diff --git a/Framework/WorkflowAlgorithms/src/ConvolutionFitSequential.cpp b/Framework/WorkflowAlgorithms/src/ConvolutionFitSequential.cpp
index 9775f12ec5beea8f564ea1987a70a25e2c835827..425fa8ef950657bd4e75cb118e9e36237fc43b86 100644
--- a/Framework/WorkflowAlgorithms/src/ConvolutionFitSequential.cpp
+++ b/Framework/WorkflowAlgorithms/src/ConvolutionFitSequential.cpp
@@ -178,8 +178,11 @@ void ConvolutionFitSequential::exec() {
}
outputWsName += backType + "_s";
outputWsName += std::to_string(specMin);
- outputWsName += "_to_";
- outputWsName += std::to_string(specMax);
+
+ if (specMin != specMax) {
+ outputWsName += "_to_";
+ outputWsName += std::to_string(specMax);
+ }
// Convert input workspace to get Q axis
const std::string tempFitWsName = "__convfit_fit_ws";
@@ -346,8 +349,12 @@ void ConvolutionFitSequential::exec() {
Progress renamerProg(this, 0.98, 1.0, specMax + 1);
for (int i = specMin; i < specMax + 1; i++) {
renamer->setProperty("InputWorkspace", groupWsNames.at(i - specMin));
- auto outName = outputWsName + "_";
- outName += std::to_string(i);
+ auto outName = outputWsName;
+
+ // Check if multiple spectrum were fit.
+ if (specMin != specMax) {
+ outName += "_" + std::to_string(i);
+ }
outName += "_Workspace";
renamer->setProperty("OutputWorkspace", outName);
renamer->executeAsChildAlg();
diff --git a/Framework/WorkflowAlgorithms/test/ConvolutionFitSequentialTest.h b/Framework/WorkflowAlgorithms/test/ConvolutionFitSequentialTest.h
index 98a519c364c9fc6b9dc58b6add538eb22e6d946e..f4658eae0a25e4b84a1f8e5a9efed4fa978deb3a 100644
--- a/Framework/WorkflowAlgorithms/test/ConvolutionFitSequentialTest.h
+++ b/Framework/WorkflowAlgorithms/test/ConvolutionFitSequentialTest.h
@@ -234,15 +234,15 @@ public:
// Assert that output is in ADS
TS_ASSERT_THROWS_NOTHING(
AnalysisDataService::Instance().retrieveWS<ITableWorkspace>(
- "SqwWs_conv_1LFixF_s0_to_0_Parameters"));
+ "SqwWs_conv_1LFixF_s0_Parameters"));
TS_ASSERT_THROWS_NOTHING(
AnalysisDataService::Instance().retrieveWS<MatrixWorkspace>(
- "SqwWs_conv_1LFixF_s0_to_0_Result"));
+ "SqwWs_conv_1LFixF_s0_Result"));
TS_ASSERT_THROWS_NOTHING(
AnalysisDataService::Instance().retrieveWS<WorkspaceGroup>(
- "SqwWs_conv_1LFixF_s0_to_0_Workspaces"));
+ "SqwWs_conv_1LFixF_s0_Workspaces"));
AnalysisDataService::Instance().clear();
}
diff --git a/MantidQt/CustomInterfaces/inc/MantidQtCustomInterfaces/Indirect/ConvFit.h b/MantidQt/CustomInterfaces/inc/MantidQtCustomInterfaces/Indirect/ConvFit.h
index 8a740ad624991b49c6b31cf19667e427e9238665..fb21cc26c6d01702e7992ed35642c44e94a0f452 100644
--- a/MantidQt/CustomInterfaces/inc/MantidQtCustomInterfaces/Indirect/ConvFit.h
+++ b/MantidQt/CustomInterfaces/inc/MantidQtCustomInterfaces/Indirect/ConvFit.h
@@ -42,9 +42,9 @@ private slots:
void fixItem();
void unFixItem();
void showTieCheckbox(QString);
+ void sequentialFitComplete(bool error);
void singleFitComplete(bool error);
void fitFunctionSelected(const QString &);
- void algorithmComplete(bool error);
void saveClicked();
void plotClicked();
void plotCurrentPreview();
@@ -73,6 +73,10 @@ private:
void initFABADAOptions();
void showFABADA(bool advanced);
void hideFABADA();
+ Mantid::API::IAlgorithm_sptr sequentialFit(const std::string &specMin,
+ const std::string &specMax,
+ QString &outputWSName);
+ void algorithmComplete(bool error, const QString &outputWSName);
Ui::ConvFit m_uiForm;
QtStringPropertyManager *m_stringManager;
diff --git a/MantidQt/CustomInterfaces/src/Indirect/ConvFit.cpp b/MantidQt/CustomInterfaces/src/Indirect/ConvFit.cpp
index 9b63403d39b1f8cfa2606fe7621748b7a18c438c..b2aa7771878b3aa4247608388244c489a18f3ead 100644
--- a/MantidQt/CustomInterfaces/src/Indirect/ConvFit.cpp
+++ b/MantidQt/CustomInterfaces/src/Indirect/ConvFit.cpp
@@ -279,29 +279,46 @@ void ConvFit::initFABADAOptions() {
*/
void ConvFit::run() {
// Get input from interface
- const auto func = createFunction(m_uiForm.ckTieCentres->isChecked());
- const auto function = std::string(func->asString());
m_runMin = m_uiForm.spSpectraMin->value();
m_runMax = m_uiForm.spSpectraMax->value();
const auto specMin = m_uiForm.spSpectraMin->text().toStdString();
const auto specMax = m_uiForm.spSpectraMax->text().toStdString();
+ auto cfs = sequentialFit(specMin, specMax, m_baseName);
+
+ // Add to batch alg runner and execute
+ m_batchAlgoRunner->addAlgorithm(cfs);
+ connect(m_batchAlgoRunner, SIGNAL(batchComplete(bool)), this,
+ SLOT(sequentialFitComplete(bool)));
+ m_batchAlgoRunner->executeBatchAsync();
+}
+
+IAlgorithm_sptr ConvFit::sequentialFit(const std::string &specMin,
+ const std::string &specMax,
+ QString &outputWSName) {
+ const auto func = createFunction(m_uiForm.ckTieCentres->isChecked());
+ const auto function = std::string(func->asString());
// Construct expected name
- m_baseName = QString::fromStdString(m_cfInputWS->getName());
+ outputWSName = QString::fromStdString(m_cfInputWS->getName());
+
// Remove _red
- const auto cutIndex = m_baseName.lastIndexOf("_");
+ const auto cutIndex = outputWSName.lastIndexOf("_");
if (cutIndex != -1) {
- m_baseName = m_baseName.left(cutIndex + 1);
+ outputWSName = outputWSName.left(cutIndex + 1);
}
+
// Add fit specific suffix
const auto bgType = backgroundString();
const auto fitType = fitTypeString();
- m_baseName += "conv_";
- m_baseName += fitType;
- m_baseName += bgType;
- m_baseName += QString::fromStdString(specMin);
- m_baseName += "_to_";
- m_baseName += QString::fromStdString(specMax);
+ outputWSName += "conv_";
+ outputWSName += fitType;
+ outputWSName += bgType;
+ outputWSName += QString::fromStdString(specMin);
+
+ if (specMin != specMax) {
+ outputWSName += "_to_";
+ outputWSName += QString::fromStdString(specMax);
+ }
// Run ConvolutionFitSequential Algorithm
auto cfs = AlgorithmManager::Instance().create("ConvolutionFitSequential");
@@ -319,13 +336,14 @@ void ConvFit::run() {
minimizerString("$outputname_$wsindex").toStdString());
cfs->setProperty("MaxIterations", static_cast<int>(m_dblManager->value(
m_properties["MaxIterations"])));
- cfs->setProperty("OutputWorkspace", (m_baseName.toStdString() + "_Result"));
+ cfs->setProperty("OutputWorkspace", (outputWSName.toStdString() + "_Result"));
+ return cfs;
+}
- // Add to batch alg runner and execute
- m_batchAlgoRunner->addAlgorithm(cfs);
- connect(m_batchAlgoRunner, SIGNAL(batchComplete(bool)), this,
- SLOT(algorithmComplete(bool)));
- m_batchAlgoRunner->executeBatchAsync();
+void ConvFit::sequentialFitComplete(bool error) {
+ disconnect(m_batchAlgoRunner, SIGNAL(batchComplete(bool)), this,
+ SLOT(sequentialFitComplete(bool)));
+ algorithmComplete(error, m_baseName);
}
/**
@@ -411,20 +429,20 @@ void ConvFit::plotCurrentPreview() {
* Handles completion of the ConvolutionFitSequential algorithm.
*
* @param error True if the algorithm was stopped due to error, false otherwise
+* @param outputWSName The name of the output workspace created from running the
+* algorithm.
*/
-void ConvFit::algorithmComplete(bool error) {
- disconnect(m_batchAlgoRunner, SIGNAL(batchComplete(bool)), this,
- SLOT(algorithmComplete(bool)));
+void ConvFit::algorithmComplete(bool error, const QString &outputWSName) {
if (error)
return;
- const auto resultName = m_baseName.toStdString() + "_Result";
+ const auto resultName = outputWSName.toStdString() + "_Result";
MatrixWorkspace_sptr resultWs =
AnalysisDataService::Instance().retrieveWS<MatrixWorkspace>(resultName);
// Name for GroupWorkspace
- const auto groupName = m_baseName.toStdString() + "_Workspaces";
+ const auto groupName = outputWSName.toStdString() + "_Workspaces";
// Add Sample logs for ResolutionFiles
const auto resFile = m_uiForm.dsResInput->getCurrentDataName().toStdString();
addSampleLogsToWorkspace(resultName, "resolution_filename", resFile,
@@ -1234,46 +1252,9 @@ void ConvFit::singleFit() {
SLOT(singleFit(bool)));
// ensure algorithm was successful
m_uiForm.ckPlotGuess->setChecked(false);
+ std::string specNo = m_uiForm.spPlotSpectrum->text().toStdString();
- CompositeFunction_sptr function =
- createFunction(m_uiForm.ckTieCentres->isChecked());
-
- // get output name
- QString fitType = fitTypeString();
- QString bgType = backgroundString();
-
- if (fitType == "") {
- g_log.error("No fit type defined.");
- }
- m_singleFitOutputName =
- runPythonCode(
- QString(
- "from IndirectCommon import getWSprefix\nprint getWSprefix('") +
- m_cfInputWSName + QString("')\n")).trimmed();
- m_singleFitOutputName +=
- QString("conv_") + fitType + bgType + m_uiForm.spPlotSpectrum->text();
- int maxIterations =
- static_cast<int>(m_dblManager->value(m_properties["MaxIterations"]));
-
- // Run fit algorithm
- m_singleFitAlg = AlgorithmManager::Instance().create("Fit");
- m_singleFitAlg->initialize();
- m_singleFitAlg->setPropertyValue("Function", function->asString());
- m_singleFitAlg->setPropertyValue("InputWorkspace",
- m_cfInputWSName.toStdString());
- m_singleFitAlg->setProperty<int>("WorkspaceIndex",
- m_uiForm.spPlotSpectrum->text().toInt());
- m_singleFitAlg->setProperty<double>(
- "StartX", m_dblManager->value(m_properties["StartX"]));
- m_singleFitAlg->setProperty<double>(
- "EndX", m_dblManager->value(m_properties["EndX"]));
- m_singleFitAlg->setProperty("Output", m_singleFitOutputName.toStdString());
- m_singleFitAlg->setProperty("CreateOutput", true);
- m_singleFitAlg->setProperty("OutputCompositeMembers", true);
- m_singleFitAlg->setProperty("ConvolveMembers", true);
- m_singleFitAlg->setProperty("MaxIterations", maxIterations);
- m_singleFitAlg->setProperty(
- "Minimizer", minimizerString(m_singleFitOutputName).toStdString());
+ m_singleFitAlg = sequentialFit(specNo, specNo, m_singleFitOutputName);
// Connection to singleFitComplete SLOT (post algorithm completion)
m_batchAlgoRunner->addAlgorithm(m_singleFitAlg);
@@ -1291,117 +1272,7 @@ void ConvFit::singleFitComplete(bool error) {
// Disconnect signal for single fit complete
disconnect(m_batchAlgoRunner, SIGNAL(batchComplete(bool)), this,
SLOT(singleFitComplete(bool)));
-
- if (error) {
- showMessageBox("Fit algorithm failed.");
- return;
- }
-
- // Plot the line on the mini plot
- m_uiForm.ppPlot->removeSpectrum("Guess");
- const auto resultName = m_singleFitOutputName + "_Workspace";
- m_previewPlotData =
- AnalysisDataService::Instance().retrieveWS<MatrixWorkspace>(
- resultName.toStdString());
- m_uiForm.ppPlot->addSpectrum("Fit", resultName, 1, Qt::red);
- m_uiForm.ppPlot->addSpectrum("Diff", resultName, 2, Qt::blue);
-
- IFunction_const_sptr outputFunc = m_singleFitAlg->getProperty("Function");
-
- QString functionName = m_uiForm.cbFitType->currentText();
-
- // Get params.
- QMap<QString, double> parameters;
- const std::vector<std::string> parNames = outputFunc->getParameterNames();
- std::vector<double> parVals;
-
- QStringList params = getFunctionParameters(functionName);
- params.reserve(static_cast<int>(parNames.size()));
-
- for (size_t i = 0; i < parNames.size(); ++i)
- parVals.push_back(outputFunc->getParameter(parNames[i]));
-
- for (size_t i = 0; i < parNames.size(); ++i)
- parameters[QString(parNames[i].c_str())] = parVals[i];
-
- // Populate Tree widget with values
- // Background should always be f0
- m_dblManager->setValue(m_properties["BGA0"], parameters["f0.A0"]);
- m_dblManager->setValue(m_properties["BGA1"], parameters["f0.A1"]);
-
- const int fitTypeIndex = m_uiForm.cbFitType->currentIndex();
-
- int funcIndex = 0;
- int subIndex = 0;
-
- // check if we're using a temperature correction
- if (m_uiForm.ckTempCorrection->isChecked() &&
- !m_uiForm.leTempCorrection->text().isEmpty()) {
- subIndex++;
- }
-
- const bool usingDeltaFunc = m_blnManager->value(m_properties["UseDeltaFunc"]);
-
- // If using a delta function with any fit type or using two Lorentzians
- const bool usingCompositeFunc =
- ((usingDeltaFunc && fitTypeIndex > 0) || fitTypeIndex == 2);
-
- const QString prefBase = "f1.f1.";
-
- if (usingDeltaFunc) {
- QString key = prefBase;
- if (usingCompositeFunc) {
- key += "f0.";
- }
-
- m_dblManager->setValue(m_properties["DeltaHeight"],
- parameters[key + "Height"]);
- m_dblManager->setValue(m_properties["DeltaCentre"],
- parameters[key + "Centre"]);
- funcIndex++;
- }
-
- QString pref = prefBase;
-
- if (usingCompositeFunc) {
- pref += "f" + QString::number(funcIndex) + ".f" +
- QString::number(subIndex) + ".";
- } else {
- pref += "f" + QString::number(subIndex) + ".";
- }
-
- if (fitTypeIndex == 2) {
- functionName = "Lorentzian 1";
- for (auto it = params.begin(); it != params.end() - 3; ++it) {
- const QString functionParam = functionName + "." + *it;
- const QString paramValue = pref + *it;
- m_dblManager->setValue(m_properties[functionParam],
- parameters[paramValue]);
- }
- funcIndex++;
- pref = prefBase;
- pref += "f" + QString::number(funcIndex) + ".f" +
- QString::number(subIndex) + ".";
-
- functionName = "Lorentzian 2";
-
- for (auto it = params.begin() + 3; it != params.end(); ++it) {
- const QString functionParam = functionName + "." + *it;
- const QString paramValue = pref + *it;
- m_dblManager->setValue(m_properties[functionParam],
- parameters[paramValue]);
- }
-
- } else {
- for (auto it = params.begin(); it != params.end(); ++it) {
- const QString functionParam = functionName + "." + *it;
- const QString paramValue = pref + *it;
- m_dblManager->setValue(m_properties[functionParam],
- parameters[paramValue]);
- }
- }
-
- m_pythonExportWsName = "";
+ algorithmComplete(error, m_singleFitOutputName);
}
/**
diff --git a/docs/source/release/v3.11.0/indirect_inelastic.rst b/docs/source/release/v3.11.0/indirect_inelastic.rst
index 20a580a73e0fb3f7dd851066a391ae2fafb05eb9..78794c8dcecefc699dd6b5ea2f1765ebd60b63be 100644
--- a/docs/source/release/v3.11.0/indirect_inelastic.rst
+++ b/docs/source/release/v3.11.0/indirect_inelastic.rst
@@ -26,6 +26,7 @@ Jump Fit
Improvements
------------
- The *S(Q, W)* interface now automatically replaces NaN values with 0.
+- EISF is now generated when performing a Single Fit, with a delta function, in the ConvFit interface.
- :ref:`FlatPlatePaalmanPingsCorrection <algm-FlatPlatePaalmanPingsCorrection>` now supports `Direct` and `Indirect` modes.