C++ MatrixWorkspace_sptr::run方法代码示例

/** Set goniometer to matrix workspace and get its rotation matrix R (from
 * Q-sample to Q-lab
 * and output 1/R
 * @brief ConvertCWSDExpToMomentum::setupTransferMatrix
 * @param dataws :: matrix workspace containing sample rotation angles
 * @param rotationMatrix :: output as matrix 1/R to convert from Q-lab to
 * Q-sample
 */
void ConvertCWSDExpToMomentum::setupTransferMatrix(
    API::MatrixWorkspace_sptr dataws, Kernel::DblMatrix &rotationMatrix) {
  // Check sample logs
  if (!dataws->run().hasProperty("_omega") ||
      !dataws->run().hasProperty("_chi") || !dataws->run().hasProperty("_phi"))
    throw std::runtime_error(
        "Data workspace does not have sample log _phi, _chi or _omega. "
        "Unable to set goniometer and calcualte roation matrix R.");

  // Call algorithm SetGoniometer
  IAlgorithm_sptr setalg = createChildAlgorithm("SetGoniometer");
  setalg->initialize();
  setalg->setProperty("Workspace", dataws);
  setalg->setProperty("Axis0", "_omega,0,1,0,-1");
  setalg->setProperty("Axis1", "_chi,0,0,1,-1");
  setalg->setProperty("Axis2", "_phi,0,1,0,-1");
  setalg->execute();

  if (setalg->isExecuted()) {
    rotationMatrix = dataws->run().getGoniometer().getR();
    g_log.debug() << "Ratation matrix: " << rotationMatrix.str() << "\n";
    rotationMatrix.Invert();
    g_log.debug() << "Ratation matrix: " << rotationMatrix.str() << "\n";
  } else
    throw std::runtime_error("Unable to set Goniometer.");

  return;
}

/*
 * Check log in workspace
 */
void ProcessDasNexusLog::checkLog(API::MatrixWorkspace_sptr ws,
                                  std::string logname) {
  // 1. Get log
  Kernel::Property *log = ws->run().getProperty(logname);
  if (!log) {
    g_log.error() << "Log " << logname << " does not exist!" << std::endl;
    throw std::invalid_argument("Non-exising log name");
  }
  Kernel::TimeSeriesProperty<double> *tslog =
      dynamic_cast<Kernel::TimeSeriesProperty<double> *>(log);
  if (!tslog) {
    g_log.error() << "Log " << logname << " is not time series log"
                  << std::endl;
    throw std::invalid_argument("Log type error!");
  }

  // 2. Survey
  std::vector<Kernel::DateAndTime> times = tslog->timesAsVector();
  g_log.information() << "Entries of times = " << times.size() << std::endl;
  size_t countsame = 0;
  size_t countinverse = 0;
  for (size_t i = 1; i < times.size(); i++) {
    Kernel::DateAndTime tprev = times[i - 1];
    Kernel::DateAndTime tpres = times[i];
    if (tprev == tpres)
      countsame++;
    else if (tprev > tpres)
      countinverse++;
  }

  // 3. Output
  Kernel::DateAndTime t0(ws->run().getProperty("run_start")->value());
  Kernel::time_duration dts = times[0] - t0;
  Kernel::time_duration dtf = times[times.size() - 1] - t0;
  size_t f = times.size() - 1;

  g_log.information() << "Number of Equal Time Stamps    = " << countsame
                      << std::endl;
  g_log.information() << "Number of Inverted Time Stamps = " << countinverse
                      << std::endl;
  g_log.information() << "Run Start = " << t0.totalNanoseconds() << std::endl;
  g_log.information() << "First Log (Absolute Time, Relative Time): "
                      << times[0].totalNanoseconds() << ", "
                      << Kernel::DateAndTime::nanosecondsFromDuration(dts)
                      << std::endl;
  g_log.information() << "Last  Log (Absolute Time, Relative Time): "
                      << times[f].totalNanoseconds() << ", "
                      << Kernel::DateAndTime::nanosecondsFromDuration(dtf)
                      << std::endl;

  return;
}

double getSourceToSampleDistance(API::MatrixWorkspace_sptr dataWS) {
  const int nguides =
      dataWS->run().getPropertyValueAsType<int>("number-of-guides");

  std::vector<std::string> pars =
      dataWS->getInstrument()->getStringParameter("aperture-distances");
  if (pars.empty())
    throw Kernel::Exception::InstrumentDefinitionError(
        "Unable to find [aperture-distances] instrument parameter");

  double SSD = 0;
  Mantid::Kernel::StringTokenizer tok(
      pars[0], ",", Mantid::Kernel::StringTokenizer::TOK_IGNORE_EMPTY);
  if (tok.count() > 0 && tok.count() < 10 && nguides >= 0 && nguides < 9) {
    const std::string distance_as_string = tok[8 - nguides];
    if (!Poco::NumberParser::tryParseFloat(distance_as_string, SSD))
      throw Kernel::Exception::InstrumentDefinitionError(
          "Bad value for source-to-sample distance");
  } else
    throw Kernel::Exception::InstrumentDefinitionError(
        "Unable to get source-to-sample distance");

  // Check for an offset
  if (dataWS->getInstrument()->hasParameter("source-distance-offset")) {
    const double offset =
        readInstrumentParameter("source-distance-offset", dataWS);
    SSD += offset;
  }
  return SSD;
}

/**
 * @brief LoadSpiceAscii::setupRunStartTime
 * @param runinfows
 * @param datetimeprop
 */
void LoadSpiceAscii::setupRunStartTime(
    API::MatrixWorkspace_sptr runinfows,
    const std::vector<std::string> &datetimeprop) {
  // Check if no need to process run start time
  if (datetimeprop.empty()) {
    g_log.information("User chooses not to set up run start date and time.");
    return;
  }

  // Parse property vector
  if (datetimeprop.size() != 4) {
    g_log.warning() << "Run start date and time property must contain 4 "
                       "strings.  User only specifies " << datetimeprop.size()
                    << ".  Set up failed."
                    << "\n";
    return;
  }

  // Parse
  std::string datelogname = datetimeprop[0];
  std::string timelogname = datetimeprop[2];
  if (!(runinfows->run().hasProperty(datelogname) &&
        runinfows->run().hasProperty(timelogname))) {
    std::stringstream errss;
    errss << "Unable to locate user specified date and time sample logs "
          << datelogname << " and " << timelogname << "."
          << "run_start will not be set up.";
    g_log.error(errss.str());
    return;
  }

  const std::string &rawdatestring =
      runinfows->run().getProperty(datelogname)->value();
  const std::string &dateformat = datetimeprop[1];
  std::string mtddatestring = processDateString(rawdatestring, dateformat);

  const std::string &rawtimestring =
      runinfows->run().getProperty(timelogname)->value();
  const std::string &timeformat = datetimeprop[3];
  std::string mtdtimestring = processTimeString(rawtimestring, timeformat);

  std::string mtddatetimestr = mtddatestring + "T" + mtdtimestring;

  // Set up property
  DateAndTime runstart(mtddatetimestr);
  addProperty<std::string>(runinfows, "run_start", runstart.toISO8601String());
}

/*
 * Write a certain number of log entries (from beginning) to file
 */
void ProcessDasNexusLog::writeLogtoFile(API::MatrixWorkspace_sptr ws,
                                        std::string logname,
                                        size_t numentriesoutput,
                                        std::string outputfilename) {
  // 1. Get log
  Kernel::Property *log = ws->run().getProperty(logname);
  Kernel::TimeSeriesProperty<double> *tslog =
      dynamic_cast<Kernel::TimeSeriesProperty<double> *>(log);
  if (!tslog)
    throw std::runtime_error("Invalid time series log: it could not be cast "
                             "(interpreted) as a time series property");
  std::vector<Kernel::DateAndTime> times = tslog->timesAsVector();
  std::vector<double> values = tslog->valuesAsVector();

  // 2. Write out
  std::ofstream ofs;
  ofs.open(outputfilename.c_str(), std::ios::out);
  ofs << "# Absolute Time (nanosecond)\tPulse Time (nanosecond)\tTOF (ms)\n";

  Kernel::DateAndTime prevtime(0);
  std::vector<double> tofs;

  for (size_t i = 0; i < numentriesoutput; i++) {
    Kernel::DateAndTime tnow = times[i];

    if (tnow > prevtime) {
      // (a) Process previous logs
      std::sort(tofs.begin(), tofs.end());
      for (double tof : tofs) {
        Kernel::DateAndTime temptime =
            prevtime + static_cast<int64_t>(tof * 100);
        ofs << temptime.totalNanoseconds() << "\t" << tnow.totalNanoseconds()
            << "\t" << tof * 0.1 << '\n';
      }
      // (b) Clear
      tofs.clear();
      // (c) Update time
      prevtime = tnow;
    }

    // (d) Push the current value
    tofs.push_back(values[i]);
  } // ENDFOR
  // Clear the last
  if (!tofs.empty()) {
    // (a) Process previous logs: note value is in unit of 100 nano-second
    std::sort(tofs.begin(), tofs.end());
    for (double tof : tofs) {
      Kernel::DateAndTime temptime = prevtime + static_cast<int64_t>(tof * 100);
      ofs << temptime.totalNanoseconds() << "\t" << prevtime.totalNanoseconds()
          << "\t" << tof * 0.1 << '\n';
    }
  } else {
    throw std::runtime_error("Impossible for this to happen!");
  }

  ofs.close();
} // END Function

/*
 * Convert DAS log to a vector of absolute time
 * @param  orderedtofs: tofs with abstimevec
 */
void ProcessDasNexusLog::convertToAbsoluteTime(
    API::MatrixWorkspace_sptr ws, std::string logname,
    std::vector<Kernel::DateAndTime> &abstimevec,
    std::vector<double> &orderedtofs) {
  // 1. Get log
  Kernel::Property *log = ws->run().getProperty(logname);
  Kernel::TimeSeriesProperty<double> *tslog =
      dynamic_cast<Kernel::TimeSeriesProperty<double> *>(log);
  if (!tslog)
    throw std::runtime_error("Invalid time series log: it could not be cast "
                             "(interpreted) as a time series property");
  std::vector<Kernel::DateAndTime> times = tslog->timesAsVector();
  std::vector<double> values = tslog->valuesAsVector();

  // 2. Get converted
  size_t numsamepulses = 0;
  std::vector<double> tofs;
  Kernel::DateAndTime prevtime(0);

  for (size_t i = 0; i < times.size(); i++) {
    Kernel::DateAndTime tnow = times[i];
    if (tnow > prevtime) {
      // (a) Process previous logs
      std::sort(tofs.begin(), tofs.end());
      for (size_t j = 0; j < tofs.size(); j++) {
        Kernel::DateAndTime temptime =
            prevtime + static_cast<int64_t>(tofs[j] * 100);
        abstimevec.push_back(temptime);
        orderedtofs.push_back(tofs[j]);
      }
      // (b) Clear
      tofs.clear();
      // (c) Update time
      prevtime = tnow;
    } else {
      numsamepulses++;
    }
    // (d) Push the current value
    tofs.push_back(values[i]);
  } // ENDFOR
  // Clear the last
  if (!tofs.empty()) {
    // (a) Process previous logs: note value is in unit of 100 nano-second
    std::sort(tofs.begin(), tofs.end());
    for (size_t j = 0; j < tofs.size(); j++) {
      Kernel::DateAndTime temptime =
          prevtime + static_cast<int64_t>(tofs[j] * 100);
      abstimevec.push_back(temptime);
      orderedtofs.push_back(tofs[j]);
    }
  } else {
    throw std::runtime_error("Impossible for this to happen!");
  }

  return;
} // END Function

/** Validate the algorithm's properties.
 *
 * @return A map of porperty names and their issues.
 */
std::map<std::string, std::string> CreateEPP::validateInputs(void) {
  std::map<std::string, std::string> issues;
  API::MatrixWorkspace_sptr inputWS =
      getProperty(PropertyNames::INPUT_WORKSPACE);
  if (!inputWS->run().hasProperty("Ei")) {
    issues[PropertyNames::INPUT_WORKSPACE] =
        "Workspace is missing the 'Ei' sample log.";
  }
  return issues;
}

/*
 * Export time stamps looking erroreous
 */
void ProcessDasNexusLog::exportErrorLog(
    API::MatrixWorkspace_sptr ws, std::vector<Kernel::DateAndTime> abstimevec,
    std::vector<Kernel::DateAndTime> pulsetimes,
    std::vector<double> orderedtofs, double dts) {
  std::string outputdir = getProperty("OutputDirectory");
  if (outputdir[outputdir.size() - 1] != '/')
    outputdir += "/";

  std::string ofilename = outputdir + "errordeltatime.txt";
  g_log.notice() << ofilename << std::endl;
  std::ofstream ofs;
  ofs.open(ofilename.c_str(), std::ios::out);

  size_t numbaddt = 0;
  Kernel::DateAndTime t0(ws->run().getProperty("run_start")->value());

  for (size_t i = 1; i < abstimevec.size(); i++) {
    double tempdts = static_cast<double>(abstimevec[i].totalNanoseconds() -
                                         abstimevec[i - 1].totalNanoseconds()) *
                     1.0E-9;
    double dev = (tempdts - dts) / dts;
    bool baddt = false;
    if (fabs(dev) > 0.5)
      baddt = true;

    if (baddt) {
      numbaddt++;
      double deltapulsetimeSec1 =
          static_cast<double>(pulsetimes[i - 1].totalNanoseconds() -
                              t0.totalNanoseconds()) *
          1.0E-9;
      double deltapulsetimeSec2 =
          static_cast<double>(pulsetimes[i].totalNanoseconds() -
                              t0.totalNanoseconds()) *
          1.0E-9;
      int index1 = static_cast<int>(deltapulsetimeSec1 * 60);
      int index2 = static_cast<int>(deltapulsetimeSec2 * 60);

      ofs << "Error d(T) = " << tempdts << "   vs   Correct d(T) = " << dts
          << std::endl;
      ofs << index1 << "\t\t" << pulsetimes[i - 1].totalNanoseconds() << "\t\t"
          << orderedtofs[i - 1] << std::endl;
      ofs << index2 << "\t\t" << pulsetimes[i].totalNanoseconds() << "\t\t"
          << orderedtofs[i] << std::endl;
    }
  }

  ofs.close();
}

/**
 * Extract the first good frame of a workspace
 * @param ws :: a workspace
 * @returns the date and time of the first good frame
 */
DateAndTime
ChangeTimeZero::getStartTimeFromWorkspace(API::MatrixWorkspace_sptr ws) const {
  auto run = ws->run();
  // Check for the first good frame in the log
  Mantid::Kernel::TimeSeriesProperty<double> *goodFrame = NULL;
  try {
    goodFrame = run.getTimeSeriesProperty<double>("proton_charge");
  } catch (std::invalid_argument) {
    throw std::invalid_argument("ChangeTimeZero: The log needs a proton_charge "
                                "time series to determine the zero time.");
  }

  DateAndTime startTime;
  if (goodFrame->size() > 0) {
    startTime = goodFrame->firstTime();
  }

  return startTime;
}

/**
 * If grouping was not provided, find the instrument from the input workspace
 * and read the default grouping from its IDF. Returns the forward and backward
 * groupings as arrays of integers.
 * @param ws :: [input] Workspace to find grouping for
 * @param forward :: [output] Forward spectrum indices for given instrument
 * @param backward :: [output] Backward spectrum indices for given instrument
 */
void CalMuonDetectorPhases::getGroupingFromInstrument(
    const API::MatrixWorkspace_sptr &ws, std::vector<int> &forward,
    std::vector<int> &backward) {
  // make sure both arrays are empty
  forward.clear();
  backward.clear();

  const auto instrument = ws->getInstrument();
  auto loader = Kernel::make_unique<API::GroupingLoader>(instrument);

  if (instrument->getName() == "MUSR" || instrument->getName() == "CHRONUS") {
    // Two possibilities for grouping - use workspace log
    auto fieldDir = ws->run().getLogData("main_field_direction");
    if (fieldDir) {
      loader = Kernel::make_unique<API::GroupingLoader>(instrument,
                                                        fieldDir->value());
    }
    if (!fieldDir) {
      throw std::invalid_argument(
          "Cannot use default instrument grouping for MUSR "
          "as main field direction is unknown");
    }
  }

  // Load grouping and find forward, backward groups
  std::string fwdRange, bwdRange;
  const auto grouping = loader->getGroupingFromIDF();
  size_t nGroups = grouping->groups.size();
  for (size_t iGroup = 0; iGroup < nGroups; iGroup++) {
    const std::string name = grouping->groupNames[iGroup];
    if (name == "fwd" || name == "left") {
      fwdRange = grouping->groups[iGroup];
    } else if (name == "bwd" || name == "bkwd" || name == "right") {
      bwdRange = grouping->groups[iGroup];
    }
  }

  // Use ArrayProperty's functionality to convert string ranges to groups
  this->setProperty("ForwardSpectra", fwdRange);
  this->setProperty("BackwardSpectra", bwdRange);
  forward = getProperty("ForwardSpectra");
  backward = getProperty("BackwardSpectra");
}

/** Execute the algorithm.
 */
void CreateEPP::exec() {
  API::MatrixWorkspace_sptr inputWS =
      getProperty(PropertyNames::INPUT_WORKSPACE);
  const auto &spectrumInfo = inputWS->spectrumInfo();
  API::ITableWorkspace_sptr outputWS =
      API::WorkspaceFactory::Instance().createTable("TableWorkspace");
  addEPPColumns(outputWS);
  const double sigma = getProperty(PropertyNames::SIGMA);
  const size_t spectraCount = spectrumInfo.size();
  outputWS->setRowCount(spectraCount);
  const auto l1 = spectrumInfo.l1();
  const double EFixed = inputWS->run().getPropertyAsSingleValue("Ei");
  for (size_t i = 0; i < spectraCount; ++i) {
    const auto l2 = spectrumInfo.l2(i);
    const auto elasticTOF = Kernel::UnitConversion::run(
        "Energy", "TOF", EFixed, l1, l2, 0, Kernel::DeltaEMode::Direct, EFixed);
    outputWS->getRef<int>(ColumnNames::WS_INDEX, i) = static_cast<int>(i);
    outputWS->getRef<double>(ColumnNames::PEAK_CENTRE, i) = elasticTOF;
    outputWS->getRef<double>(ColumnNames::PEAK_CENTRE_ERR, i) = 0;
    outputWS->getRef<double>(ColumnNames::SIGMA, i) = sigma;
    outputWS->getRef<double>(ColumnNames::SIGMA_ERR, i) = 0;
    double height = 0;
    try {
      const auto elasticIndex = inputWS->binIndexOf(elasticTOF, i);
      height = inputWS->y(i)[elasticIndex];
    } catch (std::out_of_range &) {
      std::ostringstream sout;
      sout << "EPP out of TOF range for workspace index " << i
           << ". Peak height set to zero.";
      g_log.warning() << sout.str();
    }
    outputWS->getRef<double>(ColumnNames::HEIGHT, i) = height;
    outputWS->getRef<double>(ColumnNames::CHI_SQUARED, i) = 1;
    outputWS->getRef<std::string>(ColumnNames::STATUS, i) = "success";
  }
  setProperty(PropertyNames::OUTPUT_WORKSPACE, outputWS);
}

void HFIRLoad::exec() {
  // Reduction property manager
  const std::string reductionManagerName = getProperty("ReductionProperties");
  boost::shared_ptr<PropertyManager> reductionManager;
  if (PropertyManagerDataService::Instance().doesExist(reductionManagerName)) {
    reductionManager =
        PropertyManagerDataService::Instance().retrieve(reductionManagerName);
  } else {
    reductionManager = boost::make_shared<PropertyManager>();
    PropertyManagerDataService::Instance().addOrReplace(reductionManagerName,
                                                        reductionManager);
  }

  Progress progress(this, 0, 1, 5);

  progress.report();

  // If the load algorithm isn't in the reduction properties, add it
  if (!reductionManager->existsProperty("LoadAlgorithm")) {
    auto algProp = make_unique<AlgorithmProperty>("LoadAlgorithm");
    algProp->setValue(toString());
    reductionManager->declareProperty(std::move(algProp));
  }

  const std::string fileName = getPropertyValue("Filename");

  // Output log
  std::string output_message = "";
  const double wavelength_input = getProperty("Wavelength");
  const double wavelength_spread_input = getProperty("WavelengthSpread");

  progress.report("LoadSpice2D...");

  IAlgorithm_sptr loadAlg = createChildAlgorithm("LoadSpice2D", 0, 0.2);
  loadAlg->setProperty("Filename", fileName);
  if (!isEmpty(wavelength_input)) {
    loadAlg->setProperty("Wavelength", wavelength_input);
    loadAlg->setProperty("WavelengthSpread", wavelength_spread_input);
  }
  try {
    loadAlg->executeAsChildAlg();
  } catch (...) {
    // The only way HFIR SANS can load Nexus files is if it's loading data that
    // has already
    // been processed. This will only happen with sensitivity data.
    // So if we make it here and are still unable to load the file, assume it's
    // a sensitivity file.
    // This will cover the special case where the instrument scientist uses a
    // reduced data set
    // as a sensitivity data set.
    g_log.warning() << "Unable to load file as a SPICE file. Trying to load as "
                       "a Nexus file.\n";
    loadAlg = createChildAlgorithm("Load", 0, 0.2);
    loadAlg->setProperty("Filename", fileName);
    loadAlg->executeAsChildAlg();
    Workspace_sptr dataWS_tmp = loadAlg->getProperty("OutputWorkspace");
    MatrixWorkspace_sptr dataWS =
        boost::dynamic_pointer_cast<MatrixWorkspace>(dataWS_tmp);
    dataWS->mutableRun().addProperty("is_sensitivity", 1, "", true);
    setProperty<MatrixWorkspace_sptr>("OutputWorkspace", dataWS);
    g_log.notice() << "Successfully loaded " << fileName
                   << " and setting sensitivity flag to True\n";
    return;
  }
  Workspace_sptr dataWS_tmp = loadAlg->getProperty("OutputWorkspace");
  API::MatrixWorkspace_sptr dataWS =
      boost::dynamic_pointer_cast<MatrixWorkspace>(dataWS_tmp);

  // Get the sample-detector distance
  // If SampleDetectorDistance is provided, use it!
  // Otherwise get's "sample-detector-distance" from the data file
  // And uses SampleDetectorDistanceOffset if given!
  double sdd = 0.0;
  const double sample_det_dist = getProperty("SampleDetectorDistance");
  if (!isEmpty(sample_det_dist)) {
    sdd = sample_det_dist;
  } else {
    const std::string sddName = "sample-detector-distance";
    Mantid::Kernel::Property *prop = dataWS->run().getProperty(sddName);
    Mantid::Kernel::PropertyWithValue<double> *dp =
        dynamic_cast<Mantid::Kernel::PropertyWithValue<double> *>(prop);
    if (!dp) {
      throw std::runtime_error("Could not cast (interpret) the property " +
                               sddName + " as a floating point numeric value.");
    }
    sdd = *dp;

    // Modify SDD according to offset if given
    const double sample_det_offset =
        getProperty("SampleDetectorDistanceOffset");
    if (!isEmpty(sample_det_offset)) {
      sdd += sample_det_offset;
    }
  }
  dataWS->mutableRun().addProperty("sample_detector_distance", sdd, "mm", true);

  progress.report("MoveInstrumentComponent...");

  // Move the detector to its correct position
  IAlgorithm_sptr mvAlg =
//.........这里部分代码省略.........