void ALCPeakFittingView::setFunction(const IFunction_const_sptr &newFunction) {
if (newFunction) {
size_t nParams = newFunction->nParams();
for (size_t i = 0; i < nParams; i++) {
QString name = QString::fromStdString(newFunction->parameterName(i));
double value = newFunction->getParameter(i);
double error = newFunction->getError(i);
m_ui.peaks->setParameter(name, value);
m_ui.peaks->setParamError(name, error);
}
} else {
m_ui.peaks->clear();
}
}
void ALCBaselineModellingView::setFunction(IFunction_const_sptr func) {
if (!func) {
m_ui.function->clear();
} else {
size_t nParams = func->nParams();
for (size_t i = 0; i < nParams; i++) {
QString name = QString::fromStdString(func->parameterName(i));
double value = func->getParameter(i);
double error = func->getError(i);
m_ui.function->setParameter(name, value);
m_ui.function->setParamError(name, error);
}
}
}
/**
* Creates a single-spectrum workspace filled with function values for given X values
* @param func :: Function to calculate values
* @param xValues :: X values to use
* @return Single-spectrum workspace with calculated function values
*/
MatrixWorkspace_sptr createWsFromFunction(IFunction_const_sptr func,
const std::vector<double>& xValues)
{
auto inputWs = boost::dynamic_pointer_cast<MatrixWorkspace>(
WorkspaceFactory::Instance().create("Workspace2D", 1, xValues.size(), xValues.size()));
inputWs->dataX(0) = xValues;
IAlgorithm_sptr fit = AlgorithmManager::Instance().create("Fit");
fit->setChild(true); // Don't want workspace in the ADS
fit->setProperty("Function", func->asString());
fit->setProperty("InputWorkspace", inputWs);
fit->setProperty("MaxIterations", 0); // Don't want to fit, just calculate output workspace
fit->setProperty("CreateOutput", true);
fit->execute();
MatrixWorkspace_sptr fitOutput = fit->getProperty("OutputWorkspace");
IAlgorithm_sptr extract = AlgorithmManager::Instance().create("ExtractSingleSpectrum");
extract->setChild(true); // Don't want workspace in the ADS
extract->setProperty("InputWorkspace", fitOutput);
extract->setProperty("WorkspaceIndex", 1); // "Calc"
extract->setPropertyValue("OutputWorkspace", "__NotUsed");
extract->execute();
return extract->getProperty("OutputWorkspace");
}
/// Set the weight function
void CustomPolynomial::setWeightFunction(IFunction_const_sptr wgtFun, const double& tol)
{
m_weightFunction = wgtFun;
auto cheb = dynamic_cast<const ChebFunction*>( wgtFun.get() );
if ( cheb && cheb->nfuns() == 1 && !cheb->cfun(0).hasScaling() )
{
m_fun = cheb->cfun(0).getUnscaled();
}
else
{
m_fun.bestFit( *wgtFun, tol );
}
}
void ALCBaselineModellingModel::fit(IFunction_const_sptr function,
const std::vector<Section> §ions) {
// Create a copy of the data
IAlgorithm_sptr clone = AlgorithmManager::Instance().create("CloneWorkspace");
clone->setChild(true);
clone->setProperty("InputWorkspace",
boost::const_pointer_cast<MatrixWorkspace>(m_data));
clone->setProperty("OutputWorkspace", "__NotUsed__");
clone->execute();
Workspace_sptr cloned = clone->getProperty("OutputWorkspace");
MatrixWorkspace_sptr dataToFit =
boost::dynamic_pointer_cast<MatrixWorkspace>(cloned);
assert(dataToFit); // CloneWorkspace should take care of that
disableUnwantedPoints(dataToFit, sections);
IFunction_sptr funcToFit =
FunctionFactory::Instance().createInitialized(function->asString());
IAlgorithm_sptr fit = AlgorithmManager::Instance().create("Fit");
fit->setChild(true);
fit->setProperty("Function", funcToFit);
fit->setProperty("InputWorkspace", dataToFit);
fit->setProperty("CreateOutput", true);
// Run async so that progress can be shown
Poco::ActiveResult<bool> result(fit->executeAsync());
while (!result.available()) {
QCoreApplication::processEvents();
}
if (!result.error().empty()) {
throw std::runtime_error(result.error());
}
MatrixWorkspace_sptr fitOutput = fit->getProperty("OutputWorkspace");
m_parameterTable = fit->getProperty("OutputParameters");
enableDisabledPoints(fitOutput, m_data);
setErrorsAfterFit(fitOutput);
setCorrectedData(fitOutput);
setFittedFunction(funcToFit);
m_sections = sections;
}
void ALCPeakFittingModel::fitPeaks(IFunction_const_sptr peaks)
{
IAlgorithm_sptr fit = AlgorithmManager::Instance().create("Fit");
fit->setChild(true);
fit->setProperty("Function", peaks->asString());
fit->setProperty("InputWorkspace", boost::const_pointer_cast<MatrixWorkspace>(m_data));
fit->setProperty("CreateOutput", true);
fit->setProperty("OutputCompositeMembers", true);
// Execute async so we can show progress bar
Poco::ActiveResult<bool> result(fit->executeAsync());
while (!result.available()) {
QCoreApplication::processEvents();
}
if (!result.error().empty()) {
throw std::runtime_error(result.error());
}
m_data = fit->getProperty("OutputWorkspace");
m_parameterTable = fit->getProperty("OutputParameters");
setFittedPeaks(static_cast<IFunction_sptr>(fit->getProperty("Function")));
}
void ALCBaselineModellingModel::fit(IFunction_const_sptr function, const std::vector<Section>& sections)
{
// Create a copy of the data
IAlgorithm_sptr clone = AlgorithmManager::Instance().create("CloneWorkspace");
clone->setChild(true);
clone->setProperty("InputWorkspace", boost::const_pointer_cast<MatrixWorkspace>(m_data));
clone->setProperty("OutputWorkspace", "__NotUsed__");
clone->execute();
Workspace_sptr cloned = clone->getProperty("OutputWorkspace");
MatrixWorkspace_sptr dataToFit = boost::dynamic_pointer_cast<MatrixWorkspace>(cloned);
assert(dataToFit); // CloneWorkspace should take care of that
disableUnwantedPoints(dataToFit, sections);
IFunction_sptr funcToFit =
FunctionFactory::Instance().createInitialized(function->asString());
IAlgorithm_sptr fit = AlgorithmManager::Instance().create("Fit");
fit->setChild(true);
fit->setProperty("Function", funcToFit);
fit->setProperty("InputWorkspace", dataToFit);
fit->setProperty("CreateOutput", true);
fit->execute();
MatrixWorkspace_sptr fitOutput = fit->getProperty("OutputWorkspace");
m_parameterTable = fit->getProperty("OutputParameters");
enableDisabledPoints(fitOutput,m_data);
setErrorsAfterFit(fitOutput);
setCorrectedData(fitOutput);
setFittedFunction(funcToFit);
m_sections = sections;
}
