX[i] = hDim.getX(i);
    }
  }
  if (!m_kIntegrated) {
    auto &kDim = *m_normWS->getDimension(m_kIdx);
    m_kX.resize(kDim.getNBoundaries());
    for (size_t i = 0; i < m_kX.size(); ++i) {
      m_kX[i] = kDim.getX(i);
    }
  }
  if (!m_lIntegrated) {
    auto &lDim = *m_normWS->getDimension(m_lIdx);
    m_lX.resize(lDim.getNBoundaries());
    for (size_t i = 0; i < m_lX.size(); ++i) {
      m_lX[i] = lDim.getX(i);
    }
  }
  if (!m_dEIntegrated) {
    // NOTE: store k final instead
    auto &eDim = *m_normWS->getDimension(m_eIdx);
    m_eX.resize(eDim.getNBoundaries());
    for (size_t i = 0; i < m_eX.size(); ++i) {
      double temp = m_Ei - eDim.getX(i);
      temp = std::max(temp, 0.);
      m_eX[i] = std::sqrt(energyToK * temp);
    }
  }
}
 
void MDNormDirectSC::calculateNormalization(const std::vector<coord_t> &otherValues,
                                            const Kernel::Matrix<coord_t> &affineTrans, uint16_t expInfoIndex) {
  using VectorDoubleProperty = Kernel::PropertyWithValue<std::vector<double>>;
  const auto &currentExptInfo = *(m_inputWS->getExperimentInfo(expInfoIndex));
  const auto &spectrumInfo = currentExptInfo.spectrumInfo();
  auto *rubwLog = dynamic_cast<VectorDoubleProperty *>(currentExptInfo.getLog("RUBW_MATRIX"));
  Kernel::DblMatrix rubwValue((*rubwLog)()); // includes the 2*pi factor but not goniometer for now :)
  m_rubw = currentExptInfo.run().getGoniometerMatrix() * rubwValue;
  m_rubw.Invert();
  const double protonCharge = currentExptInfo.run().getProtonCharge();
 
  calculateNormInner(spectrumInfo, protonCharge, otherValues, affineTrans);
}
 
void MDNormDirectSC::calculateNormContinuous(const std::vector<coord_t> &otherValues,
                                             const Kernel::Matrix<coord_t> &affineTrans, uint16_t expInfoIndex) {
  using VectorDoubleProperty = Kernel::PropertyWithValue<std::vector<double>>;
  const auto &currentExptInfo = *(m_inputWS->getExperimentInfo(expInfoIndex));
  const auto &spectrumInfo = currentExptInfo.spectrumInfo();
  auto *rubwLog = dynamic_cast<VectorDoubleProperty *>(currentExptInfo.getLog("RUBW_MATRIX"));
  Kernel::DblMatrix rubwValue((*rubwLog)()); // includes the 2*pi factor but not goniometer for now :)
 
  // MDEventWS was created with the "useLogTimes" option: should be only a single expInfo, but
  // gonios vary with time - we now coarse-bin it to compute the normalisation.
  const Run &run = currentExptInfo.run();
  if (!run.hasProperty(LOG_CHARGE_NAME)) {
    throw std::runtime_error("Wokspace does not contain the proton charge log. Cannot continue.");
  }
 
  double progressStart = 0.3 + 0.7 * expInfoIndex / m_numExptInfos;
  double progressEnd = 0.3 + 0.7 * (expInfoIndex + 1) / m_numExptInfos;
  double normfac = run.hasProperty("NormalizationFactor")
                       ? (*dynamic_cast<Kernel::PropertyWithValue<double> *>(run.getProperty("NormalizationFactor")))()
                       : 1.0;
  std::istringstream tosplit;
  tosplit.str((*dynamic_cast<PropertyWithValue<std::string> *>(run.getProperty("useLogTimes")))());
  std::vector<TimeSeriesProperty<double> *> logs;
  std::vector<size_t> movingGonioIndex;
  const TimeSeriesProperty<double> *protonlog = run.getTimeSeriesProperty<double>(LOG_CHARGE_NAME);
  std::vector<double> protonCharge = protonlog->valuesAsVector();
  std::vector<Types::Core::DateAndTime> protonTimes = protonlog->timesAsVector();
  Geometry::Goniometer gonio(run.getGoniometer());
 
  for (std::string name; std::getline(tosplit, name, ',');) {
    auto *log = run.getTimeSeriesProperty<double>(name);
    logs.push_back(log);
    if ((log->maxValue() - log->minValue()) > STATIONARYANGLIM) { // Assume gonio logs in degrees
      movingGonioIndex.push_back(logs.size() - 1);
    }
  }
 
  // Convert from picoCoulomb to uA.hr for SNS data
  if (protonlog->units().find("picoCoulomb") != std::string::npos) {
    normfac *= 3600.e6;
  }
 
  if (movingGonioIndex.size() == 1) {
    // If we only have a single moving gonio, bin all its values to GONIOBINSTEP degree bins and
    // run inner loop on each binned angle
    const TimeROI &timeroi = run.getTimeROI();
    const auto &gonioAxLog = logs[movingGonioIndex[0]];
    std::vector<double> filteredVals = gonioAxLog->filteredValuesAsVector(&timeroi);
    const auto &[min, max] = std::minmax_element(filteredVals.begin(), filteredVals.end());
    std::vector<double> gonioCharge(static_cast<int>((*max - *min) / GONIOBINSTEP) + 1, 0.0);
    for (size_t n = 0; n < protonCharge.size(); n++) {
      double logval = gonioAxLog->getSingleValue(protonTimes[n]);
      if (std::isnan(logval) || logval > *max || logval < *min) {
        continue;
      }
      auto idx = static_cast<size_t>(floor((logval - *min) / GONIOBINSTEP));
      gonioCharge[idx] += protonCharge[n];
    }
    m_progress->resetNumSteps(static_cast<int64_t>(gonioCharge.size()), progressStart, progressEnd);
    for (size_t n = 0; n < gonioCharge.size(); n++) {
      if (gonioCharge[n] < MINPROTONCHARGE) {
        continue;
      }
      auto nn = static_cast<double>(n);
      gonio.setRotationAngle(movingGonioIndex[0], nn * GONIOBINSTEP + *min);
      m_rubw = gonio.getR() * rubwValue;
      m_rubw.Invert();
      calculateNormInner(spectrumInfo, gonioCharge[n] / normfac, otherValues, affineTrans);
      m_progress->report();
    }
  } else {
    // Otherwise run inner loop over small bins of proton charge in time
    double chargeSum = 0.0;
    size_t i0 = 0;
    bool skipIter = false;
    m_progress->resetNumSteps(static_cast<int64_t>(protonCharge.size()), progressStart, progressEnd);
    for (size_t n = 0; n < protonCharge.size(); n++) {
      chargeSum += protonCharge[n];
      if (chargeSum > CHARGEBINSIZE) {
        size_t mid = static_cast<int>(floor(static_cast<double>(n - i0) / 2.));
        skipIter = false;
        for (size_t gAx = 0; gAx < gonio.getNumberAxes(); gAx++) {
          double logval = logs[gAx]->getSingleValue(protonTimes[mid]);
          if (std::isnan(logval)) {
            skipIter = true;
            continue;
          }
          gonio.setRotationAngle(gAx, logval);
        }
        if (!skipIter) {
          m_rubw = gonio.getR() * rubwValue;
          m_rubw.Invert();
          calculateNormInner(spectrumInfo, chargeSum / normfac, otherValues, affineTrans);
        }
        chargeSum = 0;
        i0 = n;
      }
      m_progress->report();
    }
  }
  if (m_numExptInfos > 1) {
    m_progress->resetNumSteps(m_numExptInfos - expInfoIndex, progressStart, 1.0);
  }
}
 
void MDNormDirectSC::calculateNormInner(const API::SpectrumInfo &spectrumInfo, const double protonCharge,
                                        const std::vector<coord_t> &otherValues,
                                        const Kernel::Matrix<coord_t> &affineTrans) {
  constexpr double energyToK = 8.0 * M_PI * M_PI * PhysicalConstants::NeutronMass * PhysicalConstants::meV * 1e-20 /
                               (PhysicalConstants::h * PhysicalConstants::h);
  // Mapping
  const auto ndets = static_cast<int64_t>(spectrumInfo.size());
  bool haveSA = false;
  API::MatrixWorkspace_const_sptr solidAngleWS = getProperty("SolidAngleWorkspace");
  detid2index_map solidAngDetToIdx;
  if (solidAngleWS != nullptr) {
    haveSA = true;
    solidAngDetToIdx = solidAngleWS->getDetectorIDToWorkspaceIndexMap();
  }
 
  const size_t vmdDims = 4;
 
  PRAGMA_OMP(parallel for)
  for (int64_t i = 0; i < ndets; i++) {
    PARALLEL_START_INTERRUPT_REGION
 
    if (!spectrumInfo.hasDetectors(i) || spectrumInfo.isMonitor(i) || spectrumInfo.isMasked(i)) {
      continue;
    }
    const auto &detector = spectrumInfo.detector(i);
    double theta = detector.getTwoTheta(m_samplePos, m_beamDir);
    double phi = detector.getPhi();
    // If the detector is a group, this should be the ID of the first detector
    const auto detID = detector.getID();
 
    // Intersections
    std::vector<std::array<double, 4>> intersections;
    std::vector<coord_t> pos, posNew;
    this->calculateIntersections(intersections, theta, phi);
    if (intersections.empty())
      continue;
 
    // Get solid angle for this contribution
    double solid = protonCharge;
    if (haveSA) {
      solid = solidAngleWS->y(solidAngDetToIdx.find(detID)->second)[0] * protonCharge;
    }
    // Compute final position in HKL
    // pre-allocate for efficiency and copy non-hkl dim values into place
    pos.resize(vmdDims + otherValues.size() + 1);
    std::copy(otherValues.begin(), otherValues.end(), pos.begin() + vmdDims);
    pos.emplace_back(1.f);
    for (auto it = intersections.begin() + 1; it != intersections.end(); ++it) {
      const auto &curIntSec = *it;
      const auto &prevIntSec = *(it - 1);
      // the full vector isn't used so compute only what is necessary
      double delta = (curIntSec[3] * curIntSec[3] - prevIntSec[3] * prevIntSec[3]) / energyToK;
      if (delta < 1e-10)
        continue; // Assume zero contribution if difference is small
 
      // Average between two intersections for final position
      std::transform(curIntSec.data(), curIntSec.data() + vmdDims, prevIntSec.data(), pos.begin(),
                     [](const double rhs, const double lhs) { return static_cast<coord_t>(0.5 * (rhs + lhs)); });
 
      // transform kf to energy transfer
      pos[3] = static_cast<coord_t>(m_Ei - pos[3] * pos[3] / energyToK);
      affineTrans.multiplyPoint(pos, posNew);
      size_t linIndex = m_normWS->getLinearIndexAtCoord(posNew.data());
      if (linIndex == static_cast<size_t>(-1))
        continue;
 
      // signal = integral between two consecutive intersections *solid angle
      // *PC
      double signal = solid * delta;
      Mantid::Kernel::AtomicOp(m_signalArray[linIndex], signal, std::plus<signal_t>());
    }
    PARALLEL_END_INTERRUPT_REGION
  }
  PARALLEL_CHECK_INTERRUPT_REGION
}
 
void MDNormDirectSC::calculateIntersections(std::vector<std::array<double, 4>> &intersections, const double theta,
                                            const double phi) {
  V3D qout(sin(theta) * cos(phi), sin(theta) * sin(phi), cos(theta)), qin(0., 0., m_ki);
 
  qout = m_rubw * qout;
  qin = m_rubw * qin;
  if (convention == "Crystallography") {
    qout *= -1;
    qin *= -1;
  }
  double hStart = qin.X() - qout.X() * m_kfmin, hEnd = qin.X() - qout.X() * m_kfmax;
  double kStart = qin.Y() - qout.Y() * m_kfmin, kEnd = qin.Y() - qout.Y() * m_kfmax;
  double lStart = qin.Z() - qout.Z() * m_kfmin, lEnd = qin.Z() - qout.Z() * m_kfmax;
  double eps = 1e-10;
  auto hNBins = m_hX.size();
  auto kNBins = m_kX.size();
  auto lNBins = m_lX.size();
  auto eNBins = m_eX.size();
  intersections.clear();
  intersections.reserve(hNBins + kNBins + lNBins + eNBins + 8); // 8 is 3*(min,max for each Q component)+kfmin+kfmax
 
  // calculate intersections with planes perpendicular to h
  if (fabs(hStart - hEnd) > eps) {
    double fmom = (m_kfmax - m_kfmin) / (hEnd - hStart);
    double fk = (kEnd - kStart) / (hEnd - hStart);
    double fl = (lEnd - lStart) / (hEnd - hStart);
    if (!m_hIntegrated) {
      for (size_t i = 0; i < hNBins; i++) {
        double hi = m_hX[i];
        if ((hi >= m_hmin) && (hi <= m_hmax) && ((hStart - hi) * (hEnd - hi) < 0)) {
          // if hi is between hStart and hEnd, then ki and li will be between
          // kStart, kEnd and lStart, lEnd and momi will be between m_kfmin and
          // m_kfmax
          double ki = fk * (hi - hStart) + kStart;
          double li = fl * (hi - hStart) + lStart;
          if ((ki >= m_kmin) && (ki <= m_kmax) && (li >= m_lmin) && (li <= m_lmax)) {
            double momi = fmom * (hi - hStart) + m_kfmin;
            intersections.push_back({{hi, ki, li, momi}});
          }
        }
      }
    }
    double momhMin = fmom * (m_hmin - hStart) + m_kfmin;
    if ((momhMin - m_kfmin) * (momhMin - m_kfmax) < 0) // m_kfmin>m_kfmax
    {
      // khmin and lhmin
      double khmin = fk * (m_hmin - hStart) + kStart;
      double lhmin = fl * (m_hmin - hStart) + lStart;
      if ((khmin >= m_kmin) && (khmin <= m_kmax) && (lhmin >= m_lmin) && (lhmin <= m_lmax)) {
        intersections.push_back({{m_hmin, khmin, lhmin, momhMin}});
      }
    }
    double momhMax = fmom * (m_hmax - hStart) + m_kfmin;
    if ((momhMax - m_kfmin) * (momhMax - m_kfmax) <= 0) {
      // khmax and lhmax
      double khmax = fk * (m_hmax - hStart) + kStart;
      double lhmax = fl * (m_hmax - hStart) + lStart;
      if ((khmax >= m_kmin) && (khmax <= m_kmax) && (lhmax >= m_lmin) && (lhmax <= m_lmax)) {
        intersections.push_back({{m_hmax, khmax, lhmax, momhMax}});
      }
    }
  }
 
  // calculate intersections with planes perpendicular to k
  if (fabs(kStart - kEnd) > eps) {
    double fmom = (m_kfmax - m_kfmin) / (kEnd - kStart);
    double fh = (hEnd - hStart) / (kEnd - kStart);
    double fl = (lEnd - lStart) / (kEnd - kStart);
    if (!m_kIntegrated) {
      for (size_t i = 0; i < kNBins; i++) {
        double ki = m_kX[i];
        if ((ki >= m_kmin) && (ki <= m_kmax) && ((kStart - ki) * (kEnd - ki) < 0)) {
          // if ki is between kStart and kEnd, then hi and li will be between
          // hStart, hEnd and lStart, lEnd and momi will be between m_kfmin and
          // m_kfmax
          double hi = fh * (ki - kStart) + hStart;
          double li = fl * (ki - kStart) + lStart;
          if ((hi >= m_hmin) && (hi <= m_hmax) && (li >= m_lmin) && (li <= m_lmax)) {
            double momi = fmom * (ki - kStart) + m_kfmin;
            intersections.push_back({{hi, ki, li, momi}});
          }
        }
      }
    }
    double momkMin = fmom * (m_kmin - kStart) + m_kfmin;
    if ((momkMin - m_kfmin) * (momkMin - m_kfmax) < 0) {
      // hkmin and lkmin
      double hkmin = fh * (m_kmin - kStart) + hStart;
      double lkmin = fl * (m_kmin - kStart) + lStart;
      if ((hkmin >= m_hmin) && (hkmin <= m_hmax) && (lkmin >= m_lmin) && (lkmin <= m_lmax)) {
        intersections.push_back({{hkmin, m_kmin, lkmin, momkMin}});
      }
    }
    double momkMax = fmom * (m_kmax - kStart) + m_kfmin;
    if ((momkMax - m_kfmin) * (momkMax - m_kfmax) <= 0) {
      // hkmax and lkmax
      double hkmax = fh * (m_kmax - kStart) + hStart;
      double lkmax = fl * (m_kmax - kStart) + lStart;
      if ((hkmax >= m_hmin) && (hkmax <= m_hmax) && (lkmax >= m_lmin) && (lkmax <= m_lmax)) {
        intersections.push_back({{hkmax, m_kmax, lkmax, momkMax}});
      }
    }
  }
 
  // calculate intersections with planes perpendicular to l
  if (fabs(lStart - lEnd) > eps) {
    double fmom = (m_kfmax - m_kfmin) / (lEnd - lStart);
    double fh = (hEnd - hStart) / (lEnd - lStart);
    double fk = (kEnd - kStart) / (lEnd - lStart);
    if (!m_lIntegrated) {
      for (size_t i = 0; i < lNBins; i++) {
        double li = m_lX[i];
        if ((li >= m_lmin) && (li <= m_lmax) && ((lStart - li) * (lEnd - li) < 0)) {
          double hi = fh * (li - lStart) + hStart;
          double ki = fk * (li - lStart) + kStart;
          if ((hi >= m_hmin) && (hi <= m_hmax) && (ki >= m_kmin) && (ki <= m_kmax)) {
            double momi = fmom * (li - lStart) + m_kfmin;
            intersections.push_back({{hi, ki, li, momi}});
          }
        }
      }
    }
    double momlMin = fmom * (m_lmin - lStart) + m_kfmin;
    if ((momlMin - m_kfmin) * (momlMin - m_kfmax) <= 0) {
      // hlmin and klmin
      double hlmin = fh * (m_lmin - lStart) + hStart;
      double klmin = fk * (m_lmin - lStart) + kStart;
      if ((hlmin >= m_hmin) && (hlmin <= m_hmax) && (klmin >= m_kmin) && (klmin <= m_kmax)) {
        intersections.push_back({{hlmin, klmin, m_lmin, momlMin}});
      }
    }
    double momlMax = fmom * (m_lmax - lStart) + m_kfmin;
    if ((momlMax - m_kfmin) * (momlMax - m_kfmax) < 0) {
      // hlmax and klmax
      double hlmax = fh * (m_lmax - lStart) + hStart;
      double klmax = fk * (m_lmax - lStart) + kStart;
      if ((hlmax >= m_hmin) && (hlmax <= m_hmax) && (klmax >= m_kmin) && (klmax <= m_kmax)) {
        intersections.push_back({{hlmax, klmax, m_lmax, momlMax}});
      }
    }
  }
 
  // intersections with dE
  if (!m_dEIntegrated) {
    for (size_t i = 0; i < eNBins; i++) {
      double kfi = m_eX[i];
      if ((kfi - m_kfmin) * (kfi - m_kfmax) <= 0) {
        double h = qin.X() - qout.X() * kfi;
        double k = qin.Y() - qout.Y() * kfi;
        double l = qin.Z() - qout.Z() * kfi;
        if ((h >= m_hmin) && (h <= m_hmax) && (k >= m_kmin) && (k <= m_kmax) && (l >= m_lmin) && (l <= m_lmax)) {
          intersections.push_back({{h, k, l, kfi}});
        }
      }
    }
  }
 
  // endpoints
  if ((hStart >= m_hmin) && (hStart <= m_hmax) && (kStart >= m_kmin) && (kStart <= m_kmax) && (lStart >= m_lmin) &&
      (lStart <= m_lmax)) {
    intersections.push_back({{hStart, kStart, lStart, m_kfmin}});
  }
  if ((hEnd >= m_hmin) && (hEnd <= m_hmax) && (kEnd >= m_kmin) && (kEnd <= m_kmax) && (lEnd >= m_lmin) &&
      (lEnd <= m_lmax)) {
    intersections.push_back({{hEnd, kEnd, lEnd, m_kfmax}});
  }
 
  // sort intersections by final momentum
  std::stable_sort(intersections.begin(), intersections.end(), compareMomentum);
}
 
} // namespace Mantid::MDAlgorithms