C++ IAlgorithm_sptr::getProperty方法代码示例

/**
 * 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;
}

/**
 * Execute the algorithm.
 */
void FitResolutionConvolvedModel::exec() {
  API::IAlgorithm_sptr fit = createFittingAlgorithm();
  fit->setPropertyValue("Function", createFunctionString());
  fit->setProperty("InputWorkspace", getPropertyValue(INPUT_WS_NAME));
  fit->setProperty("DomainType",
                   "Simple"); // Parallel not quite giving correct answers
  fit->setProperty("Minimizer", "Levenberg-MarquardtMD");

  const int maxIter = niterations();
  fit->setProperty("MaxIterations", maxIter);
  fit->setProperty("CreateOutput", true);
  fit->setPropertyValue("Output", getPropertyValue(SIMULATED_NAME));

  try {
    fit->execute();
  } catch (std::exception &exc) {
    throw std::runtime_error(
        std::string("FitResolutionConvolvedModel - Error running Fit: ") +
        exc.what());
  }

  // Pass on the relevant properties
  IMDEventWorkspace_sptr simulatedData = fit->getProperty("OutputWorkspace");
  this->setProperty(SIMULATED_NAME, simulatedData);

  if (this->existsProperty(OUTPUT_PARS)) {
    ITableWorkspace_sptr outputPars = fit->getProperty("OutputParameters");
    setProperty(OUTPUT_PARS, outputPars);
  }
  if (this->existsProperty(OUTPUTCOV_MATRIX)) {
    ITableWorkspace_sptr covarianceMatrix =
        fit->getProperty("OutputNormalisedCovarianceMatrix");
    setProperty(OUTPUTCOV_MATRIX, covarianceMatrix);
  }
}

  /** 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;
  }

/** 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;
}

/**
 * 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;
}

/**  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");
}

/**
 * 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();
}

/** 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);
}

/** 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;
}

/// 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");
}

/** 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;
  }
}

/**
* Set the output workspace(s) if the load's return workspace has type
* API::Workspace
* @param loader :: Shared pointer to load algorithm
*/
void LoadNexus::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(new WorkspaceProperty<Workspace>(
            name, loader->getPropertyValue(name), Direction::Output));
      }
      Workspace_sptr wkspace = loader->getProperty(name);
      setProperty(name, wkspace);
    }
  }
}

/** 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;
}

/// 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");
}

/** 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) {
//.........这里部分代码省略.........