C++ TableWorkspace_sptr::addColumn方法代码示例

TableWorkspace_sptr PoldiPeakSummary::getInitializedResultWorkspace() const {
  TableWorkspace_sptr peakResultWorkspace =
      boost::dynamic_pointer_cast<TableWorkspace>(
          WorkspaceFactory::Instance().createTable());

  peakResultWorkspace->addColumn("str", "hkl");
  peakResultWorkspace->addColumn("str", "Q");
  peakResultWorkspace->addColumn("str", "d");
  peakResultWorkspace->addColumn("double", "deltaD/d *10^3");
  peakResultWorkspace->addColumn("str", "FWHM rel. *10^3");
  peakResultWorkspace->addColumn("str", "Intensity");

  return peakResultWorkspace;
}

/**
 * Creates Dead Time Table using all the data between begin and end.
 * @param specToLoad :: vector containing the spectrum numbers to load
 * @param deadTimes :: vector containing the corresponding dead times
 * @return Dead Time Table create using the data
 */
TableWorkspace_sptr
LoadMuonNexus1::createDeadTimeTable(std::vector<int> specToLoad,
                                    std::vector<double> deadTimes) {
  TableWorkspace_sptr deadTimeTable =
      boost::dynamic_pointer_cast<TableWorkspace>(
          WorkspaceFactory::Instance().createTable("TableWorkspace"));

  deadTimeTable->addColumn("int", "spectrum");
  deadTimeTable->addColumn("double", "dead-time");

  for (size_t i = 0; i<specToLoad.size(); i++) {
    TableRow row = deadTimeTable->appendRow();
    row << specToLoad[i] << deadTimes[i];
  }

  return deadTimeTable;
}

/// Create a TableWorkspace for the statistics with appropriate columns or get
/// one from the ADS.
ITableWorkspace_sptr
SortHKL::getStatisticsTable(const std::string &name) const {
  TableWorkspace_sptr tablews;

  // Init or append to a table workspace
  bool append = getProperty("Append");
  if (append && AnalysisDataService::Instance().doesExist(name)) {
    tablews = AnalysisDataService::Instance().retrieveWS<TableWorkspace>(name);
  } else {
    tablews = boost::make_shared<TableWorkspace>();
    tablews->addColumn("str", "Resolution Shell");
    tablews->addColumn("int", "No. of Unique Reflections");
    tablews->addColumn("double", "Resolution Min");
    tablews->addColumn("double", "Resolution Max");
    tablews->addColumn("double", "Multiplicity");
    tablews->addColumn("double", "Mean ((I)/sd(I))");
    tablews->addColumn("double", "Rmerge");
    tablews->addColumn("double", "Rpim");
    tablews->addColumn("double", "Data Completeness");
  }

  return tablews;
}

/** 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.........

/** Fits each spectrum in the workspace to f(x) = A * sin( w * x + p)
 * @param ws :: [input] The workspace to fit
 * @param freq :: [input] Hint for the frequency (w)
 * @param groupName :: [input] The name of the output workspace group
 * @param resTab :: [output] Table workspace storing the asymmetries and phases
 * @param resGroup :: [output] Workspace group storing the fitting results
 */
void CalMuonDetectorPhases::fitWorkspace(const API::MatrixWorkspace_sptr &ws,
                                         double freq, std::string groupName,
                                         API::ITableWorkspace_sptr resTab,
                                         API::WorkspaceGroup_sptr &resGroup) {

  int nhist = static_cast<int>(ws->getNumberHistograms());

  // Create the fitting function f(x) = A * sin ( w * x + p )
  // The same function and initial parameters are used for each fit
  std::string funcStr = createFittingFunction(freq, true);

  // Set up results table
  resTab->addColumn("int", "Spectrum number");
  resTab->addColumn("double", "Asymmetry");
  resTab->addColumn("double", "Phase");

  const auto &indexInfo = ws->indexInfo();

  // Loop through fitting all spectra individually
  const static std::string success = "success";
  for (int wsIndex = 0; wsIndex < nhist; wsIndex++) {
    reportProgress(wsIndex, nhist);
    const auto &yValues = ws->y(wsIndex);
    auto emptySpectrum = std::all_of(yValues.begin(), yValues.end(),
                                     [](double value) { return value == 0.; });
    if (emptySpectrum) {
      g_log.warning("Spectrum " + std::to_string(wsIndex) + " is empty");
      TableWorkspace_sptr tab = boost::make_shared<TableWorkspace>();
      tab->addColumn("str", "Name");
      tab->addColumn("double", "Value");
      tab->addColumn("double", "Error");
      for (int j = 0; j < 4; j++) {
        API::TableRow row = tab->appendRow();
        if (j == PHASE_ROW) {
          row << "dummy" << 0.0 << 0.0;
        } else {
          row << "dummy" << ASYMM_ERROR << 0.0;
        }
      }

      extractDetectorInfo(*tab, *resTab, indexInfo.spectrumNumber(wsIndex));

    } else {
      auto fit = createChildAlgorithm("Fit");
      fit->initialize();
      fit->setPropertyValue("Function", funcStr);
      fit->setProperty("InputWorkspace", ws);
      fit->setProperty("WorkspaceIndex", wsIndex);
      fit->setProperty("CreateOutput", true);
      fit->setPropertyValue("Output", groupName);
      fit->execute();

      std::string status = fit->getProperty("OutputStatus");
      if (!fit->isExecuted()) {
        std::ostringstream error;
        error << "Fit failed for spectrum at workspace index " << wsIndex;
        error << ": " << status;
        throw std::runtime_error(error.str());
      } else if (status != success) {
        g_log.warning("Fit failed for spectrum at workspace index " +
                      std::to_string(wsIndex) + ": " + status);
      }

      API::MatrixWorkspace_sptr fitOut = fit->getProperty("OutputWorkspace");
      resGroup->addWorkspace(fitOut);
      API::ITableWorkspace_sptr tab = fit->getProperty("OutputParameters");
      // Now we have our fitting results stored in tab
      // but we need to extract the relevant information, i.e.
      // the detector phases (parameter 'p') and asymmetries ('A')
      extractDetectorInfo(*tab, *resTab, indexInfo.spectrumNumber(wsIndex));
    }
  }
}