/** Set up an Event workspace
  * @param numentries :: number of log entries to output
  * @param times :: vector of Kernel::DateAndTime
  * @param values :: vector of log value in double
  */
void ExportTimeSeriesLog::setupEventWorkspace(int numentries,
                                              vector<DateAndTime> &times,
                                              vector<double> values) {
  Kernel::DateAndTime runstart(
      m_dataWS->run().getProperty("run_start")->value());

  // Get some stuff from the input workspace
  const size_t numberOfSpectra = 1;
  const int YLength = static_cast<int>(m_dataWS->blocksize());

  // Make a brand new EventWorkspace
  EventWorkspace_sptr outEventWS = boost::dynamic_pointer_cast<EventWorkspace>(
      API::WorkspaceFactory::Instance().create(
          "EventWorkspace", numberOfSpectra, YLength + 1, YLength));
  // Copy geometry over.
  API::WorkspaceFactory::Instance().initializeFromParent(m_dataWS, outEventWS,
                                                         false);

  m_outWS = boost::dynamic_pointer_cast<MatrixWorkspace>(outEventWS);
  if (!m_outWS)
    throw runtime_error(
        "Output workspace cannot be casted to a MatrixWorkspace.");

  g_log.debug("[DBx336] An output workspace is generated.!");

  // Create the output event list (empty)
  EventList &outEL = outEventWS->getOrAddEventList(0);
  outEL.switchTo(WEIGHTED_NOTIME);

  // Allocate all the required memory
  outEL.reserve(numentries);
  outEL.clearDetectorIDs();

  for (size_t i = 0; i < static_cast<size_t>(numentries); i++) {
    Kernel::DateAndTime tnow = times[i];
    int64_t dt = tnow.totalNanoseconds() - runstart.totalNanoseconds();

    // convert to microseconds
    double dtmsec = static_cast<double>(dt) / 1000.0;
    outEL.addEventQuickly(WeightedEventNoTime(dtmsec, values[i], values[i]));
  }
  // Ensure thread-safety
  outEventWS->sortAll(TOF_SORT, NULL);

  // Now, create a default X-vector for histogramming, with just 2 bins.
  Kernel::cow_ptr<MantidVec> axis;
  MantidVec &xRef = axis.access();
  xRef.resize(2);
  std::vector<WeightedEventNoTime> &events = outEL.getWeightedEventsNoTime();
  xRef[0] = events.begin()->tof();
  xRef[1] = events.rbegin()->tof();

  // Set the binning axis using this.
  outEventWS->setX(0, axis);

  return;
}
Beispiel #2
0
/** Creates the output workspace, setting the X vector to the bins boundaries in
 * Qx.
 *  @return A pointer to the newly-created workspace
 */
API::MatrixWorkspace_sptr
Qxy::setUpOutputWorkspace(API::MatrixWorkspace_const_sptr inputWorkspace) {
  const double max = getProperty("MaxQxy");
  const double delta = getProperty("DeltaQ");

  int bins = static_cast<int>(max / delta);
  if (bins * delta != max)
    ++bins; // Stop at first boundary past MaxQxy if max is not a multiple of
            // delta
  const double startVal = -1.0 * delta * bins;
  bins *= 2; // go from -max to +max
  bins += 1; // Add 1 - this is a histogram

  // Create an output workspace with the same meta-data as the input
  MatrixWorkspace_sptr outputWorkspace = WorkspaceFactory::Instance().create(
      inputWorkspace, bins - 1, bins, bins - 1);
  // ... but clear the masking from the parameter map as we don't want to carry
  // that over since this is essentially
  // a 2D rebin
  ParameterMap &pmap = outputWorkspace->instrumentParameters();
  pmap.clearParametersByName("masked");

  // Create a numeric axis to replace the vertical one
  Axis *verticalAxis = new BinEdgeAxis(bins);
  outputWorkspace->replaceAxis(1, verticalAxis);

  // Build up the X values
  Kernel::cow_ptr<MantidVec> axis;
  MantidVec &horizontalAxisRef = axis.access();
  horizontalAxisRef.resize(bins);
  for (int i = 0; i < bins; ++i) {
    const double currentVal = startVal + i * delta;
    // Set the X value
    horizontalAxisRef[i] = currentVal;
    // Set the Y value on the axis
    verticalAxis->setValue(i, currentVal);
  }

  // Fill the X vectors in the output workspace
  for (int i = 0; i < bins - 1; ++i) {
    outputWorkspace->setX(i, axis);
    for (int j = 0; j < bins - j; ++j) {
      outputWorkspace->dataY(i)[j] = std::numeric_limits<double>::quiet_NaN();
      outputWorkspace->dataE(i)[j] = std::numeric_limits<double>::quiet_NaN();
    }
  }

  // Set the axis units
  outputWorkspace->getAxis(1)->unit() = outputWorkspace->getAxis(0)->unit() =
      UnitFactory::Instance().create("MomentumTransfer");
  // Set the 'Y' unit (gets confusing here...this is probably a Z axis in this
  // case)
  outputWorkspace->setYUnitLabel("Cross Section (1/cm)");

  setProperty("OutputWorkspace", outputWorkspace);
  return outputWorkspace;
}
Beispiel #3
0
/**
 * Get shortest and longest tof from the Parameters file and sets the time
 * axis
 * Properties must be present in the Parameters file: shortest-tof,
 * longest-tof
 */
void LoadSwans::setTimeAxis() {
  const unsigned int shortest_tof = static_cast<unsigned int>(
      m_ws->getInstrument()->getNumberParameter("shortest-tof")[0]);
  const unsigned int longest_tof = static_cast<unsigned int>(
      m_ws->getInstrument()->getNumberParameter("longest-tof")[0]);
  // Now, create a default X-vector for histogramming, with just 2 bins.
  Kernel::cow_ptr<MantidVec> axis;
  MantidVec &xRef = axis.access();
  xRef = {static_cast<double>(shortest_tof), static_cast<double>(longest_tof)};
  // Set the binning axis using this.
  m_ws->setAllX(axis);
}
Beispiel #4
0
/**
 * Execute the algorithm.
 */
void LoadBBY::exec() {
  // Delete the output workspace name if it existed
  std::string outName = getPropertyValue("OutputWorkspace");
  if (API::AnalysisDataService::Instance().doesExist(outName))
    API::AnalysisDataService::Instance().remove(outName);

  // Get the name of the data file.
  std::string filename = getPropertyValue(FilenameStr);
  ANSTO::Tar::File tarFile(filename);
  if (!tarFile.good())
    throw std::invalid_argument("invalid BBY file");

  // region of intreset
  std::vector<bool> roi = createRoiVector(getPropertyValue(MaskStr));

  double tofMinBoundary = getProperty(FilterByTofMinStr);
  double tofMaxBoundary = getProperty(FilterByTofMaxStr);

  double timeMinBoundary = getProperty(FilterByTimeStartStr);
  double timeMaxBoundary = getProperty(FilterByTimeStopStr);

  if (isEmpty(tofMaxBoundary))
    tofMaxBoundary = std::numeric_limits<double>::infinity();
  if (isEmpty(timeMaxBoundary))
    timeMaxBoundary = std::numeric_limits<double>::infinity();

  API::Progress prog(this, 0.0, 1.0, Progress_Total);
  prog.doReport("creating instrument");

  // create workspace
  DataObjects::EventWorkspace_sptr eventWS =
      boost::make_shared<DataObjects::EventWorkspace>();

  eventWS->initialize(HISTO_BINS_Y * HISTO_BINS_X,
                      2, // number of TOF bin boundaries
                      1);

  // set the units
  eventWS->getAxis(0)->unit() = Kernel::UnitFactory::Instance().create("TOF");
  eventWS->setYUnit("Counts");

  // set title
  const std::vector<std::string> &subFiles = tarFile.files();
  for (const auto &subFile : subFiles)
    if (subFile.compare(0, 3, "BBY") == 0) {
      std::string title = subFile;

      if (title.rfind(".hdf") == title.length() - 4)
        title.resize(title.length() - 4);

      if (title.rfind(".nx") == title.length() - 3)
        title.resize(title.length() - 3);

      eventWS->setTitle(title);
      break;
    }

  // create instrument
  InstrumentInfo instrumentInfo;

  // Geometry::Instrument_sptr instrument =
  createInstrument(tarFile, /* ref */ instrumentInfo);
  // eventWS->setInstrument(instrument);

  // load events
  size_t numberHistograms = eventWS->getNumberHistograms();

  std::vector<EventVector_pt> eventVectors(numberHistograms, nullptr);
  std::vector<size_t> eventCounts(numberHistograms, 0);

  // phase correction
  Kernel::Property *periodMasterProperty =
      getPointerToProperty(PeriodMasterStr);
  Kernel::Property *periodSlaveProperty = getPointerToProperty(PeriodSlaveStr);
  Kernel::Property *phaseSlaveProperty = getPointerToProperty(PhaseSlaveStr);

  double periodMaster;
  double periodSlave;
  double phaseSlave;

  if (periodMasterProperty->isDefault() || periodSlaveProperty->isDefault() ||
      phaseSlaveProperty->isDefault()) {

    if (!periodMasterProperty->isDefault() ||
        !periodSlaveProperty->isDefault() || !phaseSlaveProperty->isDefault()) {
      throw std::invalid_argument("Please specify PeriodMaster, PeriodSlave "
                                  "and PhaseSlave or none of them.");
    }

    // if values have not been specified in loader then use values from hdf file
    periodMaster = instrumentInfo.period_master;
    periodSlave = instrumentInfo.period_slave;
    phaseSlave = instrumentInfo.phase_slave;
  } else {
    periodMaster = getProperty(PeriodMasterStr);
    periodSlave = getProperty(PeriodSlaveStr);
    phaseSlave = getProperty(PhaseSlaveStr);

    if ((periodMaster < 0.0) || (periodSlave < 0.0))
      throw std::invalid_argument(
          "Please specify a positive value for PeriodMaster and PeriodSlave.");
  }

  double period = periodSlave;
  double shift = -1.0 / 6.0 * periodMaster - periodSlave * phaseSlave / 360.0;

  // count total events per pixel to reserve necessary memory
  ANSTO::EventCounter eventCounter(
      roi, HISTO_BINS_Y, period, shift, tofMinBoundary, tofMaxBoundary,
      timeMinBoundary, timeMaxBoundary, eventCounts);

  loadEvents(prog, "loading neutron counts", tarFile, eventCounter);

  // prepare event storage
  ANSTO::ProgressTracker progTracker(prog, "creating neutron event lists",
                                     numberHistograms, Progress_ReserveMemory);

  for (size_t i = 0; i != numberHistograms; ++i) {
    DataObjects::EventList &eventList = eventWS->getEventList(i);

    eventList.setSortOrder(DataObjects::PULSETIME_SORT);
    eventList.reserve(eventCounts[i]);

    eventList.setDetectorID(static_cast<detid_t>(i));
    eventList.setSpectrumNo(static_cast<detid_t>(i));

    DataObjects::getEventsFrom(eventList, eventVectors[i]);

    progTracker.update(i);
  }
  progTracker.complete();

  ANSTO::EventAssigner eventAssigner(
      roi, HISTO_BINS_Y, period, shift, tofMinBoundary, tofMaxBoundary,
      timeMinBoundary, timeMaxBoundary, eventVectors);

  loadEvents(prog, "loading neutron events", tarFile, eventAssigner);

  Kernel::cow_ptr<MantidVec> axis;
  MantidVec &xRef = axis.access();
  xRef.resize(2, 0.0);
  xRef[0] = std::max(
      0.0,
      floor(eventCounter.tofMin())); // just to make sure the bins hold it all
  xRef[1] = eventCounter.tofMax() + 1;
  eventWS->setAllX(axis);

  // count total number of masked bins
  size_t maskedBins = 0;
  for (size_t i = 0; i != roi.size(); i++)
    if (!roi[i])
      maskedBins++;

  if (maskedBins > 0) {
    // create list of masked bins
    std::vector<size_t> maskIndexList(maskedBins);
    size_t maskIndex = 0;

    for (size_t i = 0; i != roi.size(); i++)
      if (!roi[i])
        maskIndexList[maskIndex++] = i;

    API::IAlgorithm_sptr maskingAlg = createChildAlgorithm("MaskDetectors");
    maskingAlg->setProperty("Workspace", eventWS);
    maskingAlg->setProperty("WorkspaceIndexList", maskIndexList);
    maskingAlg->executeAsChildAlg();
  }

  // set log values
  API::LogManager &logManager = eventWS->mutableRun();

  logManager.addProperty("filename", filename);
  logManager.addProperty("att_pos", static_cast<int>(instrumentInfo.att_pos));
  logManager.addProperty("frame_count",
                         static_cast<int>(eventCounter.numFrames()));
  logManager.addProperty("period", period);

  // currently beam monitor counts are not available, instead number of frames
  // times period is used
  logManager.addProperty(
      "bm_counts", static_cast<double>(eventCounter.numFrames()) * period /
                       1.0e6); // static_cast<double>(instrumentInfo.bm_counts)

  // currently
  Kernel::time_duration duration =
      boost::posix_time::microseconds(static_cast<boost::int64_t>(
          static_cast<double>(eventCounter.numFrames()) * period));

  Kernel::DateAndTime start_time("2000-01-01T00:00:00");
  Kernel::DateAndTime end_time(start_time + duration);

  logManager.addProperty("start_time", start_time.toISO8601String());
  logManager.addProperty("end_time", end_time.toISO8601String());

  std::string time_str = start_time.toISO8601String();
  AddSinglePointTimeSeriesProperty(logManager, time_str, "L1_chopper_value",
                                   instrumentInfo.L1_chopper_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "L2_det_value",
                                   instrumentInfo.L2_det_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "L2_curtainl_value",
                                   instrumentInfo.L2_curtainl_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "L2_curtainr_value",
                                   instrumentInfo.L2_curtainr_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "L2_curtainu_value",
                                   instrumentInfo.L2_curtainu_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "L2_curtaind_value",
                                   instrumentInfo.L2_curtaind_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "D_det_value",
                                   instrumentInfo.D_det_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "D_curtainl_value",
                                   instrumentInfo.D_curtainl_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "D_curtainr_value",
                                   instrumentInfo.D_curtainr_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "D_curtainu_value",
                                   instrumentInfo.D_curtainu_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "D_curtaind_value",
                                   instrumentInfo.D_curtaind_value);
  AddSinglePointTimeSeriesProperty(logManager, time_str, "curtain_rotation",
                                   10.0);

  API::IAlgorithm_sptr loadInstrumentAlg =
      createChildAlgorithm("LoadInstrument");
  loadInstrumentAlg->setProperty("Workspace", eventWS);
  loadInstrumentAlg->setPropertyValue("InstrumentName", "BILBY");
  loadInstrumentAlg->setProperty("RewriteSpectraMap",
                                 Mantid::Kernel::OptionalBool(false));
  loadInstrumentAlg->executeAsChildAlg();

  setProperty("OutputWorkspace", eventWS);
}
Beispiel #5
0
/** Process the event file properly.
 * @param workspace :: EventWorkspace to write to.
 */
void
LoadEventPreNexus::procEvents(DataObjects::EventWorkspace_sptr &workspace) {
  this->num_error_events = 0;
  this->num_good_events = 0;
  this->num_ignored_events = 0;

  // Default values in the case of no parallel
  size_t loadBlockSize = Mantid::Kernel::DEFAULT_BLOCK_SIZE * 2;

  shortest_tof = static_cast<double>(MAX_TOF_UINT32) * TOF_CONVERSION;
  longest_tof = 0.;

  // Initialize progress reporting.
  size_t numBlocks = (max_events + loadBlockSize - 1) / loadBlockSize;

  // We want to pad out empty pixels.
  detid2det_map detector_map;
  workspace->getInstrument()->getDetectors(detector_map);

  // -------------- Determine processing mode
  std::string procMode = getProperty("UseParallelProcessing");
  if (procMode == "Serial")
    parallelProcessing = false;
  else if (procMode == "Parallel")
    parallelProcessing = true;
  else {
    // Automatic determination. Loading serially (for me) is about 3 million
    // events per second,
    // (which is sped up by ~ x 3 with parallel processing, say 10 million per
    // second, e.g. 7 million events more per seconds).
    // compared to a setup time/merging time of about 10 seconds per million
    // detectors.
    double setUpTime = double(detector_map.size()) * 10e-6;
    parallelProcessing = ((double(max_events) / 7e6) > setUpTime);
    g_log.debug() << (parallelProcessing ? "Using" : "Not using")
                  << " parallel processing." << std::endl;
  }

  // determine maximum pixel id
  detid2det_map::iterator it;
  detid_max = 0; // seems like a safe lower bound
  for (it = detector_map.begin(); it != detector_map.end(); it++)
    if (it->first > detid_max)
      detid_max = it->first;

  // Pad all the pixels
  prog->report("Padding Pixels");
  this->pixel_to_wkspindex.reserve(
      detid_max + 1); // starting at zero up to and including detid_max
  // Set to zero
  this->pixel_to_wkspindex.assign(detid_max + 1, 0);
  size_t workspaceIndex = 0;
  for (it = detector_map.begin(); it != detector_map.end(); it++) {
    if (!it->second->isMonitor()) {
      this->pixel_to_wkspindex[it->first] = workspaceIndex;
      EventList &spec = workspace->getOrAddEventList(workspaceIndex);
      spec.addDetectorID(it->first);
      // Start the spectrum number at 1
      spec.setSpectrumNo(specid_t(workspaceIndex + 1));
      workspaceIndex += 1;
    }
  }

  // For slight speed up
  loadOnlySomeSpectra = (this->spectra_list.size() > 0);

  // Turn the spectra list into a map, for speed of access
  for (std::vector<int64_t>::iterator it = spectra_list.begin();
       it != spectra_list.end(); it++)
    spectraLoadMap[*it] = true;

  CPUTimer tim;

  // --------------- Create the partial workspaces
  // ------------------------------------------
  // Vector of partial workspaces, for parallel processing.
  std::vector<EventWorkspace_sptr> partWorkspaces;
  std::vector<DasEvent *> buffers;

  /// Pointer to the vector of events
  typedef std::vector<TofEvent> *EventVector_pt;
  /// Bare array of arrays of pointers to the EventVectors
  EventVector_pt **eventVectors;

  /// How many threads will we use?
  size_t numThreads = 1;
  if (parallelProcessing)
    numThreads = size_t(PARALLEL_GET_MAX_THREADS);

  partWorkspaces.resize(numThreads);
  buffers.resize(numThreads);
  eventVectors = new EventVector_pt *[numThreads];

  // cppcheck-suppress syntaxError
  PRAGMA_OMP( parallel for if (parallelProcessing) )
  for (int i = 0; i < int(numThreads); i++) {
    // This is the partial workspace we are about to create (if in parallel)
    EventWorkspace_sptr partWS;
    if (parallelProcessing) {
      prog->report("Creating Partial Workspace");
      // Create a partial workspace
      partWS = EventWorkspace_sptr(new EventWorkspace());
      // Make sure to initialize.
      partWS->initialize(1, 1, 1);
      // Copy all the spectra numbers and stuff (no actual events to copy
      // though).
      partWS->copyDataFrom(*workspace);
      // Push it in the array
      partWorkspaces[i] = partWS;
    } else
      partWS = workspace;

    // Allocate the buffers
    buffers[i] = new DasEvent[loadBlockSize];

    // For each partial workspace, make an array where index = detector ID and
    // value = pointer to the events vector
    eventVectors[i] = new EventVector_pt[detid_max + 1];
    EventVector_pt *theseEventVectors = eventVectors[i];
    for (detid_t j = 0; j < detid_max + 1; j++) {
      size_t wi = pixel_to_wkspindex[j];
      // Save a POINTER to the vector<tofEvent>
      theseEventVectors[j] = &partWS->getEventList(wi).getEvents();
    }
  }

  g_log.debug() << tim << " to create " << partWorkspaces.size()
                << " workspaces for parallel loading." << std::endl;

  prog->resetNumSteps(numBlocks, 0.1, 0.8);

  // ---------------------------------- LOAD THE DATA --------------------------
  PRAGMA_OMP( parallel for schedule(dynamic, 1) if (parallelProcessing) )
  for (int blockNum = 0; blockNum < int(numBlocks); blockNum++) {
    PARALLEL_START_INTERUPT_REGION

    // Find the workspace for this particular thread
    EventWorkspace_sptr ws;
    size_t threadNum = 0;
    if (parallelProcessing) {
      threadNum = PARALLEL_THREAD_NUMBER;
      ws = partWorkspaces[threadNum];
    } else
      ws = workspace;

    // Get the buffer (for this thread)
    DasEvent *event_buffer = buffers[threadNum];

    // Get the speeding-up array of vector<tofEvent> where index = detid.
    EventVector_pt *theseEventVectors = eventVectors[threadNum];

    // Where to start in the file?
    size_t fileOffset = first_event + (loadBlockSize * blockNum);
    // May need to reduce size of last (or only) block
    size_t current_event_buffer_size =
        (blockNum == int(numBlocks - 1))
            ? (max_events - (numBlocks - 1) * loadBlockSize)
            : loadBlockSize;

    // Load this chunk of event data (critical block)
    PARALLEL_CRITICAL(LoadEventPreNexus_fileAccess) {
      current_event_buffer_size = eventfile->loadBlockAt(
          event_buffer, fileOffset, current_event_buffer_size);
    }

    // This processes the events. Can be done in parallel!
    procEventsLinear(ws, theseEventVectors, event_buffer,
                     current_event_buffer_size, fileOffset);

    // Report progress
    prog->report("Load Event PreNeXus");

    PARALLEL_END_INTERUPT_REGION
  }
  PARALLEL_CHECK_INTERUPT_REGION
  g_log.debug() << tim << " to load the data." << std::endl;

  // ---------------------------------- MERGE WORKSPACES BACK TOGETHER
  // --------------------------
  if (parallelProcessing) {
    PARALLEL_START_INTERUPT_REGION
    prog->resetNumSteps(workspace->getNumberHistograms(), 0.8, 0.95);

    size_t memoryCleared = 0;
    MemoryManager::Instance().releaseFreeMemory();

    // Merge all workspaces, index by index.
    PARALLEL_FOR_NO_WSP_CHECK()
    for (int iwi = 0; iwi < int(workspace->getNumberHistograms()); iwi++) {
      size_t wi = size_t(iwi);

      // The output event list.
      EventList &el = workspace->getEventList(wi);
      el.clear(false);

      // How many events will it have?
      size_t numEvents = 0;
      for (size_t i = 0; i < numThreads; i++)
        numEvents += partWorkspaces[i]->getEventList(wi).getNumberEvents();
      // This will avoid too much copying.
      el.reserve(numEvents);

      // Now merge the event lists
      for (size_t i = 0; i < numThreads; i++) {
        EventList &partEl = partWorkspaces[i]->getEventList(wi);
        el += partEl.getEvents();
        // Free up memory as you go along.
        partEl.clear(false);
      }

      // With TCMalloc, release memory when you accumulate enough to make sense
      PARALLEL_CRITICAL(LoadEventPreNexus_trackMemory) {
        memoryCleared += numEvents;
        if (memoryCleared > 10000000) // ten million events = about 160 MB
        {
          MemoryManager::Instance().releaseFreeMemory();
          memoryCleared = 0;
        }
      }
      prog->report("Merging Workspaces");
    }
    // Final memory release
    MemoryManager::Instance().releaseFreeMemory();
    g_log.debug() << tim << " to merge workspaces together." << std::endl;
    PARALLEL_END_INTERUPT_REGION
  }
  PARALLEL_CHECK_INTERUPT_REGION

  // Delete the buffers for each thread.
  for (size_t i = 0; i < numThreads; i++) {
    delete[] buffers[i];
    delete[] eventVectors[i];
  }
  delete[] eventVectors;
  // delete [] pulsetimes;

  prog->resetNumSteps(3, 0.94, 1.00);

  // finalize loading
  prog->report("Deleting Empty Lists");
  if (loadOnlySomeSpectra)
    workspace->deleteEmptyLists();

  prog->report("Setting proton charge");
  this->setProtonCharge(workspace);
  g_log.debug() << tim << " to set the proton charge log." << std::endl;

  // Make sure the MRU is cleared
  workspace->clearMRU();

  // Now, create a default X-vector for histogramming, with just 2 bins.
  Kernel::cow_ptr<MantidVec> axis;
  MantidVec &xRef = axis.access();
  xRef.resize(2);
  xRef[0] = shortest_tof - 1; // Just to make sure the bins hold it all
  xRef[1] = longest_tof + 1;
  workspace->setAllX(axis);
  this->pixel_to_wkspindex.clear();

  g_log.information() << "Read " << this->num_good_events << " events + "
                      << this->num_error_events << " errors"
                      << ". Shortest TOF: " << shortest_tof
                      << " microsec; longest TOF: " << longest_tof
                      << " microsec." << std::endl;
}
Beispiel #6
0
/**
 * Return the confidence with with this algorithm can load the file
 * @param eventEntries map of the file entries that have events
 * @param outputGroup pointer to the workspace group
 * @param nxFile Reads data from inside first first top entry
 */
void LoadMcStas::readEventData(
    const std::map<std::string, std::string> &eventEntries,
    WorkspaceGroup_sptr &outputGroup, ::NeXus::File &nxFile) {
  std::string filename = getPropertyValue("Filename");
  auto entries = nxFile.getEntries();

  // will assume that each top level entry contain one mcstas
  // generated IDF and any event data entries within this top level
  // entry are data collected for that instrument
  // This code for loading the instrument is for now adjusted code from
  // ExperimentalInfo.

  // Close data folder and go back to top level. Then read and close the
  // Instrument folder.
  nxFile.closeGroup();

  Geometry::Instrument_sptr instrument;

  // Initialize progress reporting
  int reports = 2;
  const double progressFractionInitial = 0.1;
  Progress progInitial(this, 0.0, progressFractionInitial, reports);

  try {
    nxFile.openGroup("instrument", "NXinstrument");
    std::string instrumentXML;
    nxFile.openGroup("instrument_xml", "NXnote");
    nxFile.readData("data", instrumentXML);
    nxFile.closeGroup();
    nxFile.closeGroup();

    progInitial.report("Loading instrument");

    Geometry::InstrumentDefinitionParser parser;
    std::string instrumentName = "McStas";
    parser.initialize(filename, instrumentName, instrumentXML);
    std::string instrumentNameMangled = parser.getMangledName();

    // Check whether the instrument is already in the InstrumentDataService
    if (InstrumentDataService::Instance().doesExist(instrumentNameMangled)) {
      // If it does, just use the one from the one stored there
      instrument =
          InstrumentDataService::Instance().retrieve(instrumentNameMangled);
    } else {
      // Really create the instrument
      instrument = parser.parseXML(NULL);
      // Add to data service for later retrieval
      InstrumentDataService::Instance().add(instrumentNameMangled, instrument);
    }
  } catch (...) {
    // Loader should not stop if there is no IDF.xml
    g_log.warning()
        << "\nCould not find the instrument description in the Nexus file:"
        << filename << " Ignore evntdata from data file" << std::endl;
    return;
  }
  // Finished reading Instrument. Then open new data folder again
  nxFile.openGroup("data", "NXdetector");

  // create and prepare an event workspace ready to receive the mcstas events
  progInitial.report("Set up EventWorkspace");
  EventWorkspace_sptr eventWS(new EventWorkspace());
  // initialize, where create up front number of eventlists = number of
  // detectors
  eventWS->initialize(instrument->getNumberDetectors(), 1, 1);
  // Set the units
  eventWS->getAxis(0)->unit() = UnitFactory::Instance().create("TOF");
  eventWS->setYUnit("Counts");
  // set the instrument
  eventWS->setInstrument(instrument);
  // assign detector ID to eventlists

  std::vector<detid_t> detIDs = instrument->getDetectorIDs();

  for (size_t i = 0; i < instrument->getNumberDetectors(); i++) {
    eventWS->getEventList(i).addDetectorID(detIDs[i]);
    // spectrum number are treated as equal to detector IDs for McStas data
    eventWS->getEventList(i).setSpectrumNo(detIDs[i]);
  }
  // the one is here for the moment for backward compatibility
  eventWS->rebuildSpectraMapping(true);

  bool isAnyNeutrons = false;
  // to store shortest and longest recorded TOF
  double shortestTOF(0.0);
  double longestTOF(0.0);

  const size_t numEventEntries = eventEntries.size();
  Progress progEntries(this, progressFractionInitial, 1.0, numEventEntries * 2);
  for (auto eit = eventEntries.begin(); eit != eventEntries.end(); ++eit) {
    std::string dataName = eit->first;
    std::string dataType = eit->second;

    // open second level entry
    nxFile.openGroup(dataName, dataType);
    std::vector<double> data;
    nxFile.openData("events");
    progEntries.report("read event data from nexus");

    // Need to take into account that the nexus readData method reads a
    // multi-column data entry
    // into a vector
    // The number of data column for each neutron is here hardcoded to (p, x,
    // y,  n, id, t)
    // Thus  we have
    // column  0 : p 	neutron wight
    // column  1 : x 	x coordinate
    // column  2 : y 	y coordinate
    // column  3 : n 	accumulated number of neutrons
    // column  4 : id 	pixel id
    // column  5 : t 	time

    // get info about event data
    ::NeXus::Info id_info = nxFile.getInfo();
    if (id_info.dims.size() != 2) {
      g_log.error() << "Event data in McStas nexus file not loaded. Expected "
                       "event data block to be two dimensional" << std::endl;
      return;
    }
    int64_t nNeutrons = id_info.dims[0];
    int64_t numberOfDataColumn = id_info.dims[1];
    if (nNeutrons && numberOfDataColumn != 6) {
      g_log.error() << "Event data in McStas nexus file expecting 6 columns"
                    << std::endl;
      return;
    }
    if (isAnyNeutrons == false && nNeutrons > 0)
      isAnyNeutrons = true;

    std::vector<int64_t> start(2);
    std::vector<int64_t> step(2);

    // read the event data in blocks. 1 million event is 1000000*6*8 doubles
    // about 50Mb
    int64_t nNeutronsInBlock = 1000000;
    int64_t nOfFullBlocks = nNeutrons / nNeutronsInBlock;
    int64_t nRemainingNeutrons = nNeutrons - nOfFullBlocks * nNeutronsInBlock;
    // sum over number of blocks + 1 to cover the remainder
    for (int64_t iBlock = 0; iBlock < nOfFullBlocks + 1; iBlock++) {
      if (iBlock == nOfFullBlocks) {
        // read remaining neutrons
        start[0] = nOfFullBlocks * nNeutronsInBlock;
        start[1] = 0;
        step[0] = nRemainingNeutrons;
        step[1] = numberOfDataColumn;
      } else {
        // read neutrons in a full block
        start[0] = iBlock * nNeutronsInBlock;
        start[1] = 0;
        step[0] = nNeutronsInBlock;
        step[1] = numberOfDataColumn;
      }
      const int64_t nNeutronsForthisBlock =
          step[0]; // number of neutrons read for this block
      data.resize(nNeutronsForthisBlock * numberOfDataColumn);

      // Check that the type is what it is supposed to be
      if (id_info.type == ::NeXus::FLOAT64) {
        nxFile.getSlab(&data[0], start, step);
      } else {
        g_log.warning()
            << "Entry event field is not FLOAT64! It will be skipped.\n";
        continue;
      }

      // populate workspace with McStas events
      const detid2index_map detIDtoWSindex_map =
          eventWS->getDetectorIDToWorkspaceIndexMap(true);

      progEntries.report("read event data into workspace");
      for (int64_t in = 0; in < nNeutronsForthisBlock; in++) {
        const int detectorID =
            static_cast<int>(data[4 + numberOfDataColumn * in]);
        const double detector_time = data[5 + numberOfDataColumn * in] *
                                     1.0e6; // convert to microseconds
        if (in == 0 && iBlock == 0) {
          shortestTOF = detector_time;
          longestTOF = detector_time;
        } else {
          if (detector_time < shortestTOF)
            shortestTOF = detector_time;
          if (detector_time > longestTOF)
            longestTOF = detector_time;
        }

        const size_t workspaceIndex =
            detIDtoWSindex_map.find(detectorID)->second;

        int64_t pulse_time = 0;
        // eventWS->getEventList(workspaceIndex) +=
        // TofEvent(detector_time,pulse_time);
        // eventWS->getEventList(workspaceIndex) += TofEvent(detector_time);
        eventWS->getEventList(workspaceIndex) += WeightedEvent(
            detector_time, pulse_time, data[numberOfDataColumn * in], 1.0);
      }
    } // end reading over number of blocks of an event dataset

    // nxFile.getData(data);
    nxFile.closeData();
    nxFile.closeGroup();

  } // end reading over number of event datasets

  // Create a default TOF-vector for histogramming, for now just 2 bins
  // 2 bins is the standard. However for McStas simulation data it may make
  // sense to
  // increase this number for better initial visual effect
  Kernel::cow_ptr<MantidVec> axis;
  MantidVec &xRef = axis.access();
  xRef.resize(2, 0.0);
  // if ( nNeutrons > 0)
  if (isAnyNeutrons) {
    xRef[0] = shortestTOF - 1; // Just to make sure the bins hold it all
    xRef[1] = longestTOF + 1;
  }
  // Set the binning axis
  eventWS->setAllX(axis);

  // ensure that specified name is given to workspace (eventWS) when added to
  // outputGroup
  std::string nameOfGroupWS = getProperty("OutputWorkspace");
  std::string nameUserSee = std::string("EventData_") + nameOfGroupWS;
  std::string extraProperty =
      "Outputworkspace_dummy_" +
      boost::lexical_cast<std::string>(m_countNumWorkspaceAdded);
  declareProperty(new WorkspaceProperty<Workspace>(extraProperty, nameUserSee,
                                                   Direction::Output));
  setProperty(extraProperty, boost::static_pointer_cast<Workspace>(eventWS));
  m_countNumWorkspaceAdded++; // need to increment to ensure extraProperty are
                              // unique

  outputGroup->addWorkspace(eventWS);
}