コード例 #1
0
    /**
     * Execute the algorithm
     */
    void ExtractMasking::exec()
    {
      MatrixWorkspace_const_sptr inputWS = getProperty("InputWorkspace");

      const int nHist = static_cast<int>(inputWS->getNumberHistograms());
      const int xLength(1), yLength(1);
      // Create a new workspace for the results, copy from the input to ensure that we copy over the instrument and current masking
      MatrixWorkspace_sptr outputWS = WorkspaceFactory::Instance().create(inputWS, nHist, xLength, yLength);

      Progress prog(this,0.0,1.0,nHist);
      MantidVecPtr xValues;
      xValues.access() = MantidVec(1, 0.0);

      PARALLEL_FOR2(inputWS, outputWS)
      for( int i = 0; i < nHist; ++i )
      {
        PARALLEL_START_INTERUPT_REGION
        // Spectrum in the output workspace
        ISpectrum * outSpec = outputWS->getSpectrum(i);
        // Spectrum in the input workspace
        const ISpectrum * inSpec = inputWS->getSpectrum(i);

        // Copy X, spectrum number and detector IDs
        outSpec->setX(xValues);
        outSpec->copyInfoFrom(*inSpec);

        IDetector_const_sptr inputDet;
        bool inputIsMasked(false);
        try
        {
          inputDet = inputWS->getDetector(i);
          if( inputDet->isMasked() )
          {
            inputIsMasked = true;
          }
        }
        catch(Kernel::Exception::NotFoundError &)
        {
          inputIsMasked = false;
        }

        if( inputIsMasked )
        {
          outSpec->dataY()[0] = 0.0;
          outSpec->dataE()[0] = 0.0;
        }
        else
        {
          outSpec->dataY()[0] = 1.0;
          outSpec->dataE()[0] = 1.0;
        }
        prog.report();

        PARALLEL_END_INTERUPT_REGION
      }
      PARALLEL_CHECK_INTERUPT_REGION

      setProperty("OutputWorkspace", outputWS);
    }
コード例 #2
0
void
MDHistoToWorkspace2D::checkW2D(Mantid::DataObjects::Workspace2D_sptr outWS) {
  size_t nSpectra = outWS->getNumberHistograms();
  size_t length = outWS->blocksize();
  MantidVec x, y, e;

  g_log.information() << "W2D has " << nSpectra << " histograms of length "
                      << length;
  for (size_t i = 0; i < nSpectra; i++) {
    ISpectrum *spec = outWS->getSpectrum(i);
    x = spec->dataX();
    y = spec->dataY();
    e = spec->dataE();
    if (x.size() != length) {
      g_log.information() << "Spectrum " << i << " x-size mismatch, is "
                          << x.size() << " should be " << length << "\n";
    }
    if (y.size() != length) {
      g_log.information() << "Spectrum " << i << " y-size mismatch, is "
                          << y.size() << " should be " << length << "\n";
    }
    if (e.size() != length) {
      g_log.information() << "Spectrum " << i << " e-size mismatch, is "
                          << e.size() << " should be " << length << "\n";
    }
  }
}
コード例 #3
0
ファイル: GroupDetectors2.cpp プロジェクト: trnielsen/mantid
/**
*  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";
}
コード例 #4
0
void ConvertToMatrixWorkspace::exec()
{
  MatrixWorkspace_const_sptr inputWorkspace = getProperty("InputWorkspace");
  // Let's see if we have to do anything first. Basically we want to avoid the data copy if we can
  DataObjects::EventWorkspace_const_sptr eventW = 
    boost::dynamic_pointer_cast<const DataObjects::EventWorkspace>(inputWorkspace);
  MatrixWorkspace_sptr outputWorkspace;
  if( eventW )
  {
    g_log.information() << "Converting EventWorkspace to Workspace2D.\n";

    const size_t numHists = inputWorkspace->getNumberHistograms();
    Progress prog(this,0.0,1.0,numHists*2);

    // Sort the input workspace in-place by TOF. This can be faster if there are few event lists.
    eventW->sortAll(TOF_SORT, &prog);

    // Create the output workspace. This will copy many aspects fron the input one.
    outputWorkspace = WorkspaceFactory::Instance().create(inputWorkspace);

    // ...but not the data, so do that here.
    PARALLEL_FOR2(inputWorkspace,outputWorkspace)
    for (int64_t i = 0; i < (int64_t)numHists; ++i)
    {
      PARALLEL_START_INTERUPT_REGION
      const ISpectrum * inSpec = inputWorkspace->getSpectrum(i);
      ISpectrum * outSpec = outputWorkspace->getSpectrum(i);

      outSpec->copyInfoFrom(*inSpec);
      outSpec->setX(inSpec->ptrX());
      outSpec->dataY() = inSpec->dataY();
      outSpec->dataE() = inSpec->dataE();
      
      prog.report("Binning");

      PARALLEL_END_INTERUPT_REGION
    }
    PARALLEL_CHECK_INTERUPT_REGION

    outputWorkspace->generateSpectraMap();
  }
  else
  {
コード例 #5
0
ファイル: GroupDetectors2.cpp プロジェクト: trnielsen/mantid
/**
*  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;
}
コード例 #6
0
/** 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!
}
コード例 #7
0
/**
 * 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();
}
コード例 #8
0
ファイル: SumSpectra.cpp プロジェクト: trnielsen/mantid
/** 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);

  }
}
コード例 #9
0
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();
  }

}