/** Create a new instance of the same type of workspace as that given as
* argument.
* If the optional size parameters are given, the workspace will be initialised
* using
* those; otherwise it will be initialised to the same size as the parent.
* This method should be used when you want to carry over the Workspace data
* members
* relating to the Instrument, Spectra-Detector Map, Sample & Axes to the new
* workspace.
* If the workspace is the same size as its parent, then the X data, axes and
* mask list are
* copied. If its a different size then they are not.
* @param parent A shared pointer to the parent workspace
* @param NVectors (Optional) The number of vectors/histograms/detectors in
* the workspace
* @param XLength (Optional) The number of X data points/bin boundaries in
* each vector (must all be the same)
* @param YLength (Optional) The number of data/error points in each vector
* (must all be the same)
* @return A shared pointer to the newly created instance
* @throw std::out_of_range If invalid (0 or less) size arguments are given
* @throw NotFoundException If the class is not registered in the factory
*/
MatrixWorkspace_sptr
WorkspaceFactoryImpl::create(const MatrixWorkspace_const_sptr &parent,
size_t NVectors, size_t XLength,
size_t YLength) const {
bool differentSize(true);
// Use the parent sizes if new ones are not specified
if (NVectors == size_t(-1))
NVectors = parent->getNumberHistograms();
if (XLength == size_t(-1))
XLength = parent->dataX(0).size();
if (YLength == size_t(-1)) {
differentSize = false;
YLength = parent->blocksize();
}
// If the parent is an EventWorkspace, we want it to spawn a Workspace2D (or
// managed variant) as a child
std::string id(parent->id());
if (id == "EventWorkspace")
id = "Workspace2D";
// Create an 'empty' workspace of the appropriate type and size
MatrixWorkspace_sptr ws = create(id, NVectors, XLength, YLength);
// Copy over certain parent data members
initializeFromParent(parent, ws, differentSize);
return ws;
}
/** Executes the algorithm
*/
void MultiplyRange::exec()
{
// Get the input workspace and other properties
MatrixWorkspace_const_sptr inputWS = getProperty("InputWorkspace");
m_startBin = getProperty("StartBin");
m_endBin = getProperty("EndBin");
m_factor = getProperty("Factor");
// A few checks on the input properties
const int specSize = static_cast<int>(inputWS->blocksize());
if ( isEmpty(m_endBin) ) m_endBin = specSize - 1;
if ( m_endBin >= specSize )
{
g_log.error("EndBin out of range!");
throw std::out_of_range("EndBin out of range!");
}
if ( m_endBin < m_startBin )
{
g_log.error("StartBin must be less than or equal to EndBin");
throw std::out_of_range("StartBin must be less than or equal to EndBin");
}
// Only create the output workspace if it's different to the input one
MatrixWorkspace_sptr outputWS = getProperty("OutputWorkspace");
if ( outputWS != inputWS )
{
outputWS = WorkspaceFactory::Instance().create(inputWS);
setProperty("OutputWorkspace",outputWS);
}
// Get the count of histograms in the input workspace
const int histogramCount = static_cast<int>(inputWS->getNumberHistograms());
Progress progress(this,0.0,1.0,histogramCount);
// Loop over spectra
PARALLEL_FOR2(inputWS,outputWS)
for (int i = 0; i < histogramCount; ++i)
{
PARALLEL_START_INTERUPT_REGION
// Copy over the bin boundaries
outputWS->setX(i,inputWS->refX(i));
// Copy over the data
outputWS->dataY(i) = inputWS->readY(i);
outputWS->dataE(i) = inputWS->readE(i);
MantidVec& newY = outputWS->dataY(i);
MantidVec& newE = outputWS->dataE(i);
// Now multiply the requested range
std::transform(newY.begin()+m_startBin,newY.begin()+m_endBin+1,newY.begin()+m_startBin,
std::bind2nd(std::multiplies<double>(),m_factor));
std::transform(newE.begin()+m_startBin,newE.begin()+m_endBin+1,newE.begin()+m_startBin,
std::bind2nd(std::multiplies<double>(),m_factor));
progress.report();
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
}
/**
* Creates QwtData using X and Y values from the workspace spectra.
* @param ws :: Workspace with X and Y values to use
* @param wsIndex :: Workspace index to use
* @return Pointer to created QwtData
*/
boost::shared_ptr<QwtData> curveDataFromWs(MatrixWorkspace_const_sptr ws, size_t wsIndex)
{
const double* x = &ws->readX(wsIndex)[0];
const double* y = &ws->readY(wsIndex)[0];
size_t size = ws->blocksize();
return boost::make_shared<QwtArrayData>(x,y,size);
}
/**
* Perform validation of input properties:
* - input workspace must not be empty
* - X values must be evenly spaced (unless accepting rounding errors)
* - Real and Imaginary spectra must be in range of input workspace
* - If complex, real and imaginary workspaces must be the same size
* @returns :: map of property names to errors (empty map if no errors)
*/
std::map<std::string, std::string> FFT::validateInputs() {
std::map<std::string, std::string> errors;
MatrixWorkspace_const_sptr inWS = getProperty("InputWorkspace");
if (inWS) {
const int iReal = getProperty("Real");
const int iImag = getProperty("Imaginary");
const MantidVec &X = inWS->readX(iReal);
// check that the workspace isn't empty
if (X.size() < 2) {
errors["InputWorkspace"] =
"Input workspace must have at least two values";
} else {
// Check that the x values are evenly spaced
// If accepting rounding errors, just give a warning if bins are
// different.
if (areBinWidthsUneven(X)) {
errors["InputWorkspace"] =
"X axis must be linear (all bins have same width)";
}
}
// check real, imaginary spectrum numbers and workspace sizes
int nHist = static_cast<int>(inWS->getNumberHistograms());
if (iReal >= nHist) {
errors["Real"] = "Real out of range";
}
if (iImag != EMPTY_INT()) {
MatrixWorkspace_const_sptr inImagWS = getProperty("InputImagWorkspace");
if (inImagWS) {
if (inWS->blocksize() != inImagWS->blocksize()) {
errors["Imaginary"] = "Real and Imaginary sizes do not match";
}
nHist = static_cast<int>(inImagWS->getNumberHistograms());
}
if (iImag >= nHist) {
errors["Imaginary"] = "Imaginary out of range";
}
}
}
return errors;
}
void FlatBackground::exec()
{
// Retrieve the input workspace
MatrixWorkspace_const_sptr inputWS = getProperty("InputWorkspace");
// Copy over all the data
const int numHists = static_cast<int>(inputWS->getNumberHistograms());
const int blocksize = static_cast<int>(inputWS->blocksize());
// Get the required X range
double startX,endX;
this->checkRange(startX,endX);
std::vector<int> specInds = getProperty("WorkspaceIndexList");
// check if the user passed an empty list, if so all of spec will be processed
this->getSpecInds(specInds, numHists);
// Are we removing the background?
const bool removeBackground =
std::string(getProperty("outputMode")) == "Subtract Background";
// Initialise the progress reporting object
m_progress = new Progress(this,0.0,0.2,numHists);
MatrixWorkspace_sptr outputWS = getProperty("OutputWorkspace");
// If input and output workspaces are not the same, create a new workspace for the output
if (outputWS != inputWS )
{
outputWS = WorkspaceFactory::Instance().create(inputWS);
PARALLEL_FOR2(inputWS,outputWS)
for (int i = 0; i < numHists; ++i)
{
PARALLEL_START_INTERUPT_REGION
outputWS->dataX(i) = inputWS->readX(i);
outputWS->dataY(i) = inputWS->readY(i);
outputWS->dataE(i) = inputWS->readE(i);
m_progress->report();
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
}
IMDHistoWorkspace_sptr ReflectometryTransform::executeMDNormPoly(
MatrixWorkspace_const_sptr inputWs) const {
auto input_x_dim = inputWs->getXDimension();
MDHistoDimension_sptr dim0 = MDHistoDimension_sptr(new MDHistoDimension(
input_x_dim->getName(), input_x_dim->getDimensionId(),
input_x_dim->getMDFrame(),
static_cast<Mantid::coord_t>(input_x_dim->getMinimum()),
static_cast<Mantid::coord_t>(input_x_dim->getMaximum()),
input_x_dim->getNBins()));
auto input_y_dim = inputWs->getYDimension();
MDHistoDimension_sptr dim1 = MDHistoDimension_sptr(new MDHistoDimension(
input_y_dim->getName(), input_y_dim->getDimensionId(),
input_y_dim->getMDFrame(),
static_cast<Mantid::coord_t>(input_y_dim->getMinimum()),
static_cast<Mantid::coord_t>(input_y_dim->getMaximum()),
input_y_dim->getNBins()));
auto outWs = boost::make_shared<MDHistoWorkspace>(dim0, dim1);
for (size_t nHistoIndex = 0; nHistoIndex < inputWs->getNumberHistograms();
++nHistoIndex) {
const MantidVec X = inputWs->readX(nHistoIndex);
const MantidVec Y = inputWs->readY(nHistoIndex);
const MantidVec E = inputWs->readE(nHistoIndex);
for (size_t nBinIndex = 0; nBinIndex < inputWs->blocksize(); ++nBinIndex) {
auto value_index = outWs->getLinearIndex(nBinIndex, nHistoIndex);
outWs->setSignalAt(value_index, Y[nBinIndex]);
outWs->setErrorSquaredAt(value_index, E[nBinIndex] * E[nBinIndex]);
}
}
return outWs;
}
/**
* Groups the workspace according to grouping provided.
*
* @param ws :: Workspace to group
* @param g :: The grouping information
* @return Sptr to created grouped workspace
*/
MatrixWorkspace_sptr groupWorkspace(MatrixWorkspace_const_sptr ws, const Grouping& g)
{
// As I couldn't specify multiple groups for GroupDetectors, I am going down quite a complicated
// route - for every group distinct grouped workspace is created using GroupDetectors. These
// workspaces are then merged into the output workspace.
// Create output workspace
MatrixWorkspace_sptr outWs =
WorkspaceFactory::Instance().create(ws, g.groups.size(), ws->readX(0).size(), ws->blocksize());
for(size_t gi = 0; gi < g.groups.size(); gi++)
{
Mantid::API::IAlgorithm_sptr alg = AlgorithmManager::Instance().create("GroupDetectors");
alg->setChild(true); // So Output workspace is not added to the ADS
alg->initialize();
alg->setProperty("InputWorkspace", boost::const_pointer_cast<MatrixWorkspace>(ws));
alg->setPropertyValue("SpectraList", g.groups[gi]);
alg->setPropertyValue("OutputWorkspace", "grouped"); // Is not actually used, just to make validators happy
alg->execute();
MatrixWorkspace_sptr grouped = alg->getProperty("OutputWorkspace");
// Copy the spectrum
*(outWs->getSpectrum(gi)) = *(grouped->getSpectrum(0));
// Update spectrum number
outWs->getSpectrum(gi)->setSpectrumNo(static_cast<specid_t>(gi));
// Copy to the output workspace
outWs->dataY(gi) = grouped->readY(0);
outWs->dataX(gi) = grouped->readX(0);
outWs->dataE(gi) = grouped->readE(0);
}
return outWs;
}
/**
* Execution path for NormalisedPolygon Rebinning
* @param inputWS : Workspace to be rebinned
* @param vertexes : TableWorkspace for debugging purposes
* @param dumpVertexes : determines whether vertexes will be written to for
* debugging purposes or not
* @param outputDimensions : used for the column headings for Dump Vertexes
*/
MatrixWorkspace_sptr ReflectometryTransform::executeNormPoly(
MatrixWorkspace_const_sptr inputWS,
boost::shared_ptr<Mantid::DataObjects::TableWorkspace> &vertexes,
bool dumpVertexes, std::string outputDimensions) const {
MatrixWorkspace_sptr temp = WorkspaceFactory::Instance().create(
"RebinnedOutput", m_d1NumBins, m_d0NumBins, m_d0NumBins);
RebinnedOutput_sptr outWS = boost::static_pointer_cast<RebinnedOutput>(temp);
const double widthD0 = (m_d0Max - m_d0Min) / double(m_d0NumBins);
const double widthD1 = (m_d1Max - m_d1Min) / double(m_d1NumBins);
std::vector<double> xBinsVec;
std::vector<double> zBinsVec;
VectorHelper::createAxisFromRebinParams({m_d1Min, widthD1, m_d1Max},
zBinsVec);
VectorHelper::createAxisFromRebinParams({m_d0Min, widthD0, m_d0Max},
xBinsVec);
// Put the correct bin boundaries into the workspace
auto verticalAxis = new BinEdgeAxis(zBinsVec);
outWS->replaceAxis(1, verticalAxis);
for (size_t i = 0; i < zBinsVec.size() - 1; ++i)
outWS->setX(i, xBinsVec);
verticalAxis->title() = m_d1Label;
// Prepare the required theta values
DetectorAngularCache cache = initAngularCaches(inputWS.get());
m_theta = cache.thetas;
m_thetaWidths = cache.thetaWidths;
const size_t nHistos = inputWS->getNumberHistograms();
const size_t nBins = inputWS->blocksize();
// Holds the spectrum-detector mapping
std::vector<specnum_t> specNumberMapping;
std::vector<detid_t> detIDMapping;
// Create a table for the output if we want to debug vertex positioning
addColumnHeadings(vertexes, outputDimensions);
for (size_t i = 0; i < nHistos; ++i) {
IDetector_const_sptr detector = inputWS->getDetector(i);
if (!detector || detector->isMasked() || detector->isMonitor()) {
continue;
}
// Compute polygon points
const double theta = m_theta[i];
const double thetaWidth = m_thetaWidths[i];
const double thetaHalfWidth = 0.5 * thetaWidth;
const double thetaLower = theta - thetaHalfWidth;
const double thetaUpper = theta + thetaHalfWidth;
const MantidVec &X = inputWS->readX(i);
const MantidVec &Y = inputWS->readY(i);
const MantidVec &E = inputWS->readE(i);
for (size_t j = 0; j < nBins; ++j) {
const double lamLower = X[j];
const double lamUpper = X[j + 1];
const double signal = Y[j];
const double error = E[j];
auto inputQ =
m_calculator->createQuad(lamUpper, lamLower, thetaUpper, thetaLower);
FractionalRebinning::rebinToFractionalOutput(inputQ, inputWS, i, j, outWS,
zBinsVec);
// Find which qy bin this point lies in
const auto qIndex =
std::upper_bound(zBinsVec.begin(), zBinsVec.end(), inputQ[0].Y()) -
zBinsVec.begin();
if (qIndex != 0 && qIndex < static_cast<int>(zBinsVec.size())) {
// Add this spectra-detector pair to the mapping
specNumberMapping.push_back(
outWS->getSpectrum(qIndex - 1).getSpectrumNo());
detIDMapping.push_back(detector->getID());
}
// Debugging
if (dumpVertexes) {
writeRow(vertexes, inputQ[0], i, j, signal, error);
writeRow(vertexes, inputQ[1], i, j, signal, error);
writeRow(vertexes, inputQ[2], i, j, signal, error);
writeRow(vertexes, inputQ[3], i, j, signal, error);
}
}
}
outWS->finalize();
FractionalRebinning::normaliseOutput(outWS, inputWS);
// Set the output spectrum-detector mapping
SpectrumDetectorMapping outputDetectorMap(specNumberMapping, detIDMapping);
outWS->updateSpectraUsing(outputDetectorMap);
outWS->getAxis(0)->title() = m_d0Label;
outWS->setYUnit("");
outWS->setYUnitLabel("Intensity");
return outWS;
}
void GroupDetectors2::exec()
{
// Get the input workspace
const MatrixWorkspace_const_sptr inputWS = getProperty("InputWorkspace");
//Check if it is an event workspace
const bool preserveEvents = getProperty("PreserveEvents");
EventWorkspace_const_sptr eventW = boost::dynamic_pointer_cast<const EventWorkspace>(inputWS);
if (eventW != NULL && preserveEvents)
{
this->execEvent();
return;
}
const size_t numInHists = inputWS->getNumberHistograms();
// Bin boundaries need to be the same, so do the full check on whether they actually are
if (!API::WorkspaceHelpers::commonBoundaries(inputWS))
{
g_log.error() << "Can only group if the histograms have common bin boundaries\n";
throw std::invalid_argument("Can only group if the histograms have common bin boundaries");
}
progress( m_FracCompl = CHECKBINS );
interruption_point();
// some values loaded into this vector can be negative so this needs to be a signed type
std::vector<int64_t> unGroupedInds;
//the ungrouped list could be very big but might be none at all
unGroupedInds.reserve(numInHists);
for( size_t i = 0; i < numInHists ; i++ )
{
unGroupedInds.push_back(i);
}
// read in the input parameters to make that map, if KeepUngroupedSpectra was set we'll need a list of the ungrouped spectrra too
getGroups(inputWS, unGroupedInds);
// converting the list into a set gets rid of repeated values, here the multiple GroupDetectors2::USED become one USED at the start
const std::set<int64_t> unGroupedSet(unGroupedInds.begin(), unGroupedInds.end());
// Check what the user asked to be done with ungrouped spectra
const bool keepAll = getProperty("KeepUngroupedSpectra");
// ignore the one USED value in set or ignore all the ungrouped if the user doesn't want them
const size_t numUnGrouped = keepAll ? unGroupedSet.size()-1 : 0;
MatrixWorkspace_sptr outputWS =
WorkspaceFactory::Instance().create(inputWS, m_GroupSpecInds.size()+ numUnGrouped,
inputWS->readX(0).size(), inputWS->blocksize());
// prepare to move the requested histograms into groups, first estimate how long for progress reporting. +1 in the demonator gets rid of any divide by zero risk
double prog4Copy=( (1.0 - m_FracCompl)/(static_cast<double>(numInHists-unGroupedSet.size())+1.) )*
(keepAll ? static_cast<double>(numInHists-unGroupedSet.size())/static_cast<double>(numInHists): 1.);
// Build a new map
const size_t outIndex = formGroups(inputWS, outputWS, prog4Copy);
// If we're keeping ungrouped spectra
if (keepAll)
{
// copy them into the output workspace
moveOthers(unGroupedSet, inputWS, outputWS, outIndex);
}
g_log.information() << name() << " algorithm has finished\n";
setProperty("OutputWorkspace",outputWS);
}
/** Executes the rebin algorithm
*
* @throw runtime_error Thrown if
*/
void Rebunch::exec()
{
// retrieve the properties
int n_bunch=getProperty("NBunch");
// Get the input workspace
MatrixWorkspace_const_sptr inputW = getProperty("InputWorkspace");
bool dist = inputW->isDistribution();
// workspace independent determination of length
int histnumber = static_cast<int>(inputW->size()/inputW->blocksize());
/*
const std::vector<double>& Xold = inputW->readX(0);
const std::vector<double>& Yold = inputW->readY(0);
int size_x=Xold.size();
int size_y=Yold.size();
*/
int size_x = static_cast<int>(inputW->readX(0).size());
int size_y = static_cast<int>(inputW->readY(0).size());
//signal is the same length for histogram and point data
int ny=(size_y/n_bunch);
if(size_y%n_bunch >0)ny+=1;
// default is for hist
int nx=ny+1;
bool point=false;
if (size_x==size_y)
{
point=true;
nx=ny;
}
// make output Workspace the same type is the input, but with new length of signal array
API::MatrixWorkspace_sptr outputW = API::WorkspaceFactory::Instance().create(inputW,histnumber,nx,ny);
int progress_step = histnumber / 100;
if (progress_step == 0) progress_step = 1;
PARALLEL_FOR2(inputW,outputW)
for (int hist=0; hist < histnumber;hist++)
{
PARALLEL_START_INTERUPT_REGION
// Ensure that axis information are copied to the output workspace if the axis exists
try
{
outputW->getAxis(1)->spectraNo(hist)=inputW->getAxis(1)->spectraNo(hist);
}
catch( Exception::IndexError& )
{
// Not a Workspace2D
}
// get const references to input Workspace arrays (no copying)
const MantidVec& XValues = inputW->readX(hist);
const MantidVec& YValues = inputW->readY(hist);
const MantidVec& YErrors = inputW->readE(hist);
//get references to output workspace data (no copying)
MantidVec& XValues_new=outputW->dataX(hist);
MantidVec& YValues_new=outputW->dataY(hist);
MantidVec& YErrors_new=outputW->dataE(hist);
// output data arrays are implicitly filled by function
if(point)
{
rebunch_point(XValues,YValues,YErrors,XValues_new,YValues_new,YErrors_new,n_bunch);
}
else
{
rebunch_hist(XValues,YValues,YErrors,XValues_new,YValues_new,YErrors_new,n_bunch, dist);
}
if (hist % progress_step == 0)
{
progress(double(hist)/histnumber);
interruption_point();
}
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
outputW->isDistribution(dist);
// Copy units
if (outputW->getAxis(0)->unit().get())
outputW->getAxis(0)->unit() = inputW->getAxis(0)->unit();
try
{
if (inputW->getAxis(1)->unit().get())
outputW->getAxis(1)->unit() = inputW->getAxis(1)->unit();
}
catch(Exception::IndexError&) {
// OK, so this isn't a Workspace2D
}
// Assign it to the output workspace property
setProperty("OutputWorkspace",outputW);
return;
}
void SofQWCentre::exec() {
using namespace Geometry;
MatrixWorkspace_const_sptr inputWorkspace = getProperty("InputWorkspace");
// Do the full check for common binning
if (!WorkspaceHelpers::commonBoundaries(*inputWorkspace)) {
g_log.error(
"The input workspace must have common binning across all spectra");
throw std::invalid_argument(
"The input workspace must have common binning across all spectra");
}
std::vector<double> verticalAxis;
MatrixWorkspace_sptr outputWorkspace = setUpOutputWorkspace(
inputWorkspace, getProperty("QAxisBinning"), verticalAxis);
setProperty("OutputWorkspace", outputWorkspace);
// Holds the spectrum-detector mapping
std::vector<specnum_t> specNumberMapping;
std::vector<detid_t> detIDMapping;
m_EmodeProperties.initCachedValues(*inputWorkspace, this);
int emode = m_EmodeProperties.m_emode;
// Get a pointer to the instrument contained in the workspace
Instrument_const_sptr instrument = inputWorkspace->getInstrument();
// Get the distance between the source and the sample (assume in metres)
IComponent_const_sptr source = instrument->getSource();
IComponent_const_sptr sample = instrument->getSample();
V3D beamDir = sample->getPos() - source->getPos();
beamDir.normalize();
try {
double l1 = source->getDistance(*sample);
g_log.debug() << "Source-sample distance: " << l1 << '\n';
} catch (Exception::NotFoundError &) {
g_log.error("Unable to calculate source-sample distance");
throw Exception::InstrumentDefinitionError(
"Unable to calculate source-sample distance",
inputWorkspace->getTitle());
}
// Conversion constant for E->k. k(A^-1) = sqrt(energyToK*E(meV))
const double energyToK = 8.0 * M_PI * M_PI * PhysicalConstants::NeutronMass *
PhysicalConstants::meV * 1e-20 /
(PhysicalConstants::h * PhysicalConstants::h);
// Loop over input workspace bins, reassigning data to correct bin in output
// qw workspace
const size_t numHists = inputWorkspace->getNumberHistograms();
const size_t numBins = inputWorkspace->blocksize();
Progress prog(this, 0.0, 1.0, numHists);
for (int64_t i = 0; i < int64_t(numHists); ++i) {
try {
// Now get the detector object for this histogram
IDetector_const_sptr spectrumDet = inputWorkspace->getDetector(i);
if (spectrumDet->isMonitor())
continue;
const double efixed = m_EmodeProperties.getEFixed(*spectrumDet);
// For inelastic scattering the simple relationship q=4*pi*sinTheta/lambda
// does not hold. In order to
// be completely general we must calculate the momentum transfer by
// calculating the incident and final
// wave vectors and then use |q| = sqrt[(ki - kf)*(ki - kf)]
DetectorGroup_const_sptr detGroup =
boost::dynamic_pointer_cast<const DetectorGroup>(spectrumDet);
std::vector<IDetector_const_sptr> detectors;
if (detGroup) {
detectors = detGroup->getDetectors();
} else {
detectors.push_back(spectrumDet);
}
const size_t numDets = detectors.size();
// cache to reduce number of static casts
const double numDets_d = static_cast<double>(numDets);
const auto &Y = inputWorkspace->y(i);
const auto &E = inputWorkspace->e(i);
const auto &X = inputWorkspace->x(i);
// Loop over the detectors and for each bin calculate Q
for (size_t idet = 0; idet < numDets; ++idet) {
IDetector_const_sptr det = detectors[idet];
// Calculate kf vector direction and then Q for each energy bin
V3D scatterDir = (det->getPos() - sample->getPos());
scatterDir.normalize();
for (size_t j = 0; j < numBins; ++j) {
const double deltaE = 0.5 * (X[j] + X[j + 1]);
// Compute ki and kf wave vectors and therefore q = ki - kf
double ei(0.0), ef(0.0);
if (emode == 1) {
ei = efixed;
ef = efixed - deltaE;
if (ef < 0) {
std::string mess =
"Energy transfer requested in Direct mode exceeds incident "
"energy.\n Found for det ID: " +
std::to_string(idet) + " bin No " + std::to_string(j) +
" with Ei=" + boost::lexical_cast<std::string>(efixed) +
" and energy transfer: " +
boost::lexical_cast<std::string>(deltaE);
throw std::runtime_error(mess);
}
} else {
ei = efixed + deltaE;
ef = efixed;
if (ef < 0) {
std::string mess =
"Incident energy of a neutron is negative. Are you trying to "
"process Direct data in Indirect mode?\n Found for det ID: " +
std::to_string(idet) + " bin No " + std::to_string(j) +
" with efied=" + boost::lexical_cast<std::string>(efixed) +
" and energy transfer: " +
boost::lexical_cast<std::string>(deltaE);
throw std::runtime_error(mess);
}
}
if (ei < 0)
throw std::runtime_error(
"Negative incident energy. Check binning.");
const V3D ki = beamDir * sqrt(energyToK * ei);
const V3D kf = scatterDir * (sqrt(energyToK * (ef)));
const double q = (ki - kf).norm();
// Test whether it's in range of the Q axis
if (q < verticalAxis.front() || q > verticalAxis.back())
continue;
// Find which q bin this point lies in
const MantidVec::difference_type qIndex =
std::upper_bound(verticalAxis.begin(), verticalAxis.end(), q) -
verticalAxis.begin() - 1;
// Add this spectra-detector pair to the mapping
specNumberMapping.push_back(
outputWorkspace->getSpectrum(qIndex).getSpectrumNo());
detIDMapping.push_back(det->getID());
// And add the data and it's error to that bin, taking into account
// the number of detectors contributing to this bin
outputWorkspace->mutableY(qIndex)[j] += Y[j] / numDets_d;
// Standard error on the average
outputWorkspace->mutableE(qIndex)[j] =
sqrt((pow(outputWorkspace->e(qIndex)[j], 2) + pow(E[j], 2)) /
numDets_d);
}
}
} catch (Exception::NotFoundError &) {
// Get to here if exception thrown when calculating distance to detector
// Presumably, if we get to here the spectrum will be all zeroes anyway
// (from conversion to E)
continue;
}
prog.report();
}
// If the input workspace was a distribution, need to divide by q bin width
if (inputWorkspace->isDistribution())
this->makeDistribution(outputWorkspace, verticalAxis);
// Set the output spectrum-detector mapping
SpectrumDetectorMapping outputDetectorMap(specNumberMapping, detIDMapping);
outputWorkspace->updateSpectraUsing(outputDetectorMap);
// Replace any NaNs in outputWorkspace with zeroes
if (this->getProperty("ReplaceNaNs")) {
auto replaceNans = this->createChildAlgorithm("ReplaceSpecialValues");
replaceNans->setChild(true);
replaceNans->initialize();
replaceNans->setProperty("InputWorkspace", outputWorkspace);
replaceNans->setProperty("OutputWorkspace", outputWorkspace);
replaceNans->setProperty("NaNValue", 0.0);
replaceNans->setProperty("InfinityValue", 0.0);
replaceNans->setProperty("BigNumberThreshold", DBL_MAX);
replaceNans->execute();
}
}
void SmoothData::exec()
{
// Get the input properties
MatrixWorkspace_const_sptr inputWorkspace = getProperty("InputWorkspace");
int npts = getProperty("NPoints");
// Number of smoothing points must always be an odd number, so add 1 if it isn't.
if (!(npts%2))
{
g_log.information("Adding 1 to number of smoothing points, since it must always be odd");
++npts;
}
// Check that the number of points in the smoothing isn't larger than the spectrum length
const int vecSize = static_cast<int>(inputWorkspace->blocksize());
if ( npts >= vecSize )
{
g_log.error("The number of averaging points requested is larger than the spectrum length");
throw std::out_of_range("The number of averaging points requested is larger than the spectrum length");
}
const int halfWidth = (npts-1)/2;
// Create the output workspace
MatrixWorkspace_sptr outputWorkspace = WorkspaceFactory::Instance().create(inputWorkspace);
Progress progress(this,0.0,1.0,inputWorkspace->getNumberHistograms());
PARALLEL_FOR2(inputWorkspace,outputWorkspace)
// Loop over all the spectra in the workspace
for (int i = 0; i < static_cast<int>(inputWorkspace->getNumberHistograms()); ++i)
{
PARALLEL_START_INTERUPT_REGION
// Copy the X data over. Preserves data sharing if present in input workspace.
outputWorkspace->setX(i,inputWorkspace->refX(i));
// Now get references to the Y & E vectors in the input and output workspaces
const MantidVec &Y = inputWorkspace->readY(i);
const MantidVec &E = inputWorkspace->readE(i);
MantidVec &newY = outputWorkspace->dataY(i);
MantidVec &newE = outputWorkspace->dataE(i);
// Use total to help hold our moving average
double total = 0.0, totalE = 0.0;
// First push the values ahead of the current point onto total
for (int i = 0; i < halfWidth; ++i)
{
if ( Y[i] == Y[i] ) total += Y[i]; // Exclude if NaN
totalE += E[i]*E[i];
}
// Now calculate the smoothed values for the 'end' points, where the number contributing
// to the smoothing will be less than NPoints
for (int j = 0; j <= halfWidth; ++j)
{
const int index = j+halfWidth;
if ( Y[index] == Y[index] ) total += Y[index]; // Exclude if NaN
newY[j] = total/(index+1);
totalE += E[index]*E[index];
newE[j] = sqrt(totalE)/(index+1);
}
// This is the main part, where each data point is the average of NPoints points centred on the
// current point. Note that the statistical error will be reduced by sqrt(npts) because more
// data is now contributing to each point.
for (int k = halfWidth+1; k < vecSize-halfWidth; ++k)
{
const int kp = k+halfWidth;
const int km = k-halfWidth-1;
total += (Y[kp]!=Y[kp] ? 0.0 : Y[kp]) - (Y[km]!=Y[km] ? 0.0 : Y[km]); // Exclude if NaN
newY[k] = total/npts;
totalE += E[kp]*E[kp] - E[km]*E[km];
// Use of a moving average can lead to rounding error where what should be
// zero actually comes out as a tiny negative number - bad news for sqrt so protect
newE[k] = std::sqrt(std::abs(totalE))/npts;
}
// This deals with the 'end' at the tail of each spectrum
for (int l = vecSize-halfWidth; l < vecSize; ++l)
{
const int index = l-halfWidth;
total -= (Y[index-1]!=Y[index-1] ? 0.0 : Y[index-1]); // Exclude if NaN
newY[l] = total/(vecSize-index);
totalE -= E[index-1]*E[index-1];
newE[l] = std::sqrt(std::abs(totalE))/(vecSize-index);
}
progress.report();
PARALLEL_END_INTERUPT_REGION
} // Loop over spectra
PARALLEL_CHECK_INTERUPT_REGION
// Set the output workspace to its property
setProperty("OutputWorkspace", outputWorkspace);
}
/** Executes the algorithm
*
*/
void SumSpectra::exec()
{
// Try and retrieve the optional properties
m_MinSpec = getProperty("StartWorkspaceIndex");
m_MaxSpec = getProperty("EndWorkspaceIndex");
const std::vector<int> indices_list = getProperty("ListOfWorkspaceIndices");
keepMonitors = getProperty("IncludeMonitors");
// Get the input workspace
MatrixWorkspace_const_sptr localworkspace = getProperty("InputWorkspace");
numberOfSpectra = static_cast<int>(localworkspace->getNumberHistograms());
this->yLength = static_cast<int>(localworkspace->blocksize());
// Check 'StartSpectrum' is in range 0-numberOfSpectra
if ( m_MinSpec > numberOfSpectra )
{
g_log.warning("StartWorkspaceIndex out of range! Set to 0.");
m_MinSpec = 0;
}
if (indices_list.empty())
{
//If no list was given and no max, just do all.
if ( isEmpty(m_MaxSpec) ) m_MaxSpec = numberOfSpectra-1;
}
//Something for m_MaxSpec was given but it is out of range?
if (!isEmpty(m_MaxSpec) && ( m_MaxSpec > numberOfSpectra-1 || m_MaxSpec < m_MinSpec ))
{
g_log.warning("EndWorkspaceIndex out of range! Set to max Workspace Index");
m_MaxSpec = numberOfSpectra;
}
//Make the set of indices to sum up from the list
this->indices.insert(indices_list.begin(), indices_list.end());
//And add the range too, if any
if (!isEmpty(m_MaxSpec))
{
for (int i = m_MinSpec; i <= m_MaxSpec; i++)
this->indices.insert(i);
}
//determine the output spectrum id
m_outSpecId = this->getOutputSpecId(localworkspace);
g_log.information() << "Spectra remapping gives single spectra with spectra number: "
<< m_outSpecId << "\n";
m_CalculateWeightedSum = getProperty("WeightedSum");
EventWorkspace_const_sptr eventW = boost::dynamic_pointer_cast<const EventWorkspace>(localworkspace);
if (eventW)
{
m_CalculateWeightedSum = false;
this->execEvent(eventW, this->indices);
}
else
{
//-------Workspace 2D mode -----
// Create the 2D workspace for the output
MatrixWorkspace_sptr outputWorkspace = API::WorkspaceFactory::Instance().create(localworkspace,
1,localworkspace->readX(0).size(),this->yLength);
size_t numSpectra(0); // total number of processed spectra
size_t numMasked(0); // total number of the masked and skipped spectra
size_t numZeros(0); // number of spectra which have 0 value in the first column (used in special cases of evaluating how good Puasonian statistics is)
Progress progress(this, 0, 1, this->indices.size());
// This is the (only) output spectrum
ISpectrum * outSpec = outputWorkspace->getSpectrum(0);
// Copy over the bin boundaries
outSpec->dataX() = localworkspace->readX(0);
//Build a new spectra map
outSpec->setSpectrumNo(m_outSpecId);
outSpec->clearDetectorIDs();
if (localworkspace->id() == "RebinnedOutput")
{
this->doRebinnedOutput(outputWorkspace, progress,numSpectra,numMasked,numZeros);
}
else
{
this->doWorkspace2D(localworkspace, outSpec, progress,numSpectra,numMasked,numZeros);
}
// Pointer to sqrt function
MantidVec& YError = outSpec->dataE();
typedef double (*uf)(double);
uf rs=std::sqrt;
//take the square root of all the accumulated squared errors - Assumes Gaussian errors
std::transform(YError.begin(), YError.end(), YError.begin(), rs);
outputWorkspace->generateSpectraMap();
// set up the summing statistics
outputWorkspace->mutableRun().addProperty("NumAllSpectra",int(numSpectra),"",true);
outputWorkspace->mutableRun().addProperty("NumMaskSpectra",int(numMasked),"",true);
outputWorkspace->mutableRun().addProperty("NumZeroSpectra",int(numZeros),"",true);
// Assign it to the output workspace property
setProperty("OutputWorkspace", outputWorkspace);
}
}
void Qxy::exec()
{
MatrixWorkspace_const_sptr inputWorkspace = getProperty("InputWorkspace");
MatrixWorkspace_const_sptr waveAdj = getProperty("WavelengthAdj");
MatrixWorkspace_const_sptr pixelAdj = getProperty("PixelAdj");
const bool doGravity = getProperty("AccountForGravity");
const bool doSolidAngle = getProperty("SolidAngleWeighting");
//throws if we don't have common binning or another incompatibility
Qhelper helper;
helper.examineInput(inputWorkspace, waveAdj, pixelAdj);
g_log.debug() << "All input workspaces were found to be valid\n";
// Create the output Qx-Qy grid
MatrixWorkspace_sptr outputWorkspace = this->setUpOutputWorkspace(inputWorkspace);
// Will also need an identically-sized workspace to hold the solid angle/time bin masked weight
MatrixWorkspace_sptr weights = WorkspaceFactory::Instance().create(outputWorkspace);
// Copy the X values from the output workspace to the solidAngles one
cow_ptr<MantidVec> axis;
axis.access() = outputWorkspace->readX(0);
for ( size_t i = 0; i < weights->getNumberHistograms(); ++i ) weights->setX(i,axis);
const size_t numSpec = inputWorkspace->getNumberHistograms();
const size_t numBins = inputWorkspace->blocksize();
// the samplePos is often not (0, 0, 0) because the instruments components are moved to account for the beam centre
const V3D samplePos = inputWorkspace->getInstrument()->getSample()->getPos();
// Set the progress bar (1 update for every one percent increase in progress)
Progress prog(this, 0.05, 1.0, numSpec);
// PARALLEL_FOR2(inputWorkspace,outputWorkspace)
for (int64_t i = 0; i < int64_t(numSpec); ++i)
{
// PARALLEL_START_INTERUPT_REGION
// Get the pixel relating to this spectrum
IDetector_const_sptr det;
try {
det = inputWorkspace->getDetector(i);
} catch (Exception::NotFoundError&) {
g_log.warning() << "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 bins that are included inside the RadiusCut/WaveCutcut off, those to calculate for
const size_t wavStart = helper.waveLengthCutOff(inputWorkspace, getProperty("RadiusCut"), getProperty("WaveCut"), i);
if (wavStart >= inputWorkspace->readY(i).size())
{
// all the spectra in this detector are out of range
continue;
}
V3D detPos = det->getPos()-samplePos;
// these will be re-calculated if gravity is on but without gravity there is no need
double phi = atan2(detPos.Y(),detPos.X());
double a = cos(phi);
double b = sin(phi);
double sinTheta = sin( inputWorkspace->detectorTwoTheta(det)/2.0 );
// Get references to the data for this spectrum
const MantidVec& X = inputWorkspace->readX(i);
const MantidVec& Y = inputWorkspace->readY(i);
const MantidVec& E = inputWorkspace->readE(i);
const MantidVec& axis = outputWorkspace->readX(0);
// the solid angle of the detector as seen by the sample is used for normalisation later on
double angle = det->solidAngle(samplePos);
// some bins are masked completely or partially, the following vector will contain the fractions
MantidVec maskFractions;
if ( inputWorkspace->hasMaskedBins(i) )
{
// go through the set and convert it to a vector
const MatrixWorkspace::MaskList& mask = inputWorkspace->maskedBins(i);
maskFractions.resize(numBins, 1.0);
MatrixWorkspace::MaskList::const_iterator it, itEnd(mask.end());
for (it = mask.begin(); it != itEnd; ++it)
{
// The weight for this masked bin is 1 minus the degree to which this bin is masked
maskFractions[it->first] -= it->second;
}
}
double maskFraction(1);
// this object is not used if gravity correction is off, but it is only constructed once per spectrum
GravitySANSHelper grav;
if (doGravity)
{
grav = GravitySANSHelper(inputWorkspace, det);
}
for (int j = static_cast<int>(numBins)-1; j >= static_cast<int>(wavStart); --j)
{
if( j < 0 ) break; // Be careful with counting down. Need a better fix but this will work for now
const double binWidth = X[j+1]-X[j];
// Calculate the wavelength at the mid-point of this bin
const double wavLength = X[j]+(binWidth)/2.0;
if (doGravity)
{
// SANS instruments must have their y-axis pointing up, show the detector position as where the neutron would be without gravity
sinTheta = grav.calcComponents(wavLength, a, b);
}
// Calculate |Q| for this bin
const double Q = 4.0*M_PI*sinTheta/wavLength;
// Now get the x & y components of Q.
const double Qx = a*Q;
// Test whether they're in range, if not go to next spectrum.
if ( Qx < axis.front() || Qx >= axis.back() ) break;
const double Qy = b*Q;
if ( Qy < axis.front() || Qy >= axis.back() ) break;
// Find the indices pointing to the place in the 2D array where this bin's contents should go
const MantidVec::difference_type xIndex = std::upper_bound(axis.begin(),axis.end(),Qx) - axis.begin() - 1;
const int yIndex = static_cast<int>(
std::upper_bound(axis.begin(),axis.end(),Qy) - axis.begin() - 1);
// PARALLEL_CRITICAL(qxy) /* Write to shared memory - must protect */
{
// the data will be copied to this bin in the output array
double & outputBinY = outputWorkspace->dataY(yIndex)[xIndex];
double & outputBinE = outputWorkspace->dataE(yIndex)[xIndex];
if ( boost::math::isnan(outputBinY))
{
outputBinY = outputBinE = 0;
}
// Add the contents of the current bin to the 2D array.
outputBinY += Y[j];
// add the errors in quadranture
outputBinE = std::sqrt( (outputBinE*outputBinE) + (E[j]*E[j]) );
// account for masked bins
if ( ! maskFractions.empty() )
{
maskFraction = maskFractions[j];
}
// add the total weight for this bin in the weights workspace,
// in an equivalent bin to where the data was stored
// first take into account the product of contributions to the weight which have
// no errors
double weight = 0.0;
if(doSolidAngle)
weight = maskFraction*angle;
else
weight = maskFraction;
// then the product of contributions which have errors, i.e. optional
// pixelAdj and waveAdj contributions
if (pixelAdj && waveAdj)
{
weights->dataY(yIndex)[xIndex] += weight*pixelAdj->readY(i)[0]*waveAdj->readY(0)[j];
const double pixelYSq = pixelAdj->readY(i)[0]*pixelAdj->readY(i)[0];
const double pixelESq = pixelAdj->readE(i)[0]*pixelAdj->readE(i)[0];
const double waveYSq = waveAdj->readY(0)[j]*waveAdj->readY(0)[j];
const double waveESq = waveAdj->readE(0)[j]*waveAdj->readE(0)[j];
// add product of errors from pixelAdj and waveAdj (note no error on weight is assumed)
weights->dataE(yIndex)[xIndex] += weight*weight*(waveESq*pixelYSq + pixelESq*waveYSq);
}
else if (pixelAdj)
{
weights->dataY(yIndex)[xIndex] += weight*pixelAdj->readY(i)[0];
const double pixelE = weight*pixelAdj->readE(i)[0];
// add error from pixelAdj
weights->dataE(yIndex)[xIndex] += pixelE*pixelE;
}
else if(waveAdj)
{
weights->dataY(yIndex)[xIndex] += weight*waveAdj->readY(0)[j];
const double waveE = weight*waveAdj->readE(0)[j];
// add error from waveAdj
weights->dataE(yIndex)[xIndex] += waveE*waveE;
}
else
weights->dataY(yIndex)[xIndex] += weight;
}
} // loop over single spectrum
prog.report("Calculating Q");
// PARALLEL_END_INTERUPT_REGION
} // loop over all spectra
// PARALLEL_CHECK_INTERUPT_REGION
// take sqrt of error weight values
// left to be executed here for computational efficiency
size_t numHist = weights->getNumberHistograms();
for (size_t i = 0; i < numHist; i++)
{
for (size_t j = 0; j < weights->dataE(i).size(); j++)
{
weights->dataE(i)[j] = sqrt(weights->dataE(i)[j]);
}
}
bool doOutputParts = getProperty("OutputParts");
if (doOutputParts)
{
// copy outputworkspace before it gets further modified
MatrixWorkspace_sptr ws_sumOfCounts = WorkspaceFactory::Instance().create(outputWorkspace);
for (size_t i = 0; i < ws_sumOfCounts->getNumberHistograms(); i++)
{
ws_sumOfCounts->dataX(i) = outputWorkspace->dataX(i);
ws_sumOfCounts->dataY(i) = outputWorkspace->dataY(i);
ws_sumOfCounts->dataE(i) = outputWorkspace->dataE(i);
}
helper.outputParts(this, ws_sumOfCounts, weights);
}
// Divide the output data by the solid angles
outputWorkspace /= weights;
outputWorkspace->isDistribution(true);
// Count of the number of empty cells
MatrixWorkspace::const_iterator wsIt(*outputWorkspace);
int emptyBins = 0;
for (;wsIt != wsIt.end(); ++wsIt)
{
if (wsIt->Y() < 1.0e-12) ++emptyBins;
}
// Log the number of empty bins
g_log.notice() << "There are a total of " << emptyBins << " ("
<< (100*emptyBins)/(outputWorkspace->size()) << "%) empty Q bins.\n";
}
