DiscusMultipleScatteringCorrection.cpp

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// Mantid Repository : https://github.com/mantidproject/mantid
//
// Copyright © 2020 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 "MantidAlgorithms/DiscusMultipleScatteringCorrection.h"
#include "MantidAPI/Axis.h"
#include "MantidAPI/BinEdgeAxis.h"
#include "MantidAPI/ISpectrum.h"
#include "MantidAPI/InstrumentValidator.h"
#include "MantidAPI/NumericAxis.h"
#include "MantidAPI/Sample.h"
#include "MantidAPI/SpectrumInfo.h"
#include "MantidAPI/WorkspaceFactory.h"
#include "MantidAPI/WorkspaceGroup.h"
#include "MantidAPI/WorkspaceUnitValidator.h"
#include "MantidAlgorithms/BeamProfileFactory.h"
#include "MantidDataObjects/Workspace2D.h"
#include "MantidDataObjects/WorkspaceCreation.h"
#include "MantidGeometry/Instrument.h"
#include "MantidGeometry/Instrument/DetectorInfo.h"
#include "MantidGeometry/Instrument/ReferenceFrame.h"
#include "MantidGeometry/Objects/BoundingBox.h"
#include "MantidGeometry/Objects/ShapeFactory.h"
#include "MantidKernel/BoundedValidator.h"
#include "MantidKernel/CompositeValidator.h"
#include "MantidKernel/EnabledWhenProperty.h"
#include "MantidKernel/EqualBinsChecker.h"
#include "MantidKernel/ListValidator.h"
#include "MantidKernel/Material.h"
#include "MantidKernel/MersenneTwister.h"
#include "MantidKernel/PhysicalConstants.h"
#include "MantidKernel/VectorHelper.h"
#include "MantidKernel/WarningSuppressions.h"
 
#include <boost/algorithm/string.hpp>
 
using namespace Mantid::API;
using namespace Mantid::Kernel;
using Mantid::DataObjects::Workspace2D;
namespace PhysicalConstants = Mantid::PhysicalConstants;
 
namespace {
constexpr int DEFAULT_NPATHS = 1000;
constexpr int DEFAULT_SEED = 123456789;
constexpr int DEFAULT_NSCATTERINGS = 2;
constexpr int DEFAULT_LATITUDINAL_DETS = 5;
constexpr int DEFAULT_LONGITUDINAL_DETS = 10;
 
inline double toWaveVector(double energy) { return sqrt(energy / PhysicalConstants::E_mev_toNeutronWavenumberSq); }
 
inline double fromWaveVector(double wavevector) {
  return PhysicalConstants::E_mev_toNeutronWavenumberSq * wavevector * wavevector;
}
 
struct EFixedProvider {
  explicit EFixedProvider(const ExperimentInfo &expt) : m_expt(expt), m_emode(expt.getEMode()), m_EFixed(0.0) {
    if (m_emode == DeltaEMode::Direct) {
      m_EFixed = m_expt.getEFixed();
    }
  }
  inline DeltaEMode::Type emode() const { return m_emode; }
  inline double value(const Mantid::detid_t detID) const {
    if (m_emode != DeltaEMode::Indirect)
      return m_EFixed;
    else
      return m_expt.getEFixed(detID);
  }
 
private:
  const ExperimentInfo &m_expt;
  const DeltaEMode::Type m_emode;
  double m_EFixed;
};
} // namespace
 
namespace Mantid::Algorithms {
 
std::unique_ptr<DiscusData2D> DiscusData2D::createCopy(bool clearY) {
  auto data2DNew = std::make_unique<DiscusData2D>();
  data2DNew->m_data.resize(m_data.size());
  for (size_t i = 0; i < m_data.size(); i++) {
    data2DNew->m_data[i].X = m_data[i].X;
    data2DNew->m_data[i].Y = clearY ? std::vector<double>(m_data[i].Y.size(), 0.) : m_data[i].Y;
  }
  data2DNew->m_specAxis = m_specAxis;
  return data2DNew;
}
 
const std::vector<double> &DiscusData2D::getSpecAxisValues() {
  if (!m_specAxis)
    throw std::runtime_error("DiscusData2D::getSpecAxisValues - No spec axis has been defined.");
  return *m_specAxis;
}
 
// Register the algorithm into the AlgorithmFactory
DECLARE_ALGORITHM(DiscusMultipleScatteringCorrection)
 
 
void DiscusMultipleScatteringCorrection::init() {
  // The input workspace must have an instrument
  auto wsValidator = std::make_shared<InstrumentValidator>();
 
  declareProperty(
      std::make_unique<WorkspaceProperty<>>("InputWorkspace", "", Direction::Input, wsValidator),
      "The name of the input workspace.  The input workspace must have X units of Momentum (k) for elastic "
      "calculations and units of energy transfer (DeltaE) for inelastic calculations. This is used to "
      "supply the sample details, the detector positions and the x axis range to calculate corrections for");
 
  declareProperty(std::make_unique<WorkspaceProperty<Workspace>>("StructureFactorWorkspace", "", Direction::Input),
                  "The name of the workspace containing S'(q) or S'(q, w).  For elastic calculations, the input "
                  "workspace must contain a single spectrum and have X units of momentum transfer. A workspace group "
                  "containing one workspace per component can also be supplied if a calculation is being run on a "
                  "workspace with a sample environment specified");
  declareProperty(std::make_unique<WorkspaceProperty<WorkspaceGroup>>("OutputWorkspace", "", Direction::Output),
                  "Name for the WorkspaceGroup that will be created. Each workspace in the "
                  "group contains a calculated weight for a particular number of "
                  "scattering events. The number of scattering events varies from 1 up to "
                  "the number supplied in the NumberOfScatterings parameter. The group "
                  "will also include an additional workspace for a calculation with a "
                  "single scattering event where the absorption post scattering has been "
                  "set to zero");
  auto wsKValidator = std::make_shared<WorkspaceUnitValidator>("Momentum");
  declareProperty(std::make_unique<WorkspaceProperty<>>("ScatteringCrossSection", "", Direction::Input,
                                                        PropertyMode::Optional, wsKValidator),
                  "A workspace containing the scattering cross section as a function of k, :math:`\\sigma_s(k)`. Note "
                  "- this parameter would normally be left empty which results in the tabulated cross section data "
                  "being used instead which implies no wavelength dependence");
 
  auto positiveInt = std::make_shared<Kernel::BoundedValidator<int>>();
  positiveInt->setLower(1);
  declareProperty("NumberOfSimulationPoints", EMPTY_INT(), positiveInt,
                  "The number of points on the input workspace x axis for which a simulation is attempted");
 
  declareProperty("NeutronPathsSingle", DEFAULT_NPATHS, positiveInt,
                  "The number of \"neutron\" paths to generate for single scattering");
  declareProperty("NeutronPathsMultiple", DEFAULT_NPATHS, positiveInt,
                  "The number of \"neutron\" paths to generate for multiple scattering");
  declareProperty("SeedValue", DEFAULT_SEED, positiveInt, "Seed the random number generator with this value");
  auto nScatteringsValidator = std::make_shared<Kernel::BoundedValidator<int>>();
  nScatteringsValidator->setLower(1);
  nScatteringsValidator->setUpper(5);
  declareProperty("NumberScatterings", DEFAULT_NSCATTERINGS, nScatteringsValidator, "Number of scatterings");
 
  auto interpolateOpt = createInterpolateOption();
  declareProperty(interpolateOpt->property(), interpolateOpt->propertyDoc());
  declareProperty("SparseInstrument", false,
                  "Enable simulation on special "
                  "instrument with a sparse grid of "
                  "detectors interpolating the "
                  "results to the real instrument.");
  auto threeOrMore = std::make_shared<Kernel::BoundedValidator<int>>();
  threeOrMore->setLower(3);
  declareProperty("NumberOfDetectorRows", DEFAULT_LATITUDINAL_DETS, threeOrMore,
                  "Number of detector rows in the detector grid of the sparse instrument.");
  setPropertySettings("NumberOfDetectorRows",
                      std::make_unique<EnabledWhenProperty>("SparseInstrument", ePropertyCriterion::IS_NOT_DEFAULT));
  auto twoOrMore = std::make_shared<Kernel::BoundedValidator<int>>();
  twoOrMore->setLower(2);
  declareProperty("NumberOfDetectorColumns", DEFAULT_LONGITUDINAL_DETS, twoOrMore,
                  "Number of detector columns in the detector grid "
                  "of the sparse instrument.");
  setPropertySettings("NumberOfDetectorColumns",
                      std::make_unique<EnabledWhenProperty>("SparseInstrument", ePropertyCriterion::IS_NOT_DEFAULT));
  declareProperty("ImportanceSampling", false,
                  "Enable importance sampling on the Q value chosen on multiple scatters based on Q.S(Q)");
  // Control the number of attempts made to generate a random point in the object
  declareProperty("MaxScatterPtAttempts", 5000, positiveInt,
                  "Maximum number of tries made to generate a scattering point "
                  "within the sample. Objects with holes in them, e.g. a thin "
                  "annulus can cause problems if this number is too low.\n"
                  "If a scattering point cannot be generated by increasing "
                  "this value then there is most likely a problem with "
                  "the sample geometry.");
  declareProperty("SimulateEnergiesIndependently", false,
                  "For inelastic calculation, whether the results for adjacent energy transfer bins are simulated "
                  "separately. Currently applies to Direct geometry only");
  declareProperty("NormalizeStructureFactors", false,
                  "Enable normalization of supplied structure factor(s). May be required when running a calculation "
                  "involving more than one material where the normalization of the default S(Q)=1 structure factor "
                  "doesn't match the normalization of a supplied non-isotropic structure factor");
  declareProperty("RadialCollimator", false,
                  "Enable use of a radial collimator that assign zero weights to tracks where the final scatter "
                  "is not in a position that allows the final track segment to pass through the collimator corridor "
                  "which spans from the guage volume toward the each detector");
}
 
std::map<std::string, std::string> DiscusMultipleScatteringCorrection::validateInputs() {
  std::map<std::string, std::string> issues;
  MatrixWorkspace_sptr inputWS = getProperty("InputWorkspace");
  if (inputWS == nullptr) {
    // Mainly aimed at groups. Group ws pass the property validation on MatrixWorkspace type if all members are
    // MatrixWorkspaces. We output a WorkspaceGroup for a single input workspace so can't manage input groups
    issues["InputWorkspace"] = "Input workspace must be a matrix workspace";
    return issues;
  }
  Geometry::IComponent_const_sptr sample = inputWS->getInstrument()->getSample();
  if (!sample)
    issues["InputWorkspace"] = "Input workspace does not have a Sample";
 
  bool atLeastOneValidShape = inputWS->sample().getShape().hasValidShape();
  if (!atLeastOneValidShape) {
    if (inputWS->sample().hasEnvironment()) {
      auto env = &inputWS->sample().getEnvironment();
      for (size_t i = 0; i < env->nelements(); i++) {
        if (env->getComponent(i).hasValidShape()) {
          atLeastOneValidShape = true;
          break;
        }
      }
    }
  }
  if (!atLeastOneValidShape) {
    issues["InputWorkspace"] = "Either the Sample or one of the environment parts must have a valid shape.";
  }
 
  if (inputWS->sample().getShape().hasValidShape())
    if (inputWS->sample().getMaterial().numberDensity() == 0)
      issues["InputWorkspace"] = "Sample must have a material set up with a non-zero number density\n";
  if (inputWS->sample().hasEnvironment()) {
    auto env = &inputWS->sample().getEnvironment();
    for (size_t i = 0; i < env->nelements(); i++)
      if (env->getComponent(i).hasValidShape())
        if (env->getComponent(i).material().numberDensity() == 0)
          issues["InputWorkspace"] = "Sample environment component " + std::to_string(i) +
                                     " must have a material set up with a non-zero number density\n";
  }
 
  std::vector<MatrixWorkspace_sptr> SQWSs;
  Workspace_sptr SQWSBase = getProperty("StructureFactorWorkspace");
  auto SQWSGroup = std::dynamic_pointer_cast<WorkspaceGroup>(SQWSBase);
  if (SQWSGroup) {
    auto groupMembers = SQWSGroup->getAllItems();
    std::set<std::string> materialNames;
    materialNames.insert(inputWS->sample().getMaterial().name());
    if (inputWS->sample().hasEnvironment()) {
      auto nEnvComponents = inputWS->sample().getEnvironment().nelements();
      for (size_t i = 0; i < nEnvComponents; i++)
        materialNames.insert(inputWS->sample().getEnvironment().getComponent(i).material().name());
    }
 
    for (auto &materialName : materialNames) {
      auto wsIt = std::find_if(groupMembers.begin(), groupMembers.end(),
                               [materialName](Workspace_sptr &ws) { return ws->getName() == materialName; });
      if (wsIt == groupMembers.end()) {
        issues["StructureFactorWorkspace"] =
            "No workspace for material  " + materialName + " found in S(Q,w) workspace group";
      } else
        SQWSs.push_back(std::dynamic_pointer_cast<MatrixWorkspace>(*wsIt));
    }
  } else
    SQWSs.push_back(std::dynamic_pointer_cast<MatrixWorkspace>(SQWSBase));
 
  if (inputWS->getEMode() == Kernel::DeltaEMode::Elastic) {
    if (inputWS->getAxis(0)->unit()->unitID() != "Momentum")
      issues["InputWorkspace"] += "Input workspace must have units of Momentum (k) for elastic instrument\n";
    for (auto &SQWS : SQWSs) {
      if (SQWS->getNumberHistograms() != 1)
        issues["StructureFactorWorkspace"] += "S(Q) workspace must contain a single spectrum for elastic mode\n";
 
      if (SQWS->getAxis(0)->unit()->unitID() != "MomentumTransfer")
        issues["StructureFactorWorkspace"] += "S(Q) workspace must have units of MomentumTransfer\n";
    }
  } else {
    for (auto &SQWS : SQWSs) {
      if (inputWS->getAxis(0)->unit()->unitID() != "DeltaE")
        issues["InputWorkspace"] = "Input workspace must have units of DeltaE for inelastic instrument\n";
      std::set<std::string> axisUnits;
      axisUnits.insert(SQWS->getAxis(0)->unit()->unitID());
      axisUnits.insert(SQWS->getAxis(1)->unit()->unitID());
      if (axisUnits != std::set<std::string>{"DeltaE", "MomentumTransfer"})
        issues["StructureFactorWorkspace"] +=
            "S(Q, w) workspace must have units of Energy Transfer and MomentumTransfer\n";
 
      if (SQWS->getAxis(1)->isSpectra())
        issues["StructureFactorWorkspace"] += "S(Q, w) must have a numeric spectrum axis\n";
      std::vector<double> wValues;
      if (SQWS->getAxis(0)->unit()->unitID() == "DeltaE") {
        if (!SQWS->isCommonBins())
          issues["StructureFactorWorkspace"] += "S(Q,w) must have common w values at all Q";
      }
 
      auto checkEqualQBins = [&issues](const MantidVec &qValues) {
        Kernel::EqualBinsChecker checker(qValues, 1.0E-07, -1);
        if (!checker.validate().empty())
          issues["StructureFactorWorkspace"] +=
              "S(Q,w) must have equal size bins in Q in order to support gaussian interpolation";
        ;
      };
 
      if (SQWS->getAxis(0)->unit()->unitID() == "MomentumTransfer") {
        for (size_t iHist = 0; iHist < SQWS->getNumberHistograms(); iHist++) {
          auto qValues = SQWS->dataX(iHist);
          checkEqualQBins(qValues);
        }
      } else if (SQWS->getAxis(1)->unit()->unitID() == "MomentumTransfer") {
        auto qAxis = dynamic_cast<NumericAxis *>(SQWS->getAxis(1));
        if (qAxis) {
          auto qValues = qAxis->getValues();
          checkEqualQBins(qValues);
        }
      }
    }
  }
 
  for (auto &SQWS : SQWSs) {
    for (size_t i = 0; i < SQWS->getNumberHistograms(); i++) {
      auto &y = SQWS->y(i);
      if (std::any_of(y.cbegin(), y.cend(), [](const auto yval) { return yval < 0 || std::isnan(yval); }))
        issues["StructureFactorWorkspace"] += "S(Q) workspace must have all y >= 0";
    }
  }
 
  const int nSimulationPoints = getProperty("NumberOfSimulationPoints");
  if (!isEmpty(nSimulationPoints)) {
    InterpolationOption interpOpt;
    const std::string interpValue = getPropertyValue("Interpolation");
    interpOpt.set(interpValue, false, false);
    const auto nSimPointsIssue = interpOpt.validateInputSize(nSimulationPoints);
    if (!nSimPointsIssue.empty())
      issues["NumberOfSimulationPoints"] = nSimPointsIssue;
  }
 
  const bool simulateEnergiesIndependently = getProperty("SimulateEnergiesIndependently");
  if (simulateEnergiesIndependently) {
    if (inputWS->getEMode() == Kernel::DeltaEMode::Elastic)
      issues["SimulateEnergiesIndependently"] =
          "SimulateEnergiesIndependently is only applicable to inelastic direct geometry calculations";
    if (inputWS->getEMode() == Kernel::DeltaEMode::Indirect)
      issues["SimulateEnergiesIndependently"] =
          "SimulateEnergiesIndependently is only applicable to inelastic direct geometry calculations. Different "
          "energy transfer bins are always simulated separately for indirect geometry";
  }
 
  return issues;
}
void DiscusMultipleScatteringCorrection::getXMinMax(const Mantid::API::MatrixWorkspace &ws, double &xmin,
                                                    double &xmax) const {
  // set to crazy values to start
  xmin = std::numeric_limits<double>::max();
  xmax = -1.0 * xmin;
  size_t numberOfSpectra = ws.getNumberHistograms();
  const auto &spectrumInfo = ws.spectrumInfo();
 
  // determine the data range - only return min > 0. Bins with x=0 will be skipped later on
  for (size_t wsIndex = 0; wsIndex < numberOfSpectra; wsIndex++) {
    if (spectrumInfo.hasDetectors(wsIndex) && !spectrumInfo.isMonitor(wsIndex) && !spectrumInfo.isMasked(wsIndex)) {
      const auto &dataX = ws.points(wsIndex);
      const double xfront = dataX.front();
      const double xback = dataX.back();
      if (std::isnormal(xfront) && std::isnormal(xback)) {
        if (xfront < xmin)
          xmin = xfront;
        if (xback > xmax)
          xmax = xback;
      }
    }
  }
  if (xmin > xmax)
    throw std::runtime_error("Unable to determine min and max x values for workspace");
}
 
void DiscusMultipleScatteringCorrection::prepareStructureFactors() {
  Workspace_sptr suppliedSQWS = getProperty("StructureFactorWorkspace");
  auto SQWSGroup = std::dynamic_pointer_cast<WorkspaceGroup>(suppliedSQWS);
  size_t nEnvComponents = 0;
  if (m_env)
    nEnvComponents = m_env->nelements();
  m_SQWSs.clear();
  if (SQWSGroup) {
    std::string matName = m_sampleShape->material().name();
    auto SQWSGroupMember = std::static_pointer_cast<MatrixWorkspace>(SQWSGroup->getItem(matName));
    addWorkspaceToDiscus2DData(m_sampleShape, matName, SQWSGroupMember);
    if (nEnvComponents > 0) {
      matName = m_env->getContainer().material().name();
      SQWSGroupMember = std::static_pointer_cast<MatrixWorkspace>(SQWSGroup->getItem(matName));
      addWorkspaceToDiscus2DData(m_env->getContainer().getShapePtr(), matName, SQWSGroupMember);
    }
    for (size_t i = 1; i < nEnvComponents; i++) {
      matName = m_env->getComponent(i).material().name();
      SQWSGroupMember = std::static_pointer_cast<MatrixWorkspace>(SQWSGroup->getItem(matName));
      addWorkspaceToDiscus2DData(m_env->getComponentPtr(i), matName, SQWSGroupMember);
    }
  } else {
    addWorkspaceToDiscus2DData(m_sampleShape, m_sampleShape->material().name(),
                               std::dynamic_pointer_cast<MatrixWorkspace>(suppliedSQWS));
    MatrixWorkspace_sptr isotropicSQ = DataObjects::create<Workspace2D>(
        *std::dynamic_pointer_cast<MatrixWorkspace>(suppliedSQWS), static_cast<size_t>(1),
        HistogramData::Histogram(HistogramData::Points{0.}, HistogramData::Frequencies{1.}));
    if (nEnvComponents > 0) {
      std::string_view matName = m_env->getContainer().material().name();
      g_log.information() << "Creating isotropic structure factor for " << matName << std::endl;
      addWorkspaceToDiscus2DData(m_env->getContainer().getShapePtr(), matName, isotropicSQ);
    }
    for (size_t i = 1; i < nEnvComponents; i++) {
      std::string_view matName = m_env->getComponent(i).material().name();
      g_log.information() << "Creating isotropic structure factor for " << matName << std::endl;
      addWorkspaceToDiscus2DData(m_env->getComponentPtr(i), matName, isotropicSQ);
    }
  }
}
 
void DiscusMultipleScatteringCorrection::addWorkspaceToDiscus2DData(const Geometry::IObject_const_sptr &shape,
                                                                    const std::string_view &matName,
                                                                    API::MatrixWorkspace_sptr SQWS) {
  // avoid repeated conversion of bin edges to points inside loop by converting to point data
  convertWsBothAxesToPoints(SQWS);
  // if S(Q,w) has been supplied ensure Q is along the x axis of each spectrum (so same as S(Q))
  if (SQWS->getAxis(1)->unit()->unitID() == "MomentumTransfer") {
    auto transposeAlgorithm = this->createChildAlgorithm("Transpose");
    transposeAlgorithm->initialize();
    transposeAlgorithm->setProperty("InputWorkspace", SQWS);
    transposeAlgorithm->setProperty("OutputWorkspace", "_");
    transposeAlgorithm->execute();
    SQWS = transposeAlgorithm->getProperty("OutputWorkspace");
  } else if (SQWS->getAxis(1)->isSpectra()) {
    // for elastic set w=0 on the spectrum axis to align code with inelastic
    auto newAxis = std::make_unique<NumericAxis>(std::vector<double>{0.});
    newAxis->setUnit("DeltaE");
    SQWS->replaceAxis(1, std::move(newAxis));
  }
  auto specAxis = dynamic_cast<NumericAxis *>(SQWS->getAxis(1));
  std::vector<DiscusData1D> data;
  for (size_t i = 0; i < SQWS->getNumberHistograms(); i++) {
    data.emplace_back(SQWS->histogram(i).dataX(), SQWS->histogram(i).dataY());
  }
  ComponentWorkspaceMapping SQWSMapping{
      shape, matName,
      std::make_shared<DiscusData2D>(data, std::make_shared<std::vector<double>>(specAxis->getValues()))};
  SQWSMapping.logSQ = SQWSMapping.SQ->createCopy();
  convertToLogWorkspace(SQWSMapping.logSQ);
  m_SQWSs.push_back(SQWSMapping);
}
 
void DiscusMultipleScatteringCorrection::convertWsBothAxesToPoints(MatrixWorkspace_sptr &ws) {
  if (ws->isHistogramData()) {
    if (!m_importanceSampling) {
      auto pointDataAlgorithm = this->createChildAlgorithm("ConvertToPointData");
      pointDataAlgorithm->initialize();
      pointDataAlgorithm->setProperty("InputWorkspace", ws);
      pointDataAlgorithm->setProperty("OutputWorkspace", "_");
      pointDataAlgorithm->execute();
      ws = pointDataAlgorithm->getProperty("OutputWorkspace");
    } else {
      // flat interpolation is later used on S(Q) so convert to points by assigning Y value to LH bin edge
      MatrixWorkspace_sptr SQWSPoints =
          API::WorkspaceFactory::Instance().create(ws, ws->getNumberHistograms(), ws->blocksize(), ws->blocksize());
      SQWSPoints->setSharedY(0, ws->sharedY(0));
      SQWSPoints->setSharedE(0, ws->sharedE(0));
      std::vector<double> newX = ws->histogram(0).dataX();
      newX.pop_back();
      SQWSPoints->setSharedX(0, HistogramData::Points(newX).cowData());
      ws = SQWSPoints;
    }
  }
  auto binAxis = dynamic_cast<BinEdgeAxis *>(ws->getAxis(1));
  if (binAxis) {
    auto edges = binAxis->getValues();
    std::vector<double> centres;
    VectorHelper::convertToBinCentre(edges, centres);
    auto newAxis = std::make_unique<NumericAxis>(centres);
    newAxis->setUnit(ws->getAxis(1)->unit()->unitID());
    ws->replaceAxis(1, std::move(newAxis));
  }
}
 
void DiscusMultipleScatteringCorrection::exec() {
  if (!getAlwaysStoreInADS())
    throw std::runtime_error("This algorithm explicitly stores named output workspaces in the ADS so must be run with "
                             "AlwaysStoreInADS set to true");
  const MatrixWorkspace_sptr inputWS = getProperty("InputWorkspace");
 
  prepareSampleBeamGeometry(inputWS);
  prepareStructureFactors();
  loadCollimatorInfo();
 
  MatrixWorkspace_sptr sigmaSSWS = getProperty("ScatteringCrossSection");
  if (sigmaSSWS)
    m_sigmaSS = std::make_shared<DiscusData1D>(
        DiscusData1D{sigmaSSWS->getSpectrum(0).readX(), sigmaSSWS->getSpectrum(0).readY()});
 
  // for inelastic we could calculate the qmax based on the min\max w in the S(Q,w) but that
  // would bake as assumption that S(Q,w)=0 beyond the limits of the supplied data
  double qmax = std::numeric_limits<float>::max();
  EFixedProvider efixed(*inputWS);
  m_EMode = efixed.emode();
  g_log.information("EMode=" + DeltaEMode::asString(m_EMode) + " detected");
  if (m_EMode == Kernel::DeltaEMode::Elastic) {
    double kmin, kmax;
    getXMinMax(*inputWS, kmin, kmax);
    qmax = 2 * kmax;
  }
  prepareQSQ(qmax);
 
  m_simulateEnergiesIndependently = getProperty("SimulateEnergiesIndependently");
  // call this function with dummy efixed to determine total possible simulation points
  const auto inputNbins = generateInputKOutputWList(-1.0, inputWS->points(0).rawData()).size();
 
  int nSimulationPointsInt = getProperty("NumberOfSimulationPoints");
  size_t nSimulationPoints = static_cast<size_t>(nSimulationPointsInt);
 
  if (isEmpty(nSimulationPoints)) {
    nSimulationPoints = inputNbins;
  } else if (nSimulationPoints > inputNbins) {
    g_log.warning() << "The requested number of simulation points is larger "
                       "than the maximum number of simulations per spectra. "
                       "Defaulting to "
                    << inputNbins << ".\n ";
    nSimulationPoints = inputNbins;
  }
 
  m_NormalizeSQ = getProperty("NormalizeStructureFactors");
 
  const bool useSparseInstrument = getProperty("SparseInstrument");
  SparseWorkspace_sptr sparseWS;
  if (useSparseInstrument) {
    const int latitudinalDets = getProperty("NumberOfDetectorRows");
    const int longitudinalDets = getProperty("NumberOfDetectorColumns");
    sparseWS = createSparseWorkspace(*inputWS, nSimulationPoints, latitudinalDets, longitudinalDets);
  }
  const int nScatters = getProperty("NumberScatterings");
  m_maxScatterPtAttempts = getProperty("MaxScatterPtAttempts");
  std::vector<MatrixWorkspace_sptr> simulationWSs;
  std::vector<MatrixWorkspace_sptr> outputWSs;
 
  auto noAbsOutputWS = createOutputWorkspace(*inputWS);
  auto noAbsSimulationWS = useSparseInstrument ? sparseWS->clone() : noAbsOutputWS;
  for (int i = 0; i < nScatters; i++) {
    auto outputWS = createOutputWorkspace(*inputWS);
    MatrixWorkspace_sptr simulationWS = useSparseInstrument ? sparseWS->clone() : outputWS;
    simulationWSs.emplace_back(simulationWS);
    outputWSs.emplace_back(outputWS);
  }
  const MatrixWorkspace &instrumentWS = useSparseInstrument ? *sparseWS : *inputWS;
  const auto nhists = useSparseInstrument ? sparseWS->getNumberHistograms() : inputWS->getNumberHistograms();
 
  const int nSingleScatterEvents = getProperty("NeutronPathsSingle");
  const int nMultiScatterEvents = getProperty("NeutronPathsMultiple");
 
  const int seed = getProperty("SeedValue");
 
  InterpolationOption interpolateOpt;
  bool independentErrors = (m_EMode == DeltaEMode::Direct) ? m_simulateEnergiesIndependently : true;
  interpolateOpt.set(getPropertyValue("Interpolation"), true, independentErrors);
 
  m_importanceSampling = getProperty("ImportanceSampling");
 
  // add one extra progress step per hist for the wavelength interpolation
  Progress prog(this, 0.0, 1.0, nhists * (nSimulationPoints + 1));
  prog.setNotifyStep(0.1);
  const std::string reportMsg = "Computing corrections";
 
  bool enableParallelFor = true;
  enableParallelFor = std::all_of(simulationWSs.cbegin(), simulationWSs.cend(),
                                  [](const MatrixWorkspace_sptr &ws) { return Kernel::threadSafe(*ws); });
 
  enableParallelFor = enableParallelFor && Kernel::threadSafe(*noAbsOutputWS);
 
  const auto &spectrumInfo = instrumentWS.spectrumInfo();
  const auto &detectorInfo = instrumentWS.detectorInfo();
 
  PARALLEL_FOR_IF(enableParallelFor)
  for (int64_t i = 0; i < static_cast<int64_t>(nhists); ++i) { // signed int for openMP loop
    PARALLEL_START_INTERRUPT_REGION
 
    auto &spectrum = instrumentWS.getSpectrum(i);
    Mantid::specnum_t specNo = spectrum.getSpectrumNo();
    MersenneTwister rng(seed + specNo);
    // no two theta for monitors
 
    if (spectrumInfo.hasDetectors(i) && !spectrumInfo.isMonitor(i) && !spectrumInfo.isMasked(i)) {
 
      const double eFixedValue = efixed.value(spectrumInfo.detector(i).getID());
      auto xPoints = instrumentWS.points(i).rawData();
 
      auto kInW = generateInputKOutputWList(eFixedValue, xPoints);
 
      const auto nbins = kInW.size();
      // step size = index range / number of steps requested
      const size_t nsteps = std::max(static_cast<size_t>(1), nSimulationPoints - 1);
      const size_t xStepSize = nbins == 1 ? 1 : (nbins - 1) / nsteps;
 
      // create copy of the SQ workspaces vector and fully copy any members that will be modified
      auto componentWorkspaces = m_SQWSs;
 
      if (m_importanceSampling)
        // prep invPOfQ outside the bin loop to avoid costly construction\destruction
        createInvPOfQWorkspaces(componentWorkspaces, 2);
 
      std::vector<double> kValues;
      std::transform(kInW.begin(), kInW.end(), std::back_inserter(kValues),
                     [](std::tuple<double, int, double> t) { return std::get<0>(t); });
      calculateQSQIntegralAsFunctionOfK(componentWorkspaces, kValues);
 
      for (size_t bin = 0; bin < nbins; bin += xStepSize) {
        const double kinc = std::get<0>(kInW[bin]);
        if ((kinc <= 0) || std::isnan(kinc)) {
          g_log.warning("Skipping calculation for bin with invalid x, workspace index=" + std::to_string(i) +
                        " bin index=" + std::to_string(std::get<1>(kInW[bin])));
          continue;
        }
        std::vector<double> wValues = std::get<1>(kInW[bin]) == -1 ? xPoints : std::vector{std::get<2>(kInW[bin])};
 
        if (m_importanceSampling)
          prepareCumulativeProbForQ(kinc, componentWorkspaces);
 
        auto [weights, weightsErrors] =
            simulatePaths(nSingleScatterEvents, 1, rng, componentWorkspaces, kinc, wValues, true, detectorInfo, i);
        if (std::get<1>(kInW[bin]) == -1) {
          noAbsSimulationWS->getSpectrum(i).mutableY() += weights;
          noAbsSimulationWS->getSpectrum(i).mutableE() += weightsErrors;
        } else {
          noAbsSimulationWS->getSpectrum(i).dataY()[std::get<1>(kInW[bin])] = weights[0];
          noAbsSimulationWS->getSpectrum(i).dataE()[std::get<1>(kInW[bin])] = weightsErrors[0];
        }
 
        for (int ne = 0; ne < nScatters; ne++) {
          int nEvents = ne == 0 ? nSingleScatterEvents : nMultiScatterEvents;
 
          std::tie(weights, weightsErrors) =
              simulatePaths(nEvents, ne + 1, rng, componentWorkspaces, kinc, wValues, false, detectorInfo, i);
          if (std::get<1>(kInW[bin]) == -1.0) {
            simulationWSs[ne]->getSpectrum(i).mutableY() += weights;
            simulationWSs[ne]->getSpectrum(i).mutableE() += weightsErrors;
          } else {
            simulationWSs[ne]->getSpectrum(i).dataY()[std::get<1>(kInW[bin])] = weights[0];
            simulationWSs[ne]->getSpectrum(i).dataE()[std::get<1>(kInW[bin])] = weightsErrors[0];
          }
        }
 
        prog.report(reportMsg);
 
        // Ensure we have the last point for the interpolation
        if (xStepSize > 1 && bin + xStepSize >= nbins && bin + 1 != nbins) {
          bin = nbins - xStepSize - 1;
        }
      } // bins
 
      // interpolate through points not simulated. Simulation WS only has
      // reduced X values if using sparse instrument so no interpolation
      // required
      if (!useSparseInstrument && xStepSize > 1) {
        auto histNoAbs = noAbsSimulationWS->histogram(i);
        if (xStepSize < nbins) {
          interpolateOpt.applyInplace(histNoAbs, xStepSize);
        } else {
          std::fill(histNoAbs.mutableY().begin() + 1, histNoAbs.mutableY().end(), histNoAbs.y()[0]);
        }
        noAbsOutputWS->setHistogram(i, histNoAbs);
 
        for (size_t ne = 0; ne < static_cast<size_t>(nScatters); ne++) {
          auto histnew = simulationWSs[ne]->histogram(i);
          if (xStepSize < nbins) {
            interpolateOpt.applyInplace(histnew, xStepSize);
          } else {
            std::fill(histnew.mutableY().begin() + 1, histnew.mutableY().end(), histnew.y()[0]);
          }
          outputWSs[ne]->setHistogram(i, histnew);
        }
      }
      prog.report(reportMsg);
    }
 
    PARALLEL_END_INTERRUPT_REGION
  }
  PARALLEL_CHECK_INTERRUPT_REGION
 
  if (useSparseInstrument) {
    Poco::Thread::sleep(200); // to ensure prog message changes
    const std::string reportMsgSpatialInterpolation = "Spatial Interpolation";
    prog.report(reportMsgSpatialInterpolation);
    interpolateFromSparse(*noAbsOutputWS, *std::dynamic_pointer_cast<SparseWorkspace>(noAbsSimulationWS),
                          interpolateOpt);
    for (size_t ne = 0; ne < static_cast<size_t>(nScatters); ne++) {
      interpolateFromSparse(*outputWSs[ne], *std::dynamic_pointer_cast<SparseWorkspace>(simulationWSs[ne]),
                            interpolateOpt);
    }
  }
 
  // Create workspace group that holds output workspaces
  auto wsgroup = std::make_shared<WorkspaceGroup>();
  auto outputGroupWSName = getPropertyValue("OutputWorkspace");
  if (AnalysisDataService::Instance().doesExist(outputGroupWSName))
    API::AnalysisDataService::Instance().deepRemoveGroup(outputGroupWSName);
 
  const std::string wsNamePrefix = outputGroupWSName + "_Scatter_";
  std::string wsName = wsNamePrefix + "1_NoAbs";
  setWorkspaceName(noAbsOutputWS, wsName);
  wsgroup->addWorkspace(noAbsOutputWS);
 
  for (size_t i = 0; i < outputWSs.size(); i++) {
    wsName = wsNamePrefix + std::to_string(i + 1);
    setWorkspaceName(outputWSs[i], wsName);
    wsgroup->addWorkspace(outputWSs[i]);
 
    auto integratedWorkspace = integrateWS(outputWSs[i]);
    setWorkspaceName(integratedWorkspace, wsName + "_Integrated");
    wsgroup->addWorkspace(integratedWorkspace);
  }
 
  if (outputWSs.size() > 1) {
    // create sum of multiple scatter workspaces for use in subtraction method
    auto summedMScatOutput = createOutputWorkspace(*inputWS);
    summedMScatOutput = std::accumulate(outputWSs.cbegin() + 1, outputWSs.cend(), summedMScatOutput);
    wsName = wsNamePrefix + "2_" + std::to_string(outputWSs.size()) + "_Summed";
    setWorkspaceName(summedMScatOutput, wsName);
    wsgroup->addWorkspace(summedMScatOutput);
    // create sum of all scattering order workspaces for use in ratio method
    auto summedAllScatOutput = createOutputWorkspace(*inputWS);
    summedAllScatOutput = summedMScatOutput + outputWSs[0];
    wsName = wsNamePrefix + "1_" + std::to_string(outputWSs.size()) + "_Summed";
    setWorkspaceName(summedAllScatOutput, wsName);
    wsgroup->addWorkspace(summedAllScatOutput);
    // create ratio of single to all scatter
    auto ratioOutput = createOutputWorkspace(*inputWS);
    ratioOutput = outputWSs[0] / summedAllScatOutput;
    wsName = outputGroupWSName + "_Ratio_Single_To_All";
    setWorkspaceName(ratioOutput, wsName);
    wsgroup->addWorkspace(ratioOutput);
 
    // ConvFit method being investigated by Spencer for inelastic currently uses the opposite ratio
    if (m_EMode != DeltaEMode::Elastic) {
      auto invRatioOutput = 1 / ratioOutput;
      auto replaceNans = this->createChildAlgorithm("ReplaceSpecialValues");
      replaceNans->setChild(true);
      replaceNans->initialize();
      replaceNans->setProperty("InputWorkspace", invRatioOutput);
      replaceNans->setProperty("OutputWorkspace", invRatioOutput);
      replaceNans->setProperty("NaNValue", 0.0);
      replaceNans->setProperty("InfinityValue", 0.0);
      replaceNans->execute();
      wsName = outputGroupWSName + "_Ratio_All_To_Single";
      setWorkspaceName(invRatioOutput, wsName);
      wsgroup->addWorkspace(invRatioOutput);
    }
  }
 
  // set the output property
  setProperty("OutputWorkspace", wsgroup);
 
  if (g_log.is(Kernel::Logger::Priority::PRIO_INFORMATION)) {
    g_log.information() << "Total simulation points=" << nhists * nSimulationPoints << "\n";
    for (const auto &kv : m_attemptsToGenerateInitialTrack)
      g_log.information() << "Generating initial track required " << kv.first << " attempts on " << kv.second
                          << " occasions.\n";
    g_log.information() << "Calls to interceptSurface=" << m_callsToInterceptSurface << "\n";
    g_log.information() << "Total I(k) calculations=" << m_IkCalculations << ", average per simulation point="
                        << static_cast<double>(m_IkCalculations) / static_cast<double>(nhists * nSimulationPoints)
                        << "\n";
    if (g_log.is(Kernel::Logger::Priority::PRIO_DEBUG))
      for (size_t i = 0; i < m_SQWSs.size(); i++)
        g_log.information() << "Scatters in component " << i << ": " << *(m_SQWSs[i].scatterCount) << "\n";
  }
}
 
std::vector<std::tuple<double, int, double>>
DiscusMultipleScatteringCorrection::generateInputKOutputWList(const double efixed, const std::vector<double> &xPoints) {
  std::vector<std::tuple<double, int, double>> kInW;
  const double kFixed = toWaveVector(efixed);
  if (m_EMode == DeltaEMode::Elastic) {
    int index = 0;
    std::transform(xPoints.begin(), xPoints.end(), std::back_inserter(kInW), [&index](double d) {
      auto t = std::make_tuple(d, index, 0.);
      index++;
      return t;
    });
  } else {
    if ((!m_simulateEnergiesIndependently) && (m_EMode == DeltaEMode::Direct))
      kInW.emplace_back(std::make_tuple(kFixed, -1, 0.));
    else {
      for (int i = 0; i < static_cast<int>(xPoints.size()); i++) {
        if (m_EMode == DeltaEMode::Direct)
          kInW.emplace_back(std::make_tuple(kFixed, i, xPoints[i]));
        else if (m_EMode == DeltaEMode::Indirect) {
          const double initialE = efixed + xPoints[i];
          if (initialE > 0) {
            const double kin = toWaveVector(initialE);
            kInW.emplace_back(std::make_tuple(kin, i, xPoints[i]));
          } else
            // negative kinc is filtered out later
            kInW.emplace_back(std::make_tuple(-1.0, i, xPoints[i]));
        }
      }
    }
  }
  return kInW;
}
 
void DiscusMultipleScatteringCorrection::prepareQSQ(double qmax) {
  for (auto &SQWSMapping : m_SQWSs) {
    auto &SQWS = SQWSMapping.SQ;
    std::shared_ptr<DiscusData2D> outputWS = SQWS->createCopy(true);
    std::vector<double> IOfQYFull;
    // loop through the S(Q) spectra for the different energy transfer values
    for (size_t iW = 0; iW < SQWS->getNumberHistograms(); iW++) {
      std::vector<double> qValues = SQWS->histogram(iW).X;
      std::vector<double> SQValues = SQWS->histogram(iW).Y;
      // add terminating points at 0 and qmax before multiplying by Q so no extrapolation problems
      if (qValues.front() > 0.) {
        qValues.insert(qValues.begin(), 0.);
        SQValues.insert(SQValues.begin(), SQValues.front());
      }
      if (qValues.back() < qmax) {
        qValues.push_back(qmax);
        SQValues.push_back(SQValues.back());
      }
      // add some extra points to help the Q.S(Q) integral get the right answer
      for (size_t i = 1; i < qValues.size(); i++) {
        if (std::abs(SQValues[i] - SQValues[i - 1]) >
            std::numeric_limits<double>::epsilon() * std::min(SQValues[i - 1], SQValues[i])) {
          qValues.insert(qValues.begin() + i, std::nextafter(qValues[i], -DBL_MAX));
          SQValues.insert(SQValues.begin() + i, SQValues[i - 1]);
          i++;
        }
      }
 
      std::vector<double> QSQValues;
      std::transform(SQValues.begin(), SQValues.end(), qValues.begin(), std::back_inserter(QSQValues),
                     std::multiplies<double>());
 
      outputWS->histogram(iW).X.resize(qValues.size());
      outputWS->histogram(iW).X = qValues;
      outputWS->histogram(iW).Y.resize(QSQValues.size());
      outputWS->histogram(iW).Y = QSQValues;
    }
    SQWSMapping.QSQ = outputWS;
  }
}
 
std::tuple<std::vector<double>, std::vector<double>, std::vector<double>>
DiscusMultipleScatteringCorrection::integrateQSQ(const std::shared_ptr<DiscusData2D> &QSQ, double kinc,
                                                 const bool returnCumulative) {
  std::vector<double> IOfQYFull, qValuesFull, wIndices;
  double IOfQMaxPreviousRow = 0.;
 
  auto &wValues = QSQ->getSpecAxisValues();
  std::vector<double> wWidths;
  if (wValues.size() == 1) {
    // convertToBinBoundary currently gives width of 1 for single point but because this is essential for the maths
    // set the width to 1 explicitly
    wWidths.push_back(1.);
  } else {
    std::vector<double> wBinEdges;
    wBinEdges.reserve(wValues.size() + 1);
    VectorHelper::convertToBinBoundary(wValues, wBinEdges);
    std::adjacent_difference(wBinEdges.begin(), wBinEdges.end(), std::back_inserter(wWidths));
    wWidths.erase(wWidths.begin()); // first element returned by adjacent_difference isn't a diff so delete it
  }
 
  double wMax = fromWaveVector(kinc);
  auto it = std::lower_bound(wValues.begin(), wValues.end(), wMax);
  size_t iFirstInaccessibleW = std::distance(wValues.begin(), it);
  auto nAccessibleWPoints = iFirstInaccessibleW;
 
  // loop through the S(Q) spectra for the different energy transfer values
  std::vector<double> IOfQX, IOfQY;
  // reserve minimum space required for performance
  IOfQYFull.reserve(nAccessibleWPoints);
  qValuesFull.reserve(nAccessibleWPoints);
  wIndices.reserve(nAccessibleWPoints);
  //}
  for (size_t iW = 0; iW < nAccessibleWPoints; iW++) {
    auto kf = getKf((wValues)[iW], kinc);
    auto [qmin, qrange] = getKinematicRange(kf, kinc);
    IOfQX.clear();
    IOfQY.clear();
    integrateCumulative(QSQ->histogram(iW), qmin, qmin + qrange, IOfQX, IOfQY, returnCumulative);
    // w bin width for elastic will equal 1
    double wBinWidth = wWidths[iW];
    std::transform(IOfQY.begin(), IOfQY.end(), IOfQY.begin(),
                   [IOfQMaxPreviousRow, wBinWidth](double d) -> double { return d * wBinWidth + IOfQMaxPreviousRow; });
    IOfQMaxPreviousRow = IOfQY.back();
    IOfQYFull.insert(IOfQYFull.end(), IOfQY.begin(), IOfQY.end());
    qValuesFull.insert(qValuesFull.end(), IOfQX.begin(), IOfQX.end());
    wIndices.insert(wIndices.end(), IOfQX.size(), static_cast<double>(iW));
  }
  m_IkCalculations++;
  return {IOfQYFull, qValuesFull, wIndices};
}
 
void DiscusMultipleScatteringCorrection::prepareCumulativeProbForQ(
    double kinc, const ComponentWorkspaceMappings &materialWorkspaces) {
  for (size_t iMat = 0; iMat < materialWorkspaces.size(); iMat++) {
    auto QSQ = materialWorkspaces[iMat].QSQ;
    auto [IOfQYFull, qValuesFull, wIndices] = integrateQSQ(QSQ, kinc, true);
    auto IOfQYAtQMax = IOfQYFull.empty() ? 0. : IOfQYFull.back();
    if (IOfQYAtQMax == 0.)
      throw std::runtime_error("Integral of Q * S(Q) is zero so can't generate probability distribution");
    // normalise probability range to 0-1
    std::vector<double> IOfQYNorm;
    std::transform(IOfQYFull.begin(), IOfQYFull.end(), std::back_inserter(IOfQYNorm),
                   [IOfQYAtQMax](double d) -> double { return d / IOfQYAtQMax; });
    // Store the normalized integral (= cumulative probability) on the x axis
    // The y values in the two spectra store Q, w (or w index to be precise)
    auto &InvPOfQ = materialWorkspaces[iMat].InvPOfQ;
    for (size_t i = 0; i < InvPOfQ->getNumberHistograms(); i++) {
      InvPOfQ->histogram(i).X.resize(IOfQYNorm.size());
      InvPOfQ->histogram(i).X = IOfQYNorm;
    }
    InvPOfQ->histogram(0).Y.resize(qValuesFull.size());
    InvPOfQ->histogram(0).Y = qValuesFull;
    InvPOfQ->histogram(1).Y.resize(wIndices.size());
    InvPOfQ->histogram(1).Y = wIndices;
  }
}
 
void DiscusMultipleScatteringCorrection::convertToLogWorkspace(const std::shared_ptr<DiscusData2D> &SOfQ) {
  // generate log of the structure factor to support gaussian interpolation
 
  for (size_t i = 0; i < SOfQ->getNumberHistograms(); i++) {
    auto &ySQ = SOfQ->histogram(i).Y;
 
    std::transform(ySQ.begin(), ySQ.end(), ySQ.begin(), [](double d) -> double {
      const double exp_that_gives_close_to_zero = -20.0;
      if (d == 0.)
        return exp_that_gives_close_to_zero;
      else
        return std::log(d);
    });
  }
}
 
void DiscusMultipleScatteringCorrection::calculateQSQIntegralAsFunctionOfK(ComponentWorkspaceMappings &matWSs,
                                                                           const std::vector<double> &specialKs) {
  for (auto &SQWSMapping : matWSs) {
    std::vector<double> finalkValues, QSQIntegrals;
    if (m_EMode == DeltaEMode::Elastic) {
      // Optimize performance by doing cumulative integral first at each q in S(Q) and then calculate integral for each
      // k by topping up those results
      double kMax = specialKs.back();
      std::vector<double> IOfQYFull, qValuesFull;
      std::tie(IOfQYFull, qValuesFull, std::ignore) = integrateQSQ(SQWSMapping.QSQ, kMax, true);
      for (auto k : specialKs) {
        auto qUpperLimit = 2 * k;
        auto iterPrevIntegral = std::upper_bound(qValuesFull.begin(), qValuesFull.end(), qUpperLimit) - 1;
        auto idxPrevIntegral = static_cast<size_t>(std::distance(qValuesFull.begin(), iterPrevIntegral));
        std::vector<double> ignoreVector, topUpIntegral;
        integrateCumulative(SQWSMapping.QSQ->histogram(0), *iterPrevIntegral, qUpperLimit, ignoreVector, topUpIntegral,
                            false);
        double IOfQY = IOfQYFull[idxPrevIntegral] + topUpIntegral[0];
        if (IOfQY > 0) {
          double normalisedIntegral = IOfQY / (2 * k * k);
          finalkValues.push_back(k);
          QSQIntegrals.push_back(normalisedIntegral);
        }
      }
    } else {
      // Calculate the integral for a range of k values. Not massively important which k values but choose them here
      // based on the q points in the S(Q) profile and the initial k values incident on the sample
      std::set<double> kValues(specialKs.begin(), specialKs.end());
      const std::vector<double> qValues = SQWSMapping.SQ->histogram(0).X;
      for (auto q : qValues) {
        if (q > 0)
          kValues.insert(q / 2);
      }
 
      // add a few extra points beyond supplied q range to ensure capture asymptotic value of integral/2*k*k.
      // Useful when doing a flat interpolation on m_QSQIntegral during inelastic calculation where k not known up front
      double maxSuppliedQ = qValues.back();
      if (maxSuppliedQ > 0.) {
        kValues.insert(maxSuppliedQ);
        kValues.insert(2 * maxSuppliedQ);
      }
 
      for (auto k : kValues) {
        std::vector<double> IOfQYFull;
        std::tie(IOfQYFull, std::ignore, std::ignore) = integrateQSQ(SQWSMapping.QSQ, k, false);
        auto IOfQYAtQMax = IOfQYFull.empty() ? 0. : IOfQYFull.back();
        // going to divide by this so storing zero results not useful - and don't want to interpolate a zero value
        // into a k region where the integral is actually non-zero
        if (IOfQYAtQMax > 0) {
          double normalisedIntegral = IOfQYAtQMax / (2 * k * k);
          finalkValues.push_back(k);
          QSQIntegrals.push_back(normalisedIntegral);
        }
      }
    }
    auto QSQScaleFactor = std::make_shared<DiscusData1D>(DiscusData1D{finalkValues, QSQIntegrals});
    SQWSMapping.QSQScaleFactor = QSQScaleFactor;
  }
}
 
void DiscusMultipleScatteringCorrection::integrateCumulative(const DiscusData1D &h, const double xmin,
                                                             const double xmax, std::vector<double> &resultX,
                                                             std::vector<double> &resultY,
                                                             const bool returnCumulative) {
  assert(h.X.size() == h.Y.size());
  const std::vector<double> &xValues = h.X;
  const std::vector<double> &yValues = h.Y;
 
  // set the integral to zero at xmin
  if (returnCumulative) {
    resultX.emplace_back(xmin);
    resultY.emplace_back(0.);
  }
  double sum = 0;
 
  // ensure there's a point at xmin
  if (xValues.front() > xmin)
    throw std::runtime_error("Distribution doesn't extend as far as lower integration limit, x=" +
                             std::to_string(xmin));
  // ...and a terminating point. Q.S(Q) generally not flat so assuming flat extrapolation not v useful
  if (xValues.back() < xmax)
    throw std::runtime_error("Distribution doesn't extend as far as upper integration limit, x=" +
                             std::to_string(xmax));
 
  auto iter = std::upper_bound(xValues.cbegin(), xValues.cend(), xmin);
  auto iRight = static_cast<size_t>(std::distance(xValues.cbegin(), iter));
 
  auto linearInterp = [&xValues, &yValues](const double x, const size_t lIndex, const size_t rIndex) -> double {
    return (yValues[lIndex] * (xValues[rIndex] - x) + yValues[rIndex] * (x - xValues[lIndex])) /
           (xValues[rIndex] - xValues[lIndex]);
  };
  double yToUse;
 
  // deal with partial initial segments
  if (xmin > xValues[iRight - 1]) {
    if (xmax >= xValues[iRight]) {
      double interpY = linearInterp(xmin, iRight - 1, iRight);
      yToUse = 0.5 * (interpY + yValues[iRight]);
      sum += yToUse * (xValues[iRight] - xmin);
      if (returnCumulative) {
        resultX.push_back(xValues[iRight]);
        resultY.push_back(sum);
      }
      iRight++;
    } else {
      double interpY1 = linearInterp(xmin, iRight - 1, iRight);
      double interpY2 = linearInterp(xmax, iRight - 1, iRight);
      yToUse = 0.5 * (interpY1 + interpY2);
      sum += yToUse * (xmax - xmin);
      if (returnCumulative) {
        resultX.push_back(xmax);
        resultY.push_back(sum);
      }
      iRight++;
    }
  }
 
  // integrate the intervals between each pair of points. Do this until right point is at end of vector or > xmax
  for (; iRight < xValues.size() && xValues[iRight] <= xmax; iRight++) {
    yToUse = 0.5 * (yValues[iRight - 1] + yValues[iRight]);
    double xLeft = xValues[iRight - 1];
    double xRight = xValues[iRight];
    sum += yToUse * (xRight - xLeft);
    if (returnCumulative) {
      if (xRight > std::nextafter(xLeft, DBL_MAX)) {
        resultX.emplace_back(xRight);
        resultY.emplace_back(sum);
      }
    }
  }
 
  // integrate a partial final interval if xmax is between points
  if ((xmax > xValues[iRight - 1]) && (xmin <= xValues[iRight - 1])) {
    double interpY = linearInterp(xmax, iRight - 1, iRight);
    yToUse = 0.5 * (yValues[iRight - 1] + interpY);
    sum += yToUse * (xmax - xValues[iRight - 1]);
    if (returnCumulative) {
      resultX.emplace_back(xmax);
      resultY.emplace_back(sum);
    }
  }
  if (!returnCumulative) {
    resultX.emplace_back(xmax);
    resultY.emplace_back(sum);
  }
}
 
API::MatrixWorkspace_sptr DiscusMultipleScatteringCorrection::integrateWS(const API::MatrixWorkspace_sptr &ws) {
  // don't call integrateCumulative function because want error calculation and support for bin edges
  auto integrateAlgorithm = this->createChildAlgorithm("Integration");
  integrateAlgorithm->initialize();
  integrateAlgorithm->setProperty("InputWorkspace", ws);
  integrateAlgorithm->setProperty("OutputWorkspace", "_");
  integrateAlgorithm->execute();
  MatrixWorkspace_sptr wsIntegrals = integrateAlgorithm->getProperty("OutputWorkspace");
  for (size_t i = 0; i < wsIntegrals->getNumberHistograms(); i++)
    wsIntegrals->setPoints(i, std::vector<double>{0.});
  return wsIntegrals;
}
 
std::tuple<double, double> DiscusMultipleScatteringCorrection::new_vector(const Material &material, double k,
                                                                          bool specialSingleScatterCalc) {
  double scatteringXSection, absorbXsection;
  if (specialSingleScatterCalc) {
    absorbXsection = 0;
  } else {
    const double wavelength = 2 * M_PI / k;
    absorbXsection = material.absorbXSection(wavelength);
  }
  if (m_sigmaSS) {
    scatteringXSection = interpolateFlat(*m_sigmaSS, k);
  } else {
    scatteringXSection = material.totalScatterXSection();
  }
 
  const auto sig_total = scatteringXSection + absorbXsection;
  return {sig_total, scatteringXSection};
}
 
std::tuple<double, int>
DiscusMultipleScatteringCorrection::sampleQW(const std::shared_ptr<DiscusData2D> &CumulativeProb, double x) {
  return {interpolateSquareRoot(CumulativeProb->histogram(0), x),
          static_cast<int>(interpolateFlat(CumulativeProb->histogram(1), x))};
}
 
double DiscusMultipleScatteringCorrection::interpolateSquareRoot(const DiscusData1D &histToInterpolate, double x) {
  const auto &histx = histToInterpolate.X;
  const auto &histy = histToInterpolate.Y;
  assert(histToInterpolate.X.size() == histToInterpolate.Y.size());
  if (x > histx.back()) {
    return histy.back();
  }
  if (x < histx.front()) {
    return histy.front();
  }
  const auto iter = std::upper_bound(histx.cbegin(), histx.cend(), x);
  const auto idx = static_cast<size_t>(std::distance(histx.cbegin(), iter) - 1);
  const double x0 = histx[idx];
  const double x1 = histx[idx + 1];
  const double asq = (pow(histy[idx + 1], 2) - pow(histy[idx], 2)) / (x1 - x0);
  if (asq == 0.) {
    throw std::runtime_error("Cannot perform square root interpolation on supplied distribution");
  }
  const double b = x0 - pow(histy[idx], 2) / asq;
  return sqrt(asq * (x - b));
}
 
double DiscusMultipleScatteringCorrection::interpolateFlat(const DiscusData1D &histToInterpolate, double x) {
  auto &xHisto = histToInterpolate.X;
  auto &yHisto = histToInterpolate.Y;
  if (x > xHisto.back()) {
    return yHisto.back();
  }
  if (x < xHisto.front()) {
    return yHisto.front();
  }
  // may be useful at some point to introduce a tolerance here in case x is just below a step change but seems to behave
  // OK for now
  auto iter = std::upper_bound(xHisto.cbegin(), xHisto.cend(), x);
  auto idx = static_cast<size_t>(std::distance(xHisto.cbegin(), iter) - 1);
  return yHisto[idx];
}
 
double DiscusMultipleScatteringCorrection::interpolateGaussian(const DiscusData1D &histToInterpolate, double x) {
  // could have written using points() method so it also worked on histogram data but found that the points
  // method was bottleneck on multithreaded code due to cow_ptr atomic_load
  assert(histToInterpolate.X.size() == histToInterpolate.Y.size());
  if (x > histToInterpolate.X.back()) {
    return exp(histToInterpolate.Y.back());
  }
  if (x < histToInterpolate.X.front()) {
    return exp(histToInterpolate.Y.front());
  }
  // assume log(cross section) is quadratic in k
  auto deltax = histToInterpolate.X[1] - histToInterpolate.X[0];
 
  auto iter = std::upper_bound(histToInterpolate.X.cbegin(), histToInterpolate.X.cend(), x);
  auto idx = static_cast<size_t>(std::distance(histToInterpolate.X.cbegin(), iter) - 1);
 
  // need at least two points to the right of the x value for the quadratic
  // interpolation to work
  auto ny = histToInterpolate.Y.size();
  if (ny < 3) {
    throw std::runtime_error("Need at least 3 y values to perform quadratic interpolation");
  }
  if (idx > ny - 3) {
    idx = ny - 3;
  }
  // this interpolation assumes the set of 3 bins\point have the same width
  // U=0 on point or bin edge to the left of where x lies
  const auto U = (x - histToInterpolate.X[idx]) / deltax;
  const auto &y = histToInterpolate.Y;
  const auto A = (y[idx] - 2 * y[idx + 1] + y[idx + 2]) / 2;
  const auto B = (-3 * y[idx] + 4 * y[idx + 1] - y[idx + 2]) / 2;
  const auto C = y[idx];
  return exp(A * U * U + B * U + C);
}
 
double DiscusMultipleScatteringCorrection::Interpolate2D(const ComponentWorkspaceMapping &SQWSMapping, double q,
                                                         double w) {
  double SQ = 0.;
  int iW = -1;
  auto &wValues = SQWSMapping.SQ->getSpecAxisValues();
  if (wValues.size() == 1) {
    // don't use indexOfValue here because for single point it invents a bin width of +/-0.5
    if (w == (wValues)[0])
      iW = 0;
  } else
    try {
      // required w values will often equal the points in the S(Q,w) distribution so pick nearest value
      iW = static_cast<int>(Kernel::VectorHelper::indexOfValueFromCentersNoThrow(wValues, w));
    } catch (std::out_of_range &) {
    }
  if (iW >= 0) {
    if (m_importanceSampling)
      // the square root interpolation used to look up Q, w in InvPOfQ is based on flat interpolation of S(Q) so use
      // same interpolation here for consistency
      SQ = interpolateFlat(SQWSMapping.SQ->histogram(iW), q);
    else
      SQ = interpolateGaussian(SQWSMapping.logSQ->histogram(iW), q);
  }
 
  return SQ;
}
 
GNU_DIAG_OFF("free-nonheap-object")
 
 
std::tuple<std::vector<double>, std::vector<double>> DiscusMultipleScatteringCorrection::simulatePaths(
    const int nPaths, const int nScatters, Kernel::PseudoRandomNumberGenerator &rng,
    const ComponentWorkspaceMappings &componentWorkspaces, const double kinc, const std::vector<double> &wValues,
    bool specialSingleScatterCalc, const Mantid::Geometry::DetectorInfo &detectorInfo, const size_t &histogramIndex) {
  // countZeroWeights for debugging and analysis of where importance sampling may help
  std::vector<int> countZeroWeights(wValues.size(), 0);
  std::vector<double> sumOfWeights(wValues.size(), 0.);
  std::vector<double> weightsMeans(wValues.size(), 0.), deltas(wValues.size(), 0.), weightsM2(wValues.size(), 0.),
      weightsErrors(wValues.size(), 0.);
 
  for (int ie = 0; ie < nPaths; ie++) {
    auto [success, weights] = scatter(nScatters, rng, componentWorkspaces, kinc, wValues, specialSingleScatterCalc,
                                      detectorInfo, histogramIndex);
    if (success) {
      std::transform(weights.begin(), weights.end(), sumOfWeights.begin(), sumOfWeights.begin(), std::plus<double>());
      std::transform(weights.begin(), weights.end(), countZeroWeights.begin(), countZeroWeights.begin(),
                     [](double d, int count) { return d > 0. ? count : count + 1; });
 
      // increment standard deviation using Welford algorithm
      for (size_t i = 0; i < wValues.size(); i++) {
        deltas[i] = weights[i] - weightsMeans[i];
        weightsMeans[i] += deltas[i] / static_cast<double>(ie + 1);
        weightsM2[i] += deltas[i] * (weights[i] - weightsMeans[i]);
        // calculate sample SD (M2/n-1)
        // will give NaN for m_events=1, but that's correct
        weightsErrors[i] = sqrt(weightsM2[i] / static_cast<double>(ie));
      }
 
    } else
      ie--;
  }
  for (size_t i = 0; i < wValues.size(); i++) {
    sumOfWeights[i] = sumOfWeights[i] / nPaths;
    weightsErrors[i] = weightsErrors[i] / sqrt(nPaths);
  }
 
  return {sumOfWeights, weightsErrors};
}
 
GNU_DIAG_ON("free-nonheap-object")
 
 
std::tuple<bool, std::vector<double>> DiscusMultipleScatteringCorrection::scatter(
    const int nScatters, Kernel::PseudoRandomNumberGenerator &rng,
    const ComponentWorkspaceMappings &componentWorkspaces, const double kinc, const std::vector<double> &wValues,
    bool specialSingleScatterCalc, const Mantid::Geometry::DetectorInfo &detectorInfo, const size_t &histogramIndex) {
 
  double weight = 1;
 
  auto track = start_point(rng);
  auto shapeObjectWithScatter =
      updateWeightAndPosition(track, weight, kinc, rng, specialSingleScatterCalc, componentWorkspaces);
  double scatteringXSection;
  std::tie(std::ignore, scatteringXSection) =
      new_vector(shapeObjectWithScatter->material(), kinc, specialSingleScatterCalc);
 
  auto currentComponentWorkspaces = componentWorkspaces;
  double k = kinc;
  for (int iScat = 0; iScat < nScatters - 1; iScat++) {
    if ((k != kinc)) {
      if (m_importanceSampling) {
        auto newComponentWorkspaces = componentWorkspaces;
        for (auto &SQWSMapping : currentComponentWorkspaces)
          SQWSMapping.InvPOfQ = SQWSMapping.InvPOfQ->createCopy();
        prepareCumulativeProbForQ(k, newComponentWorkspaces);
        currentComponentWorkspaces = std::move(newComponentWorkspaces);
      }
    }
    auto trackStillAlive =
        q_dir(track, shapeObjectWithScatter, currentComponentWorkspaces, k, scatteringXSection, rng, weight);
    if (!trackStillAlive)
      return {true, std::vector<double>(wValues.size(), 0.)};
    int nlinks = m_sampleShape->interceptSurface(track);
    if (m_env) {
      nlinks += m_env->interceptSurfaces(track);
      m_callsToInterceptSurface += m_env->nelements();
    }
    m_callsToInterceptSurface++;
    if (nlinks == 0) {
      return {false, {0.}};
    }
    shapeObjectWithScatter =
        updateWeightAndPosition(track, weight, k, rng, specialSingleScatterCalc, componentWorkspaces);
    std::tie(std::ignore, scatteringXSection) =
        new_vector(shapeObjectWithScatter->material(), k, specialSingleScatterCalc);
  }
 
  bool considerCollimator = getProperty("RadialCollimator");
  if (considerCollimator) {
    const auto &samplePos = detectorInfo.samplePosition();
    auto hexahedron = createCollimatorHexahedronShape(samplePos, detectorInfo, histogramIndex);
    // zero the paths if the final scatter point is not inside the collimatorCorridor shape or the collimator shape is
    // not as expected
    if ((!hexahedron) || (!hexahedron->isValid(track.startPoint())))
      return {true, std::vector<double>(wValues.size(), 0.)};
  }
 
  const auto &detPos = detectorInfo.position(histogramIndex);
  Kernel::V3D directionToDetector = detPos - track.startPoint();
  Kernel::V3D prevDirection = track.direction();
  directionToDetector.normalize();
  track.reset(track.startPoint(), directionToDetector);
  int nlinks = m_sampleShape->interceptSurface(track);
  m_callsToInterceptSurface++;
  if (m_env) {
    nlinks += m_env->interceptSurfaces(track);
    m_callsToInterceptSurface += m_env->nelements();
  }
  // due to VALID_INTERCEPT_POINT_SHIFT some tracks that skim the surface
  // of a CSGObject sample may not generate valid tracks. Start over again
  // for this event
  if (nlinks == 0) {
    return {false, {0.}};
  }
  std::vector<double> weights;
  auto scatteringXSectionFull = shapeObjectWithScatter->material().totalScatterXSection();
  // Step through required overall energy transfer (w) values and work out what
  // w that means for the final scatter. There will be a single w value for elastic
  // Slightly different approach to original DISCUS code. It stepped through the w values
  // in the supplied S(Q,w) distribution and applied each one to the final scatter. If
  // this resulted in an overall w that equalled one of the required w values it was output.
  // That approach implicitly assumed S(Q,w)=0 where not specified and that no interpolation
  // on w would be needed - this may be what's required but seems possible it might not always be
  for (auto &w : wValues) {
    const double finalE = fromWaveVector(kinc) - w;
    if (finalE > 0) {
      const double kout = toWaveVector(finalE);
      const auto qVector = directionToDetector * kout - prevDirection * k;
      const double q = qVector.norm();
      const double finalW = fromWaveVector(k) - finalE;
      auto componentWSIt = findMatchingComponent(componentWorkspaces, shapeObjectWithScatter);
      auto &componentWSMapping = *componentWSIt; // to help debugging
      double SQ = Interpolate2D(componentWSMapping, q, finalW);
      scatteringXSection = m_NormalizeSQ ? scatteringXSection / interpolateFlat(*(componentWSMapping.QSQScaleFactor), k)
                                         : scatteringXSectionFull;
 
      double AT2 = 1;
      for (auto it = track.cbegin(); it != track.cend(); it++) {
        double sigma_total;
        auto &materialPassingThrough = it->object->material();
        std::tie(sigma_total, std::ignore) = new_vector(materialPassingThrough, kout, specialSingleScatterCalc);
        double numberDensity = materialPassingThrough.numberDensityEffective();
        double vmu = 100 * numberDensity * sigma_total;
        if (specialSingleScatterCalc)
          vmu = 0;
        const double dl = it->distInsideObject;
        AT2 *= exp(-dl * vmu);
      }
      weights.emplace_back(weight * AT2 * SQ * scatteringXSection / (4 * M_PI));
    } else {
      weights.emplace_back(0.);
    }
  }
  return {true, weights};
}
 
/*
 * Construct a hexahedron shape extending from the detector's front face across the collimator openning window toward
 the sample with a legth as twice the distance from sample to detector.
 */
const std::shared_ptr<Geometry::CSGObject> DiscusMultipleScatteringCorrection::createCollimatorHexahedronShape(
    const Kernel::V3D &samplePos, const Mantid::Geometry::DetectorInfo &detectorInfo, const size_t &histogramIndex) {
  const auto shape = detectorInfo.detector(histogramIndex).shape();
  if (!shape || (shape->shape() != Mantid::Geometry::detail::ShapeInfo::GeometryShape::CUBOID)) {
    return nullptr;
  }
 
  try {
    shape->shapeInfo();
  } catch (std::exception &) {
    return nullptr;
  }
 
  const auto colCorridorShape = readFromCollimatorCorridorCache(histogramIndex);
  if (colCorridorShape) {
    return colCorridorShape;
  }
 
  const auto &detectorId = detectorInfo.detector(histogramIndex).getID();
  const auto &detectorAbsolPos = detectorInfo.position(detectorInfo.indexOf(detectorId));
  const auto cuboidGeometry = shape->shapeInfo().cuboidGeometry();
 
  // Positions of the detector's front face
  const auto &detLeftFrontBottomPos = detectorAbsolPos + cuboidGeometry.leftFrontBottom;
  const auto &detLeftFrontTopPos = detectorAbsolPos + cuboidGeometry.leftFrontTop;
  const auto &detRightFrontBottomPos = detectorAbsolPos + cuboidGeometry.rightFrontBottom;
  const auto detRightFrontTopPos = detLeftFrontTopPos + detRightFrontBottomPos - detLeftFrontBottomPos;
 
  const auto detCentrePos =
      (detLeftFrontBottomPos + detLeftFrontTopPos + detRightFrontBottomPos + detRightFrontTopPos) / 4.0;
  const auto detTopMiddlePos = (detLeftFrontTopPos + detRightFrontTopPos) / 2.0;
 
  // Sanity check to avoid dividing by zero
  if ((detRightFrontTopPos == detLeftFrontTopPos) || (detTopMiddlePos == detCentrePos) || (detCentrePos == samplePos)) {
    return nullptr;
  }
 
  // Define the unit vectors needed for calculations
  const auto unitVecSampleToDet = Kernel::normalize(detCentrePos - samplePos);
  const auto unitVecLeftToRight = Kernel::normalize(
      V3D(-1.0 * unitVecSampleToDet.Z(), 0,
          -1.0 * unitVecSampleToDet.X())); // this is a vector normal to unitVecSampleToDet on XZ plane
 
  const auto colOpenningLeftTopPos =
      (unitVecSampleToDet * m_collimatorInfo->m_innerRadius * cos(m_collimatorInfo->m_halfAngularExtent)) + samplePos +
      (m_collimatorInfo->m_axisVec * (m_collimatorInfo->m_plateHeight / 2.0)) -
      (unitVecLeftToRight * m_collimatorInfo->m_innerRadius * sin(m_collimatorInfo->m_halfAngularExtent));
  const auto colOpenningRightTopPos =
      (unitVecSampleToDet * m_collimatorInfo->m_innerRadius * cos(m_collimatorInfo->m_halfAngularExtent)) + samplePos +
      (m_collimatorInfo->m_axisVec * (m_collimatorInfo->m_plateHeight / 2.0)) +
      (unitVecLeftToRight * m_collimatorInfo->m_innerRadius * sin(m_collimatorInfo->m_halfAngularExtent));
  const auto colOpenningLeftBottomPos =
      (unitVecSampleToDet * m_collimatorInfo->m_innerRadius * cos(m_collimatorInfo->m_halfAngularExtent)) + samplePos -
      (m_collimatorInfo->m_axisVec * (m_collimatorInfo->m_plateHeight / 2.0)) -
      (unitVecLeftToRight * m_collimatorInfo->m_innerRadius * sin(m_collimatorInfo->m_halfAngularExtent));
  const auto colOpenningRightBottomPos =
      (unitVecSampleToDet * m_collimatorInfo->m_innerRadius * cos(m_collimatorInfo->m_halfAngularExtent)) + samplePos -
      (m_collimatorInfo->m_axisVec * (m_collimatorInfo->m_plateHeight / 2.0)) +
      (unitVecLeftToRight * m_collimatorInfo->m_innerRadius * sin(m_collimatorInfo->m_halfAngularExtent));
 
  // Sanity check to avoid dividing by zero
  if ((colOpenningLeftTopPos == detLeftFrontTopPos) || (colOpenningLeftBottomPos == detLeftFrontBottomPos) ||
      (colOpenningRightTopPos == detRightFrontTopPos) || (colOpenningRightBottomPos == detRightFrontBottomPos)) {
    return nullptr;
  }
 
  // Unit vectors along the sides of hexahedron shape
  const auto unitVecAlongLeftTopLeg = Kernel::normalize(colOpenningLeftTopPos - detLeftFrontTopPos);
  const auto unitVecAlongLeftBottomLeg = Kernel::normalize(colOpenningLeftBottomPos - detLeftFrontBottomPos);
  const auto unitVecAlongRightTopLeg = Kernel::normalize(colOpenningRightTopPos - detRightFrontTopPos);
  const auto unitVecAlongRightBottomLeg = Kernel::normalize(colOpenningRightBottomPos - detRightFrontBottomPos);
 
  // Positions of the hexahedron extended towards the sample for each of its legs to have a length twice the lenght of
  // sample to detector
  double sampleCentreToDetDistance = (detCentrePos - samplePos).norm();
  const auto leftFrontBottomPoint = detRightFrontTopPos + unitVecAlongRightTopLeg * sampleCentreToDetDistance * 2.0;
  const auto hexaHedronLegsLenRatio =
      (leftFrontBottomPoint - detRightFrontTopPos).norm() / (colOpenningRightTopPos - detRightFrontTopPos).norm();
  const auto leftBackBottomPoint = detLeftFrontTopPos + unitVecAlongLeftTopLeg * hexaHedronLegsLenRatio *
                                                            (colOpenningLeftTopPos - detLeftFrontTopPos).norm();
  const auto rightFrontBottomPoint =
      detRightFrontBottomPos +
      unitVecAlongRightBottomLeg * hexaHedronLegsLenRatio * (colOpenningRightBottomPos - detRightFrontBottomPos).norm();
  const auto rightBackBottomPoint =
      detLeftFrontBottomPos +
      unitVecAlongLeftBottomLeg * hexaHedronLegsLenRatio * (colOpenningLeftBottomPos - detLeftFrontBottomPos).norm();
  std::ostringstream xmlShapeStream;
  xmlShapeStream << "<hexahedron id=\"corridor-shape\" >"
                 << "<left-back-bottom-point x=\"" << leftBackBottomPoint.X() << "\""
                 << " y=\"" << leftBackBottomPoint.Y() << "\""
                 << " z=\"" << leftBackBottomPoint.Z() << "\" />"
                 << "<left-front-bottom-point x=\"" << leftFrontBottomPoint.X() << "\""
                 << " y=\"" << leftFrontBottomPoint.Y() << "\""
                 << " z=\"" << leftFrontBottomPoint.Z() << "\" />"
                 << "<right-front-bottom-point x=\"" << rightFrontBottomPoint.X() << "\""
                 << " y=\"" << rightFrontBottomPoint.Y() << "\""
                 << " z=\"" << rightFrontBottomPoint.Z() << "\" />"
                 << "<right-back-bottom-point x=\"" << rightBackBottomPoint.X() << "\""
                 << " y=\"" << rightBackBottomPoint.Y() << "\""
                 << " z=\"" << rightBackBottomPoint.Z() << "\" />"
                 << "<left-back-top-point x=\"" << detLeftFrontTopPos.X() << "\""
                 << " y=\"" << detLeftFrontTopPos.Y() << "\""
                 << " z=\"" << detLeftFrontTopPos.Z() << "\" />"
                 << "<left-front-top-point x=\"" << detRightFrontTopPos.X() << "\""
                 << " y=\"" << detRightFrontTopPos.Y() << "\""
                 << " z=\"" << detRightFrontTopPos.Z() << "\" />"
                 << "<right-front-top-point x=\"" << detRightFrontBottomPos.X() << "\""
                 << " y=\"" << detRightFrontBottomPos.Y() << "\""
                 << " z=\"" << detRightFrontBottomPos.Z() << "\" />"
                 << "<right-back-top-point x=\"" << detLeftFrontBottomPos.X() << "\""
                 << " y=\"" << detLeftFrontBottomPos.Y() << "\""
                 << " z=\"" << detLeftFrontBottomPos.Z() << "\" />"
                 << "</hexahedron>";
  Geometry::ShapeFactory shapeMaker;
  const auto collimatorCorridorCsgObj = shapeMaker.createShape(xmlShapeStream.str());
  writeToCollimatorCorridorCache(histogramIndex, collimatorCorridorCsgObj);
  return collimatorCorridorCsgObj;
}
 
const std::shared_ptr<Geometry::CSGObject>
DiscusMultipleScatteringCorrection::readFromCollimatorCorridorCache(const std::size_t &histogramIndex) {
  std::shared_lock<std::shared_mutex> guard(m_mutexCorridorCache);
  const auto itCollimatorCorridor = m_collimatorCorridorCache.find(histogramIndex);
  if (itCollimatorCorridor != m_collimatorCorridorCache.end()) {
    return itCollimatorCorridor->second;
  }
  return nullptr;
}
 
void DiscusMultipleScatteringCorrection::writeToCollimatorCorridorCache(
    const std::size_t &histogramIndex, const std::shared_ptr<Geometry::CSGObject> &collimatorCorridorCsgObj) {
  std::unique_lock<std::shared_mutex> guard(m_mutexCorridorCache);
  m_collimatorCorridorCache[histogramIndex] = collimatorCorridorCsgObj;
}
 
void DiscusMultipleScatteringCorrection::loadCollimatorInfo() {
  m_collimatorCorridorCache.clear(); // Clear the cache for collimator corridor shapes
  const bool radialCollimator = getProperty("RadialCollimator");
  if (radialCollimator) {
    m_collimatorInfo = std::make_unique<CollimatorInfo>();
    // Collimator inner radius
    m_collimatorInfo->m_innerRadius = getDoubleParamFromIDF("col-radius");
    // Half of the angular extent of the collimator seen from the sample
    m_collimatorInfo->m_halfAngularExtent = 0.5 * getDoubleParamFromIDF("col-angular-extent");
    // Height of collimator plate
    m_collimatorInfo->m_plateHeight = getDoubleParamFromIDF("col-plate-height");
    m_collimatorInfo->m_axisVec = getV3DParamFromIDF("col-axis");
  }
}
 
double DiscusMultipleScatteringCorrection::getDoubleParamFromIDF(std::string paramName) {
  if (!m_instrument->hasParameter(paramName)) {
    throw std::runtime_error("Cannot find parameter:" + paramName + " from instrument parameter file");
  }
  std::vector<double> val_vec = m_instrument->getNumberParameter(paramName, true);
  if (val_vec.empty()) {
    throw std::runtime_error("No value specified for:" + paramName + " in the instrument parameter file");
  }
 
  return static_cast<double>(val_vec.front());
}
 
Kernel::V3D DiscusMultipleScatteringCorrection::getV3DParamFromIDF(std::string paramName) {
  if (!m_instrument->hasParameter(paramName)) {
    throw std::runtime_error("Cannot find parameter:" + paramName + " from instrument parameter file");
  }
 
  std::string paramValStr = m_instrument->getStringParameter(paramName)[0];
  std::vector<std::string> v3dStrComponent;
  boost::split(v3dStrComponent, paramValStr, boost::is_any_of(","));
  if (v3dStrComponent.size() != 3) {
    throw std::runtime_error("Invalid number of coordinates given for parameter:" + paramName +
                             " in instrument parameter file");
  }
  std::vector<double> v3dComponents(3);
  std::transform(v3dStrComponent.begin(), v3dStrComponent.end(), v3dComponents.begin(),
                 [](const std::string &str) -> double { return std::stod(str); });
 
  return Kernel::V3D(v3dComponents[0], v3dComponents[1], v3dComponents[2]);
}
 
double DiscusMultipleScatteringCorrection::getKf(const double deltaE, const double kinc) {
  double kf;
  if (deltaE == 0.) {
    kf = kinc; // avoid costly sqrt
  } else {
    // slightly concerned that rounding errors moving between k and E may mean we take the sqrt of
    // a negative number in here. deltaE was capped using a threshold calculated using fromWaveVector so
    // hopefully any rounding will affect fromWaveVector(kinc) in same direction
    kf = toWaveVector(fromWaveVector(kinc) - deltaE);
    assert(!std::isnan(kf));
  }
  return kf;
} // namespace Mantid::Algorithms
 
std::tuple<double, double> DiscusMultipleScatteringCorrection::getKinematicRange(double kf, double ki) {
  const double qmin = abs(kf - ki);
  const double qrange = 2 * std::min(ki, kf);
  return {qmin, qrange};
}
std::tuple<double, double, int, double>
DiscusMultipleScatteringCorrection::sampleQWUniform(const std::vector<double> &wValues,
                                                    Kernel::PseudoRandomNumberGenerator &rng, const double kinc) {
 
  // in order to keep integration limits constant sample full range of w even if some not kinematically accessible
  // Note - Discus took different approach where it sampled q,w from kinematically accessible range only but it
  // only calculated for double scattering and easier to normalise in that case
  double wRange;
  /*
  // The rectangular integration region could be restricted further by limiting w range by calculating max possible w
  // TO DO: validate the results for this optimisation
  // the energy transfer must always be less than the positive value corresponding to energy going from ki to 0
  // Note - this is still the case for indirect because on a multiple scatter the kf isn't kfixed
  double wMax = fromWaveVector(kinc);
  // find largest w bin centre that is < wmax and then sample w up to the next bin edge
  auto it = std::lower_bound(wValues.begin(), wValues.end(), wMax);
  int iWMax = static_cast<int>(std::distance(wValues.begin(), it) - 1);*/
  int iW = 0;
  if (wValues.size() == 1) {
    iW = 0;
    wRange = 1;
  } else {
    std::vector<double> wBinEdges;
    wBinEdges.reserve(wValues.size() + 1);
    VectorHelper::convertToBinBoundary(wValues, wBinEdges);
    // w bins not necessarily equal so don't just sample w index
    wRange = /*std::min(wMax, wBinEdges[iWMax + 1])*/ wBinEdges.back() - wBinEdges.front();
    double w = wBinEdges.front() + rng.nextValue() * wRange;
    iW = static_cast<int>(Kernel::VectorHelper::indexOfValueFromCentersNoThrow(wValues, w));
  }
  double maxkf = toWaveVector(fromWaveVector(kinc) - wValues.front());
  double qRange = kinc + maxkf;
  double q = qRange * rng.nextValue();
  return {q, qRange, iW, wRange};
}
 
double DiscusMultipleScatteringCorrection::getQSQIntegral(const DiscusData1D &QSQScaleFactor, double k) {
  // the QSQIntegrals were divided by k^2 so in theory they should be ~flat
  return interpolateFlat(QSQScaleFactor, k) * 2 * k * k;
}
 
bool DiscusMultipleScatteringCorrection::q_dir(Geometry::Track &track, const Geometry::IObject *shapePtr,
                                               const ComponentWorkspaceMappings &componentWorkspaces, double &k,
                                               const double scatteringXSection,
                                               Kernel::PseudoRandomNumberGenerator &rng, double &weight) {
  const double kinc = k;
  double QQ;
  int iW;
  auto componentWSIt = findMatchingComponent(componentWorkspaces, shapePtr);
  if (m_importanceSampling) {
    std::tie(QQ, iW) = sampleQW(componentWSIt->InvPOfQ, rng.nextValue());
    k = getKf(componentWSIt->SQ->getSpecAxisValues()[iW], kinc);
    weight = weight * scatteringXSection;
  } else {
    double qrange, wRange;
    auto &wValues = componentWSIt->SQ->getSpecAxisValues();
    std::tie(QQ, qrange, iW, wRange) = sampleQWUniform(wValues, rng, kinc);
    // if w inaccessible return (ie treat as zero weight) rather than retry so that integration stays over full w
    // range
    if (fromWaveVector(kinc) - wValues[iW] <= 0)
      return false;
    k = getKf(wValues[iW], kinc);
    double SQ = interpolateGaussian(componentWSIt->logSQ->histogram(iW), QQ);
    // integrate over rectangular area of qw space
    weight = weight * scatteringXSection * SQ * QQ * qrange * wRange;
    if (SQ > 0) {
      double integralQSQ = getQSQIntegral(*componentWSIt->QSQScaleFactor, kinc);
      assert(integralQSQ != 0.);
      weight = weight / integralQSQ;
    } else
      return false;
  }
  // T = 2theta
  const double cosT = (kinc * kinc + k * k - QQ * QQ) / (2 * kinc * k);
  // if q not accessible return rather than retry so that integration stays over rectangular area
  if (std::abs(cosT) > 1.0)
    return false;
 
  updateTrackDirection(track, cosT, rng.nextValue() * 2 * M_PI);
  return true;
}
 
void DiscusMultipleScatteringCorrection::updateTrackDirection(Geometry::Track &track, const double cosT,
                                                              const double phi) {
  const auto B3 = sqrt(1 - cosT * cosT);
  const auto B2 = cosT;
  // possible to do this using the Quat class instead??
  // Quat(const double _deg, const V3D &_axis);
  // Quat(acos(cosT)*180/M_PI,
  // Kernel::V3D(track.direction()[],track.direction()[],0))
 
  // Rodrigues formula with final term equal to zero
  // v_rot = cosT * v + sinT(k x v)
  // with rotation axis k orthogonal to v
  // Define k by first creating two vectors orthogonal to v:
  // (vy, -vx, 0) by inspection
  // and then (-vz * vx, -vy * vz, vx * vx + vy * vy) as cross product
  // Then define k as combination of these:
  // sin(phi) * (vy, -vx, 0) + cos(phi) * (-vx * vz, -vy * vz, 1 - vz * vz)
  // ...with division by normalisation factor of sqrt(vx * vx + vy * vy)
  // Note: xyz convention here isn't the standard Mantid one. x=beam, z=up
  const auto vy = track.direction()[0];
  const auto vz = track.direction()[1];
  const auto vx = track.direction()[2];
  double UKX, UKY, UKZ;
  if (vz * vz < 1.0) {
    // calculate A2 from vx^2 + vy^2 rather than 1-vz^2 to reduce floating point rounding error when vz close to
    // 1
    auto A2 = sqrt(vx * vx + vy * vy);
    auto UQTZ = cos(phi) * A2;
    auto UQTX = -cos(phi) * vz * vx / A2 + sin(phi) * vy / A2;
    auto UQTY = -cos(phi) * vz * vy / A2 - sin(phi) * vx / A2;
    UKX = B2 * vx + B3 * UQTX;
    UKY = B2 * vy + B3 * UQTY;
    UKZ = B2 * vz + B3 * UQTZ;
  } else {
    // definition of phi in general formula is dependent on v. So may see phi "redefinition" as vx and vy tend
    // to zero and you move from general formula to this special case
    UKX = B3 * cos(phi);
    UKY = B3 * sin(phi);
    UKZ = B2 * vz;
  }
  track.reset(track.startPoint(), Kernel::V3D(UKY, UKZ, UKX));
}
 
Geometry::Track DiscusMultipleScatteringCorrection::start_point(Kernel::PseudoRandomNumberGenerator &rng) {
  for (int i = 0; i < m_maxScatterPtAttempts; i++) {
    auto t = generateInitialTrack(rng);
    int nlinks = m_sampleShape->interceptSurface(t);
    m_callsToInterceptSurface++;
    if (m_env) {
      nlinks += m_env->interceptSurfaces(t);
      m_callsToInterceptSurface += m_env->nelements();
    }
    if (nlinks > 0) {
      if (i > 0) {
        if (g_log.is(Kernel::Logger::Priority::PRIO_WARNING)) {
          m_attemptsToGenerateInitialTrack[i + 1]++;
        }
      }
      return t;
    }
  }
  throw std::runtime_error(
      "DiscusMultipleScatteringCorrection::start_point() - Unable to generate entry point into sample after " +
      std::to_string(m_maxScatterPtAttempts) + " attempts. Try increasing MaxScatterPtAttempts");
}
 
const Geometry::IObject *DiscusMultipleScatteringCorrection::updateWeightAndPosition(
    Geometry::Track &track, double &weight, const double k, Kernel::PseudoRandomNumberGenerator &rng,
    bool specialSingleScatterCalc, const ComponentWorkspaceMappings &componentWorkspaces) {
  double totalMuL = 0.;
  auto nlinks = track.count();
  // Set default size to 5 (same as in LineIntersectVisit.h)
  boost::container::small_vector<std::tuple<const Geometry::IObject *, double, double, double>, 5> geometryObjects;
  geometryObjects.reserve(nlinks);
  // loop through all the track segments calculating some useful quantities for later
  for (auto it = track.cbegin(); it != track.cend(); it++) {
    const double trackSegLength = it->distInsideObject;
    const auto geometryObj = it->object;
    double sigma_total;
    std::tie(sigma_total, std::ignore) = new_vector(geometryObj->material(), k, specialSingleScatterCalc);
    double vmu = 100 * geometryObj->material().numberDensityEffective() * sigma_total;
    double muL = trackSegLength * vmu;
    totalMuL += muL;
    // some overlap between the quantities stored here but since calculated them all may as well store them all
    geometryObjects.emplace_back(geometryObj, vmu, muL, sigma_total);
  }
 
  // randomly sample distance travelled across a total muL and work out which component this sits in
  double b4Overall = (1.0 - exp(-totalMuL));
  double muL = -log(1 - rng.nextValue() * b4Overall);
  double vl = 0.;
  double newWeight = 0.;
  double prevExpTerms = 1.;
  std::tuple<const Geometry::IObject *, double, double, double> geometryObjectDetails;
  for (size_t i = 0; i < geometryObjects.size(); i++) {
    geometryObjectDetails = geometryObjects[i];
    auto muL_i = std::get<2>(geometryObjectDetails);
    auto vmu_i = std::get<1>(geometryObjectDetails);
    if (muL - muL_i > 0) {
      vl += muL_i / vmu_i;
      muL = muL - muL_i;
      prevExpTerms *= exp(-muL_i);
    } else {
      vl += muL / vmu_i;
      double b4 = (1.0 - exp(-muL_i)) * prevExpTerms;
      auto sigma_total = std::get<3>(geometryObjectDetails);
      newWeight = b4 / sigma_total;
      break;
    }
  }
  weight = weight * newWeight;
  // At the moment this doesn't cope if sample shape is concave eg if track has more than one segment inside the
  // sample with segment outside sample in between
  // Note - this clears the track intersections but the sample\environment shapes live on
  inc_xyz(track, vl);
  auto geometryObject = std::get<0>(geometryObjectDetails);
  if (g_log.is(Kernel::Logger::Priority::PRIO_DEBUG)) {
    auto componentIt = findMatchingComponent(componentWorkspaces, geometryObject);
    (*(componentIt->scatterCount))++;
  }
  return geometryObject;
}
 
Geometry::Track DiscusMultipleScatteringCorrection::generateInitialTrack(Kernel::PseudoRandomNumberGenerator &rng) {
  // generate random point on front surface of sample bounding box
  // The change of variables from length to t1 means this still samples the points fairly in the integration
  // volume even in shapes like cylinders where the depth varies across xy
  auto neutron = m_beamProfile->generatePoint(rng, m_activeRegion);
  auto ptx = neutron.startPos.X();
  auto pty = neutron.startPos.Y();
 
  auto ptOnBeamProfile = Kernel::V3D();
  ptOnBeamProfile[m_refframe->pointingHorizontal()] = ptx;
  ptOnBeamProfile[m_refframe->pointingUp()] = pty;
  ptOnBeamProfile[m_refframe->pointingAlongBeam()] = m_sourcePos[m_refframe->pointingAlongBeam()];
  auto toSample = Kernel::V3D();
  toSample[m_refframe->pointingAlongBeam()] = 1.;
  return Geometry::Track(ptOnBeamProfile, toSample);
}
 
void DiscusMultipleScatteringCorrection::inc_xyz(Geometry::Track &track, double vl) {
  Kernel::V3D position = track.front().entryPoint;
  Kernel::V3D direction = track.direction();
  const auto x = position[0] + vl * direction[0];
  const auto y = position[1] + vl * direction[1];
  const auto z = position[2] + vl * direction[2];
  const auto startPoint = V3D(x, y, z);
  track.clearIntersectionResults();
  track.reset(startPoint, track.direction());
}
 
std::shared_ptr<SparseWorkspace>
DiscusMultipleScatteringCorrection::createSparseWorkspace(const API::MatrixWorkspace &modelWS, const size_t nXPoints,
                                                          const size_t rows, const size_t columns) {
  auto sparseWS = std::make_shared<SparseWorkspace>(modelWS, nXPoints, rows, columns);
  return sparseWS;
}
 
void DiscusMultipleScatteringCorrection::createInvPOfQWorkspaces(ComponentWorkspaceMappings &matWSs, size_t nhists) {
  for (auto &SQWSMapping : matWSs) {
    auto &QSQ = SQWSMapping.QSQ;
    size_t expectedMaxSize =
        std::accumulate(QSQ->histograms().cbegin(), QSQ->histograms().cend(), static_cast<size_t>(0),
                        [](const size_t value, const DiscusData1D &histo) { return value + histo.Y.size(); });
    auto ws = std::make_shared<DiscusData2D>(std::vector<DiscusData1D>(nhists), nullptr);
    ws->histogram(0).X.reserve(expectedMaxSize);
    for (size_t i = 0; i < nhists; i++)
      ws->histogram(i).Y.reserve(expectedMaxSize);
    SQWSMapping.InvPOfQ = ws;
  }
}
 
MatrixWorkspace_sptr DiscusMultipleScatteringCorrection::createOutputWorkspace(const MatrixWorkspace &inputWS) const {
  MatrixWorkspace_uptr outputWS = DataObjects::create<Workspace2D>(inputWS);
  // The algorithm computes the signal values at bin centres so they should
  // be treated as a distribution
  outputWS->setDistribution(true);
  outputWS->setYUnit("");
  outputWS->setYUnitLabel("Scattered Weight");
  return outputWS;
}
 
std::unique_ptr<InterpolationOption> DiscusMultipleScatteringCorrection::createInterpolateOption() {
  auto interpolationOpt = std::make_unique<InterpolationOption>();
  return interpolationOpt;
}
 
void DiscusMultipleScatteringCorrection::interpolateFromSparse(
    MatrixWorkspace &targetWS, const SparseWorkspace &sparseWS,
    const Mantid::Algorithms::InterpolationOption &interpOpt) {
  const auto &spectrumInfo = targetWS.spectrumInfo();
  const auto refFrame = targetWS.getInstrument()->getReferenceFrame();
  PARALLEL_FOR_IF(Kernel::threadSafe(targetWS, sparseWS))
  for (int64_t i = 0; i < static_cast<decltype(i)>(spectrumInfo.size()); ++i) {
    PARALLEL_START_INTERRUPT_REGION
    if (spectrumInfo.hasDetectors(i) && !spectrumInfo.isMonitor(i)) {
      double lat, lon;
      std::tie(lat, lon) = spectrumInfo.geographicalAngles(i);
      const auto spatiallyInterpHisto = sparseWS.bilinearInterpolateFromDetectorGrid(lat, lon);
      if (spatiallyInterpHisto.size() > 1) {
        auto targetHisto = targetWS.histogram(i);
        interpOpt.applyInPlace(spatiallyInterpHisto, targetHisto);
        targetWS.setHistogram(i, targetHisto);
      } else {
        targetWS.mutableY(i) = spatiallyInterpHisto.y().front();
      }
    }
    PARALLEL_END_INTERRUPT_REGION
  }
  PARALLEL_CHECK_INTERRUPT_REGION
}
 
void DiscusMultipleScatteringCorrection::correctForWorkspaceNameClash(std::string &wsName) {
  bool noClash(false);
 
  for (int i = 0; !noClash; ++i) {
    std::string wsIndex; // dont use an index if there is no other
                         // workspace
    if (i > 0) {
      wsIndex = "_" + std::to_string(i);
    }
 
    bool wsExists = AnalysisDataService::Instance().doesExist(wsName + wsIndex);
    if (!wsExists) {
      wsName += wsIndex;
      noClash = true;
    }
  }
}
 
void DiscusMultipleScatteringCorrection::setWorkspaceName(const API::MatrixWorkspace_sptr &ws, std::string wsName) {
  correctForWorkspaceNameClash(wsName);
  API::AnalysisDataService::Instance().addOrReplace(wsName, ws);
}
 
const ComponentWorkspaceMapping *
DiscusMultipleScatteringCorrection::findMatchingComponent(const ComponentWorkspaceMappings &componentWorkspaces,
                                                          const Geometry::IObject *shapeObjectWithScatter) {
  // Currently look up based on the raw pointer value. Did consider looking up based on something more human readable
  // such as the component id or name but this isn't guaranteed to be set and a string key may be longer than the
  // pointer which is probably 8 bytes
  auto componentWSIt = std::find_if(componentWorkspaces.begin(), componentWorkspaces.end(),
                                    [shapeObjectWithScatter](const ComponentWorkspaceMapping &SQWS) {
                                      return SQWS.ComponentPtr.get() == shapeObjectWithScatter;
                                    });
  assert(componentWSIt != componentWorkspaces.end());
  // can't return iterator because boost have moved vec_iterator into a different namespace post v1.65.1 so won't
  // build on all platforms
  return &(*componentWSIt);
}
 
void DiscusMultipleScatteringCorrection::prepareSampleBeamGeometry(const API::MatrixWorkspace_sptr &inputWS) {
  m_sampleShape = inputWS->sample().getShapePtr();
  try {
    m_env = &inputWS->sample().getEnvironment();
  } catch (std::runtime_error &) {
    // swallow this as no defined environment from getEnvironment
  }
  // generate the bounding box before the multithreaded section
  m_activeRegion = m_sampleShape->getBoundingBox();
  if (m_env) {
    const auto &envBox = m_env->boundingBox();
    m_activeRegion.grow(envBox);
  }
  m_instrument = inputWS->getInstrument();
  m_beamProfile = BeamProfileFactory::createBeamProfile(*m_instrument, inputWS->sample());
  m_refframe = m_instrument->getReferenceFrame();
  m_sourcePos = m_instrument->getSource()->getPos();
}
 
} // namespace Mantid::Algorithms