/**
 * Calls Gaussian1D as a child algorithm to fit the offset peak in a spectrum
 * @param mosaic
 * @param rcrystallite
 * @param inname
 * @param corrOption
 * @param pointOption
 * @param tofParams
 * @return
 */
double OptimizeExtinctionParameters::fitMosaic(
    double mosaic, double rcrystallite, std::string inname,
    std::string corrOption, std::string pointOption, std::string tofParams) {
  PeaksWorkspace_sptr inputW = boost::dynamic_pointer_cast<PeaksWorkspace>(
      AnalysisDataService::Instance().retrieve(inname));
  std::vector<double> tofParam =
      Kernel::VectorHelper::splitStringIntoVector<double>(tofParams);
  if (mosaic < 0.0 || rcrystallite < 0.0)
    return 1e300;

  API::IAlgorithm_sptr tofextinction =
      createChildAlgorithm("TOFExtinction", 0.0, 0.2);
  tofextinction->setProperty("InputWorkspace", inputW);
  tofextinction->setProperty("OutputWorkspace", "tmp");
  tofextinction->setProperty("ExtinctionCorrectionType", corrOption);
  tofextinction->setProperty<double>("Mosaic", mosaic);
  tofextinction->setProperty<double>("Cell", tofParam[0]);
  tofextinction->setProperty<double>("RCrystallite", rcrystallite);
  tofextinction->executeAsChildAlg();
  PeaksWorkspace_sptr peaksW = tofextinction->getProperty("OutputWorkspace");

  API::IAlgorithm_sptr sorthkl = createChildAlgorithm("SortHKL", 0.0, 0.2);
  sorthkl->setProperty("InputWorkspace", peaksW);
  sorthkl->setProperty("OutputWorkspace", peaksW);
  sorthkl->setProperty("PointGroup", pointOption);
  sorthkl->executeAsChildAlg();
  double Chisq = sorthkl->getProperty("OutputChi2");
  std::cout << mosaic << "  " << rcrystallite << "  " << Chisq << "\n";
  return Chisq;
}
/**
 * Places the detector at the right sample_detector_distance
 */
void LoadSpice2D::moveDetector(double sample_detector_distance,
                               double translation_distance) {
  // Some tests fail if the detector is moved here.
  // TODO: Move the detector here and not the SANSLoad
  UNUSED_ARG(translation_distance);

  // Move the detector to the right position
  API::IAlgorithm_sptr mover = createChildAlgorithm("MoveInstrumentComponent");

  // Finding the name of the detector object.
  std::string detID =
      m_workspace->getInstrument()->getStringParameter("detector-name")[0];

  g_log.information("Moving " + detID);
  try {
    mover->setProperty<API::MatrixWorkspace_sptr>("Workspace", m_workspace);
    mover->setProperty("ComponentName", detID);
    mover->setProperty("Z", sample_detector_distance / 1000.0);
    // mover->setProperty("X", -translation_distance);
    mover->execute();
  } catch (std::invalid_argument &e) {
    g_log.error("Invalid argument to MoveInstrumentComponent Child Algorithm");
    g_log.error(e.what());
  } catch (std::runtime_error &e) {
    g_log.error(
        "Unable to successfully run MoveInstrumentComponent Child Algorithm");
    g_log.error(e.what());
  }
}
/** Handler of the start notifications. Adds an algorithm call to the script.
 * @param alg :: Shared pointer to the starting algorithm.
 */
void RecordPythonScript::startingHandle(API::IAlgorithm_sptr alg)
{
  auto props= alg->getProperties();

  std::string algString;
  for(auto p = props.begin() ; p != props.end(); ++p)
  {
    std::string opener = "='"; 
    if ((**p).value().find('\\') != std::string::npos )
    {
      opener= "=r'";
    }

    std::string paramString = (**p).name() + opener + (**p).value() + "'";

    // Miss out parameters that are empty.
    if(paramString.length() != 0)
    {
      if(algString.length() != 0)
      {
        algString += ",";
      }
      algString += paramString;
    }
  }

  m_generatedScript +=  alg->name() + "(" + algString + ")\n";
}
/**
 * Removes exponential decay from a workspace
 * @param wsInput :: [input] Workspace to work on
 * @return :: Workspace with decay removed
 */
API::MatrixWorkspace_sptr CalMuonDetectorPhases::removeExpDecay(
    const API::MatrixWorkspace_sptr &wsInput) {
  API::IAlgorithm_sptr remove = createChildAlgorithm("RemoveExpDecay");
  remove->setProperty("InputWorkspace", wsInput);
  remove->executeAsChildAlg();
  API::MatrixWorkspace_sptr wsRem = remove->getProperty("OutputWorkspace");
  return wsRem;
}
/** Call edit instrument geometry
  */
API::MatrixWorkspace_sptr AlignAndFocusPowder::editInstrument(
    API::MatrixWorkspace_sptr ws, std::vector<double> polars,
    std::vector<specnum_t> specids, std::vector<double> l2s,
    std::vector<double> phis) {
  g_log.information() << "running EditInstrumentGeometry started at "
                      << Kernel::DateAndTime::getCurrentTime() << "\n";

  API::IAlgorithm_sptr editAlg = createChildAlgorithm("EditInstrumentGeometry");
  editAlg->setProperty("Workspace", ws);
  if (m_l1 > 0.)
    editAlg->setProperty("PrimaryFlightPath", m_l1);
  if (!polars.empty())
    editAlg->setProperty("Polar", polars);
  if (!specids.empty())
    editAlg->setProperty("SpectrumIDs", specids);
  if (!l2s.empty())
    editAlg->setProperty("L2", l2s);
  if (!phis.empty())
    editAlg->setProperty("Azimuthal", phis);
  editAlg->executeAsChildAlg();

  ws = editAlg->getProperty("Workspace");

  return ws;
}
std::string FrameworkManagerProxy::createAlgorithmDocs(const std::string& algName, const int version)
{
  const std::string EOL="\n";
  API::IAlgorithm_sptr algm = API::AlgorithmManager::Instance().createUnmanaged(algName, version);
  algm->initialize();

  // Put in the quick overview message
  std::stringstream buffer;
  std::string temp = algm->getOptionalMessage();
  if (temp.size() > 0)
    buffer << temp << EOL << EOL;

  // get a sorted copy of the properties
  PropertyVector properties(algm->getProperties());
  std::sort(properties.begin(), properties.end(), PropertyOrdering());

  // generate the sanitized names
  StringVector names(properties.size());
  size_t numProps = properties.size();
  for ( size_t i = 0; i < numProps; ++i) 
  {
    names[i] = removeCharacters(properties[i]->name(), "");
  }

  buffer << "Property descriptions: " << EOL << EOL;
  // write the actual property descriptions
  Mantid::Kernel::Property *prop;
  for ( size_t i = 0; i < numProps; ++i) 
  {
    prop = properties[i];
    buffer << names[i] << "("
           << Mantid::Kernel::Direction::asText(prop->direction());
    if (!prop->isValid().empty())
      buffer << ":req";
    buffer << ") *" << prop->type() << "* ";
    std::set<std::string> allowed = prop->allowedValues();
    if (!prop->documentation().empty() || !allowed.empty())
    {
      buffer << "      " << prop->documentation();
      if (!allowed.empty())
      {
        buffer << " [" << Kernel::Strings::join(allowed.begin(), allowed.end(), ", ");
        buffer << "]";
      }
      buffer << EOL;
      if( i < numProps - 1 ) buffer << EOL;
    }
  }

  return buffer.str();
}
Exemple #7
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/**
 * Create the concrete instance use for the actual loading.
 * @param startProgress :: The percentage progress value of the overall
 * algorithm where this child algorithm starts
 * @param endProgress :: The percentage progress value of the overall
 * algorithm where this child algorithm ends
 * @param logging :: Set to false to disable logging from the child algorithm
 */
API::IAlgorithm_sptr Load::createLoader(const double startProgress,
                                        const double endProgress,
                                        const bool logging) const {
  std::string name = getPropertyValue("LoaderName");
  int version = getProperty("LoaderVersion");
  API::IAlgorithm_sptr loader =
      API::AlgorithmManager::Instance().createUnmanaged(name, version);
  loader->initialize();
  if (!loader) {
    throw std::runtime_error("Cannot create loader for \"" +
                             getPropertyValue("Filename") + "\"");
  }
  setUpLoader(loader, startProgress, endProgress, logging);
  return loader;
}
Exemple #8
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/// Run ConvertUnits as a sub-algorithm to convert to dSpacing
MatrixWorkspace_sptr DiffractionFocussing::convertUnitsToDSpacing(const API::MatrixWorkspace_sptr& workspace)
{
  const std::string CONVERSION_UNIT = "dSpacing";

  Unit_const_sptr xUnit = workspace->getAxis(0)->unit();

  g_log.information() << "Converting units from "<< xUnit->label() << " to " << CONVERSION_UNIT<<".\n";

  API::IAlgorithm_sptr childAlg = createSubAlgorithm("ConvertUnits", 0.34, 0.66);
  childAlg->setProperty("InputWorkspace", workspace);
  childAlg->setPropertyValue("Target",CONVERSION_UNIT);
  childAlg->executeAsSubAlg();

  return childAlg->getProperty("OutputWorkspace");
}
Exemple #9
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/**
 * Declare any additional properties of the concrete loader here
 * @param loader A pointer to the concrete loader
 */
void Load::declareLoaderProperties(const API::IAlgorithm_sptr &loader) {
  // If we have switch loaders then the concrete loader will have different
  // properties
  // so take care of ensuring Load has the correct ones
  // THIS IS A COPY as the properties are mutated as we move through them
  const std::vector<Property *> existingProps = this->getProperties();
  for (auto existingProp : existingProps) {
    const std::string &name = existingProp->name();
    // Wipe all properties except the Load native ones
    if (m_baseProps.find(name) == m_baseProps.end()) {
      this->removeProperty(name);
    }
  }

  const std::vector<Property *> &loaderProps = loader->getProperties();
  size_t numProps(loaderProps.size());
  for (size_t i = 0; i < numProps; ++i) {
    Property *loadProp = loaderProps[i];
    if (loadProp->name() == m_filenamePropName)
      continue;
    try {
      auto propClone = std::unique_ptr<Property>(loadProp->clone());
      propClone->clearSettings(); // Get rid of special settings because it
                                  // does not work in custom GUI.
      declareProperty(std::move(propClone), loadProp->documentation());
    } catch (Exception::ExistsError &) {
      // Already exists as a static property
      continue;
    }
  }
}
void LoadNexusMonitors2::runLoadLogs(const std::string filename,
                                     API::MatrixWorkspace_sptr localWorkspace) {
  // do the actual work
  API::IAlgorithm_sptr loadLogs = createChildAlgorithm("LoadNexusLogs");

  // Now execute the Child Algorithm. Catch and log any error, but don't stop.
  try {
    g_log.information() << "Loading logs from NeXus file..." << std::endl;
    loadLogs->setPropertyValue("Filename", filename);
    loadLogs->setProperty<API::MatrixWorkspace_sptr>("Workspace",
                                                     localWorkspace);
    loadLogs->execute();
  } catch (...) {
    g_log.error() << "Error while loading Logs from Nexus. Some sample logs "
                     "may be missing." << std::endl;
  }
}
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/**
 * Set the output workspace(s) if the load's return workspace has type
 * API::Workspace
 * @param loader :: Shared pointer to load algorithm
 */
void Load::setOutputWorkspace(const API::IAlgorithm_sptr &loader) {
  // Go through each OutputWorkspace property and check whether we need to make
  // a counterpart here
  const std::vector<Property *> &loaderProps = loader->getProperties();
  const size_t count = loader->propertyCount();
  for (size_t i = 0; i < count; ++i) {
    Property *prop = loaderProps[i];
    if (dynamic_cast<IWorkspaceProperty *>(prop) &&
        prop->direction() == Direction::Output) {
      const std::string &name = prop->name();
      if (!this->existsProperty(name)) {
        declareProperty(Kernel::make_unique<WorkspaceProperty<Workspace>>(
            name, loader->getPropertyValue(name), Direction::Output));
      }
      Workspace_sptr wkspace = getOutputWorkspace(name, loader);
      setProperty(name, wkspace);
    }
  }
}
/// Run Rebin as a Child Algorithm to harmonise the bin boundaries
void DiffractionFocussing::RebinWorkspace(
    API::MatrixWorkspace_sptr &workspace) {

  double min = 0;
  double max = 0;
  double step = 0;

  calculateRebinParams(workspace, min, max, step);
  std::vector<double> paramArray{min, -step, max};

  g_log.information() << "Rebinning from " << min << " to " << max << " in "
                      << step << " logaritmic steps.\n";

  API::IAlgorithm_sptr childAlg = createChildAlgorithm("Rebin");
  childAlg->setProperty<MatrixWorkspace_sptr>("InputWorkspace", workspace);
  childAlg->setProperty<std::vector<double>>("Params", paramArray);
  childAlg->executeAsChildAlg();
  workspace = childAlg->getProperty("OutputWorkspace");
}
Exemple #13
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/**
 * Return an output workspace property dealing with the lack of connection
 * between of
 * WorkspaceProperty types
 * @param propName :: The name of the property
 * @param loader :: The loader algorithm
 * @returns A pointer to the OutputWorkspace property of the Child Algorithm
 */
API::Workspace_sptr
Load::getOutputWorkspace(const std::string &propName,
                         const API::IAlgorithm_sptr &loader) const {
  // @todo Need to try and find a better way using the getValue methods
  try {
    return loader->getProperty(propName);
  } catch (std::runtime_error &) {
  }

  // Try a MatrixWorkspace
  try {
    MatrixWorkspace_sptr childWS = loader->getProperty(propName);
    return childWS;
  } catch (std::runtime_error &) {
  }

  // EventWorkspace
  try {
    IEventWorkspace_sptr childWS = loader->getProperty(propName);
    return childWS;
  } catch (std::runtime_error &) {
  }

  // IMDEventWorkspace
  try {
    IMDEventWorkspace_sptr childWS = loader->getProperty(propName);
    return childWS;
  } catch (std::runtime_error &) {
  }

  // General IMDWorkspace
  try {
    IMDWorkspace_sptr childWS = loader->getProperty(propName);
    return childWS;
  } catch (std::runtime_error &) {
  }

  // ITableWorkspace?
  try {
    ITableWorkspace_sptr childWS = loader->getProperty(propName);
    return childWS;
  } catch (std::runtime_error &) {
  }

  // Just workspace?
  try {
    Workspace_sptr childWS = loader->getProperty(propName);
    return childWS;
  } catch (std::runtime_error &) {
  }

  g_log.debug() << "Workspace property " << propName
                << " did not return to MatrixWorkspace, EventWorkspace, "
                   "IMDEventWorkspace, IMDWorkspace\n";
  return Workspace_sptr();
}
Exemple #14
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/** Run the Child Algorithm LoadInstrument (as for LoadRaw)
 * @param inst_name :: The name written in the Nexus file
 * @param localWorkspace :: The workspace to insert the instrument into
 */
void LoadSpice2D::runLoadInstrument(
    const std::string &inst_name,
    DataObjects::Workspace2D_sptr localWorkspace) {

  API::IAlgorithm_sptr loadInst = createChildAlgorithm("LoadInstrument");

  // Now execute the Child Algorithm. Catch and log any error, but don't stop.
  try {
    loadInst->setPropertyValue("InstrumentName", inst_name);
    loadInst->setProperty<API::MatrixWorkspace_sptr>("Workspace",
                                                     localWorkspace);
    loadInst->setProperty("RewriteSpectraMap",
                          Mantid::Kernel::OptionalBool(true));
    loadInst->execute();
  } catch (std::invalid_argument &) {
    g_log.information("Invalid argument to LoadInstrument Child Algorithm");
  } catch (std::runtime_error &) {
    g_log.information(
        "Unable to successfully run LoadInstrument Child Algorithm");
  }
}
Exemple #15
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void Load::findFilenameProperty(const API::IAlgorithm_sptr &loader) {
  // Use the first file property as the main Filename
  const auto &props = loader->getProperties();
  for (auto prop : props) {
    auto *fp = dynamic_cast<API::MultipleFileProperty *>(prop);
    auto *fp2 = dynamic_cast<API::FileProperty *>(prop);
    if (fp) {
      m_filenamePropName = fp->name();
      break;
    }
    if (fp2) {
      m_filenamePropName = fp2->name();
      break;
    }
  }
  if (m_filenamePropName.empty()) {
    setPropertyValue("LoaderName", "");
    setProperty("LoaderVersion", -1);
    throw std::runtime_error("Cannot find FileProperty on " + loader->name() +
                             " algorithm.");
  }
}
Exemple #16
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/**
 * Set the loader option for use as a Child Algorithm.
 * @param loader :: Concrete loader
 * @param startProgress :: The start progress fraction
 * @param endProgress :: The end progress fraction
 * @param logging:: If true, enable logging
 */
void Load::setUpLoader(API::IAlgorithm_sptr &loader, const double startProgress,
                       const double endProgress, const bool logging) const {
  // Set as a child so that we are in control of output storage
  loader->setChild(true);
  loader->setLogging(logging);
  // If output workspaces are nameless, give them a temporary name to satisfy
  // validator
  const std::vector<Property *> &props = loader->getProperties();
  for (auto prop : props) {
    auto wsProp = dynamic_cast<IWorkspaceProperty *>(prop);

    if (wsProp && !wsProp->isOptional() &&
        prop->direction() == Direction::Output) {
      if (prop->value().empty())
        prop->setValue("LoadChildWorkspace");
    }
  }
  if (startProgress >= 0. && endProgress > startProgress && endProgress <= 1.) {
    loader->addObserver(this->progressObserver());
    setChildStartProgress(startProgress);
    setChildEndProgress(endProgress);
  }
}
/**  Group detectors in the workspace.
 *  @param ws :: A local workspace
 *  @param spectraList :: A list of spectra to group.
 */
void PlotAsymmetryByLogValue::groupDetectors(API::MatrixWorkspace_sptr& ws,const std::vector<int>& spectraList)
{
    API::IAlgorithm_sptr group = createChildAlgorithm("GroupDetectors");
    group->setProperty("InputWorkspace",ws);
    group->setProperty("SpectraList",spectraList);
    group->setProperty("KeepUngroupedSpectra",true);
    group->execute();
    ws = group->getProperty("OutputWorkspace");
}
/** Rebin
*/
API::MatrixWorkspace_sptr
AlignAndFocusPowder::rebin(API::MatrixWorkspace_sptr matrixws) {
  if (m_resampleX != 0) {
    // ResampleX
    g_log.information() << "running ResampleX(NumberBins=" << abs(m_resampleX)
                        << ", LogBinning=" << (m_resampleX < 0) << ", dMin("
                        << m_dmins.size() << "), dmax(" << m_dmaxs.size()
                        << ")) started at "
                        << Kernel::DateAndTime::getCurrentTime() << "\n";
    API::IAlgorithm_sptr alg = createChildAlgorithm("ResampleX");
    alg->setProperty("InputWorkspace", matrixws);
    alg->setProperty("OutputWorkspace", matrixws);
    if ((!m_dmins.empty()) && (!m_dmaxs.empty())) {
      size_t numHist = m_outputW->getNumberHistograms();
      if ((numHist == m_dmins.size()) && (numHist == m_dmaxs.size())) {
        alg->setProperty("XMin", m_dmins);
        alg->setProperty("XMax", m_dmaxs);
      } else {
        g_log.information()
            << "Number of dmin and dmax values don't match the "
            << "number of workspace indices. Ignoring the parameters.\n";
      }
    }
    alg->setProperty("NumberBins", abs(m_resampleX));
    alg->setProperty("LogBinning", (m_resampleX < 0));
    alg->executeAsChildAlg();
    matrixws = alg->getProperty("OutputWorkspace");
    return matrixws;
  } else {
    g_log.information() << "running Rebin( ";
    for (double param : m_params)
      g_log.information() << param << " ";
    g_log.information() << ") started at "
                        << Kernel::DateAndTime::getCurrentTime() << "\n";
    API::IAlgorithm_sptr rebin3Alg = createChildAlgorithm("Rebin");
    rebin3Alg->setProperty("InputWorkspace", matrixws);
    rebin3Alg->setProperty("OutputWorkspace", matrixws);
    rebin3Alg->setProperty("Params", m_params);
    rebin3Alg->executeAsChildAlg();
    matrixws = rebin3Alg->getProperty("OutputWorkspace");
    return matrixws;
  }
}
/** Extracts relevant data from a workspace
 * @param startTime :: [input] First X value to consider
 * @param endTime :: [input] Last X value to consider
 * @return :: Pre-processed workspace to fit
 */
API::MatrixWorkspace_sptr
CalMuonDetectorPhases::extractDataFromWorkspace(double startTime,
                                                double endTime) {
  // Extract counts from startTime to endTime
  API::IAlgorithm_sptr crop = createChildAlgorithm("CropWorkspace");
  crop->setProperty("InputWorkspace", m_inputWS);
  crop->setProperty("XMin", startTime);
  crop->setProperty("XMax", endTime);
  crop->executeAsChildAlg();
  boost::shared_ptr<API::MatrixWorkspace> wsCrop =
      crop->getProperty("OutputWorkspace");
  return wsCrop;
}
/** Call diffraction focus to a matrix workspace.
  */
API::MatrixWorkspace_sptr
AlignAndFocusPowder::diffractionFocus(API::MatrixWorkspace_sptr ws) {
  if (!m_groupWS) {
    g_log.information() << "not focussing data\n";
    return ws;
  }

  g_log.information() << "running DiffractionFocussing. \n";

  API::IAlgorithm_sptr focusAlg = createChildAlgorithm("DiffractionFocussing");
  focusAlg->setProperty("InputWorkspace", ws);
  focusAlg->setProperty("OutputWorkspace", ws);
  focusAlg->setProperty("GroupingWorkspace", m_groupWS);
  focusAlg->setProperty("PreserveEvents", m_preserveEvents);
  focusAlg->executeAsChildAlg();
  ws = focusAlg->getProperty("OutputWorkspace");

  return ws;
}
Exemple #21
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void LoadILLSANS::moveDetectorVertical(double shift,
                                       const std::string &componentName) {

  API::IAlgorithm_sptr mover = createChildAlgorithm("MoveInstrumentComponent");
  V3D pos = getComponentPosition(componentName);
  try {
    mover->setProperty<MatrixWorkspace_sptr>("Workspace", m_localWorkspace);
    mover->setProperty("ComponentName", componentName);
    mover->setProperty("X", pos.X());
    mover->setProperty("Y", shift);
    mover->setProperty("Z", pos.Z());
    mover->setProperty("RelativePosition", false);
    mover->executeAsChildAlg();
    g_log.debug() << "Moving component '" << componentName
                  << "' to Y = " << shift << '\n';
  } catch (std::exception &e) {
    g_log.error() << "Cannot move the component '" << componentName
                  << "' to Y = " << shift << '\n';
    g_log.error() << e.what() << '\n';
  }
}
Exemple #22
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/** Fit background function
  */
void ProcessBackground::fitBackgroundFunction(std::string bkgdfunctiontype) {
  // Get background type and create bakground function
  BackgroundFunction_sptr bkgdfunction =
      createBackgroundFunction(bkgdfunctiontype);

  int bkgdorder = getProperty("OutputBackgroundOrder");
  bkgdfunction->setAttributeValue("n", bkgdorder);

  if (bkgdfunctiontype == "Chebyshev") {
    double xmin = m_outputWS->readX(0).front();
    double xmax = m_outputWS->readX(0).back();
    g_log.information() << "Chebyshev Fit range: " << xmin << ", " << xmax
                        << "\n";
    bkgdfunction->setAttributeValue("StartX", xmin);
    bkgdfunction->setAttributeValue("EndX", xmax);
  }

  g_log.information() << "Fit selected background " << bkgdfunctiontype
                      << " to data workspace with "
                      << m_outputWS->getNumberHistograms() << " spectra."
                      << "\n";

  // Fit input (a few) background pionts to get initial guess
  API::IAlgorithm_sptr fit;
  try {
    fit = this->createChildAlgorithm("Fit", 0.9, 1.0, true);
  } catch (Exception::NotFoundError &) {
    g_log.error() << "Requires CurveFitting library." << std::endl;
    throw;
  }

  g_log.information() << "Fitting background function: "
                      << bkgdfunction->asString() << "\n";

  double startx = m_lowerBound;
  double endx = m_upperBound;
  fit->setProperty("Function",
                   boost::dynamic_pointer_cast<API::IFunction>(bkgdfunction));
  fit->setProperty("InputWorkspace", m_outputWS);
  fit->setProperty("WorkspaceIndex", 0);
  fit->setProperty("MaxIterations", 500);
  fit->setProperty("StartX", startx);
  fit->setProperty("EndX", endx);
  fit->setProperty("Minimizer", "Levenberg-MarquardtMD");
  fit->setProperty("CostFunction", "Least squares");

  fit->executeAsChildAlg();

  // Get fit status and chi^2
  std::string fitStatus = fit->getProperty("OutputStatus");
  bool allowedfailure = (fitStatus.find("cannot") < fitStatus.size()) &&
                        (fitStatus.find("tolerance") < fitStatus.size());
  if (fitStatus.compare("success") != 0 && !allowedfailure) {
    g_log.error() << "ProcessBackground: Fit Status = " << fitStatus
                  << ".  Not to update fit result" << std::endl;
    throw std::runtime_error("Bad Fit");
  }

  const double chi2 = fit->getProperty("OutputChi2overDoF");
  g_log.information() << "Fit background: Fit Status = " << fitStatus
                      << ", chi2 = " << chi2 << "\n";

  // Get out the parameter names
  API::IFunction_sptr funcout = fit->getProperty("Function");
  TableWorkspace_sptr outbkgdparws = boost::make_shared<TableWorkspace>();
  outbkgdparws->addColumn("str", "Name");
  outbkgdparws->addColumn("double", "Value");

  TableRow typerow = outbkgdparws->appendRow();
  typerow << bkgdfunctiontype << 0.;

  vector<string> parnames = funcout->getParameterNames();
  size_t nparam = funcout->nParams();
  for (size_t i = 0; i < nparam; ++i) {
    TableRow newrow = outbkgdparws->appendRow();
    newrow << parnames[i] << funcout->getParameter(i);
  }

  TableRow chi2row = outbkgdparws->appendRow();
  chi2row << "Chi-square" << chi2;

  g_log.information() << "Set table workspace (#row = "
                      << outbkgdparws->rowCount()
                      << ") to OutputBackgroundParameterTable. "
                      << "\n";
  setProperty("OutputBackgroundParameterWorkspace", outbkgdparws);

  // Set output workspace
  const MantidVec &vecX = m_outputWS->readX(0);
  const MantidVec &vecY = m_outputWS->readY(0);
  FunctionDomain1DVector domain(vecX);
  FunctionValues values(domain);

  funcout->function(domain, values);

  MantidVec &dataModel = m_outputWS->dataY(1);
  MantidVec &dataDiff = m_outputWS->dataY(2);
  for (size_t i = 0; i < dataModel.size(); ++i) {
    dataModel[i] = values[i];
    dataDiff[i] = vecY[i] - dataModel[i];
  }

  return;
}
Exemple #23
0
/** Select background automatically
 */
DataObjects::Workspace2D_sptr
ProcessBackground::autoBackgroundSelection(Workspace2D_sptr bkgdWS) {
  // Get background type and create bakground function
  BackgroundFunction_sptr bkgdfunction = createBackgroundFunction(m_bkgdType);

  int bkgdorder = getProperty("BackgroundOrder");
  if (bkgdorder == 0)
    g_log.warning("(Input) background function order is 0.  It might not be "
                  "able to give a good estimation.");

  bkgdfunction->setAttributeValue("n", bkgdorder);
  bkgdfunction->initialize();

  g_log.information() << "Input background points has "
                      << bkgdWS->readX(0).size() << " data points for fit "
                      << bkgdorder << "-th order " << bkgdfunction->name()
                      << " (background) function" << bkgdfunction->asString()
                      << "\n";

  // Fit input (a few) background pionts to get initial guess
  API::IAlgorithm_sptr fit;
  try {
    fit = this->createChildAlgorithm("Fit", 0.0, 0.2, true);
  } catch (Exception::NotFoundError &) {
    g_log.error() << "Requires CurveFitting library." << std::endl;
    throw;
  }

  double startx = m_lowerBound;
  double endx = m_upperBound;
  fit->setProperty("Function",
                   boost::dynamic_pointer_cast<API::IFunction>(bkgdfunction));
  fit->setProperty("InputWorkspace", bkgdWS);
  fit->setProperty("WorkspaceIndex", 0);
  fit->setProperty("MaxIterations", 500);
  fit->setProperty("StartX", startx);
  fit->setProperty("EndX", endx);
  fit->setProperty("Minimizer", "Levenberg-Marquardt");
  fit->setProperty("CostFunction", "Least squares");

  fit->executeAsChildAlg();

  // Get fit result
  // a) Status
  std::string fitStatus = fit->getProperty("OutputStatus");
  bool allowedfailure = (fitStatus.find("cannot") < fitStatus.size()) &&
                        (fitStatus.find("tolerance") < fitStatus.size());
  if (fitStatus.compare("success") != 0 && !allowedfailure) {
    g_log.error() << "ProcessBackground: Fit Status = " << fitStatus
                  << ".  Not to update fit result" << std::endl;
    throw std::runtime_error("Bad Fit");
  }

  // b) check that chi2 got better
  const double chi2 = fit->getProperty("OutputChi2overDoF");
  g_log.information() << "Fit background: Fit Status = " << fitStatus
                      << ", chi2 = " << chi2 << "\n";

  // Filter and construct for the output workspace
  Workspace2D_sptr outws = filterForBackground(bkgdfunction);

  return outws;
} // END OF FUNCTION
/** Executes the algorithm
 *  @throw Exception::FileError If the grouping file cannot be opened or read
 * successfully
 *  @throw runtime_error If unable to run one of the Child Algorithms
 * successfully
 */
void AlignAndFocusPowder::exec() {
  // retrieve the properties
  m_inputW = getProperty("InputWorkspace");
  m_inputEW = boost::dynamic_pointer_cast<EventWorkspace>(m_inputW);
  m_instName = m_inputW->getInstrument()->getName();
  m_instName =
      Kernel::ConfigService::Instance().getInstrument(m_instName).shortName();
  std::string calFilename = getPropertyValue("CalFileName");
  std::string groupFilename = getPropertyValue("GroupFilename");
  m_calibrationWS = getProperty("CalibrationWorkspace");
  m_maskWS = getProperty("MaskWorkspace");
  m_groupWS = getProperty("GroupingWorkspace");
  DataObjects::TableWorkspace_sptr maskBinTableWS = getProperty("MaskBinTable");
  m_l1 = getProperty("PrimaryFlightPath");
  specids = getProperty("SpectrumIDs");
  l2s = getProperty("L2");
  tths = getProperty("Polar");
  phis = getProperty("Azimuthal");
  m_params = getProperty("Params");
  dspace = getProperty("DSpacing");
  auto dmin = getVecPropertyFromPmOrSelf("DMin", m_dmins);
  auto dmax = getVecPropertyFromPmOrSelf("DMax", m_dmaxs);
  LRef = getProperty("UnwrapRef");
  DIFCref = getProperty("LowResRef");
  minwl = getProperty("CropWavelengthMin");
  maxwl = getProperty("CropWavelengthMax");
  if (maxwl == 0.)
    maxwl = EMPTY_DBL(); // python can only specify 0 for unused
  tmin = getProperty("TMin");
  tmax = getProperty("TMax");
  m_preserveEvents = getProperty("PreserveEvents");
  m_resampleX = getProperty("ResampleX");
  // determine some bits about d-space and binning
  if (m_resampleX != 0) {
    m_params.clear(); // ignore the normal rebin parameters
  } else if (m_params.size() == 1) {
    if (dmax > 0.)
      dspace = true;
    else
      dspace = false;
  }
  if (dspace) {
    if (m_params.size() == 1 && dmax > 0) {
      double step = m_params[0];
      m_params.clear();
      if (step > 0 || dmin > 0) {
        m_params.push_back(dmin);
        m_params.push_back(step);
        m_params.push_back(dmax);
        g_log.information() << "d-Spacing Binning: " << m_params[0] << "  "
                            << m_params[1] << "  " << m_params[2] << "\n";
      }
    }
  } else {
    if (m_params.size() == 1 && tmax > 0) {
      double step = m_params[0];
      if (step > 0 || tmin > 0) {
        m_params[0] = tmin;
        m_params.push_back(step);
        m_params.push_back(tmax);
        g_log.information() << "TOF Binning: " << m_params[0] << "  "
                            << m_params[1] << "  " << m_params[2] << "\n";
      }
    }
  }
  xmin = 0.;
  xmax = 0.;
  if (tmin > 0.) {
    xmin = tmin;
  }
  if (tmax > 0.) {
    xmax = tmax;
  }
  if (!dspace && m_params.size() == 3) {
    xmin = m_params[0];
    xmax = m_params[2];
  }

  // Low resolution
  int lowresoffset = getProperty("LowResSpectrumOffset");
  if (lowresoffset < 0) {
    m_processLowResTOF = false;
  } else {
    m_processLowResTOF = true;
    m_lowResSpecOffset = static_cast<size_t>(lowresoffset);
  }

  loadCalFile(calFilename, groupFilename);

  // Now setup the output workspace
  m_outputW = getProperty("OutputWorkspace");
  if (m_inputEW) {
    if (m_outputW != m_inputW) {
      m_outputEW = m_inputEW->clone();
    }
    m_outputEW = boost::dynamic_pointer_cast<EventWorkspace>(m_outputW);
  } else {
    if (m_outputW != m_inputW) {
      m_outputW = WorkspaceFactory::Instance().create(m_inputW);
    }
  }

  if (m_processLowResTOF) {
    if (!m_inputEW) {
      throw std::runtime_error(
          "Input workspace is not EventWorkspace.  It is not supported now.");
    } else {
      // Make a brand new EventWorkspace
      m_lowResEW = boost::dynamic_pointer_cast<EventWorkspace>(
          WorkspaceFactory::Instance().create(
              "EventWorkspace", m_inputEW->getNumberHistograms(), 2, 1));

      // Cast to the matrixOutputWS and save it
      m_lowResW = boost::dynamic_pointer_cast<MatrixWorkspace>(m_lowResEW);
      // m_lowResW->setName(lowreswsname);
    }
  }

  // set up a progress bar with the "correct" number of steps
  m_progress = new Progress(this, 0., 1., 22);

  if (m_inputEW) {
    double tolerance = getProperty("CompressTolerance");
    if (tolerance > 0.) {
      g_log.information() << "running CompressEvents(Tolerance=" << tolerance
                          << ") started at "
                          << Kernel::DateAndTime::getCurrentTime() << "\n";
      API::IAlgorithm_sptr compressAlg = createChildAlgorithm("CompressEvents");
      compressAlg->setProperty("InputWorkspace", m_outputEW);
      compressAlg->setProperty("OutputWorkspace", m_outputEW);
      compressAlg->setProperty("OutputWorkspace", m_outputEW);
      compressAlg->setProperty("Tolerance", tolerance);
      compressAlg->executeAsChildAlg();
      m_outputEW = compressAlg->getProperty("OutputWorkspace");
      m_outputW = boost::dynamic_pointer_cast<MatrixWorkspace>(m_outputEW);
    } else {
      g_log.information() << "Not compressing event list\n";
      doSortEvents(m_outputW); // still sort to help some thing out
    }
  }
  m_progress->report();

  if (xmin > 0. || xmax > 0.) {
    double tempmin;
    double tempmax;
    m_outputW->getXMinMax(tempmin, tempmax);

    g_log.information() << "running CropWorkspace(TOFmin=" << xmin
                        << ", TOFmax=" << xmax << ") started at "
                        << Kernel::DateAndTime::getCurrentTime() << "\n";
    API::IAlgorithm_sptr cropAlg = createChildAlgorithm("CropWorkspace");
    cropAlg->setProperty("InputWorkspace", m_outputW);
    cropAlg->setProperty("OutputWorkspace", m_outputW);
    if ((xmin > 0.) && (xmin > tempmin))
      cropAlg->setProperty("Xmin", xmin);
    if ((xmax > 0.) && (xmax < tempmax))
      cropAlg->setProperty("Xmax", xmax);
    cropAlg->executeAsChildAlg();
    m_outputW = cropAlg->getProperty("OutputWorkspace");
    m_outputEW = boost::dynamic_pointer_cast<EventWorkspace>(m_outputW);
  }
  m_progress->report();

  // filter the input events if appropriate
  double removePromptPulseWidth = getProperty("RemovePromptPulseWidth");
  if (removePromptPulseWidth > 0.) {
    m_outputEW = boost::dynamic_pointer_cast<EventWorkspace>(m_outputW);
    if (m_outputEW->getNumberEvents() > 0) {
      g_log.information() << "running RemovePromptPulse(Width="
                          << removePromptPulseWidth << ") started at "
                          << Kernel::DateAndTime::getCurrentTime() << "\n";
      API::IAlgorithm_sptr filterPAlg =
          createChildAlgorithm("RemovePromptPulse");
      filterPAlg->setProperty("InputWorkspace", m_outputW);
      filterPAlg->setProperty("OutputWorkspace", m_outputW);
      filterPAlg->setProperty("Width", removePromptPulseWidth);
      filterPAlg->executeAsChildAlg();
      m_outputW = filterPAlg->getProperty("OutputWorkspace");
      m_outputEW = boost::dynamic_pointer_cast<EventWorkspace>(m_outputW);
    } else {
      g_log.information("skipping RemovePromptPulse on empty EventWorkspace");
    }
  }
  m_progress->report();

  if (maskBinTableWS) {
    g_log.information() << "running MaskBinsFromTable started at "
                        << Kernel::DateAndTime::getCurrentTime() << "\n";
    API::IAlgorithm_sptr alg = createChildAlgorithm("MaskBinsFromTable");
    alg->setProperty("InputWorkspace", m_outputW);
    alg->setProperty("OutputWorkspace", m_outputW);
    alg->setProperty("MaskingInformation", maskBinTableWS);
    alg->executeAsChildAlg();
    m_outputW = alg->getProperty("OutputWorkspace");
    m_outputEW = boost::dynamic_pointer_cast<EventWorkspace>(m_outputW);
  }
  m_progress->report();

  if (m_maskWS) {
    g_log.information() << "running MaskDetectors started at "
                        << Kernel::DateAndTime::getCurrentTime() << "\n";
    API::IAlgorithm_sptr maskAlg = createChildAlgorithm("MaskDetectors");
    maskAlg->setProperty("Workspace", m_outputW);
    maskAlg->setProperty("MaskedWorkspace", m_maskWS);
    maskAlg->executeAsChildAlg();
    Workspace_sptr tmpW = maskAlg->getProperty("Workspace");
    m_outputW = boost::dynamic_pointer_cast<MatrixWorkspace>(tmpW);
    m_outputEW = boost::dynamic_pointer_cast<EventWorkspace>(m_outputW);
  }
  m_progress->report();

  if (!dspace)
    m_outputW = rebin(m_outputW);
  m_progress->report();

  if (m_calibrationWS) {
    g_log.information() << "running AlignDetectors started at "
                        << Kernel::DateAndTime::getCurrentTime() << "\n";
    API::IAlgorithm_sptr alignAlg = createChildAlgorithm("AlignDetectors");
    alignAlg->setProperty("InputWorkspace", m_outputW);
    alignAlg->setProperty("OutputWorkspace", m_outputW);
    alignAlg->setProperty("CalibrationWorkspace", m_calibrationWS);
    alignAlg->executeAsChildAlg();
    m_outputW = alignAlg->getProperty("OutputWorkspace");
  } else {
    m_outputW = convertUnits(m_outputW, "dSpacing");
  }
  m_progress->report();

  if (LRef > 0. || minwl > 0. || DIFCref > 0. || (!isEmpty(maxwl))) {
    m_outputW = convertUnits(m_outputW, "TOF");
  }
  m_progress->report();

  // Beyond this point, low resolution TOF workspace is considered.
  if (LRef > 0.) {
    g_log.information() << "running UnwrapSNS(LRef=" << LRef << ",Tmin=" << tmin
                        << ",Tmax=" << tmax << ") started at "
                        << Kernel::DateAndTime::getCurrentTime() << "\n";
    API::IAlgorithm_sptr removeAlg = createChildAlgorithm("UnwrapSNS");
    removeAlg->setProperty("InputWorkspace", m_outputW);
    removeAlg->setProperty("OutputWorkspace", m_outputW);
    removeAlg->setProperty("LRef", LRef);
    if (tmin > 0.)
      removeAlg->setProperty("Tmin", tmin);
    if (tmax > tmin)
      removeAlg->setProperty("Tmax", tmax);
    removeAlg->executeAsChildAlg();
    m_outputW = removeAlg->getProperty("OutputWorkspace");
  }
  m_progress->report();

  if (minwl > 0. || (!isEmpty(maxwl))) { // just crop the worksapce
    // turn off the low res stuff
    m_processLowResTOF = false;

    EventWorkspace_sptr ews =
        boost::dynamic_pointer_cast<EventWorkspace>(m_outputW);
    if (ews)
      g_log.information() << "Number of events = " << ews->getNumberEvents()
                          << ". ";
    g_log.information("\n");

    m_outputW = convertUnits(m_outputW, "Wavelength");

    g_log.information() << "running CropWorkspace(WavelengthMin=" << minwl;
    if (!isEmpty(maxwl))
      g_log.information() << ", WavelengthMax=" << maxwl;
    g_log.information() << ") started at "
                        << Kernel::DateAndTime::getCurrentTime() << "\n";

    API::IAlgorithm_sptr removeAlg = createChildAlgorithm("CropWorkspace");
    removeAlg->setProperty("InputWorkspace", m_outputW);
    removeAlg->setProperty("OutputWorkspace", m_outputW);
    removeAlg->setProperty("XMin", minwl);
    removeAlg->setProperty("XMax", maxwl);
    removeAlg->executeAsChildAlg();
    m_outputW = removeAlg->getProperty("OutputWorkspace");
    if (ews)
      g_log.information() << "Number of events = " << ews->getNumberEvents()
                          << ".\n";
  } else if (DIFCref > 0.) {
    g_log.information() << "running RemoveLowResTof(RefDIFC=" << DIFCref
                        << ",K=3.22) started at "
                        << Kernel::DateAndTime::getCurrentTime() << "\n";
    EventWorkspace_sptr ews =
        boost::dynamic_pointer_cast<EventWorkspace>(m_outputW);
    if (ews)
      g_log.information() << "Number of events = " << ews->getNumberEvents()
                          << ". ";
    g_log.information("\n");

    API::IAlgorithm_sptr removeAlg = createChildAlgorithm("RemoveLowResTOF");
    removeAlg->setProperty("InputWorkspace", m_outputW);
    removeAlg->setProperty("OutputWorkspace", m_outputW);
    removeAlg->setProperty("ReferenceDIFC", DIFCref);
    removeAlg->setProperty("K", 3.22);
    if (tmin > 0.)
      removeAlg->setProperty("Tmin", tmin);
    if (m_processLowResTOF)
      removeAlg->setProperty("LowResTOFWorkspace", m_lowResW);

    removeAlg->executeAsChildAlg();
    m_outputW = removeAlg->getProperty("OutputWorkspace");
    if (m_processLowResTOF)
      m_lowResW = removeAlg->getProperty("LowResTOFWorkspace");
  }
  m_progress->report();

  EventWorkspace_sptr ews =
      boost::dynamic_pointer_cast<EventWorkspace>(m_outputW);
  if (ews) {
    size_t numhighevents = ews->getNumberEvents();
    if (m_processLowResTOF) {
      EventWorkspace_sptr lowes =
          boost::dynamic_pointer_cast<EventWorkspace>(m_lowResW);
      size_t numlowevents = lowes->getNumberEvents();
      g_log.information() << "Number of high TOF events = " << numhighevents
                          << "; "
                          << "Number of low TOF events = " << numlowevents
                          << ".\n";
    }
  }
  m_progress->report();

  // Convert units
  if (LRef > 0. || minwl > 0. || DIFCref > 0. || (!isEmpty(maxwl))) {
    m_outputW = convertUnits(m_outputW, "dSpacing");
    if (m_processLowResTOF)
      m_lowResW = convertUnits(m_lowResW, "dSpacing");
  }
  m_progress->report();

  if (dspace) {
    m_outputW = rebin(m_outputW);
    if (m_processLowResTOF)
      m_lowResW = rebin(m_lowResW);
  }
  m_progress->report();

  doSortEvents(m_outputW);
  if (m_processLowResTOF)
    doSortEvents(m_lowResW);
  m_progress->report();

  // Diffraction focus
  m_outputW = diffractionFocus(m_outputW);
  if (m_processLowResTOF)
    m_lowResW = diffractionFocus(m_lowResW);
  m_progress->report();

  doSortEvents(m_outputW);
  if (m_processLowResTOF)
    doSortEvents(m_lowResW);
  m_progress->report();

  // this next call should probably be in for rebin as well
  // but it changes the system tests
  if (dspace && m_resampleX != 0) {
    m_outputW = rebin(m_outputW);
    if (m_processLowResTOF)
      m_lowResW = rebin(m_lowResW);
  }
  m_progress->report();

  // edit the instrument geometry
  if (m_groupWS &&
      (m_l1 > 0 || !tths.empty() || !l2s.empty() || !phis.empty())) {
    size_t numreg = m_outputW->getNumberHistograms();

    try {
      // set up the vectors for doing everything
      auto specidsSplit = splitVectors(specids, numreg, "specids");
      auto tthsSplit = splitVectors(tths, numreg, "two-theta");
      auto l2sSplit = splitVectors(l2s, numreg, "L2");
      auto phisSplit = splitVectors(phis, numreg, "phi");

      // Edit instrument
      m_outputW = editInstrument(m_outputW, tthsSplit.reg, specidsSplit.reg,
                                 l2sSplit.reg, phisSplit.reg);

      if (m_processLowResTOF) {
        m_lowResW = editInstrument(m_lowResW, tthsSplit.low, specidsSplit.low,
                                   l2sSplit.low, phisSplit.low);
      }
    } catch (std::runtime_error &e) {
      g_log.warning("Not editing instrument geometry:");
      g_log.warning(e.what());
    }
  }
  m_progress->report();

  // Conjoin 2 workspaces if there is low resolution
  if (m_processLowResTOF) {
    m_outputW = conjoinWorkspaces(m_outputW, m_lowResW, m_lowResSpecOffset);
  }
  m_progress->report();

  // Convert units to TOF
  m_outputW = convertUnits(m_outputW, "TOF");
  m_progress->report();

  // compress again if appropriate
  double tolerance = getProperty("CompressTolerance");
  m_outputEW = boost::dynamic_pointer_cast<EventWorkspace>(m_outputW);
  if ((m_outputEW) && (tolerance > 0.)) {
    g_log.information() << "running CompressEvents(Tolerance=" << tolerance
                        << ") started at "
                        << Kernel::DateAndTime::getCurrentTime() << "\n";
    API::IAlgorithm_sptr compressAlg = createChildAlgorithm("CompressEvents");
    compressAlg->setProperty("InputWorkspace", m_outputEW);
    compressAlg->setProperty("OutputWorkspace", m_outputEW);
    compressAlg->setProperty("OutputWorkspace", m_outputEW);
    compressAlg->setProperty("Tolerance", tolerance);
    compressAlg->executeAsChildAlg();
    m_outputEW = compressAlg->getProperty("OutputWorkspace");
    m_outputW = boost::dynamic_pointer_cast<MatrixWorkspace>(m_outputEW);
  }
  m_progress->report();

  if ((!m_params.empty()) && (m_params.size() != 1)) {
    m_params.erase(m_params.begin());
    m_params.pop_back();
  }
  if (!m_dmins.empty())
    m_dmins.clear();
  if (!m_dmaxs.empty())
    m_dmaxs.clear();

  m_outputW = rebin(m_outputW);
  m_progress->report();

  // return the output workspace
  setProperty("OutputWorkspace", m_outputW);
}
  /** Fit function
    * Minimizer: "Levenberg-MarquardtMD"/"Simplex"
   */
  bool RefinePowderInstrumentParameters2::doFitFunction(IFunction_sptr function, Workspace2D_sptr dataws, int wsindex,
                                                        string minimizer, int numiters, double& chi2, string& fitstatus)
  {
    // 0. Debug output
    stringstream outss;
    outss << "Fit function: " << m_positionFunc->asString() << endl << "Data To Fit: \n";
    for (size_t i = 0; i < dataws->readX(0).size(); ++i)
      outss << dataws->readX(wsindex)[i] << "\t\t" << dataws->readY(wsindex)[i] << "\t\t"
            << dataws->readE(wsindex)[i] << "\n";
    g_log.information() << outss.str();

    // 1. Create and setup fit algorithm
    API::IAlgorithm_sptr fitalg = createChildAlgorithm("Fit", 0.0, 0.2, true);
    fitalg->initialize();

    fitalg->setProperty("Function", function);
    fitalg->setProperty("InputWorkspace", dataws);
    fitalg->setProperty("WorkspaceIndex", wsindex);
    fitalg->setProperty("Minimizer", minimizer);
    fitalg->setProperty("CostFunction", "Least squares");
    fitalg->setProperty("MaxIterations", numiters);
    fitalg->setProperty("CalcErrors", true);

    // 2. Fit
    bool successfulfit = fitalg->execute();
    if (!fitalg->isExecuted() || ! successfulfit)
    {
      // Early return due to bad fit
      g_log.warning("Fitting to instrument geometry function failed. ");
      chi2 = DBL_MAX;
      fitstatus = "Minimizer throws exception.";
      return false;
    }

    // 3. Understand solution
    chi2 = fitalg->getProperty("OutputChi2overDoF");
    string tempfitstatus = fitalg->getProperty("OutputStatus");
    fitstatus = tempfitstatus;

    bool goodfit = fitstatus.compare("success") == 0;

    stringstream dbss;
    dbss << "Fit Result (GSL):  Chi^2 = " << chi2
         << "; Fit Status = " << fitstatus << ", Return Bool = " << goodfit << std::endl;
    vector<string> funcparnames = function->getParameterNames();
    for (size_t i = 0; i < funcparnames.size(); ++i)
      dbss << funcparnames[i] << " = " << setw(20) << function->getParameter(funcparnames[i])
           << " +/- " << function->getError(i) << "\n";
    g_log.debug() << dbss.str();

    return goodfit;
  }
Exemple #26
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);
}
/**
  * Gaussian fit to determine peak position if no user position given.
  *
  * @return :: detector position of the peak: Gaussian fit and position
  * of the maximum (serves as start value for the optimization)
  */
double LoadILLReflectometry::reflectometryPeak() {
  if (!isDefault("BeamCentre")) {
    return getProperty("BeamCentre");
  }
  size_t startIndex;
  size_t endIndex;
  std::tie(startIndex, endIndex) =
      fitIntegrationWSIndexRange(*m_localWorkspace);
  IAlgorithm_sptr integration = createChildAlgorithm("Integration");
  integration->initialize();
  integration->setProperty("InputWorkspace", m_localWorkspace);
  integration->setProperty("OutputWorkspace", "__unused_for_child");
  integration->setProperty("StartWorkspaceIndex", static_cast<int>(startIndex));
  integration->setProperty("EndWorkspaceIndex", static_cast<int>(endIndex));
  integration->execute();
  MatrixWorkspace_sptr integralWS = integration->getProperty("OutputWorkspace");
  IAlgorithm_sptr transpose = createChildAlgorithm("Transpose");
  transpose->initialize();
  transpose->setProperty("InputWorkspace", integralWS);
  transpose->setProperty("OutputWorkspace", "__unused_for_child");
  transpose->execute();
  integralWS = transpose->getProperty("OutputWorkspace");
  rebinIntegralWorkspace(*integralWS);
  // determine initial height: maximum value
  const auto maxValueIt =
      std::max_element(integralWS->y(0).cbegin(), integralWS->y(0).cend());
  const double height = *maxValueIt;
  // determine initial centre: index of the maximum value
  const size_t maxIndex = std::distance(integralWS->y(0).cbegin(), maxValueIt);
  const double centreByMax = static_cast<double>(maxIndex);
  g_log.debug() << "Peak maximum position: " << centreByMax << '\n';
  // determine sigma
  const auto &ys = integralWS->y(0);
  auto lessThanHalfMax = [height](const double x) { return x < 0.5 * height; };
  using IterType = HistogramData::HistogramY::const_iterator;
  std::reverse_iterator<IterType> revMaxValueIt{maxValueIt};
  auto revMinFwhmIt = std::find_if(revMaxValueIt, ys.crend(), lessThanHalfMax);
  auto maxFwhmIt = std::find_if(maxValueIt, ys.cend(), lessThanHalfMax);
  std::reverse_iterator<IterType> revMaxFwhmIt{maxFwhmIt};
  if (revMinFwhmIt == ys.crend() || maxFwhmIt == ys.cend()) {
    g_log.warning() << "Couldn't determine fwhm of beam, using position of max "
                       "value as beam center.\n";
    return centreByMax;
  }
  const double fwhm =
      static_cast<double>(std::distance(revMaxFwhmIt, revMinFwhmIt) + 1);
  g_log.debug() << "Initial fwhm (full width at half maximum): " << fwhm
                << '\n';
  // generate Gaussian
  auto func =
      API::FunctionFactory::Instance().createFunction("CompositeFunction");
  auto sum = boost::dynamic_pointer_cast<API::CompositeFunction>(func);
  func = API::FunctionFactory::Instance().createFunction("Gaussian");
  auto gaussian = boost::dynamic_pointer_cast<API::IPeakFunction>(func);
  gaussian->setHeight(height);
  gaussian->setCentre(centreByMax);
  gaussian->setFwhm(fwhm);
  sum->addFunction(gaussian);
  func = API::FunctionFactory::Instance().createFunction("LinearBackground");
  func->setParameter("A0", 0.);
  func->setParameter("A1", 0.);
  sum->addFunction(func);
  // call Fit child algorithm
  API::IAlgorithm_sptr fit = createChildAlgorithm("Fit");
  fit->initialize();
  fit->setProperty("Function",
                   boost::dynamic_pointer_cast<API::IFunction>(sum));
  fit->setProperty("InputWorkspace", integralWS);
  fit->setProperty("StartX", centreByMax - 3 * fwhm);
  fit->setProperty("EndX", centreByMax + 3 * fwhm);
  fit->execute();
  const std::string fitStatus = fit->getProperty("OutputStatus");
  if (fitStatus != "success") {
    g_log.warning("Fit not successful, using position of max value.\n");
    return centreByMax;
  }
  const auto centre = gaussian->centre();
  g_log.debug() << "Sigma: " << gaussian->fwhm() << '\n';
  g_log.debug() << "Estimated peak position: " << centre << '\n';
  return centre;
}
/** Calls Gaussian1D as a child algorithm to fit the offset peak in a spectrum
  *
  * @param wi :: The Workspace Index to fit.
  * @param inputW :: Input workspace.
  * @param peakPositions :: Peak positions.
  * @param fitWindows :: Fit windows.
  * @param nparams :: Number of parameters.
  * @param minD :: Min distance.
  * @param maxD :: Max distance.
  * @param peakPosToFit :: Actual peak positions to fit (output).
  * @param peakPosFitted :: Actual peak positions fitted (output).
  * @param chisq :: chisq.
  * @param peakHeights :: vector for fitted heights of peaks
  * @param i_highestpeak:: index of the highest peak among all peaks
  * @param resolution :: spectrum's resolution delta(d)/d
  * @param dev_resolution :: standard deviation resolution
  * @return The number of peaks in range
  */
int GetDetOffsetsMultiPeaks::fitSpectra(
    const int64_t wi, MatrixWorkspace_sptr inputW,
    const std::vector<double> &peakPositions,
    const std::vector<double> &fitWindows, size_t &nparams, double &minD,
    double &maxD, std::vector<double> &peakPosToFit,
    std::vector<double> &peakPosFitted, std::vector<double> &chisq,
    std::vector<double> &peakHeights, int &i_highestpeak, double &resolution,
    double &dev_resolution) {
  // Default overall fit range is the whole spectrum
  const MantidVec &X = inputW->readX(wi);
  minD = X.front();
  maxD = X.back();

  // Trim in the edges based on where the data turns off of zero
  const MantidVec &Y = inputW->readY(wi);
  size_t minDindex = 0;
  for (; minDindex < Y.size(); ++minDindex) {
    if (Y[minDindex] > 0.) {
      minD = X[minDindex];
      break;
    }
  }
  if (minD >= maxD) {
    // throw if minD >= maxD
    std::stringstream ess;
    ess << "Stuff went wrong with wkspIndex=" << wi
        << " specIndex=" << inputW->getSpectrum(wi)->getSpectrumNo();
    throw std::runtime_error(ess.str());
  }

  size_t maxDindex = Y.size() - 1;
  for (; maxDindex > minDindex; --maxDindex) {
    if (Y[maxDindex] > 0.) {
      maxD = X[maxDindex];
      break;
    }
  }
  std::stringstream dbss;
  dbss << "D-RANGE[" << inputW->getSpectrum(wi)->getSpectrumNo()
       << "]: " << minD << " -> " << maxD;
  g_log.debug(dbss.str());

  // Setup the fit windows
  bool useFitWindows = (!fitWindows.empty());
  std::vector<double> fitWindowsToUse;
  for (int i = 0; i < static_cast<int>(peakPositions.size()); ++i) {
    if ((peakPositions[i] > minD) && (peakPositions[i] < maxD)) {
      if (m_useFitWindowTable) {
        fitWindowsToUse.push_back(std::max(m_vecFitWindow[wi][2 * i], minD));
        fitWindowsToUse.push_back(
            std::min(m_vecFitWindow[wi][2 * i + 1], maxD));
      } else if (useFitWindows) {
        fitWindowsToUse.push_back(std::max(fitWindows[2 * i], minD));
        fitWindowsToUse.push_back(std::min(fitWindows[2 * i + 1], maxD));
      }
      peakPosToFit.push_back(peakPositions[i]);
    }
  }
  int numPeaksInRange = static_cast<int>(peakPosToFit.size());
  if (numPeaksInRange == 0) {
    std::stringstream outss;
    outss << "Spectrum " << wi << " has no peak in range (" << minD << ", "
          << maxD << ")";
    g_log.information(outss.str());
    return 0;
  }

  // Fit peaks
  API::IAlgorithm_sptr findpeaks =
      createChildAlgorithm("FindPeaks", -1, -1, false);
  findpeaks->setProperty("InputWorkspace", inputW);
  findpeaks->setProperty<int>("FWHM", 7);
  findpeaks->setProperty<int>("Tolerance", 4);
  // FindPeaks will do the checking on the validity of WorkspaceIndex
  findpeaks->setProperty("WorkspaceIndex", static_cast<int>(wi));

  // Get the specified peak positions, which is optional
  findpeaks->setProperty("PeakPositions", peakPosToFit);
  if (useFitWindows)
    findpeaks->setProperty("FitWindows", fitWindowsToUse);
  findpeaks->setProperty<std::string>("PeakFunction", m_peakType);
  findpeaks->setProperty<std::string>("BackgroundType", m_backType);
  findpeaks->setProperty<bool>("HighBackground",
                               this->getProperty("HighBackground"));
  findpeaks->setProperty<int>("MinGuessedPeakWidth", 4);
  findpeaks->setProperty<int>("MaxGuessedPeakWidth", 4);
  findpeaks->setProperty<double>("MinimumPeakHeight", m_minPeakHeight);
  findpeaks->setProperty("StartFromObservedPeakCentre", true);
  findpeaks->executeAsChildAlg();

  // Collect fitting resutl of all peaks
  ITableWorkspace_sptr peakslist = findpeaks->getProperty("PeaksList");

  // use tmpPeakPosToFit to shuffle the vectors
  std::vector<double> tmpPeakPosToFit;
  generatePeaksList(peakslist, static_cast<int>(wi), peakPosToFit,
                    tmpPeakPosToFit, peakPosFitted, peakHeights, chisq,
                    (useFitWindows || m_useFitWindowTable), fitWindowsToUse,
                    minD, maxD, resolution, dev_resolution);
  peakPosToFit = tmpPeakPosToFit;

  nparams = peakPosFitted.size();

  // Find the highest peak
  i_highestpeak = -1;
  double maxheight = 0;
  for (int i = 0; i < static_cast<int>(peakPosFitted.size()); ++i) {
    double tmpheight = peakHeights[i];
    if (tmpheight > maxheight) {
      maxheight = tmpheight;
      i_highestpeak = i;
    }
  }

  return numPeaksInRange;
}
/**
 * Creates a managed version of a specified algorithm.
 * @param algName :: The name of the algorithm to execute.
 * @param version :: The version number (default=-1=highest version).
 * @return Pointer to algorithm.
 **/
API::IAlgorithm_sptr FrameworkManagerProxy::createUnmanagedAlgorithm(const std::string& algName, const int version)
{
  API::IAlgorithm_sptr alg = API::AlgorithmManager::Instance().createUnmanaged(algName, version);
  alg->initialize();
  return alg;
}
/** Perform SortHKL on the output workspaces
 *
 * @param ws :: any PeaksWorkspace
 * @param runName :: string to put in statistics table
 */
void StatisticsOfPeaksWorkspace::doSortHKL(Mantid::API::Workspace_sptr ws,
                                           std::string runName) {
  std::string pointGroup = getPropertyValue("PointGroup");
  std::string latticeCentering = getPropertyValue("LatticeCentering");
  std::string wkspName = getPropertyValue("OutputWorkspace");
  std::string tableName = getPropertyValue("StatisticsTable");
  API::IAlgorithm_sptr statsAlg = createChildAlgorithm("SortHKL");
  statsAlg->setProperty("InputWorkspace", ws);
  statsAlg->setPropertyValue("OutputWorkspace", wkspName);
  statsAlg->setPropertyValue("StatisticsTable", tableName);
  statsAlg->setProperty("PointGroup", pointGroup);
  statsAlg->setProperty("LatticeCentering", latticeCentering);
  statsAlg->setProperty("RowName", runName);
  if (runName.compare("Overall") != 0)
    statsAlg->setProperty("Append", true);
  statsAlg->executeAsChildAlg();
  PeaksWorkspace_sptr statsWksp = statsAlg->getProperty("OutputWorkspace");
  ITableWorkspace_sptr tablews = statsAlg->getProperty("StatisticsTable");
  if (runName.compare("Overall") == 0)
    setProperty("OutputWorkspace", statsWksp);
  setProperty("StatisticsTable", tablews);
}