/*
* Sum up all the unmasked detector pixels.
*
* @param rebinnedWS: workspace where all the wavelength bins have been grouped together
* @param sum: sum of all the unmasked detector pixels (counts)
* @param error: error on sum (counts)
* @param nPixels: number of unmasked detector pixels that contributed to sum
*/
void CalculateEfficiency::sumUnmaskedDetectors(MatrixWorkspace_sptr rebinnedWS,
double& sum, double& error, int& nPixels)
{
// Number of spectra
const int numberOfSpectra = static_cast<int>(rebinnedWS->getNumberHistograms());
sum = 0.0;
error = 0.0;
nPixels = 0;
for (int i = 0; i < numberOfSpectra; i++)
{
progress(0.2+0.2*i/numberOfSpectra, "Computing sensitivity");
// Get the detector object for this spectrum
IDetector_const_sptr det = rebinnedWS->getDetector(i);
// If this detector is masked, skip to the next one
if ( det->isMasked() ) continue;
// If this detector is a monitor, skip to the next one
if ( det->isMonitor() ) continue;
// Retrieve the spectrum into a vector
const MantidVec& YValues = rebinnedWS->readY(i);
const MantidVec& YErrors = rebinnedWS->readE(i);
sum += YValues[0];
error += YErrors[0]*YErrors[0];
nPixels++;
}
error = std::sqrt(error);
}
/** Returns the detectors of interest, specified via processing instructions.
* Note that this returns the names of the parent detectors of the first and
* last spectrum indices in the processing instructions. It is assumed that all
* the interim detectors have the same parent.
*
* @param instructions :: processing instructions defining detectors of interest
* @param inputWS :: the input workspace
* @return :: the names of the detectors of interest
*/
std::vector<std::string> ReflectometryReductionOneAuto2::getDetectorNames(
const std::string &instructions, MatrixWorkspace_sptr inputWS) {
std::vector<std::string> wsIndices;
boost::split(wsIndices, instructions, boost::is_any_of(":,-+"));
// vector of comopnents
std::vector<std::string> detectors;
try {
for (const auto &wsIndex : wsIndices) {
size_t index = boost::lexical_cast<size_t>(wsIndex);
auto detector = inputWS->getDetector(index);
auto parent = detector->getParent();
if (parent) {
auto parentType = parent->type();
auto detectorName = (parentType == "Instrument") ? detector->getName()
: parent->getName();
detectors.push_back(detectorName);
}
}
} catch (boost::bad_lexical_cast &) {
throw std::runtime_error("Invalid processing instructions: " +
instructions);
}
return detectors;
}
/** Execute the algorithm.
*/
void WeightedMeanOfWorkspace::exec()
{
MatrixWorkspace_sptr inputWS = this->getProperty("InputWorkspace");
// Check if it is an event workspace
EventWorkspace_const_sptr eventW = boost::dynamic_pointer_cast<const EventWorkspace>(inputWS);
if (eventW != NULL)
{
throw std::runtime_error("WeightedMeanOfWorkspace cannot handle EventWorkspaces!");
}
// Create the output workspace
MatrixWorkspace_sptr singleValued = WorkspaceFactory::Instance().create("WorkspaceSingleValue", 1, 1, 1);
// Calculate weighted mean
std::size_t numHists = inputWS->getNumberHistograms();
double averageValue = 0.0;
double weightSum = 0.0;
for (std::size_t i = 0; i < numHists; ++i)
{
try
{
IDetector_const_sptr det = inputWS->getDetector(i);
if( det->isMonitor() || det->isMasked() )
{
continue;
}
}
catch (...)
{
// Swallow these if no instrument is found
;
}
MantidVec y = inputWS->dataY(i);
MantidVec e = inputWS->dataE(i);
double weight = 0.0;
for (std::size_t j = 0; j < y.size(); ++j)
{
if (!boost::math::isnan(y[j]) && !boost::math::isinf(y[j]) &&
!boost::math::isnan(e[j]) && !boost::math::isinf(e[j]))
{
weight = 1.0 / (e[j] * e[j]);
averageValue += (y[j] * weight);
weightSum += weight;
}
}
}
singleValued->dataX(0)[0] = 0.0;
singleValued->dataY(0)[0] = averageValue / weightSum;
singleValued->dataE(0)[0] = std::sqrt(weightSum);
this->setProperty("OutputWorkspace", singleValued);
}
/**
* Get the detector component. Use the name provided as a property as the basis
*for the lookup as a priority.
*
* Throws if the name is invalid.
* @param workspace : Workspace from instrument with detectors
* @param isPointDetector : True if this is a point detector. Used to guess a
*name.
* @return The component : The component object found.
*/
boost::shared_ptr<const Mantid::Geometry::IComponent>
SpecularReflectionAlgorithm::getDetectorComponent(
MatrixWorkspace_sptr workspace, const bool isPointDetector) const {
boost::shared_ptr<const IComponent> searchResult;
if (!isPropertyDefault("SpectrumNumbersOfDetectors")) {
const std::vector<int> spectrumNumbers =
this->getProperty("SpectrumNumbersOfDetectors");
const bool strictSpectrumChecking =
this->getProperty("StrictSpectrumChecking");
checkSpectrumNumbers(spectrumNumbers, strictSpectrumChecking, g_log);
auto specToWorkspaceIndex = workspace->getSpectrumToWorkspaceIndexMap();
DetectorGroup_sptr allDetectors = boost::make_shared<DetectorGroup>();
const auto &spectrumInfo = workspace->spectrumInfo();
for (auto index : spectrumNumbers) {
const size_t spectrumNumber{static_cast<size_t>(index)};
auto it = specToWorkspaceIndex.find(index);
if (it == specToWorkspaceIndex.end()) {
std::stringstream message;
message << "Spectrum number " << spectrumNumber
<< " does not exist in the InputWorkspace";
throw std::invalid_argument(message.str());
}
const size_t workspaceIndex = it->second;
auto detector = workspace->getDetector(workspaceIndex);
if (spectrumInfo.isMasked(workspaceIndex))
g_log.warning() << "Adding a detector (ID:" << detector->getID()
<< ") that is flagged as masked.\n";
allDetectors->addDetector(detector);
}
searchResult = allDetectors;
} else {
Mantid::Geometry::Instrument_const_sptr inst = workspace->getInstrument();
std::string componentToCorrect =
isPointDetector ? "point-detector" : "linedetector";
if (!isPropertyDefault("DetectorComponentName")) {
componentToCorrect = this->getPropertyValue("DetectorComponentName");
}
searchResult = inst->getComponentByName(componentToCorrect);
if (searchResult == nullptr) {
throw std::invalid_argument(componentToCorrect +
" does not exist. Check input properties.");
}
}
return searchResult;
}
//calculate time from sample to detector
double ModeratorTzero::CalculateT2(MatrixWorkspace_sptr inputWS, size_t i)
{
static const double convFact = 1.0e-6*sqrt(2*PhysicalConstants::meV/PhysicalConstants::NeutronMass);
double t2(-1.0); // negative initialization signals error
// Get detector position
IDetector_const_sptr det;
try
{
det = inputWS->getDetector(i);
}
catch (Exception::NotFoundError&)
{
return t2;
}
if( det->isMonitor() )
{
t2 = 0.0; //t2=0.0 since there is no sample to detector path
}
else
{
IComponent_const_sptr sample = m_instrument->getSample();
// Get final energy E_f, final velocity v_f
std::vector< double > wsProp=det->getNumberParameter("Efixed");
if ( !wsProp.empty() )
{
double E2 = wsProp.at(0); //[E2]=meV
double v2 = convFact * sqrt(E2); //[v2]=meter/microsec
try
{
double L2 = det->getDistance(*sample);
t2 = L2 / v2;
}
catch (Exception::NotFoundError &)
{
g_log.error("Unable to calculate detector-sample distance");
throw Exception::InstrumentDefinitionError("Unable to calculate detector-sample distance", inputWS->getTitle());
}
}
else
{
g_log.debug() <<"Efixed not found for detector "<< i << std::endl;
}
}
return t2;
} // end of CalculateT2(const MatrixWorkspace_sptr inputWS, size_t i)
/** Convert a workspace to Q
*
* @param inputWS : The input workspace (in wavelength) to convert to Q
* @return : output workspace in Q
*/
MatrixWorkspace_sptr
ReflectometryReductionOne2::convertToQ(MatrixWorkspace_sptr inputWS) {
bool const moreThanOneDetector = inputWS->getDetector(0)->nDets() > 1;
bool const shouldCorrectAngle =
!(*getProperty("ThetaIn")).isDefault() && !summingInQ();
if (shouldCorrectAngle && moreThanOneDetector) {
if (inputWS->getNumberHistograms() > 1) {
throw std::invalid_argument(
"Expected a single group in "
"ProcessingInstructions to be able to "
"perform angle correction, found " +
std::to_string(inputWS->getNumberHistograms()));
}
MatrixWorkspace_sptr IvsQ = inputWS->clone();
auto &XOut0 = IvsQ->mutableX(0);
const auto &XIn0 = inputWS->x(0);
double const theta = getProperty("ThetaIn");
double const factor = 4.0 * M_PI * sin(theta * M_PI / 180.0);
std::transform(XIn0.rbegin(), XIn0.rend(), XOut0.begin(),
[factor](double x) { return factor / x; });
auto &Y0 = IvsQ->mutableY(0);
auto &E0 = IvsQ->mutableE(0);
std::reverse(Y0.begin(), Y0.end());
std::reverse(E0.begin(), E0.end());
IvsQ->getAxis(0)->unit() =
UnitFactory::Instance().create("MomentumTransfer");
return IvsQ;
} else {
auto convertUnits = this->createChildAlgorithm("ConvertUnits");
convertUnits->initialize();
convertUnits->setProperty("InputWorkspace", inputWS);
convertUnits->setProperty("Target", "MomentumTransfer");
convertUnits->setProperty("AlignBins", false);
convertUnits->execute();
MatrixWorkspace_sptr IvsQ = convertUnits->getProperty("OutputWorkspace");
return IvsQ;
}
}
/** Execute the algorithm.
*/
void LoadNXSPE::exec() {
std::string filename = getProperty("Filename");
// quicly check if it's really nxspe
try {
::NeXus::File file(filename);
std::string mainEntry = (*(file.getEntries().begin())).first;
file.openGroup(mainEntry, "NXentry");
file.openData("definition");
if (identiferConfidence(file.getStrData()) < 1) {
throw std::invalid_argument("Not NXSPE");
}
file.close();
} catch (...) {
throw std::invalid_argument("Not NeXus or not NXSPE");
}
// Load the data
::NeXus::File file(filename);
std::string mainEntry = (*(file.getEntries().begin())).first;
file.openGroup(mainEntry, "NXentry");
file.openGroup("NXSPE_info", "NXcollection");
std::map<std::string, std::string> entries = file.getEntries();
std::vector<double> temporary;
double fixed_energy, psi = 0.;
if (!entries.count("fixed_energy")) {
throw std::invalid_argument("fixed_energy field was not found");
}
file.openData("fixed_energy");
file.getData(temporary);
fixed_energy = temporary.at(0);
file.closeData();
if (entries.count("psi")) {
file.openData("psi");
file.getData(temporary);
psi = temporary.at(0);
file.closeData();
}
int kikfscaling = 0;
if (entries.count("ki_over_kf_scaling")) {
file.openData("ki_over_kf_scaling");
std::vector<int> temporaryint;
file.getData(temporaryint);
kikfscaling = temporaryint.at(0);
file.closeData();
}
file.closeGroup(); // NXSPE_Info
file.openGroup("data", "NXdata");
entries = file.getEntries();
if (!entries.count("data")) {
throw std::invalid_argument("data field was not found");
}
file.openData("data");
::NeXus::Info info = file.getInfo();
std::size_t numSpectra = static_cast<std::size_t>(info.dims.at(0));
std::size_t numBins = static_cast<std::size_t>(info.dims.at(1));
std::vector<double> data;
file.getData(data);
file.closeData();
if (!entries.count("error")) {
throw std::invalid_argument("error field was not found");
}
file.openData("error");
std::vector<double> error;
file.getData(error);
file.closeData();
if (!entries.count("energy")) {
throw std::invalid_argument("energy field was not found");
}
file.openData("energy");
std::vector<double> energies;
file.getData(energies);
file.closeData();
if (!entries.count("azimuthal")) {
throw std::invalid_argument("azimuthal field was not found");
}
file.openData("azimuthal");
std::vector<double> azimuthal;
file.getData(azimuthal);
file.closeData();
if (!entries.count("azimuthal_width")) {
throw std::invalid_argument("azimuthal_width field was not found");
}
file.openData("azimuthal_width");
std::vector<double> azimuthal_width;
file.getData(azimuthal_width);
file.closeData();
if (!entries.count("polar")) {
throw std::invalid_argument("polar field was not found");
}
file.openData("polar");
std::vector<double> polar;
file.getData(polar);
file.closeData();
if (!entries.count("polar_width")) {
throw std::invalid_argument("polar_width field was not found");
}
file.openData("polar_width");
std::vector<double> polar_width;
file.getData(polar_width);
file.closeData();
// distance might not have been saved in all NXSPE files
std::vector<double> distance;
if (entries.count("distance")) {
file.openData("distance");
file.getData(distance);
file.closeData();
}
file.closeGroup(); // data group
file.closeGroup(); // Main entry
file.close();
// check if dimensions of the vectors are correct
if ((error.size() != data.size()) || (azimuthal.size() != numSpectra) ||
(azimuthal_width.size() != numSpectra) || (polar.size() != numSpectra) ||
(polar_width.size() != numSpectra) ||
((energies.size() != numBins) && (energies.size() != numBins + 1))) {
throw std::invalid_argument(
"incompatible sizes of fields in the NXSPE file");
}
MatrixWorkspace_sptr outputWS = boost::dynamic_pointer_cast<MatrixWorkspace>(
WorkspaceFactory::Instance().create("Workspace2D", numSpectra,
energies.size(), numBins));
// Need to get hold of the parameter map
outputWS->getAxis(0)->unit() = UnitFactory::Instance().create("DeltaE");
outputWS->setYUnit("SpectraNumber");
// add logs
outputWS->mutableRun().addLogData(
new PropertyWithValue<double>("Ei", fixed_energy));
outputWS->mutableRun().addLogData(new PropertyWithValue<double>("psi", psi));
outputWS->mutableRun().addLogData(new PropertyWithValue<std::string>(
"ki_over_kf_scaling", kikfscaling == 1 ? "true" : "false"));
// Set Goniometer
Geometry::Goniometer gm;
gm.pushAxis("psi", 0, 1, 0, psi);
outputWS->mutableRun().setGoniometer(gm, true);
// generate instrument
Geometry::Instrument_sptr instrument(new Geometry::Instrument("NXSPE"));
outputWS->setInstrument(instrument);
Geometry::ObjComponent *source = new Geometry::ObjComponent("source");
source->setPos(0.0, 0.0, -10.0);
instrument->add(source);
instrument->markAsSource(source);
Geometry::ObjComponent *sample = new Geometry::ObjComponent("sample");
instrument->add(sample);
instrument->markAsSamplePos(sample);
Geometry::Object_const_sptr cuboid(
createCuboid(0.1, 0.1, 0.1)); // FIXME: memory hog on rendering. Also,
// make each detector separate size
for (std::size_t i = 0; i < numSpectra; ++i) {
double r = 1.0;
if (!distance.empty()) {
r = distance.at(i);
}
Kernel::V3D pos;
pos.spherical(r, polar.at(i), azimuthal.at(i));
Geometry::Detector *det =
new Geometry::Detector("pixel", static_cast<int>(i + 1), sample);
det->setPos(pos);
det->setShape(cuboid);
instrument->add(det);
instrument->markAsDetector(det);
}
Geometry::ParameterMap &pmap = outputWS->instrumentParameters();
std::vector<double>::iterator itdata = data.begin(), iterror = error.begin(),
itdataend, iterrorend;
API::Progress prog = API::Progress(this, 0.0, 0.9, numSpectra);
for (std::size_t i = 0; i < numSpectra; ++i) {
itdataend = itdata + numBins;
iterrorend = iterror + numBins;
outputWS->dataX(i) = energies;
if ((!boost::math::isfinite(*itdata)) || (*itdata <= -1e10)) // masked bin
{
outputWS->dataY(i) = std::vector<double>(numBins, 0);
outputWS->dataE(i) = std::vector<double>(numBins, 0);
pmap.addBool(outputWS->getDetector(i)->getComponentID(), "masked", true);
} else {
outputWS->dataY(i) = std::vector<double>(itdata, itdataend);
outputWS->dataE(i) = std::vector<double>(iterror, iterrorend);
}
itdata = (itdataend);
iterror = (iterrorend);
prog.report();
}
setProperty("OutputWorkspace", outputWS);
}
void TOFSANSResolutionByPixel::exec() {
MatrixWorkspace_sptr inOutWS = getProperty("Workspace");
double deltaR = getProperty("DeltaR");
double R1 = getProperty("SourceApertureRadius");
double R2 = getProperty("SampleApertureRadius");
// Convert to meters
deltaR /= 1000.0;
R1 /= 1000.0;
R2 /= 1000.0;
const MatrixWorkspace_sptr sigmaModeratorVSwavelength =
getProperty("SigmaModerator");
// create interpolation table from sigmaModeratorVSwavelength
Kernel::Interpolation lookUpTable;
const MantidVec xInterpolate = sigmaModeratorVSwavelength->readX(0);
const MantidVec yInterpolate = sigmaModeratorVSwavelength->readY(0);
// prefer the input to be a pointworkspace and create interpolation function
if (sigmaModeratorVSwavelength->isHistogramData()) {
g_log.notice() << "mid-points of SigmaModerator histogram bins will be "
"used for interpolation.";
for (size_t i = 0; i < xInterpolate.size() - 1; ++i) {
const double midpoint = xInterpolate[i + 1] - xInterpolate[i];
lookUpTable.addPoint(midpoint, yInterpolate[i]);
}
} else {
for (size_t i = 0; i < xInterpolate.size(); ++i) {
lookUpTable.addPoint(xInterpolate[i], yInterpolate[i]);
}
}
const V3D samplePos = inOutWS->getInstrument()->getSample()->getPos();
const V3D sourcePos = inOutWS->getInstrument()->getSource()->getPos();
const V3D SSD = samplePos - sourcePos;
const double L1 = SSD.norm();
const int numberOfSpectra = static_cast<int>(inOutWS->getNumberHistograms());
Progress progress(this, 0.0, 1.0, numberOfSpectra);
for (int i = 0; i < numberOfSpectra; i++) {
IDetector_const_sptr det;
try {
det = inOutWS->getDetector(i);
} catch (Exception::NotFoundError &) {
g_log.information() << "Spectrum index " << i
<< " has no detector assigned to it - discarding"
<< std::endl;
}
// If no detector found or if it's masked or a monitor, skip onto the next
// spectrum
if (!det || det->isMonitor() || det->isMasked())
continue;
// Get the flight path from the sample to the detector pixel
const V3D scatteredFlightPathV3D = det->getPos() - samplePos;
const double L2 = scatteredFlightPathV3D.norm();
const double Lsum = L1 + L2;
// calculate part that is wavelenght independent
const double dTheta2 = (4.0 * M_PI * M_PI / 12.0) *
(3.0 * R1 * R1 / (L1 * L1) +
3.0 * R2 * R2 * Lsum * Lsum / (L1 * L1 * L2 * L2) +
(deltaR * deltaR) / (L2 * L2));
// Multiplicative factor to go from lambda to Q
// Don't get fooled by the function name...
const double theta = inOutWS->detectorTwoTheta(det);
const double factor = 4.0 * M_PI * sin(theta / 2.0);
const MantidVec &xIn = inOutWS->readX(i);
MantidVec &yIn = inOutWS->dataY(i);
const size_t xLength = xIn.size();
// for each wavelenght bin of each pixel calculate a q-resolution
for (size_t j = 0; j < xLength - 1; j++) {
// use the midpoint of each bin
const double wl = (xIn[j + 1] + xIn[j]) / 2.0;
// Calculate q. Alternatively q could be calculated using ConvertUnit
const double q = factor / wl;
// wavelenght spread from bin assumed to be
const double sigmaSpreadFromBin = xIn[j + 1] - xIn[j];
// wavelenght spread from moderatorm, converted from microseconds to
// wavelengths
const double sigmaModerator =
lookUpTable.value(wl) * 3.9560 / (1000.0 * Lsum);
// calculate wavelenght resolution from moderator and histogram time bin
const double sigmaLambda =
std::sqrt(sigmaSpreadFromBin * sigmaSpreadFromBin / 12.0 +
sigmaModerator * sigmaModerator);
// calculate sigmaQ for a given lambda and pixel
const double sigmaOverLambdaTimesQ = q * sigmaLambda / wl;
const double sigmaQ = std::sqrt(
dTheta2 / (wl * wl) + sigmaOverLambdaTimesQ * sigmaOverLambdaTimesQ);
// update inout workspace with this sigmaQ
yIn[j] = sigmaQ;
}
progress.report("Computing Q resolution");
}
}
/**
* This function handles the logic for summing RebinnedOutput workspaces.
* @param outputWorkspace the workspace to hold the summed input
* @param progress the progress indicator
* @param numSpectra
* @param numMasked
* @param numZeros
*/
void SumSpectra::doRebinnedOutput(MatrixWorkspace_sptr outputWorkspace,
Progress &progress, size_t &numSpectra,
size_t &numMasked, size_t &numZeros) {
// Get a copy of the input workspace
MatrixWorkspace_sptr temp = getProperty("InputWorkspace");
// First, we need to clean the input workspace for nan's and inf's in order
// to treat the data correctly later. This will create a new private
// workspace that will be retrieved as mutable.
IAlgorithm_sptr alg = this->createChildAlgorithm("ReplaceSpecialValues");
alg->setProperty<MatrixWorkspace_sptr>("InputWorkspace", temp);
std::string outName = "_" + temp->getName() + "_clean";
alg->setProperty("OutputWorkspace", outName);
alg->setProperty("NaNValue", 0.0);
alg->setProperty("NaNError", 0.0);
alg->setProperty("InfinityValue", 0.0);
alg->setProperty("InfinityError", 0.0);
alg->executeAsChildAlg();
MatrixWorkspace_sptr localworkspace = alg->getProperty("OutputWorkspace");
// Transform to real workspace types
RebinnedOutput_sptr inWS =
boost::dynamic_pointer_cast<RebinnedOutput>(localworkspace);
RebinnedOutput_sptr outWS =
boost::dynamic_pointer_cast<RebinnedOutput>(outputWorkspace);
// Get references to the output workspaces's data vectors
ISpectrum *outSpec = outputWorkspace->getSpectrum(0);
MantidVec &YSum = outSpec->dataY();
MantidVec &YError = outSpec->dataE();
MantidVec &FracSum = outWS->dataF(0);
MantidVec Weight;
std::vector<size_t> nZeros;
if (m_calculateWeightedSum) {
Weight.assign(YSum.size(), 0);
nZeros.assign(YSum.size(), 0);
}
numSpectra = 0;
numMasked = 0;
numZeros = 0;
// Loop over spectra
std::set<int>::iterator it;
// for (int i = m_minSpec; i <= m_maxSpec; ++i)
for (it = m_indices.begin(); it != m_indices.end(); ++it) {
int i = *it;
// Don't go outside the range.
if ((i >= m_numberOfSpectra) || (i < 0)) {
g_log.error() << "Invalid index " << i
<< " was specified. Sum was aborted.\n";
break;
}
try {
// Get the detector object for this spectrum
Geometry::IDetector_const_sptr det = localworkspace->getDetector(i);
// Skip monitors, if the property is set to do so
if (!m_keepMonitors && det->isMonitor())
continue;
// Skip masked detectors
if (det->isMasked()) {
numMasked++;
continue;
}
} catch (...) {
// if the detector not found just carry on
}
numSpectra++;
// Retrieve the spectrum into a vector
const MantidVec &YValues = localworkspace->readY(i);
const MantidVec &YErrors = localworkspace->readE(i);
const MantidVec &FracArea = inWS->readF(i);
if (m_calculateWeightedSum) {
for (int k = 0; k < this->m_yLength; ++k) {
if (YErrors[k] != 0) {
double errsq = YErrors[k] * YErrors[k] * FracArea[k] * FracArea[k];
YError[k] += errsq;
Weight[k] += 1. / errsq;
YSum[k] += YValues[k] * FracArea[k] / errsq;
FracSum[k] += FracArea[k];
} else {
nZeros[k]++;
FracSum[k] += FracArea[k];
}
}
} else {
for (int k = 0; k < this->m_yLength; ++k) {
YSum[k] += YValues[k] * FracArea[k];
YError[k] += YErrors[k] * YErrors[k] * FracArea[k] * FracArea[k];
FracSum[k] += FracArea[k];
}
}
// Map all the detectors onto the spectrum of the output
outSpec->addDetectorIDs(localworkspace->getSpectrum(i)->getDetectorIDs());
progress.report();
}
if (m_calculateWeightedSum) {
numZeros = 0;
for (size_t i = 0; i < Weight.size(); i++) {
if (nZeros[i] == 0)
YSum[i] *= double(numSpectra) / Weight[i];
else
numZeros += nZeros[i];
}
}
// Create the correct representation
outWS->finalize();
}
void CalculateEfficiency::normalizeDetectors(MatrixWorkspace_sptr rebinnedWS,
MatrixWorkspace_sptr outputWS, double sum, double error, int nPixels,
double min_eff, double max_eff)
{
// Number of spectra
const size_t numberOfSpectra = rebinnedWS->getNumberHistograms();
// Empty vector to store the pixels that outside the acceptable efficiency range
std::vector<size_t> dets_to_mask;
for (size_t i = 0; i < numberOfSpectra; i++)
{
const double currProgress = 0.4+0.2*((double)i/(double)numberOfSpectra);
progress(currProgress, "Computing sensitivity");
// Get the detector object for this spectrum
IDetector_const_sptr det = rebinnedWS->getDetector(i);
// If this detector is masked, skip to the next one
if ( det->isMasked() ) continue;
// Retrieve the spectrum into a vector
const MantidVec& YIn = rebinnedWS->readY(i);
const MantidVec& EIn = rebinnedWS->readE(i);
MantidVec& YOut = outputWS->dataY(i);
MantidVec& EOut = outputWS->dataE(i);
// If this detector is a monitor, skip to the next one
if ( det->isMonitor() )
{
YOut[0] = 1.0;
EOut[0] = 0.0;
continue;
}
// Normalize counts to get relative efficiency
YOut[0] = nPixels/sum * YIn[0];
const double err_sum = YIn[0]/sum*error;
EOut[0] = nPixels/std::abs(sum) * std::sqrt(EIn[0]*EIn[0] + err_sum*err_sum);
// Mask this detector if the signal is outside the acceptable band
if ( !isEmpty(min_eff) && YOut[0] < min_eff ) dets_to_mask.push_back(i);
if ( !isEmpty(max_eff) && YOut[0] > max_eff ) dets_to_mask.push_back(i);
}
// If we identified pixels to be masked, mask them now
if ( !dets_to_mask.empty() )
{
// Mask detectors that were found to be outside the acceptable efficiency band
try
{
IAlgorithm_sptr mask = createChildAlgorithm("MaskDetectors", 0.8, 0.9);
// First we mask detectors in the output workspace
mask->setProperty<MatrixWorkspace_sptr>("Workspace", outputWS);
mask->setProperty< std::vector<size_t> >("WorkspaceIndexList", dets_to_mask);
mask->execute();
mask = createChildAlgorithm("MaskDetectors", 0.9, 1.0);
// Then we mask the same detectors in the input workspace
mask->setProperty<MatrixWorkspace_sptr>("Workspace", rebinnedWS);
mask->setProperty< std::vector<size_t> >("WorkspaceIndexList", dets_to_mask);
mask->execute();
} catch (std::invalid_argument& err)
{
std::stringstream e;
e << "Invalid argument to MaskDetectors Child Algorithm: " << err.what();
g_log.error(e.str());
} catch (std::runtime_error& err)
{
std::stringstream e;
e << "Unable to successfully run MaskDetectors Child Algorithm: " << err.what();
g_log.error(e.str());
}
}
}
/** Executes the algorithm. Reading in the file and creating and populating
* the output workspace
*
* @throw std::runtime_error If the instrument cannot be loaded by the LoadInstrument ChildAlgorithm
* @throw InstrumentDefinitionError Thrown if issues with the content of XML instrument file not covered by LoadInstrument
* @throw std::invalid_argument If the optional properties are set to invalid values
*/
void LoadEmptyInstrument::exec()
{
// Get other properties
const double detector_value = getProperty("DetectorValue");
const double monitor_value = getProperty("MonitorValue");
// load the instrument into this workspace
MatrixWorkspace_sptr ws = this->runLoadInstrument();
Instrument_const_sptr instrument = ws->getInstrument();
// Get number of detectors stored in instrument
const size_t number_spectra = instrument->getNumberDetectors();
// Check that we have some spectra for the workspace
if( number_spectra == 0){
g_log.error("Instrument has no detectors, unable to create workspace for it");
throw Kernel::Exception::InstrumentDefinitionError("No detectors found in instrument");
}
bool MakeEventWorkspace = getProperty("MakeEventWorkspace");
MatrixWorkspace_sptr outWS;
if (MakeEventWorkspace)
{
//Make a brand new EventWorkspace
EventWorkspace_sptr localWorkspace = boost::dynamic_pointer_cast<EventWorkspace>(
API::WorkspaceFactory::Instance().create("EventWorkspace", number_spectra, 2, 1));
//Copy geometry over.
API::WorkspaceFactory::Instance().initializeFromParent(ws, localWorkspace, true);
// Cast to matrix WS
outWS = boost::dynamic_pointer_cast<MatrixWorkspace>(localWorkspace);
}
else
{
// Now create the outputworkspace and copy over the instrument object
DataObjects::Workspace2D_sptr localWorkspace =
boost::dynamic_pointer_cast<DataObjects::Workspace2D>(WorkspaceFactory::Instance().create(ws,number_spectra,2,1));
outWS = boost::dynamic_pointer_cast<MatrixWorkspace>(localWorkspace);
}
outWS->rebuildSpectraMapping( true /* include monitors */);
// ---- Set the values ----------
if (!MakeEventWorkspace)
{
MantidVecPtr x,v,v_monitor;
x.access().resize(2); x.access()[0]=1.0; x.access()[1]=2.0;
v.access().resize(1); v.access()[0]=detector_value;
v_monitor.access().resize(1); v_monitor.access()[0]=monitor_value;
for (size_t i=0; i < outWS->getNumberHistograms(); i++)
{
IDetector_const_sptr det = outWS->getDetector(i);
if ( det->isMonitor() )
outWS->setData(i, v_monitor, v_monitor);
else
outWS->setData(i, v, v);
}
}
// Save in output
this->setProperty("OutputWorkspace", outWS);
}
void TOFSANSResolutionByPixel::exec()
{
MatrixWorkspace_sptr inOutWS = getProperty("InputWorkspace");
double deltaR = getProperty("DeltaR");
double R1 = getProperty("SourceApertureRadius");
double R2 = getProperty("SampleApertureRadius");
// Convert to meters
deltaR /= 1000.0;
R1 /= 1000.0;
R2 /= 1000.0;
const double sigmaModeratorMicroSec = getProperty("SigmaModerator");
const V3D samplePos = inOutWS->getInstrument()->getSample()->getPos();
const V3D sourcePos = inOutWS->getInstrument()->getSource()->getPos();
const V3D SSD = samplePos - sourcePos;
const double L1 = SSD.norm();
const int numberOfSpectra = static_cast<int>(inOutWS->getNumberHistograms());
Progress progress(this,0.0,1.0,numberOfSpectra);
//PARALLEL_FOR1(inOutWS)
for (int i = 0; i < numberOfSpectra; i++)
{
//PARALLEL_START_INTERUPT_REGION
IDetector_const_sptr det;
try {
det = inOutWS->getDetector(i);
} catch (Exception::NotFoundError&) {
g_log.information() << "Spectrum index " << i << " has no detector assigned to it - discarding" << std::endl;
// Catch if no detector. Next line tests whether this happened - test placed
// outside here because Mac Intel compiler doesn't like 'continue' in a catch
// in an openmp block.
}
// If no detector found or if it's masked or a monitor, skip onto the next spectrum
if ( !det || det->isMonitor() || det->isMasked() ) continue;
// Get the flight path from the sample to the detector pixel
const V3D scatteredFlightPathV3D = det->getPos() - samplePos;
const double L2 = scatteredFlightPathV3D.norm();
const double Lsum = L1+L2;
// calculate part that is wavelenght independent
const double dTheta2 = (4.0 * M_PI * M_PI / 12.0) *
( 3.0*R1*R1/(L1*L1) + 3.0*R2*R2*Lsum*Lsum/(L1*L1*L2*L2) + (deltaR*deltaR)/(L2*L2) );
// Multiplicative factor to go from lambda to Q
// Don't get fooled by the function name...
const double theta = inOutWS->detectorTwoTheta(det);
const double factor = 4.0 * M_PI * sin( theta/2.0 );
const MantidVec& xIn = inOutWS->readX(i);
MantidVec& yIn = inOutWS->dataY(i);
const size_t xLength = xIn.size();
for ( size_t j = 0; j < xLength-1; j++)
{
// Calculate q. Alternatively q could be calculated using ConvertUnit
const double wl = (xIn[j+1]+xIn[j])/2.0;
const double q = factor/wl;
// calculate wavelenght resolution from moderator and histogram time bin width and
// convert to from unit of micro-seconds to Aangstrom
const double sigmaLambda = sigmaModeratorMicroSec*3.9560/(1000.0*Lsum);
// calculate sigmaQ for a given lambda and pixel
const double sigmaOverLambdaTimesQ = q*sigmaLambda/wl;
const double sigmaQ = std::sqrt(dTheta2/(wl*wl)+sigmaOverLambdaTimesQ*sigmaOverLambdaTimesQ);
// update inout workspace with this sigmaQ
yIn[j] = sigmaQ;
}
progress.report("Computing Q resolution");
//PARALLEL_END_INTERUPT_REGION
}
}
/**
* Execute the algorithm.
*/
void SofQW3::exec()
{
MatrixWorkspace_sptr inputWS = getProperty("InputWorkspace");
// Do the full check for common binning
if( !WorkspaceHelpers::commonBoundaries(inputWS) )
{
throw std::invalid_argument("The input workspace must have common binning across all spectra");
}
RebinnedOutput_sptr outputWS = this->setUpOutputWorkspace(inputWS,
getProperty("QAxisBinning"),
m_Qout);
g_log.debug() << "Workspace type: " << outputWS->id() << std::endl;
setProperty("OutputWorkspace", outputWS);
const size_t nEnergyBins = inputWS->blocksize();
const size_t nHistos = inputWS->getNumberHistograms();
// Progress reports & cancellation
const size_t nreports(nHistos * nEnergyBins);
m_progress = boost::shared_ptr<API::Progress>(new API::Progress(this, 0.0,
1.0,
nreports));
// Compute input caches
this->initCachedValues(inputWS);
std::vector<double> par = inputWS->getInstrument()->getNumberParameter("detector-neighbour-offset");
if (par.empty())
{
// Index theta cache
this->initThetaCache(inputWS);
}
else
{
g_log.debug() << "Offset: " << par[0] << std::endl;
this->m_detNeighbourOffset = static_cast<int>(par[0]);
this->getValuesAndWidths(inputWS);
}
const MantidVec & X = inputWS->readX(0);
PARALLEL_FOR2(inputWS, outputWS)
for (int64_t i = 0; i < static_cast<int64_t>(nHistos); ++i) // signed for openmp
{
PARALLEL_START_INTERUPT_REGION
DetConstPtr detector = inputWS->getDetector(i);
if (detector->isMasked() || detector->isMonitor())
{
continue;
}
double theta = this->m_theta[i];
double phi = 0.0;
double thetaWidth = 0.0;
double phiWidth = 0.0;
// Non-PSD mode
if (par.empty())
{
thetaWidth = this->m_thetaWidth;
}
// PSD mode
else
{
phi = this->m_phi[i];
thetaWidth = this->m_thetaWidths[i];
phiWidth = this->m_phiWidths[i];
}
double thetaHalfWidth = 0.5 * thetaWidth;
double phiHalfWidth = 0.5 * phiWidth;
const double thetaLower = theta - thetaHalfWidth;
const double thetaUpper = theta + thetaHalfWidth;
const double phiLower = phi - phiHalfWidth;
const double phiUpper = phi + phiHalfWidth;
const double efixed = this->getEFixed(detector);
for(size_t j = 0; j < nEnergyBins; ++j)
{
m_progress->report("Computing polygon intersections");
// For each input polygon test where it intersects with
// the output grid and assign the appropriate weights of Y/E
const double dE_j = X[j];
const double dE_jp1 = X[j+1];
const V2D ll(dE_j, this->calculateQ(efixed, dE_j, thetaLower, phiLower));
const V2D lr(dE_jp1, this->calculateQ(efixed, dE_jp1, thetaLower, phiLower));
const V2D ur(dE_jp1, this->calculateQ(efixed, dE_jp1, thetaUpper, phiUpper));
const V2D ul(dE_j, this->calculateQ(efixed, dE_j, thetaUpper, phiUpper));
Quadrilateral inputQ = Quadrilateral(ll, lr, ur, ul);
this->rebinToFractionalOutput(inputQ, inputWS, i, j, outputWS, m_Qout);
}
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
outputWS->finalize();
this->normaliseOutput(outputWS, inputWS);
}
/** Convert a SPICE 2D Det MatrixWorkspace to MDEvents and append to an
* MDEventWorkspace
* It is optional to use a virtual instrument or copy from input data workspace
* @brief ConvertCWSDExpToMomentum::convertSpiceMatrixToMomentumMDEvents
* @param dataws :: data matrix workspace
* @param usevirtual :: boolean flag to use virtual instrument
* @param startdetid :: starting detid for detectors from this workspace mapping
* to virtual instrument in MDEventWorkspace
* @param runnumber :: run number for all MDEvents created from this matrix
* workspace
*/
void ConvertCWSDExpToMomentum::convertSpiceMatrixToMomentumMDEvents(
MatrixWorkspace_sptr dataws, bool usevirtual, const detid_t &startdetid,
const int runnumber) {
// Create transformation matrix from which the transformation is
Kernel::DblMatrix rotationMatrix;
setupTransferMatrix(dataws, rotationMatrix);
g_log.information() << "Before insert new event, output workspace has "
<< m_outputWS->getNEvents() << "Events.\n";
// Creates a new instance of the MDEventInserte to output workspace
MDEventWorkspace<MDEvent<3>, 3>::sptr mdws_mdevt_3 =
boost::dynamic_pointer_cast<MDEventWorkspace<MDEvent<3>, 3>>(m_outputWS);
MDEventInserter<MDEventWorkspace<MDEvent<3>, 3>::sptr> inserter(mdws_mdevt_3);
// Calcualte k_i: it is assumed that all k_i are same for one Pt.
// number, i.e., one 2D XML file
Kernel::V3D sourcePos = dataws->getInstrument()->getSource()->getPos();
Kernel::V3D samplePos = dataws->getInstrument()->getSample()->getPos();
if (dataws->readX(0).size() != 2)
throw std::runtime_error(
"Input matrix workspace has wrong dimension in X-axis.");
double momentum = 0.5 * (dataws->readX(0)[0] + dataws->readX(0)[1]);
Kernel::V3D ki = (samplePos - sourcePos) * (momentum / sourcePos.norm());
g_log.debug() << "Source at " << sourcePos.toString()
<< ", Norm = " << sourcePos.norm()
<< ", momentum = " << momentum << "\n"
<< "k_i = " << ki.toString() << "\n";
// Go though each spectrum to conver to MDEvent
size_t numspec = dataws->getNumberHistograms();
double maxsignal = 0;
size_t nummdevents = 0;
for (size_t iws = 0; iws < numspec; ++iws) {
// Get detector positions and signal
double signal = dataws->readY(iws)[0];
// Skip event with 0 signal
if (signal < 0.001)
continue;
double error = dataws->readE(iws)[0];
Kernel::V3D detpos = dataws->getDetector(iws)->getPos();
std::vector<Mantid::coord_t> q_sample(3);
// Calculate Q-sample and new detector ID in virtual instrument.
Kernel::V3D qlab = convertToQSample(samplePos, ki, detpos, momentum,
q_sample, rotationMatrix);
detid_t native_detid = dataws->getDetector(iws)->getID();
detid_t detid = native_detid + startdetid;
// Insert
inserter.insertMDEvent(
static_cast<float>(signal), static_cast<float>(error * error),
static_cast<uint16_t>(runnumber), detid, q_sample.data());
updateQRange(q_sample);
g_log.debug() << "Q-lab = " << qlab.toString() << "\n";
g_log.debug() << "Insert DetID " << detid << ", signal = " << signal
<< ", with q_sample = " << q_sample[0] << ", " << q_sample[1]
<< ", " << q_sample[2] << "\n";
// Update some statistical inforamtion
if (signal > maxsignal)
maxsignal = signal;
++nummdevents;
}
g_log.information() << "Imported Matrixworkspace: Max. Signal = " << maxsignal
<< ", Add " << nummdevents << " MDEvents "
<< "\n";
// Add experiment info including instrument, goniometer and run number
ExperimentInfo_sptr expinfo = boost::make_shared<ExperimentInfo>();
if (usevirtual)
expinfo->setInstrument(m_virtualInstrument);
else {
Geometry::Instrument_const_sptr tmp_inst = dataws->getInstrument();
expinfo->setInstrument(tmp_inst);
}
expinfo->mutableRun().setGoniometer(dataws->run().getGoniometer(), false);
expinfo->mutableRun().addProperty("run_number", runnumber);
// Add all the other propertys from original data workspace
const std::vector<Kernel::Property *> vec_property =
dataws->run().getProperties();
for (auto property : vec_property) {
expinfo->mutableRun().addProperty(property->clone());
}
m_outputWS->addExperimentInfo(expinfo);
return;
}
/** Convert the workspace units using TOF as an intermediate step in the
* conversion
* @param fromUnit :: The unit of the input workspace
* @param inputWS :: The input workspace
* @returns A shared pointer to the output workspace
*/
MatrixWorkspace_sptr ConvertUnitsUsingDetectorTable::convertViaTOF(
Kernel::Unit_const_sptr fromUnit, API::MatrixWorkspace_const_sptr inputWS) {
using namespace Geometry;
// Let's see if we are using a TableWorkspace to override parameters
TableWorkspace_sptr paramWS = getProperty("DetectorParameters");
// See if we have supplied a DetectorParameters Workspace
// TODO: Check if paramWS is NULL and if so throw an exception
// const std::string l1ColumnLabel("l1");
// Let's check all the columns exist and are readable
try {
auto spectraColumnTmp = paramWS->getColumn("spectra");
auto l1ColumnTmp = paramWS->getColumn("l1");
auto l2ColumnTmp = paramWS->getColumn("l2");
auto twoThetaColumnTmp = paramWS->getColumn("twotheta");
auto efixedColumnTmp = paramWS->getColumn("efixed");
auto emodeColumnTmp = paramWS->getColumn("emode");
} catch (...) {
throw Exception::InstrumentDefinitionError(
"DetectorParameter TableWorkspace is not defined correctly.");
}
// Now let's take a reference to the vectors.
const auto &l1Column = paramWS->getColVector<double>("l1");
const auto &l2Column = paramWS->getColVector<double>("l2");
const auto &twoThetaColumn = paramWS->getColVector<double>("twotheta");
const auto &efixedColumn = paramWS->getColVector<double>("efixed");
const auto &emodeColumn = paramWS->getColVector<int>("emode");
const auto &spectraColumn = paramWS->getColVector<int>("spectra");
Progress prog(this, 0.2, 1.0, m_numberOfSpectra);
int64_t numberOfSpectra_i =
static_cast<int64_t>(m_numberOfSpectra); // cast to make openmp happy
// Get the unit object for each workspace
Kernel::Unit_const_sptr outputUnit = m_outputUnit;
std::vector<double> emptyVec;
int failedDetectorCount = 0;
// Perform Sanity Validation before creating workspace
size_t checkIndex = 0;
int checkSpecNo = inputWS->getDetector(checkIndex)->getID();
auto checkSpecIter =
std::find(spectraColumn.begin(), spectraColumn.end(), checkSpecNo);
if (checkSpecIter != spectraColumn.end()) {
size_t detectorRow = std::distance(spectraColumn.begin(), checkSpecIter);
// copy the X values for the check
auto checkXValues = inputWS->readX(checkIndex);
// Convert the input unit to time-of-flight
auto checkFromUnit = std::unique_ptr<Unit>(fromUnit->clone());
auto checkOutputUnit = std::unique_ptr<Unit>(outputUnit->clone());
double checkdelta = 0;
checkFromUnit->toTOF(checkXValues, emptyVec, l1Column[detectorRow],
l2Column[detectorRow], twoThetaColumn[detectorRow],
emodeColumn[detectorRow], efixedColumn[detectorRow],
checkdelta);
// Convert from time-of-flight to the desired unit
checkOutputUnit->fromTOF(checkXValues, emptyVec, l1Column[detectorRow],
l2Column[detectorRow], twoThetaColumn[detectorRow],
emodeColumn[detectorRow],
efixedColumn[detectorRow], checkdelta);
}
// create the output workspace
MatrixWorkspace_sptr outputWS = this->setupOutputWorkspace(inputWS);
EventWorkspace_sptr eventWS =
boost::dynamic_pointer_cast<EventWorkspace>(outputWS);
assert(static_cast<bool>(eventWS) == m_inputEvents); // Sanity check
// TODO: Check why this parallel stuff breaks
// Loop over the histograms (detector spectra)
// PARALLEL_FOR_IF(Kernel::threadSafe(*outputWS))
for (int64_t i = 0; i < numberOfSpectra_i; ++i) {
// Lets find what row this spectrum Number appears in our detector table.
// PARALLEL_START_INTERUPT_REGION
std::size_t wsid = i;
try {
double deg2rad = M_PI / 180.;
auto det = outputWS->getDetector(i);
int specNo = det->getID();
// int spectraNumber = static_cast<int>(spectraColumn->toDouble(i));
// wsid = outputWS->getIndexFromSpectrumNumber(spectraNumber);
g_log.debug() << "###### Spectra #" << specNo
<< " ==> Workspace ID:" << wsid << '\n';
// Now we need to find the row that contains this spectrum
std::vector<int>::const_iterator specIter;
specIter = std::find(spectraColumn.begin(), spectraColumn.end(), specNo);
if (specIter != spectraColumn.end()) {
const size_t detectorRow =
std::distance(spectraColumn.begin(), specIter);
const double l1 = l1Column[detectorRow];
const double l2 = l2Column[detectorRow];
const double twoTheta = twoThetaColumn[detectorRow] * deg2rad;
const double efixed = efixedColumn[detectorRow];
const int emode = emodeColumn[detectorRow];
if (g_log.is(Logger::Priority::PRIO_DEBUG)) {
g_log.debug() << "specNo from detector table = "
<< spectraColumn[detectorRow] << '\n';
g_log.debug() << "###### Spectra #" << specNo
<< " ==> Det Table Row:" << detectorRow << '\n';
g_log.debug() << "\tL1=" << l1 << ",L2=" << l2 << ",TT=" << twoTheta
<< ",EF=" << efixed << ",EM=" << emode << '\n';
}
// Make local copies of the units. This allows running the loop in
// parallel
auto localFromUnit = std::unique_ptr<Unit>(fromUnit->clone());
auto localOutputUnit = std::unique_ptr<Unit>(outputUnit->clone());
/// @todo Don't yet consider hold-off (delta)
const double delta = 0.0;
std::vector<double> values(outputWS->x(wsid).begin(),
outputWS->x(wsid).end());
// Convert the input unit to time-of-flight
localFromUnit->toTOF(values, emptyVec, l1, l2, twoTheta, emode, efixed,
delta);
// Convert from time-of-flight to the desired unit
localOutputUnit->fromTOF(values, emptyVec, l1, l2, twoTheta, emode,
efixed, delta);
outputWS->mutableX(wsid) = std::move(values);
// EventWorkspace part, modifying the EventLists.
if (m_inputEvents) {
eventWS->getSpectrum(wsid)
.convertUnitsViaTof(localFromUnit.get(), localOutputUnit.get());
}
} else {
// Not found
failedDetectorCount++;
outputWS->maskWorkspaceIndex(wsid);
}
} catch (Exception::NotFoundError &) {
// Get to here if exception thrown when calculating distance to detector
failedDetectorCount++;
// Since you usually (always?) get to here when there's no attached
// detectors, this call is
// the same as just zeroing out the data (calling clearData on the
// spectrum)
outputWS->maskWorkspaceIndex(i);
}
prog.report("Convert to " + m_outputUnit->unitID());
// PARALLEL_END_INTERUPT_REGION
} // loop over spectra
// PARALLEL_CHECK_INTERUPT_REGION
if (failedDetectorCount != 0) {
g_log.information() << "Something went wrong for " << failedDetectorCount
<< " spectra. Masking spectrum.\n";
}
if (m_inputEvents)
eventWS->clearMRU();
return outputWS;
}
void TOFSANSResolutionByPixel::exec() {
MatrixWorkspace_sptr inWS = getProperty("InputWorkspace");
double deltaR = getProperty("DeltaR");
double R1 = getProperty("SourceApertureRadius");
double R2 = getProperty("SampleApertureRadius");
const bool doGravity = getProperty("AccountForGravity");
// Check the input
checkInput(inWS);
// Setup outputworkspace
auto outWS = setupOutputWorkspace(inWS);
// Convert to meters
deltaR /= 1000.0;
R1 /= 1000.0;
R2 /= 1000.0;
// The moderator workspace needs to match the data workspace
// in terms of wavelength binning
const MatrixWorkspace_sptr sigmaModeratorVSwavelength =
getModeratorWorkspace(inWS);
// create interpolation table from sigmaModeratorVSwavelength
Kernel::Interpolation lookUpTable;
const MantidVec xInterpolate = sigmaModeratorVSwavelength->readX(0);
const MantidVec yInterpolate = sigmaModeratorVSwavelength->readY(0);
// prefer the input to be a pointworkspace and create interpolation function
if (sigmaModeratorVSwavelength->isHistogramData()) {
g_log.notice() << "mid-points of SigmaModerator histogram bins will be "
"used for interpolation.";
for (size_t i = 0; i < xInterpolate.size() - 1; ++i) {
const double midpoint = (xInterpolate[i + 1] + xInterpolate[i]) / 2.0;
lookUpTable.addPoint(midpoint, yInterpolate[i]);
}
} else {
for (size_t i = 0; i < xInterpolate.size(); ++i) {
lookUpTable.addPoint(xInterpolate[i], yInterpolate[i]);
}
}
// Calculate the L1 distance
const V3D samplePos = inWS->getInstrument()->getSample()->getPos();
const V3D sourcePos = inWS->getInstrument()->getSource()->getPos();
const V3D SSD = samplePos - sourcePos;
const double L1 = SSD.norm();
// Get the collimation length
double LCollim = getProperty("CollimationLength");
if (LCollim == 0.0) {
auto collimationLengthEstimator = SANSCollimationLengthEstimator();
LCollim = collimationLengthEstimator.provideCollimationLength(inWS);
g_log.information() << "No collimation length was specified. A default "
"collimation length was estimated to be " << LCollim
<< std::endl;
} else {
g_log.information() << "The collimation length is " << LCollim
<< std::endl;
}
const int numberOfSpectra = static_cast<int>(inWS->getNumberHistograms());
Progress progress(this, 0.0, 1.0, numberOfSpectra);
for (int i = 0; i < numberOfSpectra; i++) {
IDetector_const_sptr det;
try {
det = inWS->getDetector(i);
} catch (Exception::NotFoundError &) {
g_log.information() << "Spectrum index " << i
<< " has no detector assigned to it - discarding"
<< std::endl;
}
// If no detector found or if it's masked or a monitor, skip onto the next
// spectrum
if (!det || det->isMonitor() || det->isMasked())
continue;
// Get the flight path from the sample to the detector pixel
const V3D samplePos = inWS->getInstrument()->getSample()->getPos();
const V3D scatteredFlightPathV3D = det->getPos() - samplePos;
const double L2 = scatteredFlightPathV3D.norm();
TOFSANSResolutionByPixelCalculator calculator;
const double waveLengthIndependentFactor =
calculator.getWavelengthIndependentFactor(R1, R2, deltaR, LCollim, L2);
// Multiplicative factor to go from lambda to Q
// Don't get fooled by the function name...
const double theta = inWS->detectorTwoTheta(det);
double sinTheta = sin(theta / 2.0);
double factor = 4.0 * M_PI * sinTheta;
const MantidVec &xIn = inWS->readX(i);
const size_t xLength = xIn.size();
// Gravity correction
boost::shared_ptr<GravitySANSHelper> grav;
if (doGravity) {
grav = boost::make_shared<GravitySANSHelper>(inWS, det,
getProperty("ExtraLength"));
}
// Get handles on the outputWorkspace
MantidVec &yOut = outWS->dataY(i);
// for each wavelenght bin of each pixel calculate a q-resolution
for (size_t j = 0; j < xLength - 1; j++) {
// use the midpoint of each bin
const double wl = (xIn[j + 1] + xIn[j]) / 2.0;
// Calculate q. Alternatively q could be calculated using ConvertUnit
// If we include a gravity correction we need to adjust sinTheta
// for each wavelength (in Angstrom)
if (doGravity) {
double sinThetaGrav = grav->calcSinTheta(wl);
factor = 4.0 * M_PI * sinThetaGrav;
}
const double q = factor / wl;
// wavelenght spread from bin assumed to be
const double sigmaSpreadFromBin = xIn[j + 1] - xIn[j];
// Get the uncertainty in Q
auto sigmaQ = calculator.getSigmaQValue(lookUpTable.value(wl),
waveLengthIndependentFactor, q,
wl, sigmaSpreadFromBin, L1, L2);
// Insert the Q value and the Q resolution into the outputworkspace
yOut[j] = sigmaQ;
}
progress.report("Computing Q resolution");
}
// Set the y axis label
outWS->setYUnitLabel("QResolution");
setProperty("OutputWorkspace", outWS);
}
