/**
* Apply the created mapping to the workspace
*/
void CreateSimulationWorkspace::applyDetectorMapping() {
size_t wsIndex(0);
for (auto iter = m_detGroups.begin(); iter != m_detGroups.end(); ++iter) {
ISpectrum *spectrum = m_outputWS->getSpectrum(wsIndex);
spectrum->setSpectrumNo(
static_cast<specid_t>(wsIndex + 1)); // Ensure a contiguous mapping
spectrum->clearDetectorIDs();
spectrum->addDetectorIDs(iter->second);
++wsIndex;
}
}
/**
* Only to be used if the KeepUnGrouped property is true, moves the spectra that were not selected
* to be in a group to the end of the output spectrum
* @param unGroupedSet :: list of WORKSPACE indexes that were included in a group
* @param inputWS :: user selected input workspace for the algorithm
* @param outputWS :: user selected output workspace for the algorithm
* @param outIndex :: the next spectra index available after the grouped spectra
*/
void GroupDetectors2::moveOthers(const std::set<int64_t> &unGroupedSet, API::MatrixWorkspace_const_sptr inputWS, API::MatrixWorkspace_sptr outputWS,
size_t outIndex)
{
g_log.debug() << "Starting to copy the ungrouped spectra" << std::endl;
double prog4Copy = (1. - 1.*static_cast<double>(m_FracCompl))/static_cast<double>(unGroupedSet.size());
std::set<int64_t>::const_iterator copyFrIt = unGroupedSet.begin();
// go thorugh all the spectra in the input workspace
for ( ; copyFrIt != unGroupedSet.end(); ++copyFrIt )
{
if( *copyFrIt == USED ) continue; //Marked as not to be used
size_t sourceIndex = static_cast<size_t>(*copyFrIt);
// The input spectrum we'll copy
const ISpectrum * inputSpec = inputWS->getSpectrum(sourceIndex);
// Destination of the copying
ISpectrum * outputSpec = outputWS->getSpectrum(outIndex);
// Copy the data
outputSpec->dataX() = inputSpec->dataX();
outputSpec->dataY() = inputSpec->dataY();
outputSpec->dataE() = inputSpec->dataE();
// Spectrum numbers etc.
outputSpec->setSpectrumNo(inputSpec->getSpectrumNo());
outputSpec->clearDetectorIDs();
outputSpec->addDetectorIDs( inputSpec->getDetectorIDs() );
// go to the next free index in the output workspace
outIndex ++;
// make regular progress reports and check for cancelling the algorithm
if ( outIndex % INTERVAL == 0 )
{
m_FracCompl += INTERVAL*prog4Copy;
if ( m_FracCompl > 1.0 )
{
m_FracCompl = 1.0;
}
progress(m_FracCompl);
interruption_point();
}
}
// Refresh the spectraDetectorMap
outputWS->generateSpectraMap();
g_log.debug() << name() << " copied " << unGroupedSet.size()-1 << " ungrouped spectra\n";
}
/**
* Move the user selected spectra in the input workspace into groups in the output workspace
* @param inputWS :: user selected input workspace for the algorithm
* @param outputWS :: user selected output workspace for the algorithm
* @param prog4Copy :: the amount of algorithm progress to attribute to moving a single spectra
* @return number of new grouped spectra
*/
size_t GroupDetectors2::formGroups( API::MatrixWorkspace_const_sptr inputWS, API::MatrixWorkspace_sptr outputWS,
const double prog4Copy)
{
// get "Behaviour" string
const std::string behaviour = getProperty("Behaviour");
int bhv = 0;
if ( behaviour == "Average" ) bhv = 1;
API::MatrixWorkspace_sptr beh = API::WorkspaceFactory::Instance().create(
"Workspace2D", static_cast<int>(m_GroupSpecInds.size()), 1, 1);
g_log.debug() << name() << ": Preparing to group spectra into " << m_GroupSpecInds.size() << " groups\n";
// where we are copying spectra to, we start copying to the start of the output workspace
size_t outIndex = 0;
// Only used for averaging behaviour. We may have a 1:1 map where a Divide would be waste as it would be just dividing by 1
bool requireDivide(false);
for ( storage_map::const_iterator it = m_GroupSpecInds.begin(); it != m_GroupSpecInds.end() ; ++it )
{
// This is the grouped spectrum
ISpectrum * outSpec = outputWS->getSpectrum(outIndex);
// The spectrum number of the group is the key
outSpec->setSpectrumNo(it->first);
// Start fresh with no detector IDs
outSpec->clearDetectorIDs();
// Copy over X data from first spectrum, the bin boundaries for all spectra are assumed to be the same here
outSpec->dataX() = inputWS->readX(0);
// the Y values and errors from spectra being grouped are combined in the output spectrum
// Keep track of number of detectors required for masking
size_t nonMaskedSpectra(0);
beh->dataX(outIndex)[0] = 0.0;
beh->dataE(outIndex)[0] = 0.0;
for( std::vector<size_t>::const_iterator wsIter = it->second.begin(); wsIter != it->second.end(); ++wsIter)
{
const size_t originalWI = *wsIter;
// detectors to add to firstSpecNum
const ISpectrum * fromSpectrum = inputWS->getSpectrum(originalWI);
// Add up all the Y spectra and store the result in the first one
// Need to keep the next 3 lines inside loop for now until ManagedWorkspace mru-list works properly
MantidVec &firstY = outSpec->dataY();
MantidVec::iterator fYit;
MantidVec::iterator fEit = outSpec->dataE().begin();
MantidVec::const_iterator Yit = fromSpectrum->dataY().begin();
MantidVec::const_iterator Eit = fromSpectrum->dataE().begin();
for (fYit = firstY.begin(); fYit != firstY.end(); ++fYit, ++fEit, ++Yit, ++Eit)
{
*fYit += *Yit;
// Assume 'normal' (i.e. Gaussian) combination of errors
*fEit = std::sqrt( (*fEit)*(*fEit) + (*Eit)*(*Eit) );
}
// detectors to add to the output spectrum
outSpec->addDetectorIDs(fromSpectrum->getDetectorIDs() );
try
{
Geometry::IDetector_const_sptr det = inputWS->getDetector(originalWI);
if( !det->isMasked() ) ++nonMaskedSpectra;
}
catch(Exception::NotFoundError&)
{
// If a detector cannot be found, it cannot be masked
++nonMaskedSpectra;
}
}
if( nonMaskedSpectra == 0 ) ++nonMaskedSpectra; // Avoid possible divide by zero
if(!requireDivide) requireDivide = (nonMaskedSpectra > 1);
beh->dataY(outIndex)[0] = static_cast<double>(nonMaskedSpectra);
// make regular progress reports and check for cancelling the algorithm
if ( outIndex % INTERVAL == 0 )
{
m_FracCompl += INTERVAL*prog4Copy;
if ( m_FracCompl > 1.0 )
m_FracCompl = 1.0;
progress(m_FracCompl);
interruption_point();
}
outIndex ++;
}
// Refresh the spectraDetectorMap
outputWS->generateSpectraMap();
if ( bhv == 1 && requireDivide )
{
g_log.debug() << "Running Divide algorithm to perform averaging.\n";
Mantid::API::IAlgorithm_sptr divide = createChildAlgorithm("Divide");
divide->initialize();
divide->setProperty<API::MatrixWorkspace_sptr>("LHSWorkspace", outputWS);
divide->setProperty<API::MatrixWorkspace_sptr>("RHSWorkspace", beh);
divide->setProperty<API::MatrixWorkspace_sptr>("OutputWorkspace", outputWS);
divide->execute();
}
g_log.debug() << name() << " created " << outIndex << " new grouped spectra\n";
return outIndex;
}
/** Load a single bank into the workspace
*
* @param nexusfilename :: file to open
* @param entry_name :: NXentry name
* @param bankName :: NXdata bank name
* @param WS :: workspace to modify
* @param id_to_wi :: det ID to workspace index mapping
*/
void LoadTOFRawNexus::loadBank(const std::string &nexusfilename,
const std::string &entry_name,
const std::string &bankName,
API::MatrixWorkspace_sptr WS,
const detid2index_map &id_to_wi) {
g_log.debug() << "Loading bank " << bankName << std::endl;
// To avoid segfaults on RHEL5/6 and Fedora
m_fileMutex.lock();
// Navigate to the point in the file
auto file = new ::NeXus::File(nexusfilename);
file->openGroup(entry_name, "NXentry");
file->openGroup("instrument", "NXinstrument");
file->openGroup(bankName, "NXdetector");
size_t m_numPixels = 0;
std::vector<uint32_t> pixel_id;
if (!m_assumeOldFile) {
// Load the pixel IDs
file->readData("pixel_id", pixel_id);
m_numPixels = pixel_id.size();
if (m_numPixels == 0) {
file->close();
m_fileMutex.unlock();
g_log.warning() << "Invalid pixel_id data in " << bankName << std::endl;
return;
}
} else {
// Load the x and y pixel offsets
std::vector<float> xoffsets;
std::vector<float> yoffsets;
file->readData("x_pixel_offset", xoffsets);
file->readData("y_pixel_offset", yoffsets);
m_numPixels = xoffsets.size() * yoffsets.size();
if (0 == m_numPixels) {
file->close();
m_fileMutex.unlock();
g_log.warning() << "Invalid (x,y) offsets in " << bankName << std::endl;
return;
}
size_t bankNum = 0;
if (bankName.size() > 4) {
if (bankName.substr(0, 4) == "bank") {
bankNum = boost::lexical_cast<size_t>(bankName.substr(4));
bankNum--;
} else {
file->close();
m_fileMutex.unlock();
g_log.warning() << "Invalid bank number for " << bankName << std::endl;
return;
}
}
// All good, so construct the pixel ID listing
size_t numX = xoffsets.size();
size_t numY = yoffsets.size();
for (size_t i = 0; i < numX; i++) {
for (size_t j = 0; j < numY; j++) {
pixel_id.push_back(
static_cast<uint32_t>(j + numY * (i + numX * bankNum)));
}
}
}
size_t iPart = 0;
if (m_spec_max != Mantid::EMPTY_INT()) {
uint32_t ifirst = pixel_id[0];
range_check out_range(m_spec_min, m_spec_max, id_to_wi);
auto newEnd = std::remove_if(pixel_id.begin(), pixel_id.end(), out_range);
pixel_id.erase(newEnd, pixel_id.end());
// check if beginning or end of array was erased
if (ifirst != pixel_id[0])
iPart = m_numPixels - pixel_id.size();
m_numPixels = pixel_id.size();
if (m_numPixels == 0) {
file->close();
m_fileMutex.unlock();
g_log.warning() << "No pixels from " << bankName << std::endl;
return;
};
}
// Load the TOF vector
std::vector<float> tof;
file->readData(m_axisField, tof);
size_t m_numBins = tof.size() - 1;
if (tof.size() <= 1) {
file->close();
m_fileMutex.unlock();
g_log.warning() << "Invalid " << m_axisField << " data in " << bankName
<< std::endl;
return;
}
// Make a shared pointer
MantidVecPtr Xptr;
MantidVec &X = Xptr.access();
X.resize(tof.size(), 0);
X.assign(tof.begin(), tof.end());
// Load the data. Coerce ints into double.
std::string errorsField = "";
std::vector<double> data;
file->openData(m_dataField);
file->getDataCoerce(data);
if (file->hasAttr("errors"))
file->getAttr("errors", errorsField);
file->closeData();
// Load the errors
bool hasErrors = !errorsField.empty();
std::vector<double> errors;
if (hasErrors) {
try {
file->openData(errorsField);
file->getDataCoerce(errors);
file->closeData();
} catch (...) {
g_log.information() << "Error loading the errors field, '" << errorsField
<< "' for bank " << bankName
<< ". Will use sqrt(counts). " << std::endl;
hasErrors = false;
}
}
/*if (data.size() != m_numBins * m_numPixels)
{ file->close(); m_fileMutex.unlock(); g_log.warning() << "Invalid size of '"
<< m_dataField << "' data in " << bankName << std::endl; return; }
if (hasErrors && (errors.size() != m_numBins * m_numPixels))
{ file->close(); m_fileMutex.unlock(); g_log.warning() << "Invalid size of '"
<< errorsField << "' errors in " << bankName << std::endl; return; }
*/
// Have all the data I need
m_fileMutex.unlock();
file->close();
for (size_t i = iPart; i < iPart + m_numPixels; i++) {
// Find the workspace index for this detector
detid_t pixelID = pixel_id[i - iPart];
size_t wi = id_to_wi.find(pixelID)->second;
// Set the basic info of that spectrum
ISpectrum *spec = WS->getSpectrum(wi);
spec->setSpectrumNo(specid_t(wi + 1));
spec->setDetectorID(pixel_id[i - iPart]);
// Set the shared X pointer
spec->setX(X);
// Extract the Y
MantidVec &Y = spec->dataY();
Y.assign(data.begin() + i * m_numBins, data.begin() + (i + 1) * m_numBins);
MantidVec &E = spec->dataE();
if (hasErrors) {
// Copy the errors from the loaded document
E.assign(errors.begin() + i * m_numBins,
errors.begin() + (i + 1) * m_numBins);
} else {
// Now take the sqrt(Y) to give E
E = Y;
std::transform(E.begin(), E.end(), E.begin(), (double (*)(double))sqrt);
}
}
// Done!
}
/** 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 GroupDetectors::exec()
{
// Get the input workspace
const MatrixWorkspace_sptr WS = getProperty("Workspace");
std::vector<size_t> indexList = getProperty("WorkspaceIndexList");
std::vector<specid_t> spectraList = getProperty("SpectraList");
const std::vector<detid_t> detectorList = getProperty("DetectorList");
// Could create a Validator to replace the below
if ( indexList.empty() && spectraList.empty() && detectorList.empty() )
{
g_log.information(name() +
": WorkspaceIndexList, SpectraList, and DetectorList properties are all empty, no grouping done");
return;
}
// Bin boundaries need to be the same, so check if they actually are
if (!API::WorkspaceHelpers::commonBoundaries(WS))
{
g_log.error("Can only group if the histograms have common bin boundaries");
throw std::runtime_error("Can only group if the histograms have common bin boundaries");
}
// If the spectraList property has been set, need to loop over the workspace looking for the
// appropriate spectra number and adding the indices they are linked to the list to be processed
if ( ! spectraList.empty() )
{
WS->getIndicesFromSpectra(spectraList,indexList);
}// End dealing with spectraList
else if ( ! detectorList.empty() )
{
// Dealing with DetectorList
//convert from detectors to workspace indices
WS->getIndicesFromDetectorIDs(detectorList, indexList);
}
if ( indexList.empty() )
{
g_log.warning("Nothing to group");
return;
}
const size_t vectorSize = WS->blocksize();
const specid_t firstIndex = static_cast<specid_t>(indexList[0]);
ISpectrum * firstSpectrum = WS->getSpectrum(firstIndex);
setProperty("ResultIndex",firstIndex);
// loop over the spectra to group
Progress progress(this, 0.0, 1.0, static_cast<int>(indexList.size()-1));
for (size_t i = 0; i < indexList.size()-1; ++i)
{
// The current spectrum
const size_t currentIndex = indexList[i+1];
ISpectrum * spec = WS->getSpectrum(currentIndex);
// Add the current detector to belong to the first spectrum
firstSpectrum->addDetectorIDs(spec->getDetectorIDs());
// Add up all the Y spectra and store the result in the first one
// Need to keep the next 3 lines inside loop for now until ManagedWorkspace mru-list works properly
MantidVec &firstY = WS->dataY(firstIndex);
MantidVec::iterator fYit;
MantidVec::iterator fEit = firstSpectrum->dataE().begin();
MantidVec::iterator Yit = spec->dataY().begin();
MantidVec::iterator Eit = spec->dataE().begin();
for (fYit = firstY.begin(); fYit != firstY.end(); ++fYit, ++fEit, ++Yit, ++Eit)
{
*fYit += *Yit;
// Assume 'normal' (i.e. Gaussian) combination of errors
*fEit = sqrt( (*fEit)*(*fEit) + (*Eit)*(*Eit) );
}
// Now zero the now redundant spectrum and set its spectraNo to indicate this (using -1)
// N.B. Deleting spectra would cause issues for ManagedWorkspace2D, hence the the approach taken here
spec->dataY().assign(vectorSize,0.0);
spec->dataE().assign(vectorSize,0.0);
spec->setSpectrumNo(-1);
spec->clearDetectorIDs();
progress.report();
}
}
