/**
* Initialize diagnosis table.
*/
void MuonSequentialFitDialog::initDiagnosisTable()
{
QStringList headerLabels;
// Add two static columns
headerLabels << "Run" << "Fit quality";
// Add remaining columns - one for every fit function parameter
IFunction_sptr fitFunc = m_fitPropBrowser->getFittingFunction();
for(size_t i = 0; i < fitFunc->nParams(); i++)
{
QString paramName = QString::fromStdString( fitFunc->parameterName(i) );
headerLabels << paramName;
headerLabels << paramName + "_Err";
}
m_ui.diagnosisTable->setColumnCount( headerLabels.size() );
m_ui.diagnosisTable->setHorizontalHeaderLabels(headerLabels);
// Make the table fill all the available space and columns be resized to fit contents
m_ui.diagnosisTable->horizontalHeader()->setResizeMode(QHeaderView::ResizeToContents);
// Make rows alternate bg colors for better user experience
m_ui.diagnosisTable->setAlternatingRowColors(true);
}
/**
* Gets a list of parameters for a given fit function.
*
* @return List fo parameters
*/
QStringList JumpFit::getFunctionParameters(const QString &functionName) {
QStringList parameters;
IFunction_sptr func =
FunctionFactory::Instance().createFunction(functionName.toStdString());
for (size_t i = 0; i < func->nParams(); i++)
parameters << QString::fromStdString(func->parameterName(i));
return parameters;
}
/// Returns a TableWorkspace with refined cell parameters and error.
ITableWorkspace_sptr PoldiFitPeaks2D::getRefinedCellParameters(
const IFunction_sptr &fitFunction) const {
Poldi2DFunction_sptr poldi2DFunction =
boost::dynamic_pointer_cast<Poldi2DFunction>(fitFunction);
if (!poldi2DFunction || poldi2DFunction->nFunctions() < 1) {
throw std::invalid_argument(
"Cannot process function that is not a Poldi2DFunction.");
}
// Create a new table for lattice parameters
ITableWorkspace_sptr latticeParameterTable =
WorkspaceFactory::Instance().createTable();
latticeParameterTable->addColumn("str", "Parameter");
latticeParameterTable->addColumn("double", "Value");
latticeParameterTable->addColumn("double", "Error");
// The first function should be PoldiSpectrumPawleyFunction
boost::shared_ptr<PoldiSpectrumPawleyFunction> poldiPawleyFunction =
boost::dynamic_pointer_cast<PoldiSpectrumPawleyFunction>(
poldi2DFunction->getFunction(0));
if (!poldiPawleyFunction) {
throw std::invalid_argument("First function in Poldi2DFunction is not "
"PoldiSpectrumPawleyFunction.");
}
// Get the actual PawleyFunction to extract parameters.
IPawleyFunction_sptr pawleyFunction =
boost::dynamic_pointer_cast<IPawleyFunction>(
poldiPawleyFunction->getDecoratedFunction());
if (pawleyFunction) {
CompositeFunction_sptr pawleyParts =
boost::dynamic_pointer_cast<CompositeFunction>(
pawleyFunction->getDecoratedFunction());
// The first function in PawleyFunction contains the parameters
IFunction_sptr pawleyParameters = pawleyParts->getFunction(0);
for (size_t i = 0; i < pawleyParameters->nParams(); ++i) {
TableRow newRow = latticeParameterTable->appendRow();
newRow << pawleyParameters->parameterName(i)
<< pawleyParameters->getParameter(i)
<< pawleyParameters->getError(i);
}
}
return latticeParameterTable;
}
API::MatrixWorkspace_sptr
CreateFloodWorkspace::removeBackground(API::MatrixWorkspace_sptr ws) {
g_log.information() << "Remove background "
<< getPropertyValue(Prop::BACKGROUND) << '\n';
auto fitWS = transpose(ws);
auto const &x = fitWS->x(0);
// Define the fitting interval
double startX = getProperty(Prop::START_X);
double endX = getProperty(Prop::END_X);
std::vector<double> excludeFromFit;
if (isDefault(Prop::START_X)) {
startX = x.front();
} else {
excludeFromFit.push_back(x.front());
excludeFromFit.push_back(startX);
}
if (isDefault(Prop::END_X)) {
endX = x.back();
} else {
excludeFromFit.push_back(endX);
excludeFromFit.push_back(x.back());
}
// Exclude any bad detectors.
for (auto i : m_excludedSpectra) {
excludeFromFit.push_back(i);
excludeFromFit.push_back(i);
}
std::string const function = getBackgroundFunction();
// Fit the data to determine unwanted background
auto alg = createChildAlgorithm("Fit", 0.9, 0.99);
alg->setProperty("Function", function);
alg->setProperty("InputWorkspace", fitWS);
alg->setProperty("WorkspaceIndex", 0);
if (!excludeFromFit.empty()) {
alg->setProperty("Exclude", excludeFromFit);
}
alg->setProperty("Output", "fit");
alg->execute();
IFunction_sptr func = alg->getProperty("Function");
g_log.information() << "Background function parameters:\n";
for (size_t i = 0; i < func->nParams(); ++i) {
g_log.information() << " " << func->parameterName(i) << ": "
<< func->getParameter(i) << '\n';
}
// Divide the workspace by the fitted curve to remove the background
// and scale to values around 1
MatrixWorkspace_sptr bkgWS = alg->getProperty("OutputWorkspace");
auto const &bkg = bkgWS->y(1);
auto const nHisto = static_cast<int>(ws->getNumberHistograms());
PARALLEL_FOR_IF(Kernel::threadSafe(*ws, *bkgWS))
for (int i = 0; i < nHisto; ++i) {
PARALLEL_START_INTERUPT_REGION
auto const xVal = x[i];
if (isExcludedSpectrum(xVal)) {
ws->mutableY(i)[0] = VERY_BIG_VALUE;
ws->mutableE(i)[0] = 0.0;
} else if (xVal >= startX && xVal <= endX) {
auto const background = bkg[i];
if (background <= 0.0) {
throw std::runtime_error(
"Background is expected to be positive, found value " +
std::to_string(background) + " at spectrum with workspace index " +
std::to_string(i));
}
ws->mutableY(i)[0] /= background;
ws->mutableE(i)[0] /= background;
} else {
ws->mutableY(i)[0] = 1.0;
ws->mutableE(i)[0] = 0.0;
}
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
// Remove the logs
ws->setSharedRun(make_cow<Run>());
return ws;
}
