diff --git a/Framework/API/inc/MantidAPI/ExperimentInfo.h b/Framework/API/inc/MantidAPI/ExperimentInfo.h
index f31cba3a94c58fd2c9fc117d937d649ae31e7486..04a28cd65fee13843f52eb0dcf894653c7a0673b 100644
--- a/Framework/API/inc/MantidAPI/ExperimentInfo.h
+++ b/Framework/API/inc/MantidAPI/ExperimentInfo.h
@@ -104,6 +104,8 @@ public:
const Run &run() const;
/// Writable version of the run object
Run &mutableRun();
+ void setSharedRun(Kernel::cow_ptr<Run> run);
+
/// Access a log for this experiment.
Kernel::Property *getLog(const std::string &log) const;
/// Access a single value from a log for this experiment.
@@ -187,10 +189,6 @@ protected:
boost::shared_ptr<ModeratorModel> m_moderatorModel;
/// Description of the choppers for this experiment.
std::list<boost::shared_ptr<ChopperModel>> m_choppers;
- /// The information on the sample environment
- boost::shared_ptr<Sample> m_sample;
- /// The run information
- boost::shared_ptr<Run> m_run;
/// Parameters modifying the base instrument
boost::shared_ptr<Geometry::ParameterMap> m_parmap;
/// The base (unparametrized) instrument
@@ -218,15 +216,18 @@ private:
// Loads the xml from an instrument file with some basic error handling
std::string loadInstrumentXML(const std::string &filename);
+
+ /// The information on the sample environment
+ Kernel::cow_ptr<Sample> m_sample;
+ /// The run information
+ Kernel::cow_ptr<Run> m_run;
+
/// Detector grouping information
mutable std::unordered_map<detid_t, size_t> m_det2group;
void cacheDefaultDetectorGrouping() const; // Not thread-safe
void invalidateAllSpectrumDefinitions();
mutable std::once_flag m_defaultDetectorGroupingCached;
- /// Mutex to protect against cow_ptr copying
- mutable std::recursive_mutex m_mutex;
-
mutable std::unique_ptr<Beamline::SpectrumInfo> m_spectrumInfo;
mutable std::unique_ptr<SpectrumInfo> m_spectrumInfoWrapper;
mutable std::mutex m_spectrumInfoMutex;
diff --git a/Framework/API/inc/MantidAPI/WorkspaceFactory.h b/Framework/API/inc/MantidAPI/WorkspaceFactory.h
index 4afc17aa358bb398ec64bb7098878ca9c4b18550..75d1b95df77630b56343a5b79360b1677fa5e8b6 100644
--- a/Framework/API/inc/MantidAPI/WorkspaceFactory.h
+++ b/Framework/API/inc/MantidAPI/WorkspaceFactory.h
@@ -82,10 +82,6 @@ public:
MatrixWorkspace &child,
const bool differentSize) const;
- void initializeFromParentWithoutLogs(const MatrixWorkspace &parent,
- MatrixWorkspace &child,
- const bool differentSize) const;
-
/// Create a ITableWorkspace
boost::shared_ptr<ITableWorkspace>
createTable(const std::string &className = "TableWorkspace") const;
diff --git a/Framework/API/src/ExperimentInfo.cpp b/Framework/API/src/ExperimentInfo.cpp
index aad114140a74c02c5f3d0f3b7556509f6e6f6b48..3eb512910b36fe4eb1418b035d51e54ae03edf13 100644
--- a/Framework/API/src/ExperimentInfo.cpp
+++ b/Framework/API/src/ExperimentInfo.cpp
@@ -66,8 +66,7 @@ Kernel::Logger g_log("ExperimentInfo");
/** Constructor
*/
ExperimentInfo::ExperimentInfo()
- : m_moderatorModel(), m_choppers(), m_sample(new Sample()),
- m_run(new Run()), m_parmap(new ParameterMap()),
+ : m_moderatorModel(), m_choppers(), m_parmap(new ParameterMap()),
sptr_instrument(new Instrument()) {
m_parmap->setInstrument(sptr_instrument.get());
}
@@ -91,7 +90,7 @@ ExperimentInfo::~ExperimentInfo() = default;
*/
void ExperimentInfo::copyExperimentInfoFrom(const ExperimentInfo *other) {
m_sample = other->m_sample;
- m_run = other->m_run->clone();
+ m_run = other->m_run;
this->setInstrument(other->getInstrument());
if (other->m_moderatorModel)
m_moderatorModel = other->m_moderatorModel->clone();
@@ -602,30 +601,17 @@ ChopperModel &ExperimentInfo::chopperModel(const size_t index) const {
*/
const Sample &ExperimentInfo::sample() const {
populateIfNotLoaded();
- std::lock_guard<std::recursive_mutex> lock(m_mutex);
return *m_sample;
}
/** Get a reference to the Sample associated with this workspace.
* This non-const method will copy the sample if it is shared between
* more than one workspace, and the reference returned will be to the copy.
-* Can ONLY be taken by reference!
* @return reference to sample object
*/
Sample &ExperimentInfo::mutableSample() {
populateIfNotLoaded();
- // Use a double-check for sharing so that we only
- // enter the critical region if absolutely necessary
- if (!m_sample.unique()) {
- std::lock_guard<std::recursive_mutex> lock(m_mutex);
- // Check again because another thread may have taken copy
- // and dropped reference count since previous check
- if (!m_sample.unique()) {
- boost::shared_ptr<Sample> oldData = m_sample;
- m_sample = boost::make_shared<Sample>(*oldData);
- }
- }
- return *m_sample;
+ return m_sample.access();
}
/** Get a constant reference to the Run object associated with this workspace.
@@ -633,30 +619,22 @@ Sample &ExperimentInfo::mutableSample() {
*/
const Run &ExperimentInfo::run() const {
populateIfNotLoaded();
- std::lock_guard<std::recursive_mutex> lock(m_mutex);
return *m_run;
}
/** Get a reference to the Run object associated with this workspace.
* This non-const method will copy the Run object if it is shared between
* more than one workspace, and the reference returned will be to the copy.
-* Can ONLY be taken by reference!
* @return reference to Run object
*/
Run &ExperimentInfo::mutableRun() {
populateIfNotLoaded();
- // Use a double-check for sharing so that we only
- // enter the critical region if absolutely necessary
- if (!m_run.unique()) {
- std::lock_guard<std::recursive_mutex> lock(m_mutex);
- // Check again because another thread may have taken copy
- // and dropped reference count since previous check
- if (!m_run.unique()) {
- boost::shared_ptr<Run> oldData = m_run;
- m_run = boost::make_shared<Run>(*oldData);
- }
- }
- return *m_run;
+ return m_run.access();
+}
+
+/// Set the run object. Use in particular to clear run without copying old run.
+void ExperimentInfo::setSharedRun(Kernel::cow_ptr<Run> run) {
+ m_run = std::move(run);
}
/**
diff --git a/Framework/API/src/WorkspaceFactory.cpp b/Framework/API/src/WorkspaceFactory.cpp
index 3f29b9c437032a8e04ffd6246cd999831e9bc021..88525dfa5d5b01926b840b8c6e748effe8e890b0 100644
--- a/Framework/API/src/WorkspaceFactory.cpp
+++ b/Framework/API/src/WorkspaceFactory.cpp
@@ -78,29 +78,20 @@ WorkspaceFactoryImpl::create(const MatrixWorkspace_const_sptr &parent,
}
/** Initialize a workspace from its parent
- * This sets values such as instrument, units, sample, spectramap.
+ * This sets values such as title, instrument, units, sample, spectramap.
* This does NOT copy any data.
- * This does NOT copy any sample logs, i.e., Run object of the workspace won't
- * be copied
- * from its parent.
- * @brief WorkspaceFactoryImpl::initializeFromParentWithoutLogs
- * @param parent
- * @param child
- * @param differentSize
+ *
+ * @param parent :: the parent workspace
+ * @param child :: the child workspace
+ * @param differentSize :: A flag to indicate if the two workspace will be
+ *different sizes
*/
-void WorkspaceFactoryImpl::initializeFromParentWithoutLogs(
+void WorkspaceFactoryImpl::initializeFromParent(
const MatrixWorkspace &parent, MatrixWorkspace &child,
const bool differentSize) const {
child.setTitle(parent.getTitle());
child.setComment(parent.getComment());
- child.setInstrument(parent.getInstrument()); // This call also copies the
- // SHARED POINTER to the
- // parameter map
-
- // This call will (should) perform a COPY of the parameter map.
- child.instrumentParameters();
- child.m_sample = parent.m_sample;
- child.m_run = boost::make_shared<API::Run>();
+ child.copyExperimentInfoFrom(&parent);
child.setYUnit(parent.m_YUnit);
child.setYUnitLabel(parent.m_YUnitLabel);
child.setDistribution(parent.isDistribution());
@@ -144,22 +135,6 @@ void WorkspaceFactoryImpl::initializeFromParentWithoutLogs(
}
}
-/** Initialize a workspace from its parent
- * This sets values such as title, instrument, units, sample, spectramap.
- * This does NOT copy any data.
- *
- * @param parent :: the parent workspace
- * @param child :: the child workspace
- * @param differentSize :: A flag to indicate if the two workspace will be
- *different sizes
- */
-void WorkspaceFactoryImpl::initializeFromParent(
- const MatrixWorkspace &parent, MatrixWorkspace &child,
- const bool differentSize) const {
- initializeFromParentWithoutLogs(parent, child, differentSize);
- child.m_run = parent.m_run;
-}
-
/** Creates a new instance of the class with the given name, and allocates
* memory for the arrays
* @param className The name of the class you wish to create
diff --git a/Framework/Algorithms/src/CropToComponent.cpp b/Framework/Algorithms/src/CropToComponent.cpp
index 239cb9e95d8181babd577311dacbe786b7da90a9..42d0b5b62483a5d7a7bf11c9fcf29f5364435095 100644
--- a/Framework/Algorithms/src/CropToComponent.cpp
+++ b/Framework/Algorithms/src/CropToComponent.cpp
@@ -1,45 +1,27 @@
#include "MantidAPI/AlgorithmManager.h"
#include "MantidAPI/MatrixWorkspace.h"
#include "MantidAlgorithms/CropToComponent.h"
-#include "MantidGeometry/IDetector.h"
#include "MantidGeometry/Instrument.h"
+#include "MantidGeometry/Instrument/ComponentInfo.h"
#include "MantidKernel/ArrayProperty.h"
+#include "MantidIndexing/Conversion.h"
+#include "MantidIndexing/GlobalSpectrumIndex.h"
+#include "MantidIndexing/IndexInfo.h"
namespace {
-
-void getDetectors(
- Mantid::API::MatrixWorkspace_sptr workspace,
- const std::vector<std::string> &componentNames,
- std::vector<Mantid::Geometry::IDetector_const_sptr> &detectors) {
- auto instrument = workspace->getInstrument();
+std::vector<size_t>
+getDetectorIndices(const Mantid::API::MatrixWorkspace &workspace,
+ const std::vector<std::string> &componentNames) {
+ const auto &compInfo = workspace.componentInfo();
+ const auto instrument = workspace.getInstrument();
+ std::vector<size_t> detIndices;
for (const auto &componentName : componentNames) {
- instrument->getDetectorsInBank(detectors, componentName);
- }
-}
-
-void getWorkspaceIndices(
- Mantid::API::MatrixWorkspace_sptr workspace,
- std::vector<Mantid::Geometry::IDetector_const_sptr> &detectors,
- std::vector<size_t> &workspaceIndices) {
- const auto numberOfDetectors = static_cast<int>(detectors.size());
- std::vector<Mantid::detid_t> detectorIds(numberOfDetectors);
-
- PARALLEL_FOR_NO_WSP_CHECK()
- for (int index = 0; index < numberOfDetectors; ++index) {
- auto det = detectors[index];
- detectorIds[index] = det->getID();
+ const auto comp = instrument->getComponentByName(componentName);
+ const auto compIndex = compInfo.indexOf(comp->getComponentID());
+ const auto indices = compInfo.detectorsInSubtree(compIndex);
+ detIndices.insert(detIndices.end(), indices.begin(), indices.end());
}
-
- // Get the corresponding workspace indices
- auto detIdToWorkspaceIndexMap =
- workspace->getDetectorIDToWorkspaceIndexMap(true);
- PARALLEL_FOR_NO_WSP_CHECK()
- for (int index = 0; index < numberOfDetectors; ++index) {
- workspaceIndices[index] = detIdToWorkspaceIndexMap[detectorIds[index]];
- }
-
- // Sort the workspace indices
- std::sort(workspaceIndices.begin(), workspaceIndices.end());
+ return detIndices;
}
}
@@ -99,12 +81,13 @@ void CropToComponent::exec() {
getProperty("InputWorkspace");
// Get all detectors
- std::vector<Mantid::Geometry::IDetector_const_sptr> detectors;
- getDetectors(inputWorkspace, componentNames, detectors);
+ const auto &detectorIndices =
+ getDetectorIndices(*inputWorkspace, componentNames);
// Get the corresponding workspace indices from the detectors
- std::vector<size_t> workspaceIndices(detectors.size());
- getWorkspaceIndices(inputWorkspace, detectors, workspaceIndices);
+ const auto &workspaceIndices =
+ inputWorkspace->indexInfo().globalSpectrumIndicesFromDetectorIndices(
+ detectorIndices);
// Run ExtractSpectra in order to obtain the cropped workspace
auto extract_alg = Mantid::API::AlgorithmManager::Instance().createUnmanaged(
@@ -113,7 +96,8 @@ void CropToComponent::exec() {
extract_alg->initialize();
extract_alg->setProperty("InputWorkspace", inputWorkspace);
extract_alg->setProperty("OutputWorkspace", "dummy");
- extract_alg->setProperty("WorkspaceIndexList", workspaceIndices);
+ extract_alg->setProperty("WorkspaceIndexList",
+ Indexing::castVector<size_t>(workspaceIndices));
extract_alg->execute();
Mantid::API::MatrixWorkspace_sptr outputWorkspace =
extract_alg->getProperty("OutputWorkspace");
diff --git a/Framework/Algorithms/src/FilterEvents.cpp b/Framework/Algorithms/src/FilterEvents.cpp
index 936759f7cd0cd4699be40d6da404bf941cc301b1..d92c13eaeaac35f67096b5c0968f56bfc1083a58 100644
--- a/Framework/Algorithms/src/FilterEvents.cpp
+++ b/Framework/Algorithms/src/FilterEvents.cpp
@@ -1092,7 +1092,9 @@ void FilterEvents::createOutputWorkspaces() {
}
boost::shared_ptr<EventWorkspace> optws =
- createWithoutLogs<DataObjects::EventWorkspace>(*m_eventWS);
+ create<EventWorkspace>(*m_eventWS);
+ // Clear Run without copying first.
+ optws->setSharedRun(Kernel::make_cow<Run>());
m_outputWorkspacesMap.emplace(wsgroup, optws);
// Add information, including title and comment, to output workspace
@@ -1202,7 +1204,9 @@ void FilterEvents::createOutputWorkspacesMatrixCase() {
// create new workspace from input EventWorkspace and all the sample logs
// are copied to the new one
boost::shared_ptr<EventWorkspace> optws =
- createWithoutLogs<DataObjects::EventWorkspace>(*m_eventWS);
+ create<EventWorkspace>(*m_eventWS);
+ // Clear Run without copying first.
+ optws->setSharedRun(Kernel::make_cow<Run>());
m_outputWorkspacesMap.emplace(wsgroup, optws);
// TODO/ISSUE/NOW - How about comment and info similar to
@@ -1292,7 +1296,9 @@ void FilterEvents::createOutputWorkspacesTableSplitterCase() {
// create new workspace
boost::shared_ptr<EventWorkspace> optws =
- createWithoutLogs<DataObjects::EventWorkspace>(*m_eventWS);
+ create<EventWorkspace>(*m_eventWS);
+ // Clear Run without copying first.
+ optws->setSharedRun(Kernel::make_cow<Run>());
m_outputWorkspacesMap.emplace(wsgroup, optws);
// TODO/NOW/ISSUE -- How about comment and info?
diff --git a/Framework/Algorithms/test/CropToComponentTest.h b/Framework/Algorithms/test/CropToComponentTest.h
index 7fe5592e554f0ca84fba0bbaf88ba2239366a945..7f3f1d58e7d5d457cbb8857c466499963f11aa01 100644
--- a/Framework/Algorithms/test/CropToComponentTest.h
+++ b/Framework/Algorithms/test/CropToComponentTest.h
@@ -91,6 +91,9 @@ public:
auto inputWorkspace =
getSampleWorkspace(numberOfBanks, numberOfPixelsPerBank);
std::vector<std::string> componentNames = {"bank3"};
+ // Clearing some IDs in bank2 should not cause issues, compare
+ // test_throws_if_no_spectrum_for_detector.
+ inputWorkspace->getSpectrum(9).clearDetectorIDs();
// Act
Mantid::Algorithms::CropToComponent crop;
@@ -110,6 +113,29 @@ public:
std::iota(expectedIDs.begin(), expectedIDs.end(), 27);
}
+ void test_throws_if_no_spectrum_for_detector() {
+ // Arrange
+ int numberOfBanks = 4;
+ int numberOfPixelsPerBank = 3;
+
+ auto inputWorkspace =
+ getSampleWorkspace(numberOfBanks, numberOfPixelsPerBank);
+ std::vector<std::string> componentNames = {"bank3"};
+ // Clear some IDs in bank3.
+ inputWorkspace->getSpectrum(18).clearDetectorIDs();
+
+ // Act
+ Mantid::Algorithms::CropToComponent crop;
+ crop.setChild(true);
+ crop.initialize();
+ crop.setProperty("InputWorkspace", inputWorkspace);
+ crop.setProperty("OutputWorkspace", "dummy");
+ crop.setProperty("ComponentNames", componentNames);
+ TS_ASSERT_THROWS_EQUALS(
+ crop.execute(), const std::runtime_error &e, std::string(e.what()),
+ "Some of the requested detectors do not have a corresponding spectrum");
+ }
+
void test_that_incorrect_component_name_is_not_accepeted() {
// Arrange
int numberOfBanks = 4;
diff --git a/Framework/CurveFitting/CMakeLists.txt b/Framework/CurveFitting/CMakeLists.txt
index 154f38ab4e310a0482a1541e4fd09ac1d4e0020c..18aa84dbcfa919e253f8369bb664e7b6643adedf 100644
--- a/Framework/CurveFitting/CMakeLists.txt
+++ b/Framework/CurveFitting/CMakeLists.txt
@@ -32,14 +32,12 @@ set ( SRC_FILES
src/CostFunctions/CostFuncUnweightedLeastSquares.cpp
src/FitMW.cpp
src/FuncMinimizers/BFGS_Minimizer.cpp
- src/FuncMinimizers/DTRSMinimizer.cpp
src/FuncMinimizers/DampedGaussNewtonMinimizer.cpp
src/FuncMinimizers/DerivMinimizer.cpp
src/FuncMinimizers/FABADAMinimizer.cpp
src/FuncMinimizers/FRConjugateGradientMinimizer.cpp
src/FuncMinimizers/LevenbergMarquardtMDMinimizer.cpp
src/FuncMinimizers/LevenbergMarquardtMinimizer.cpp
- src/FuncMinimizers/MoreSorensenMinimizer.cpp
src/FuncMinimizers/PRConjugateGradientMinimizer.cpp
src/FuncMinimizers/SimplexMinimizer.cpp
src/FuncMinimizers/SteepestDescentMinimizer.cpp
@@ -196,14 +194,12 @@ set ( INC_FILES
inc/MantidCurveFitting/FortranMatrix.h
inc/MantidCurveFitting/FortranVector.h
inc/MantidCurveFitting/FuncMinimizers/BFGS_Minimizer.h
- inc/MantidCurveFitting/FuncMinimizers/DTRSMinimizer.h
inc/MantidCurveFitting/FuncMinimizers/DampedGaussNewtonMinimizer.h
inc/MantidCurveFitting/FuncMinimizers/DerivMinimizer.h
inc/MantidCurveFitting/FuncMinimizers/FABADAMinimizer.h
inc/MantidCurveFitting/FuncMinimizers/FRConjugateGradientMinimizer.h
inc/MantidCurveFitting/FuncMinimizers/LevenbergMarquardtMDMinimizer.h
inc/MantidCurveFitting/FuncMinimizers/LevenbergMarquardtMinimizer.h
- inc/MantidCurveFitting/FuncMinimizers/MoreSorensenMinimizer.h
inc/MantidCurveFitting/FuncMinimizers/PRConjugateGradientMinimizer.h
inc/MantidCurveFitting/FuncMinimizers/SimplexMinimizer.h
inc/MantidCurveFitting/FuncMinimizers/SteepestDescentMinimizer.h
@@ -356,16 +352,15 @@ set ( TEST_FILES
FortranMatrixTest.h
FortranVectorTest.h
FuncMinimizers/BFGSTest.h
- FuncMinimizers/DTRSMinimizerTest.h
FuncMinimizers/DampedGaussNewtonMinimizerTest.h
FuncMinimizers/ErrorMessagesTest.h
FuncMinimizers/FABADAMinimizerTest.h
FuncMinimizers/FRConjugateGradientTest.h
FuncMinimizers/LevenbergMarquardtMDTest.h
FuncMinimizers/LevenbergMarquardtTest.h
- FuncMinimizers/MoreSorensenTest.h
FuncMinimizers/PRConjugateGradientTest.h
FuncMinimizers/SimplexTest.h
+ FuncMinimizers/TrustRegionMinimizerTest.h
FunctionDomain1DSpectrumCreatorTest.h
FunctionFactoryConstraintTest.h
FunctionParameterDecoratorFitTest.h
diff --git a/Framework/CurveFitting/inc/MantidCurveFitting/FuncMinimizers/DTRSMinimizer.h b/Framework/CurveFitting/inc/MantidCurveFitting/FuncMinimizers/DTRSMinimizer.h
deleted file mode 100644
index d0e9051cc3f5ce461583ce896a2de9ed42e67d8e..0000000000000000000000000000000000000000
--- a/Framework/CurveFitting/inc/MantidCurveFitting/FuncMinimizers/DTRSMinimizer.h
+++ /dev/null
@@ -1,63 +0,0 @@
-#ifndef MANTID_CURVEFITTING_DTRSMINIMIZER_H_
-#define MANTID_CURVEFITTING_DTRSMINIMIZER_H_
-
-#include "MantidCurveFitting/FuncMinimizers/TrustRegionMinimizer.h"
-
-namespace Mantid {
-namespace CurveFitting {
-namespace FuncMinimisers {
-
-/** A GALAHAD trust region minimizer.
-
- Copyright © 2009 ISIS Rutherford Appleton Laboratory, NScD Oak Ridge
- National Laboratory & European Spallation Source
-
- This file is part of Mantid.
-
- Mantid is free software; you can redistribute it and/or modify
- it under the terms of the GNU General Public License as published by
- the Free Software Foundation; either version 3 of the License, or
- (at your option) any later version.
-
- Mantid is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU General Public License for more details.
-
- You should have received a copy of the GNU General Public License
- along with this program. If not, see <http://www.gnu.org/licenses/>.
-
- File change history is stored at: <https://github.com/mantidproject/mantid>.
- Code Documentation is available at: <http://doxygen.mantidproject.org>
-*/
-class DLLExport DTRSMinimizer : public TrustRegionMinimizer {
-public:
- /// constructor and destructor
- DTRSMinimizer();
- /// Name of the minimizer.
- std::string name() const override;
-
-private:
- void calculateStep(const DoubleFortranMatrix &J, const DoubleFortranVector &f,
- const DoubleFortranMatrix &hf,
- const DoubleFortranVector &g, double Delta,
- DoubleFortranVector &d, double &normd,
- const NLLS::nlls_options &options) override;
-
- void solveDtrs(const DoubleFortranMatrix &J, const DoubleFortranVector &f,
- const DoubleFortranMatrix &hf, double Delta,
- DoubleFortranVector &d, double &normd,
- const NLLS::nlls_options &options);
-
- // Used for calculating step
- DoubleFortranMatrix m_A, m_ev;
- DoubleFortranVector m_ew, m_v, m_v_trans, m_d_trans;
- NLLS::all_eig_symm_work m_all_eig_symm_ws;
- DoubleFortranVector m_scale;
-};
-
-} // namespace FuncMinimisers
-} // namespace CurveFitting
-} // namespace Mantid
-
-#endif /*MANTID_CURVEFITTING_DTRSMINIMIZER_H_*/
diff --git a/Framework/CurveFitting/inc/MantidCurveFitting/FuncMinimizers/MoreSorensenMinimizer.h b/Framework/CurveFitting/inc/MantidCurveFitting/FuncMinimizers/MoreSorensenMinimizer.h
deleted file mode 100644
index 63bddd5fea8f084195d37795b35779ed2b4f4615..0000000000000000000000000000000000000000
--- a/Framework/CurveFitting/inc/MantidCurveFitting/FuncMinimizers/MoreSorensenMinimizer.h
+++ /dev/null
@@ -1,70 +0,0 @@
-#ifndef MANTID_CURVEFITTING_MORESORENSENMINIMIZER_H_
-#define MANTID_CURVEFITTING_MORESORENSENMINIMIZER_H_
-
-//----------------------------------------------------------------------
-// Includes
-//----------------------------------------------------------------------
-#include "MantidCurveFitting/FuncMinimizers/TrustRegionMinimizer.h"
-
-namespace Mantid {
-namespace CurveFitting {
-namespace FuncMinimisers {
-
-/** A More-Sorensen trust region minimizer.
-
- Copyright © 2009 ISIS Rutherford Appleton Laboratory, NScD Oak Ridge
- National Laboratory & European Spallation Source
-
- This file is part of Mantid.
-
- Mantid is free software; you can redistribute it and/or modify
- it under the terms of the GNU General Public License as published by
- the Free Software Foundation; either version 3 of the License, or
- (at your option) any later version.
-
- Mantid is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU General Public License for more details.
-
- You should have received a copy of the GNU General Public License
- along with this program. If not, see <http://www.gnu.org/licenses/>.
-
- File change history is stored at: <https://github.com/mantidproject/mantid>.
- Code Documentation is available at: <http://doxygen.mantidproject.org>
-*/
-class DLLExport MoreSorensenMinimizer : public TrustRegionMinimizer {
-public:
- /// constructor and destructor
- MoreSorensenMinimizer();
- /// Name of the minimizer.
- std::string name() const override;
-
-private:
- void calculateStep(const DoubleFortranMatrix &J, const DoubleFortranVector &f,
- const DoubleFortranMatrix &hf,
- const DoubleFortranVector &g, double Delta,
- DoubleFortranVector &d, double &normd,
- const NLLS::nlls_options &options) override;
-
- void solveSubproblem(const DoubleFortranMatrix &J,
- const DoubleFortranVector &f,
- const DoubleFortranMatrix &hf, double Delta,
- DoubleFortranVector &d, double &nd,
- const NLLS::nlls_options &options);
-
- bool getPdShift(double &sigma, DoubleFortranVector &d,
- const NLLS::nlls_options &options);
-
- // Used for calculating step
- DoubleFortranMatrix m_A, m_LtL, m_AplusSigma;
- DoubleFortranVector m_v, m_q, m_y1;
- NLLS::min_eig_symm_work m_min_eig_symm_ws;
- DoubleFortranVector m_scale;
-};
-
-} // namespace FuncMinimisers
-} // namespace CurveFitting
-} // namespace Mantid
-
-#endif /*MANTID_CURVEFITTING_MORESORENSENMINIMIZER_H_*/
diff --git a/Framework/CurveFitting/inc/MantidCurveFitting/FuncMinimizers/TrustRegionMinimizer.h b/Framework/CurveFitting/inc/MantidCurveFitting/FuncMinimizers/TrustRegionMinimizer.h
index 753bd294192d6f29fdf85aba9ba54219b1077f20..f971fe2e1b7a2ebe11d374b1556ad5e602bc3ac3 100644
--- a/Framework/CurveFitting/inc/MantidCurveFitting/FuncMinimizers/TrustRegionMinimizer.h
+++ b/Framework/CurveFitting/inc/MantidCurveFitting/FuncMinimizers/TrustRegionMinimizer.h
@@ -14,7 +14,7 @@
namespace Mantid {
namespace CurveFitting {
namespace FuncMinimisers {
-/** A base class for least squares trust region minimizers.
+/** Trust Region minimizer class using the DTRS method of GALAHAD.
Copyright © 2009 ISIS Rutherford Appleton Laboratory, NScD Oak Ridge
National Laboratory & European Spallation Source
@@ -48,6 +48,8 @@ public:
bool iterate(size_t) override;
/// Return current value of the cost function
double costFunctionVal() override;
+ /// Name of the minimizer.
+ std::string name() const override;
private:
/// Evaluate the fitting function and calculate the residuals.
@@ -58,12 +60,10 @@ private:
void evalHF(const DoubleFortranVector &x, const DoubleFortranVector &f,
DoubleFortranMatrix &h) const;
/// Find a correction vector to the parameters.
- virtual void calculateStep(const DoubleFortranMatrix &J,
- const DoubleFortranVector &f,
- const DoubleFortranMatrix &hf,
- const DoubleFortranVector &g, double Delta,
- DoubleFortranVector &d, double &normd,
- const NLLS::nlls_options &options) = 0;
+ void calculateStep(const DoubleFortranMatrix &J, const DoubleFortranVector &f,
+ const DoubleFortranMatrix &hf, double Delta,
+ DoubleFortranVector &d, double &normd,
+ const NLLS::nlls_options &options);
/// Stored cost function
boost::shared_ptr<CostFunctions::CostFuncLeastSquares> m_leastSquares;
@@ -81,6 +81,12 @@ private:
NLLS::nlls_inform m_inform;
/// Temporary and helper objects
NLLS::NLLS_workspace m_workspace;
+
+ // Used for calculating step in DTRS method
+ DoubleFortranMatrix m_A, m_ev;
+ DoubleFortranVector m_ew, m_v, m_v_trans, m_d_trans;
+ NLLS::all_eig_symm_work m_all_eig_symm_ws;
+ DoubleFortranVector m_scale;
};
} // namespace FuncMinimisers
diff --git a/Framework/CurveFitting/src/FuncMinimizers/DTRSMinimizer.cpp b/Framework/CurveFitting/src/FuncMinimizers/DTRSMinimizer.cpp
deleted file mode 100644
index b2841bb337973c2bda5d657f514f6cd5ebe998c6..0000000000000000000000000000000000000000
--- a/Framework/CurveFitting/src/FuncMinimizers/DTRSMinimizer.cpp
+++ /dev/null
@@ -1,1005 +0,0 @@
-// This code was originally translated from Fortran code on
-// https://ccpforge.cse.rl.ac.uk/gf/project/ral_nlls June 2016
-//----------------------------------------------------------------------
-// Includes
-//----------------------------------------------------------------------
-#include "MantidCurveFitting/FuncMinimizers/DTRSMinimizer.h"
-#include "MantidCurveFitting/RalNlls/TrustRegion.h"
-#include "MantidAPI/FuncMinimizerFactory.h"
-
-#include <algorithm>
-#include <limits>
-
-namespace Mantid {
-namespace CurveFitting {
-namespace FuncMinimisers {
-
-// clang-format off
-///@cond nodoc
-DECLARE_FUNCMINIMIZER(DTRSMinimizer, Trust Region)
-///@endcond
-// clang-format on
-
-DTRSMinimizer::DTRSMinimizer() : TrustRegionMinimizer() {}
-
-/** Name of the minimizer.
- */
-std::string DTRSMinimizer::name() const { return "Trust Region"; }
-
-namespace {
-
-const double HUGEST = std::numeric_limits<double>::max();
-const double EPSILON_MCH = std::numeric_limits<double>::epsilon();
-const double LARGEST = HUGEST;
-const double LOWER_DEFAULT = -0.5 * LARGEST;
-const double UPPER_DEFAULT = LARGEST;
-const double POINT4 = 0.4;
-const double ZERO = 0.0;
-const double ONE = 1.0;
-const double TWO = 2.0;
-const double THREE = 3.0;
-const double FOUR = 4.0;
-const double SIX = 6.0;
-const double HALF = 0.5;
-const double ONESIXTH = ONE / SIX;
-const double SIXTH = ONESIXTH;
-const double ONE_THIRD = ONE / THREE;
-const double TWO_THIRDS = TWO / THREE;
-const double THREE_QUARTERS = 0.75;
-const double TWENTY_FOUR = 24.0;
-const int MAX_DEGREE = 3;
-const int HISTORY_MAX = 100;
-const double TEN_EPSILON_MCH = 10.0 * EPSILON_MCH;
-const double ROOTS_TOL = TEN_EPSILON_MCH;
-const double INFINITE_NUMBER = HUGEST;
-
-/** Replacement for FORTRAN's SIGN intrinsic function
- */
-inline double sign(double x, double y) { return y >= 0.0 ? fabs(x) : -fabs(x); }
-
-//! - - - - - - - - - - - - - - - - - - - - - - -
-//! control derived type with component defaults
-//! - - - - - - - - - - - - - - - - - - - - - - -
-struct dtrs_control_type {
- //! maximum degree of Taylor approximant allowed
- int taylor_max_degree = 3;
-
- //! any entry of H that is smaller than h_min * MAXVAL( H ) we be treated as
- // zero
- double h_min = EPSILON_MCH;
-
- //! lower and upper bounds on the multiplier, if known
- double lower = LOWER_DEFAULT;
- double upper = UPPER_DEFAULT;
-
- //! stop when | ||x|| - radius | <=
- //! max( stop_normal * radius, stop_absolute_normal )
- double stop_normal = EPSILON_MCH;
- double stop_absolute_normal = EPSILON_MCH;
-
- //! is the solution is REQUIRED to lie on the boundary (i.e., is the
- // constraint
- //! an equality)?
- bool equality_problem = false;
-};
-
-//! - - - - - - - - - - - - - - - - - - - - - - - -
-//! history derived type with component defaults
-//! - - - - - - - - - - - - - - - - - - - - - - - -
-struct dtrs_history_type {
- //
- //! value of lambda
- double lambda = 0.0;
-
- //! corresponding value of ||x(lambda)||_M
- double x_norm = 0.0;
-};
-
-//! - - - - - - - - - - - - - - - - - - - - - - -
-//! inform derived type with component defaults
-//! - - - - - - - - - - - - - - - - - - - - - - -
-struct dtrs_inform_type {
- //
-
- //! the number of (||x||_M,lambda) pairs in the history
- int len_history = 0;
-
- //! the value of the quadratic function
- double obj = HUGEST;
-
- //! the M-norm of x, ||x||_M
- double x_norm = 0.0;
-
- //! the Lagrange multiplier corresponding to the trust-region constraint
- double multiplier = 0.0;
-
- //! a lower bound max(0,-lambda_1), where lambda_1 is the left-most
- //! eigenvalue of (H,M)
- double pole = 0.0;
-
- //! has the hard case occurred?
- bool hard_case = false;
-
- //! history information
- std::vector<dtrs_history_type> history;
-};
-
-/** Get the largest of the four values.
- * @param a :: Value number 1.
- * @param b :: Value number 2.
- * @param c :: Value number 3.
- * @param d :: Value number 4.
- */
-double biggest(double a, double b, double c, double d) {
- return std::max(std::max(a, b), std::max(c, d));
-}
-
-/** Get the largest of the three values.
- * @param a :: Value number 1.
- * @param b :: Value number 2.
- * @param c :: Value number 3.
- */
-double biggest(double a, double b, double c) {
- return std::max(std::max(a, b), c);
-}
-
-/** Find the largest by absolute value element of a vector.
- * @param v :: The searched vector.
- */
-double maxAbsVal(const DoubleFortranVector &v) {
- auto p = v.indicesOfMinMaxElements();
- return std::max(fabs(v.get(p.first)), fabs(v.get(p.second)));
-}
-
-/** Find the minimum and maximum elements of a vector.
- * @param v :: The searched vector.
- * @returns :: A pair of doubles where the first is the minimum and
- * the second is the maxumum.
- */
-std::pair<double, double> minMaxValues(const DoubleFortranVector &v) {
- auto p = v.indicesOfMinMaxElements();
- return std::make_pair(v.get(p.first), v.get(p.second));
-}
-
-/** Compute the 2-norm of a vector which is a square root of the
- * sum of squares of its elements.
- * @param v :: The vector.
- */
-double twoNorm(const DoubleFortranVector &v) {
- if (v.size() == 0)
- return 0.0;
- return gsl_blas_dnrm2(v.gsl());
-}
-
-/** Get the dot-product of two vectors of the same size.
- * @param v1 :: The first vector.
- * @param v2 :: The second vector.
- */
-double dotProduct(const DoubleFortranVector &v1,
- const DoubleFortranVector &v2) {
- return v1.dot(v2);
-}
-
-/** Find the maximum element in the first n elements of a vector.
- * @param v :: The vector.
- * @param n :: The number of elements to examine.
- */
-double maxVal(const DoubleFortranVector &v, int n) {
- double res = std::numeric_limits<double>::lowest();
- for (int i = 1; i <= n; ++i) {
- auto val = v(i);
- if (val > res) {
- res = val;
- }
- }
- return res;
-}
-
-/** Find the number and values of real roots of the quadratic equation
- *
- * a2 * x**2 + a1 * x + a0 = 0
- *
- * where a0, a1 and a2 are real
- * @param a0 :: The free coefficient.
- * @param a1 :: The coefficient at the linear term.
- * @param a2 :: The coefficient at the quadratic term.
- * @param tol :: A tolerance for comparing doubles.
- * @param nroots :: The output number of real roots.
- * @param root1 :: The first real root if nroots > 0.
- * @param root2 :: The second real root if nroots = 2.
- */
-void rootsQuadratic(double a0, double a1, double a2, double tol, int &nroots,
- double &root1, double &root2) {
-
- auto rhs = tol * a1 * a1;
- if (fabs(a0 * a2) > rhs) { // really is quadratic
- root2 = a1 * a1 - FOUR * a2 * a0;
- if (fabs(root2) <= pow(EPSILON_MCH * a1, 2)) { // numerical double root
- nroots = 2;
- root1 = -HALF * a1 / a2;
- root2 = root1;
- } else if (root2 < ZERO) { // complex not real roots
- nroots = 0;
- root1 = ZERO;
- root2 = ZERO;
- } else { // distint real roots
- auto d = -HALF * (a1 + sign(sqrt(root2), a1));
- nroots = 2;
- root1 = d / a2;
- root2 = a0 / d;
- if (root1 > root2) {
- d = root1;
- root1 = root2;
- root2 = d;
- }
- }
- } else if (a2 == ZERO) {
- if (a1 == ZERO) {
- if (a0 == ZERO) { // the function is zero
- nroots = 1;
- root1 = ZERO;
- root2 = ZERO;
- } else { // the function is constant
- nroots = 0;
- root1 = ZERO;
- root2 = ZERO;
- }
- } else { // the function is linear
- nroots = 1;
- root1 = -a0 / a1;
- root2 = ZERO;
- }
- } else { // very ill-conditioned quadratic
- nroots = 2;
- if (-a1 / a2 > ZERO) {
- root1 = ZERO;
- root2 = -a1 / a2;
- } else {
- root1 = -a1 / a2;
- root2 = ZERO;
- }
- }
-
- // perfom a Newton iteration to ensure that the roots are accurate
-
- if (nroots >= 1) {
- auto p = (a2 * root1 + a1) * root1 + a0;
- auto pprime = TWO * a2 * root1 + a1;
- if (pprime != ZERO) {
- root1 = root1 - p / pprime;
- }
- if (nroots == 2) {
- p = (a2 * root2 + a1) * root2 + a0;
- pprime = TWO * a2 * root2 + a1;
- if (pprime != ZERO) {
- root2 = root2 - p / pprime;
- }
- }
- }
-}
-
-/** Find the number and values of real roots of the cubic equation
- *
- * a3 * x**3 + a2 * x**2 + a1 * x + a0 = 0
- *
- * where a0, a1, a2 and a3 are real
- * @param a0 :: The free coefficient.
- * @param a1 :: The coefficient at the linear term.
- * @param a2 :: The coefficient at the quadratic term.
- * @param a3 :: The coefficient at the cubic term.
- * @param tol :: A tolerance for comparing doubles.
- * @param nroots :: The output number of real roots.
- * @param root1 :: The first real root.
- * @param root2 :: The second real root if nroots > 1.
- * @param root3 :: The third real root if nroots == 3.
- */
-void rootsCubic(double a0, double a1, double a2, double a3, double tol,
- int &nroots, double &root1, double &root2, double &root3) {
-
- // Check to see if the cubic is actually a quadratic
- if (a3 == ZERO) {
- rootsQuadratic(a0, a1, a2, tol, nroots, root1, root2);
- root3 = INFINITE_NUMBER;
- return;
- }
-
- // Deflate the polnomial if the trailing coefficient is zero
- if (a0 == ZERO) {
- root1 = ZERO;
- rootsQuadratic(a1, a2, a3, tol, nroots, root2, root3);
- nroots = nroots + 1;
- return;
- }
-
- // 1. Use Nonweiler's method (CACM 11:4, 1968, pp269)
-
- double c0 = a0 / a3;
- double c1 = a1 / a3;
- double c2 = a2 / a3;
-
- double s = c2 / THREE;
- double t = s * c2;
- double b = 0.5 * (s * (TWO_THIRDS * t - c1) + c0);
- t = (t - c1) / THREE;
- double c = t * t * t;
- double d = b * b - c;
-
- // 1 real + 2 equal real or 2 complex roots
- if (d >= ZERO) {
- d = pow(sqrt(d) + fabs(b), ONE_THIRD);
- if (d != ZERO) {
- if (b > ZERO) {
- b = -d;
- } else {
- b = d;
- }
- c = t / b;
- }
- d = sqrt(THREE_QUARTERS) * (b - c);
- b = b + c;
- c = -0.5 * b - s;
- root1 = b - s;
- if (d == ZERO) {
- nroots = 3;
- root2 = c;
- root3 = c;
- } else {
- nroots = 1;
- }
- } else { // 3 real roots
- if (b == ZERO) {
- d = TWO_THIRDS * atan(ONE);
- } else {
- d = atan(sqrt(-d) / fabs(b)) / THREE;
- }
- if (b < ZERO) {
- b = TWO * sqrt(t);
- } else {
- b = -TWO * sqrt(t);
- }
- c = cos(d) * b;
- t = -sqrt(THREE_QUARTERS) * sin(d) * b - HALF * c;
- d = -t - c - s;
- c = c - s;
- t = t - s;
- if (fabs(c) > fabs(t)) {
- root3 = c;
- } else {
- root3 = t;
- t = c;
- }
- if (fabs(d) > fabs(t)) {
- root2 = d;
- } else {
- root2 = t;
- t = d;
- }
- root1 = t;
- nroots = 3;
- }
-
- // reorder the roots
-
- if (nroots == 3) {
- if (root1 > root2) {
- double a = root2;
- root2 = root1;
- root1 = a;
- }
- if (root2 > root3) {
- double a = root3;
- if (root1 > root3) {
- a = root1;
- root1 = root3;
- }
- root3 = root2;
- root2 = a;
- }
- }
-
- // perfom a Newton iteration to ensure that the roots are accurate
- double p = ((a3 * root1 + a2) * root1 + a1) * root1 + a0;
- double pprime = (THREE * a3 * root1 + TWO * a2) * root1 + a1;
- if (pprime != ZERO) {
- root1 = root1 - p / pprime;
- // p = ((a3 * root1 + a2) * root1 + a1) * root1 + a0; // never used
- }
-
- if (nroots == 3) {
- p = ((a3 * root2 + a2) * root2 + a1) * root2 + a0;
- pprime = (THREE * a3 * root2 + TWO * a2) * root2 + a1;
- if (pprime != ZERO) {
- root2 = root2 - p / pprime;
- // p = ((a3 * root2 + a2) * root2 + a1) * root2 + a0; // never used
- }
-
- p = ((a3 * root3 + a2) * root3 + a1) * root3 + a0;
- pprime = (THREE * a3 * root3 + TWO * a2) * root3 + a1;
- if (pprime != ZERO) {
- root3 = root3 - p / pprime;
- // p = ((a3 * root3 + a2) * root3 + a1) * root3 + a0; // never used
- }
- }
-}
-
-/** Compute pi_beta = ||x||^beta and its derivatives
- * Extracted wholesale from module RAL_NLLS_RQS
- *
- * @param max_order :: Maximum order of derivative.
- * @param beta :: Power.
- * @param x_norm2 :: (0) value of ||x||^2,
- * (i) ith derivative of ||x||^2, i = 1, max_order
- * @param pi_beta :: (0) value of ||x||^beta,
- * (i) ith derivative of ||x||^beta, i = 1, max_order
- */
-void dtrsPiDerivs(int max_order, double beta,
- const DoubleFortranVector &x_norm2,
- DoubleFortranVector &pi_beta) {
- double hbeta = HALF * beta;
- pi_beta(0) = pow(x_norm2(0), hbeta);
- pi_beta(1) = hbeta * (pow(x_norm2(0), (hbeta - ONE))) * x_norm2(1);
- if (max_order == 1)
- return;
- pi_beta(2) = hbeta * (pow(x_norm2(0), (hbeta - TWO))) *
- ((hbeta - ONE) * pow(x_norm2(1), 2) + x_norm2(0) * x_norm2(2));
- if (max_order == 2)
- return;
- pi_beta(3) = hbeta * (pow(x_norm2(0), (hbeta - THREE))) *
- (x_norm2(3) * pow(x_norm2(0), 2) +
- (hbeta - ONE) * (THREE * x_norm2(0) * x_norm2(1) * x_norm2(2) +
- (hbeta - TWO) * pow(x_norm2(1), 3)));
-}
-
-/** Set initial values for the TRS control parameters
- *
- * @param control :: A structure containing control information.
- */
-void dtrsInitialize(dtrs_control_type &control) {
- control.stop_normal = pow(EPSILON_MCH, 0.75);
- control.stop_absolute_normal = pow(EPSILON_MCH, 0.75);
-}
-
-/** Solve the trust-region subproblem
- *
- * minimize 1/2 <x, H x> + <c, x> + f
- * subject to ||x||_2 <= radius or ||x||_2 = radius
- *
- * where H is diagonal, using a secular iteration
- *
- * @param n :: The number of unknowns.
- * @param radius :: The trust-region radius.
- * @param f :: The value of constant term for the quadratic function
- * @param c :: A vector of values for the linear term c.
- * @param h :: A vector of values for the diagonal matrix H.
- * @param x :: The required solution vector x.
- * @param control :: A structure containing control information.
- * @param inform :: A structure containing information.
- */
-void dtrsSolveMain(int n, double radius, double f, const DoubleFortranVector &c,
- const DoubleFortranVector &h, DoubleFortranVector &x,
- const dtrs_control_type &control, dtrs_inform_type &inform) {
-
- // set initial values
-
- if (x.len() != n) {
- x.allocate(n);
- }
- x.zero();
- inform.x_norm = ZERO;
- inform.obj = f;
- inform.hard_case = false;
- double delta_lambda = ZERO;
-
- // Check that arguments are OK
- if (n < 0) {
- throw std::runtime_error(
- "Number of unknowns for trust-region subproblem is negative.");
- }
- if (radius < 0) {
- throw std::runtime_error(
- "Trust-region radius for trust-region subproblem is negative");
- }
-
- DoubleFortranVector x_norm2(0, MAX_DEGREE), pi_beta(0, MAX_DEGREE);
-
- // compute the two-norm of c and the extreme eigenvalues of H
-
- double c_norm = twoNorm(c);
- double lambda_min = 0.0;
- double lambda_max = 0.0;
- std::tie(lambda_min, lambda_max) = minMaxValues(h);
-
- double lambda = 0.0;
- //! check for the trivial case
- if (c_norm == ZERO && lambda_min >= ZERO) {
- if (control.equality_problem) {
- int i_hard = 1; // TODO: is init value of 1 correct?
- for (int i = 1; i <= n; ++i) { // do i = 1, n
- if (h(i) == lambda_min) {
- i_hard = i;
- break;
- }
- }
- x(i_hard) = ONE / radius;
- inform.x_norm = radius;
- inform.obj = f + lambda_min * radius * radius;
- }
- return;
- }
-
- // construct values lambda_l and lambda_u for which lambda_l <=
- // lambda_optimal
- // <= lambda_u, and ensure that all iterates satisfy lambda_l <= lambda
- // <= lambda_u
-
- double c_norm_over_radius = c_norm / radius;
- double lambda_l = 0.0, lambda_u = 0.0;
- if (control.equality_problem) {
- lambda_l =
- biggest(control.lower, -lambda_min, c_norm_over_radius - lambda_max);
- lambda_u = std::min(control.upper, c_norm_over_radius - lambda_min);
- } else {
- lambda_l = biggest(control.lower, ZERO, -lambda_min,
- c_norm_over_radius - lambda_max);
- lambda_u = std::min(control.upper,
- std::max(ZERO, c_norm_over_radius - lambda_min));
- }
- lambda = lambda_l;
-
- // check for the "hard case"
- if (lambda == -lambda_min) {
- int i_hard = 1; // TODO: is init value of 1 correct?
- double c2 = ZERO;
- inform.hard_case = true;
- for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
- if (h(i) == lambda_min) {
- if (fabs(c(i)) > EPSILON_MCH * c_norm) {
- inform.hard_case = false;
- c2 = c2 + pow(c(i), 2);
- } else {
- i_hard = i;
- }
- }
- }
-
- // the hard case may occur
- if (inform.hard_case) {
- for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
- if (h(i) != lambda_min) {
- x(i) = -c(i) / (h(i) + lambda);
- } else {
- x(i) = ZERO;
- }
- }
- inform.x_norm = twoNorm(x);
-
- // the hard case does occur
-
- if (inform.x_norm <= radius) {
- if (inform.x_norm < radius) {
-
- // compute the step alpha so that x + alpha e_i_hard lies on the
- // trust-region
- // boundary and gives the smaller value of q
-
- auto utx = x(i_hard) / radius;
- auto distx =
- (radius - inform.x_norm) * ((radius + inform.x_norm) / radius);
- auto alpha = sign(
- distx / (fabs(utx) + sqrt(pow(utx, 2) + distx / radius)), utx);
-
- // record the optimal values
-
- x(i_hard) = x(i_hard) + alpha;
- }
- inform.x_norm = twoNorm(x);
- inform.obj = f + HALF * (dotProduct(c, x) - lambda * pow(radius, 2));
- return;
-
- // the hard case didn't occur after all
- } else {
- inform.hard_case = false;
-
- // compute the first derivative of ||x|(lambda)||^2 - radius^2
- auto w_norm2 = ZERO;
- for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
- if (h(i) != lambda_min)
- w_norm2 = w_norm2 + pow(c(i), 2) / pow((h(i) + lambda), 3);
- }
- x_norm2(1) = -TWO * w_norm2;
-
- // compute the newton correction
-
- lambda = lambda + (pow(inform.x_norm, 2) - pow(radius, 2)) / x_norm2(1);
- lambda_l = std::max(lambda_l, lambda);
- }
-
- // there is a singularity at lambda. compute the point for which the
- // sum of squares of the singular terms is equal to radius^2
- } else {
- lambda = lambda + std::max(sqrt(c2) / radius, lambda * EPSILON_MCH);
- lambda_l = std::max(lambda_l, lambda);
- }
- }
-
- // the iterates will all be in the L region. Prepare for the main loop
- auto max_order = std::max(1, std::min(MAX_DEGREE, control.taylor_max_degree));
-
- // start the main loop
- for (;;) {
-
- // if h(lambda) is positive definite, solve h(lambda) x = - c
-
- for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
- x(i) = -c(i) / (h(i) + lambda);
- }
-
- // compute the two-norm of x
- inform.x_norm = twoNorm(x);
- x_norm2(0) = pow(inform.x_norm, 2);
-
- // if the newton step lies within the trust region, exit
-
- if (lambda == ZERO && inform.x_norm <= radius) {
- inform.obj = f + HALF * dotProduct(c, x);
- return;
- }
-
- //! the current estimate gives a good approximation to the required
- //! root
-
- if (fabs(inform.x_norm - radius) <=
- std::max(control.stop_normal * radius, control.stop_absolute_normal)) {
- break;
- }
-
- lambda_l = std::max(lambda_l, lambda);
-
- // record, for the future, values of lambda which give small ||x||
- if (inform.len_history < HISTORY_MAX) {
- dtrs_history_type history_item;
- history_item.lambda = lambda;
- history_item.x_norm = inform.x_norm;
- inform.history.push_back(history_item);
- inform.len_history = inform.len_history + 1;
- }
-
- // a lambda in L has been found. It is now simply a matter of applying
- // a variety of Taylor-series-based methods starting from this lambda
-
- // precaution against rounding producing lambda outside L
-
- if (lambda > lambda_u) {
- throw std::runtime_error(
- "Lambda for trust-region subproblem is ill conditioned");
- }
-
- // compute first derivatives of x^T M x
-
- // form ||w||^2 = x^T H^-1(lambda) x
-
- double w_norm2 = ZERO;
- for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
- w_norm2 = w_norm2 + pow(c(i), 2) / pow(h(i) + lambda, 3);
- }
-
- // compute the first derivative of x_norm2 = x^T M x
- x_norm2(1) = -TWO * w_norm2;
-
- // compute pi_beta = ||x||^beta and its first derivative when beta = - 1
- double beta = -ONE;
- dtrsPiDerivs(1, beta, x_norm2, pi_beta);
-
- // compute the Newton correction (for beta = - 1)
-
- delta_lambda = -(pi_beta(0) - pow((radius), beta)) / pi_beta(1);
-
- DoubleFortranVector lambda_new(3);
- int n_lambda = 1;
- lambda_new(n_lambda) = lambda + delta_lambda;
-
- if (max_order >= 3) {
-
- // compute the second derivative of x^T x
-
- double z_norm2 = ZERO;
- for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
- z_norm2 = z_norm2 + pow(c(i), 2) / pow((h(i) + lambda), 4);
- }
- x_norm2(2) = SIX * z_norm2;
-
- // compute the third derivatives of x^T x
-
- double v_norm2 = ZERO;
- for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
- v_norm2 = v_norm2 + pow(c(i), 2) / pow((h(i) + lambda), 5);
- }
- x_norm2(3) = -TWENTY_FOUR * v_norm2;
-
- // compute pi_beta = ||x||^beta and its derivatives when beta = 2
-
- beta = TWO;
- dtrsPiDerivs(max_order, beta, x_norm2, pi_beta);
-
- // compute the "cubic Taylor approximaton" step (beta = 2)
-
- auto a_0 = pi_beta(0) - pow((radius), beta);
- auto a_1 = pi_beta(1);
- auto a_2 = HALF * pi_beta(2);
- auto a_3 = SIXTH * pi_beta(3);
- auto a_max = biggest(fabs(a_0), fabs(a_1), fabs(a_2), fabs(a_3));
- if (a_max > ZERO) {
- a_0 = a_0 / a_max;
- a_1 = a_1 / a_max;
- a_2 = a_2 / a_max;
- a_3 = a_3 / a_max;
- }
- int nroots = 0;
- double root1 = 0, root2 = 0, root3 = 0;
-
- rootsCubic(a_0, a_1, a_2, a_3, ROOTS_TOL, nroots, root1, root2, root3);
- n_lambda = n_lambda + 1;
- if (nroots == 3) {
- lambda_new(n_lambda) = lambda + root3;
- } else {
- lambda_new(n_lambda) = lambda + root1;
- }
-
- // compute pi_beta = ||x||^beta and its derivatives when beta = - 0.4
-
- beta = -POINT4;
- dtrsPiDerivs(max_order, beta, x_norm2, pi_beta);
-
- // compute the "cubic Taylor approximaton" step (beta = - 0.4)
-
- a_0 = pi_beta(0) - pow((radius), beta);
- a_1 = pi_beta(1);
- a_2 = HALF * pi_beta(2);
- a_3 = SIXTH * pi_beta(3);
- a_max = biggest(fabs(a_0), fabs(a_1), fabs(a_2), fabs(a_3));
- if (a_max > ZERO) {
- a_0 = a_0 / a_max;
- a_1 = a_1 / a_max;
- a_2 = a_2 / a_max;
- a_3 = a_3 / a_max;
- }
- rootsCubic(a_0, a_1, a_2, a_3, ROOTS_TOL, nroots, root1, root2, root3);
- n_lambda = n_lambda + 1;
- if (nroots == 3) {
- lambda_new(n_lambda) = lambda + root3;
- } else {
- lambda_new(n_lambda) = lambda + root1;
- }
- }
-
- // compute the best Taylor improvement
-
- auto lambda_plus = maxVal(lambda_new, n_lambda);
- delta_lambda = lambda_plus - lambda;
- lambda = lambda_plus;
-
- // improve the lower bound if possible
-
- lambda_l = std::max(lambda_l, lambda_plus);
-
- // check that the best Taylor improvement is significant
-
- if (fabs(delta_lambda) < EPSILON_MCH * std::max(ONE, fabs(lambda))) {
- break;
- }
-
- } // for(;;)
-}
-
-/** Solve the trust-region subproblem
- *
- * minimize q(x) = 1/2 <x, H x> + <c, x> + f
- * subject to ||x||_2 <= radius or ||x||_2 = radius
- *
- * where H is diagonal, using a secular iteration
- *
- * @param n :: The number of unknowns.
- * @param radius :: The trust-region radius.
- * @param f :: The value of constant term for the quadratic function.
- * @param c :: A vector of values for the linear term c.
- * @param h :: A vector of values for the diagonal matrix H.
- * @param x :: The required solution vector x.
- * @param control :: A structure containing control information.
- * @param inform :: A structure containing information.
- */
-void dtrsSolve(int n, double radius, double f, const DoubleFortranVector &c,
- const DoubleFortranVector &h, DoubleFortranVector &x,
- const dtrs_control_type &control, dtrs_inform_type &inform) {
- // scale the problem to solve instead
- // minimize q_s(x_s) = 1/2 <x_s, H_s x_s> + <c_s, x_s> + f_s
- // subject to ||x_s||_2 <= radius_s or ||x_s||_2 = radius_s
-
- // where H_s = H / s_h and c_s = c / s_c for scale factors s_h and s_c
-
- // This corresponds to
- // radius_s = ( s_h / s_c ) radius,
- // f_s = ( s_h / s_c^2 ) f
- // and the solution may be recovered as
- // x = ( s_c / s_h ) x_s
- // lambda = s_h lambda_s
- // q(x) = ( s_c^2 / s_ h ) q_s(x_s)
-
- // scale H by the largest H and remove relatively tiny H
-
- DoubleFortranVector h_scale(n);
- auto scale_h = maxAbsVal(h); // MAXVAL( ABS( H ) )
- if (scale_h > ZERO) {
- for (int i = 1; i <= n; ++i) { // do i = 1, n
- if (fabs(h(i)) >= control.h_min * scale_h) {
- h_scale(i) = h(i) / scale_h;
- } else {
- h_scale(i) = ZERO;
- }
- }
- } else {
- scale_h = ONE;
- h_scale.zero();
- }
-
- // scale c by the largest c and remove relatively tiny c
-
- DoubleFortranVector c_scale(n);
- auto scale_c = maxAbsVal(c); // maxval( abs( c ) )
- if (scale_c > ZERO) {
- for (int i = 1; i <= n; ++i) { // do i = 1, n
- if (fabs(c(i)) >= control.h_min * scale_c) {
- c_scale(i) = c(i) / scale_c;
- } else {
- c_scale(i) = ZERO;
- }
- }
- } else {
- scale_c = ONE;
- c_scale.zero();
- }
-
- double radius_scale = (scale_h / scale_c) * radius;
- double f_scale = (scale_h / pow(scale_c, 2)) * f;
-
- auto control_scale = control;
- if (control_scale.lower != LOWER_DEFAULT) {
- control_scale.lower = control_scale.lower / scale_h;
- }
- if (control_scale.upper != UPPER_DEFAULT) {
- control_scale.upper = control_scale.upper / scale_h;
- }
-
- // solve the scaled problem
-
- dtrsSolveMain(n, radius_scale, f_scale, c_scale, h_scale, x, control_scale,
- inform);
-
- // unscale the solution, function value, multiplier and related values
-
- // x = ( scale_c / scale_h ) * x
- x *= scale_c / scale_h;
- inform.obj *= pow(scale_c, 2) / scale_h;
- inform.multiplier *= scale_h;
- inform.pole *= scale_h;
- for (size_t i = 0; i < inform.history.size();
- ++i) { // do i = 1, inform.len_history
- inform.history[i].lambda *= scale_h;
- inform.history[i].x_norm *= scale_c / scale_h;
- }
-}
-
-} // namespace
-
-/** Solve the trust-region subproblem using
- * the DTRS method from Galahad
- *
- * This method needs H to be diagonal, so we need to
- * pre-process
- *
- * main output d, the soln to the TR subproblem
- * @param J :: The Jacobian.
- * @param f :: The residuals.
- * @param hf :: The Hessian (sort of).
- * @param Delta :: The raduis of the trust region.
- * @param d :: The output vector of corrections to the parameters giving the
- * solution to the TR subproblem.
- * @param normd :: The 2-norm of d.
- * @param options :: The options.
- */
-void DTRSMinimizer::solveDtrs(const DoubleFortranMatrix &J,
- const DoubleFortranVector &f,
- const DoubleFortranMatrix &hf, double Delta,
- DoubleFortranVector &d, double &normd,
- const NLLS::nlls_options &options) {
-
- dtrs_control_type dtrs_options;
- dtrs_inform_type dtrs_inform;
-
- // The code finds
- // d = arg min_p w^T p + 0.5 * p^T D p
- // s.t. ||p|| \leq Delta
- //
- // where D is diagonal
- //
- // our probem in naturally in the form
- //
- // d = arg min_p v^T p + 0.5 * p^T H p
- // s.t. ||p|| \leq Delta
- //
- // first, find the matrix H and vector v
- // Set A = J^T J
- NLLS::matmultInner(J, m_A);
- // add any second order information...
- // so A = J^T J + HF
- m_A += hf;
-
- // now form v = J^T f
- NLLS::multJt(J, f, m_v);
-
- // if scaling needed, do it
- if (options.scale != 0) {
- applyScaling(J, m_A, m_v, m_scale, options);
- }
-
- // Now that we have the unprocessed matrices, we need to get an
- // eigendecomposition to make A diagonal
- //
- NLLS::allEigSymm(m_A, m_ew, m_ev);
-
- // We can now change variables, setting y = Vp, getting
- // Vd = arg min_(Vx) v^T p + 0.5 * (Vp)^T D (Vp)
- // s.t. ||x|| \leq Delta
- // <=>
- // Vd = arg min_(Vx) V^Tv^T (Vp) + 0.5 * (Vp)^T D (Vp)
- // s.t. ||x|| \leq Delta
- // <=>
- // we need to get the transformed vector v
- NLLS::multJt(m_ev, m_v, m_v_trans);
-
- // we've now got the vectors we need, pass to dtrsSolve
- dtrsInitialize(dtrs_options);
-
- auto n = J.len2();
- if (m_v_trans.len() != n) {
- m_v_trans.allocate(n);
- }
-
- for (int ii = 1; ii <= n; ++ii) { // for_do(ii, 1,n)
- if (fabs(m_v_trans(ii)) < EPSILON_MCH) {
- m_v_trans(ii) = ZERO;
- }
- if (fabs(m_ew(ii)) < EPSILON_MCH) {
- m_ew(ii) = ZERO;
- }
- }
-
- dtrsSolve(n, Delta, ZERO, m_v_trans, m_ew, m_d_trans, dtrs_options,
- dtrs_inform);
-
- // and return the un-transformed vector
- NLLS::multJ(m_ev, m_d_trans, d);
-
- normd = NLLS::norm2(d); // ! ||d||_D
-
- if (options.scale != 0) {
- for (int ii = 1; ii <= n; ++ii) { // for_do(ii, 1, n)
- d(ii) = d(ii) / m_scale(ii);
- }
- }
-
-} // solveDtrs
-
-/** Implements the abstarct method of TrustRegionMinimizer.
- */
-void DTRSMinimizer::calculateStep(const DoubleFortranMatrix &J,
- const DoubleFortranVector &f,
- const DoubleFortranMatrix &hf,
- const DoubleFortranVector &, double Delta,
- DoubleFortranVector &d, double &normd,
- const NLLS::nlls_options &options) {
- solveDtrs(J, f, hf, Delta, d, normd, options);
-}
-
-} // namespace FuncMinimisers
-} // namespace CurveFitting
-} // namespace Mantid
diff --git a/Framework/CurveFitting/src/FuncMinimizers/MoreSorensenMinimizer.cpp b/Framework/CurveFitting/src/FuncMinimizers/MoreSorensenMinimizer.cpp
deleted file mode 100644
index 8f74fef1df4fe243710fa92746e98c6f6d632ef1..0000000000000000000000000000000000000000
--- a/Framework/CurveFitting/src/FuncMinimizers/MoreSorensenMinimizer.cpp
+++ /dev/null
@@ -1,320 +0,0 @@
-// This code was originally translated from Fortran code on
-// https://ccpforge.cse.rl.ac.uk/gf/project/ral_nlls June 2016
-//----------------------------------------------------------------------
-// Includes
-//----------------------------------------------------------------------
-#include "MantidCurveFitting/FuncMinimizers/MoreSorensenMinimizer.h"
-#include "MantidAPI/FuncMinimizerFactory.h"
-#include "MantidCurveFitting/RalNlls/TrustRegion.h"
-#include <cmath>
-
-namespace Mantid {
-namespace CurveFitting {
-namespace FuncMinimisers {
-
-// clang-format off
-///@cond nodoc
-DECLARE_FUNCMINIMIZER(MoreSorensenMinimizer,More-Sorensen)
-///@endcond
-// clang-format on
-
-MoreSorensenMinimizer::MoreSorensenMinimizer() : TrustRegionMinimizer() {}
-
-/// Name of the minimizer.
-std::string MoreSorensenMinimizer::name() const { return "More-Sorensen"; }
-
-namespace {
-
-/** Solve a system of linear equations. The system's matrix must be
- * positive-definite.
- * @param A :: A matrix of a system of equations.
- * Must be positive-definite for success.
- * @param b :: A vector of the right-hand side.
- * @param LtL :: A work matrix.
- * @param x :: A vector that receives the solution.
- * @return true if successful
- */
-bool solveSpd(const DoubleFortranMatrix &A, const DoubleFortranVector &b,
- DoubleFortranMatrix &LtL, DoubleFortranVector &x) {
- // Fortran code uses this:
- // dposv('L', n, 1, LtL, n, x, n, inform.external_return)
- // This is the GSL replacement:
- LtL = A;
- auto res = gsl_linalg_cholesky_decomp(LtL.gsl());
- if (res == GSL_EDOM) {
- // Matrix is not positive definite, return for retry.
- return false;
- }
- gsl_linalg_cholesky_solve(LtL.gsl(), b.gsl(), x.gsl());
- return true;
-}
-
-/** Calculate the leftmost eigenvalue of a matrix.
- * @param A :: A matrix to analyse.
- * @param sigma :: A variable to receive the value of the smallest
- * eigenvalue.
- * @param y :: A vector that receives the corresponding eigenvector.
- */
-void minEigSymm(const DoubleFortranMatrix &A, double &sigma,
- DoubleFortranVector &y) {
- auto M = A;
- DoubleFortranVector ew;
- DoubleFortranMatrix ev;
- M.eigenSystem(ew, ev);
- auto ind = ew.sortIndices();
- int imin = static_cast<int>(ind[0]) + 1;
- sigma = ew(imin);
- int n = static_cast<int>(A.size1());
- y.allocate(n);
- for (int i = 1; i <= n; ++i) {
- y(i) = ev(i, imin);
- }
-}
-
-/** Calculate AplusSigma = A + sigma * I
- * @param sigma :: The value of the diagonal shift.
- * @param AplusSigma :: The resulting matrix.
- */
-void shiftMatrix(const DoubleFortranMatrix &A, double sigma,
- DoubleFortranMatrix &AplusSigma) {
- AplusSigma = A;
- auto n = A.len1();
- for (int i = 1; i <= n; ++i) { // for_do(i,1,n)
- AplusSigma(i, i) = AplusSigma(i, i) + sigma;
- }
-}
-
-/** Negate a vector
- * @param v :: A vector.
- */
-DoubleFortranVector negative(const DoubleFortranVector &v) {
- DoubleFortranVector neg = v;
- neg *= -1.0;
- return neg;
-}
-
-/** A subroutine to find the optimal beta such that
- * || d || = Delta, where d = a + beta * b
- *
- * uses the approach from equation (3.20b),
- * "Methods for non-linear least squares problems" (2nd edition, 2004)
- * by Madsen, Nielsen and Tingleff
- * @param a :: The first vector.
- * @param b :: The second vector.
- * @param Delta :: The Delta.
- * @param beta :: The beta.
- * @return true if successful
- */
-bool findBeta(const DoubleFortranVector &a, const DoubleFortranVector &b,
- double Delta, double &beta) {
-
- auto c = a.dot(b);
-
- auto norma2 = pow(NLLS::norm2(a), 2);
- auto normb2 = pow(NLLS::norm2(b), 2);
-
- double discrim = pow(c, 2) + (normb2) * (pow(Delta, 2) - norma2);
- if (discrim < NLLS::ZERO) {
- return false;
- }
-
- if (c <= 0) {
- beta = (-c + sqrt(discrim)) / normb2;
- } else {
- beta = (pow(Delta, 2) - norma2) / (c + sqrt(discrim));
- }
- return true;
-}
-
-} // namespace
-
-/** Given an indefinite matrix m_A, find a shift sigma
-* such that (A + sigma I) is positive definite.
-* @param sigma :: The result (shift).
-* @param d :: A solution vector to the system of linear equations
-* with the found positive defimnite matrix. The RHS vector is -m_v.
-* @param options :: The options.
-* @return true if successful
-*/
-bool MoreSorensenMinimizer::getPdShift(double &sigma, DoubleFortranVector &d,
- const NLLS::nlls_options &options) {
- int no_shifts = 0;
- bool successful_shift = false;
- while (!successful_shift) {
- shiftMatrix(m_A, sigma, m_AplusSigma);
- successful_shift = solveSpd(m_AplusSigma, negative(m_v), m_LtL, d);
- if (!successful_shift) {
- // We try again with a shifted sigma, but no too many times.
- no_shifts = no_shifts + 1;
- if (no_shifts == 10) {
- return false;
- }
- sigma = sigma + (pow(10.0, no_shifts)) * options.more_sorensen_shift;
- }
- }
- return true;
-}
-
-/** Solve the trust-region subproblem using
- * the method of More and Sorensen
- *
- * Using the implementation as in Algorithm 7.3.6
- * of Trust Region Methods
- *
- * main output d, the soln to the TR subproblem
- * @param J :: The Jacobian.
- * @param f :: The residuals.
- * @param hf :: The Hessian (sort of).
- * @param Delta :: The raduis of the trust region.
- * @param d :: The output vector of corrections to the parameters giving the
- * solution to the TR subproblem.
- * @param nd :: The 2-norm of d.
- * @param options :: The options.
- */
-void MoreSorensenMinimizer::solveSubproblem(const DoubleFortranMatrix &J,
- const DoubleFortranVector &f,
- const DoubleFortranMatrix &hf,
- double Delta,
- DoubleFortranVector &d, double &nd,
- const NLLS::nlls_options &options) {
-
- // The code finds
- // d = arg min_p v^T p + 0.5 * p^T A p
- // s.t. ||p|| \leq Delta
- //
- // set A and v for the model being considered here...
-
- // Set A = J^T J
- NLLS::matmultInner(J, m_A);
- // add any second order information...
- // so A = J^T J + HF
- m_A += hf;
- // now form v = J^T f
- NLLS::multJt(J, f, m_v);
-
- // if scaling needed, do it
- if (options.scale != 0) {
- applyScaling(J, m_A, m_v, m_scale, options);
- }
-
- auto n = J.len2();
- auto scaleBack = [n, &d, &options, this]() {
- if (options.scale != 0) {
- for (int i = 1; i <= n; ++i) {
- d(i) = d(i) / m_scale(i);
- }
- }
- };
-
- auto local_ms_shift = options.more_sorensen_shift;
- // d = -A\v
- DoubleFortranVector negv = m_v;
- negv *= -1.0;
- bool matrix_ok = solveSpd(m_A, negv, m_LtL, d);
- double sigma = 0.0;
- if (matrix_ok) {
- // A is symmetric positive definite....
- sigma = NLLS::ZERO;
- } else {
- // shift and try again
- minEigSymm(m_A, sigma, m_y1);
- sigma = -(sigma - local_ms_shift);
- // find a shift that makes (A + sigma I) positive definite
- bool ok = getPdShift(sigma, d, options);
- if (!ok) {
- scaleBack();
- return;
- }
- }
-
- nd = NLLS::norm2(d);
- if (!std::isfinite(nd)) {
- throw std::runtime_error("Step is NaN or infinite.");
- }
-
- // now, we're not in the trust region initally, so iterate....
- auto sigma_shift = NLLS::ZERO;
- int no_restarts = 0;
- // set 'small' in the context of the algorithm
- double epsilon =
- std::max(options.more_sorensen_tol * Delta, options.more_sorensen_tiny);
- int it = 1;
- for (; it <= options.more_sorensen_maxits; ++it) {
-
- if (nd <= Delta + epsilon) {
- // we're within the tr radius
- if (fabs(sigma) < options.more_sorensen_tiny ||
- fabs(nd - Delta) < epsilon) {
- // we're good....exit
- break;
- }
- if (m_y1.len() == n) {
- double alpha = 0.0;
- if (findBeta(d, m_y1, Delta, alpha)) {
- DoubleFortranVector tmp = m_y1;
- tmp *= alpha;
- d += tmp;
- }
- }
- // also good....exit
- break;
- }
-
- // m_q = R'\d
- // DTRSM( "Left", "Lower", "No Transpose", "Non-unit", n, 1, one, m_LtL, n,
- // m_q, n );
- for (int j = 1; j <= m_LtL.len1(); ++j) {
- for (int k = j + 1; k <= m_LtL.len1(); ++k) {
- m_LtL(j, k) = 0.0;
- }
- }
- m_LtL.solve(d, m_q);
-
- auto nq = NLLS::norm2(m_q);
- sigma_shift = (pow((nd / nq), 2)) * ((nd - Delta) / Delta);
- if (fabs(sigma_shift) < options.more_sorensen_tiny * fabs(sigma)) {
- if (no_restarts < 1) {
- // find a shift that makes (A + sigma I) positive definite
- bool ok = getPdShift(sigma, d, options);
- if (!ok) {
- break;
- }
- no_restarts = no_restarts + 1;
- } else {
- // we're not going to make progress...jump out
- throw std::runtime_error("Not making progress.");
- }
- } else {
- sigma = sigma + sigma_shift;
- }
-
- shiftMatrix(m_A, sigma, m_AplusSigma);
- DoubleFortranVector negv = m_v;
- negv *= -1.0;
- bool matrix_ok = solveSpd(m_AplusSigma, negv, m_LtL, d);
- if (!matrix_ok) {
- break;
- }
-
- nd = NLLS::norm2(d);
- }
-
- if (it == options.more_sorensen_maxits) {
- // maxits reached, not converged
- throw std::runtime_error("No convergence in maximum number of iterations.");
- }
- scaleBack();
-}
-
-/** Implements the abstract method of TrustRegionMinimizer.
- */
-void MoreSorensenMinimizer::calculateStep(
- const DoubleFortranMatrix &J, const DoubleFortranVector &f,
- const DoubleFortranMatrix &hf, const DoubleFortranVector &, double Delta,
- DoubleFortranVector &d, double &normd, const NLLS::nlls_options &options) {
- solveSubproblem(J, f, hf, Delta, d, normd, options);
-}
-
-} // namespace FuncMinimisers
-} // namespace CurveFitting
-} // namespace Mantid
diff --git a/Framework/CurveFitting/src/FuncMinimizers/TrustRegionMinimizer.cpp b/Framework/CurveFitting/src/FuncMinimizers/TrustRegionMinimizer.cpp
index 4cde25729569d2e769c9369f1fc427a4777460c3..2b4c732e7120eec05e4b92c7c63ccbf038b4e4d0 100644
--- a/Framework/CurveFitting/src/FuncMinimizers/TrustRegionMinimizer.cpp
+++ b/Framework/CurveFitting/src/FuncMinimizers/TrustRegionMinimizer.cpp
@@ -5,6 +5,7 @@
//----------------------------------------------------------------------
#include "MantidCurveFitting/FuncMinimizers/TrustRegionMinimizer.h"
#include "MantidCurveFitting/RalNlls/TrustRegion.h"
+#include "MantidAPI/FuncMinimizerFactory.h"
#include <cmath>
@@ -12,11 +13,21 @@ namespace Mantid {
namespace CurveFitting {
namespace FuncMinimisers {
+// clang-format off
+///@cond nodoc
+DECLARE_FUNCMINIMIZER(TrustRegionMinimizer, Trust Region)
+///@endcond
+// clang-format on
+
TrustRegionMinimizer::TrustRegionMinimizer() : m_function() {
declareProperty("InitialRadius", 100.0,
"Initial radius of the trust region.");
}
+/** Name of the minimizer.
+*/
+std::string TrustRegionMinimizer::name() const { return "Trust Region"; }
+
/** Initialise the minimizer.
* @param costFunction :: The cost function to minimize. Must be the least
* squares.
@@ -241,7 +252,7 @@ bool TrustRegionMinimizer::iterate(size_t) {
return true;
}
// Calculate the step d that the model thinks we should take next
- calculateStep(w.J, w.f, w.hf, w.g, w.Delta, w.d, w.normd, options);
+ calculateStep(w.J, w.f, w.hf, w.Delta, w.d, w.normd, options);
// Accept the step?
w.Xnew = X;
@@ -405,6 +416,973 @@ bool TrustRegionMinimizer::iterate(size_t) {
return true;
}
+/** DTRS method **/
+namespace {
+
+const double HUGEST = std::numeric_limits<double>::max();
+const double EPSILON_MCH = std::numeric_limits<double>::epsilon();
+const double LARGEST = HUGEST;
+const double LOWER_DEFAULT = -0.5 * LARGEST;
+const double UPPER_DEFAULT = LARGEST;
+const double POINT4 = 0.4;
+const double ZERO = 0.0;
+const double ONE = 1.0;
+const double TWO = 2.0;
+const double THREE = 3.0;
+const double FOUR = 4.0;
+const double SIX = 6.0;
+const double HALF = 0.5;
+const double ONESIXTH = ONE / SIX;
+const double SIXTH = ONESIXTH;
+const double ONE_THIRD = ONE / THREE;
+const double TWO_THIRDS = TWO / THREE;
+const double THREE_QUARTERS = 0.75;
+const double TWENTY_FOUR = 24.0;
+const int MAX_DEGREE = 3;
+const int HISTORY_MAX = 100;
+const double TEN_EPSILON_MCH = 10.0 * EPSILON_MCH;
+const double ROOTS_TOL = TEN_EPSILON_MCH;
+const double INFINITE_NUMBER = HUGEST;
+
+/** Replacement for FORTRAN's SIGN intrinsic function
+*/
+inline double sign(double x, double y) { return y >= 0.0 ? fabs(x) : -fabs(x); }
+
+//! - - - - - - - - - - - - - - - - - - - - - - -
+//! control derived type with component defaults
+//! - - - - - - - - - - - - - - - - - - - - - - -
+struct control_type {
+ //! maximum degree of Taylor approximant allowed
+ int taylor_max_degree = 3;
+
+ //! any entry of H that is smaller than h_min * MAXVAL( H ) we be treated as
+ // zero
+ double h_min = EPSILON_MCH;
+
+ //! lower and upper bounds on the multiplier, if known
+ double lower = LOWER_DEFAULT;
+ double upper = UPPER_DEFAULT;
+
+ //! stop when | ||x|| - radius | <=
+ //! max( stop_normal * radius, stop_absolute_normal )
+ double stop_normal = EPSILON_MCH;
+ double stop_absolute_normal = EPSILON_MCH;
+
+ //! is the solution is REQUIRED to lie on the boundary (i.e., is the
+ // constraint
+ //! an equality)?
+ bool equality_problem = false;
+};
+
+//! - - - - - - - - - - - - - - - - - - - - - - - -
+//! history derived type with component defaults
+//! - - - - - - - - - - - - - - - - - - - - - - - -
+struct history_type {
+ //
+ //! value of lambda
+ double lambda = 0.0;
+
+ //! corresponding value of ||x(lambda)||_M
+ double x_norm = 0.0;
+};
+
+//! - - - - - - - - - - - - - - - - - - - - - - -
+//! inform derived type with component defaults
+//! - - - - - - - - - - - - - - - - - - - - - - -
+struct inform_type {
+ //
+
+ //! the number of (||x||_M,lambda) pairs in the history
+ int len_history = 0;
+
+ //! the value of the quadratic function
+ double obj = HUGEST;
+
+ //! the M-norm of x, ||x||_M
+ double x_norm = 0.0;
+
+ //! the Lagrange multiplier corresponding to the trust-region constraint
+ double multiplier = 0.0;
+
+ //! a lower bound max(0,-lambda_1), where lambda_1 is the left-most
+ //! eigenvalue of (H,M)
+ double pole = 0.0;
+
+ //! has the hard case occurred?
+ bool hard_case = false;
+
+ //! history information
+ std::vector<history_type> history;
+};
+
+/** Get the largest of the four values.
+* @param a :: Value number 1.
+* @param b :: Value number 2.
+* @param c :: Value number 3.
+* @param d :: Value number 4.
+*/
+double biggest(double a, double b, double c, double d) {
+ return std::max(std::max(a, b), std::max(c, d));
+}
+
+/** Get the largest of the three values.
+* @param a :: Value number 1.
+* @param b :: Value number 2.
+* @param c :: Value number 3.
+*/
+double biggest(double a, double b, double c) {
+ return std::max(std::max(a, b), c);
+}
+
+/** Find the largest by absolute value element of a vector.
+* @param v :: The searched vector.
+*/
+double maxAbsVal(const DoubleFortranVector &v) {
+ auto p = v.indicesOfMinMaxElements();
+ return std::max(fabs(v.get(p.first)), fabs(v.get(p.second)));
+}
+
+/** Find the minimum and maximum elements of a vector.
+* @param v :: The searched vector.
+* @returns :: A pair of doubles where the first is the minimum and
+* the second is the maxumum.
+*/
+std::pair<double, double> minMaxValues(const DoubleFortranVector &v) {
+ auto p = v.indicesOfMinMaxElements();
+ return std::make_pair(v.get(p.first), v.get(p.second));
+}
+
+/** Compute the 2-norm of a vector which is a square root of the
+* sum of squares of its elements.
+* @param v :: The vector.
+*/
+double twoNorm(const DoubleFortranVector &v) {
+ if (v.size() == 0)
+ return 0.0;
+ return gsl_blas_dnrm2(v.gsl());
+}
+
+/** Get the dot-product of two vectors of the same size.
+* @param v1 :: The first vector.
+* @param v2 :: The second vector.
+*/
+double dotProduct(const DoubleFortranVector &v1,
+ const DoubleFortranVector &v2) {
+ return v1.dot(v2);
+}
+
+/** Find the maximum element in the first n elements of a vector.
+* @param v :: The vector.
+* @param n :: The number of elements to examine.
+*/
+double maxVal(const DoubleFortranVector &v, int n) {
+ double res = std::numeric_limits<double>::lowest();
+ for (int i = 1; i <= n; ++i) {
+ auto val = v(i);
+ if (val > res) {
+ res = val;
+ }
+ }
+ return res;
+}
+
+/** Find the number and values of real roots of the quadratic equation
+*
+* a2 * x**2 + a1 * x + a0 = 0
+*
+* where a0, a1 and a2 are real
+* @param a0 :: The free coefficient.
+* @param a1 :: The coefficient at the linear term.
+* @param a2 :: The coefficient at the quadratic term.
+* @param tol :: A tolerance for comparing doubles.
+* @param nroots :: The output number of real roots.
+* @param root1 :: The first real root if nroots > 0.
+* @param root2 :: The second real root if nroots = 2.
+*/
+void rootsQuadratic(double a0, double a1, double a2, double tol, int &nroots,
+ double &root1, double &root2) {
+
+ auto rhs = tol * a1 * a1;
+ if (fabs(a0 * a2) > rhs) { // really is quadratic
+ root2 = a1 * a1 - FOUR * a2 * a0;
+ if (fabs(root2) <= pow(EPSILON_MCH * a1, 2)) { // numerical double root
+ nroots = 2;
+ root1 = -HALF * a1 / a2;
+ root2 = root1;
+ } else if (root2 < ZERO) { // complex not real roots
+ nroots = 0;
+ root1 = ZERO;
+ root2 = ZERO;
+ } else { // distint real roots
+ auto d = -HALF * (a1 + sign(sqrt(root2), a1));
+ nroots = 2;
+ root1 = d / a2;
+ root2 = a0 / d;
+ if (root1 > root2) {
+ d = root1;
+ root1 = root2;
+ root2 = d;
+ }
+ }
+ } else if (a2 == ZERO) {
+ if (a1 == ZERO) {
+ if (a0 == ZERO) { // the function is zero
+ nroots = 1;
+ root1 = ZERO;
+ root2 = ZERO;
+ } else { // the function is constant
+ nroots = 0;
+ root1 = ZERO;
+ root2 = ZERO;
+ }
+ } else { // the function is linear
+ nroots = 1;
+ root1 = -a0 / a1;
+ root2 = ZERO;
+ }
+ } else { // very ill-conditioned quadratic
+ nroots = 2;
+ if (-a1 / a2 > ZERO) {
+ root1 = ZERO;
+ root2 = -a1 / a2;
+ } else {
+ root1 = -a1 / a2;
+ root2 = ZERO;
+ }
+ }
+
+ // perfom a Newton iteration to ensure that the roots are accurate
+
+ if (nroots >= 1) {
+ auto p = (a2 * root1 + a1) * root1 + a0;
+ auto pprime = TWO * a2 * root1 + a1;
+ if (pprime != ZERO) {
+ root1 = root1 - p / pprime;
+ }
+ if (nroots == 2) {
+ p = (a2 * root2 + a1) * root2 + a0;
+ pprime = TWO * a2 * root2 + a1;
+ if (pprime != ZERO) {
+ root2 = root2 - p / pprime;
+ }
+ }
+ }
+}
+
+/** Find the number and values of real roots of the cubic equation
+*
+* a3 * x**3 + a2 * x**2 + a1 * x + a0 = 0
+*
+* where a0, a1, a2 and a3 are real
+* @param a0 :: The free coefficient.
+* @param a1 :: The coefficient at the linear term.
+* @param a2 :: The coefficient at the quadratic term.
+* @param a3 :: The coefficient at the cubic term.
+* @param tol :: A tolerance for comparing doubles.
+* @param nroots :: The output number of real roots.
+* @param root1 :: The first real root.
+* @param root2 :: The second real root if nroots > 1.
+* @param root3 :: The third real root if nroots == 3.
+*/
+void rootsCubic(double a0, double a1, double a2, double a3, double tol,
+ int &nroots, double &root1, double &root2, double &root3) {
+
+ // Check to see if the cubic is actually a quadratic
+ if (a3 == ZERO) {
+ rootsQuadratic(a0, a1, a2, tol, nroots, root1, root2);
+ root3 = INFINITE_NUMBER;
+ return;
+ }
+
+ // Deflate the polnomial if the trailing coefficient is zero
+ if (a0 == ZERO) {
+ root1 = ZERO;
+ rootsQuadratic(a1, a2, a3, tol, nroots, root2, root3);
+ nroots = nroots + 1;
+ return;
+ }
+
+ // 1. Use Nonweiler's method (CACM 11:4, 1968, pp269)
+
+ double c0 = a0 / a3;
+ double c1 = a1 / a3;
+ double c2 = a2 / a3;
+
+ double s = c2 / THREE;
+ double t = s * c2;
+ double b = 0.5 * (s * (TWO_THIRDS * t - c1) + c0);
+ t = (t - c1) / THREE;
+ double c = t * t * t;
+ double d = b * b - c;
+
+ // 1 real + 2 equal real or 2 complex roots
+ if (d >= ZERO) {
+ d = pow(sqrt(d) + fabs(b), ONE_THIRD);
+ if (d != ZERO) {
+ if (b > ZERO) {
+ b = -d;
+ } else {
+ b = d;
+ }
+ c = t / b;
+ }
+ d = sqrt(THREE_QUARTERS) * (b - c);
+ b = b + c;
+ c = -0.5 * b - s;
+ root1 = b - s;
+ if (d == ZERO) {
+ nroots = 3;
+ root2 = c;
+ root3 = c;
+ } else {
+ nroots = 1;
+ }
+ } else { // 3 real roots
+ if (b == ZERO) {
+ d = TWO_THIRDS * atan(ONE);
+ } else {
+ d = atan(sqrt(-d) / fabs(b)) / THREE;
+ }
+ if (b < ZERO) {
+ b = TWO * sqrt(t);
+ } else {
+ b = -TWO * sqrt(t);
+ }
+ c = cos(d) * b;
+ t = -sqrt(THREE_QUARTERS) * sin(d) * b - HALF * c;
+ d = -t - c - s;
+ c = c - s;
+ t = t - s;
+ if (fabs(c) > fabs(t)) {
+ root3 = c;
+ } else {
+ root3 = t;
+ t = c;
+ }
+ if (fabs(d) > fabs(t)) {
+ root2 = d;
+ } else {
+ root2 = t;
+ t = d;
+ }
+ root1 = t;
+ nroots = 3;
+ }
+
+ // reorder the roots
+
+ if (nroots == 3) {
+ if (root1 > root2) {
+ double a = root2;
+ root2 = root1;
+ root1 = a;
+ }
+ if (root2 > root3) {
+ double a = root3;
+ if (root1 > root3) {
+ a = root1;
+ root1 = root3;
+ }
+ root3 = root2;
+ root2 = a;
+ }
+ }
+
+ // perfom a Newton iteration to ensure that the roots are accurate
+ double p = ((a3 * root1 + a2) * root1 + a1) * root1 + a0;
+ double pprime = (THREE * a3 * root1 + TWO * a2) * root1 + a1;
+ if (pprime != ZERO) {
+ root1 = root1 - p / pprime;
+ // p = ((a3 * root1 + a2) * root1 + a1) * root1 + a0; // never used
+ }
+
+ if (nroots == 3) {
+ p = ((a3 * root2 + a2) * root2 + a1) * root2 + a0;
+ pprime = (THREE * a3 * root2 + TWO * a2) * root2 + a1;
+ if (pprime != ZERO) {
+ root2 = root2 - p / pprime;
+ // p = ((a3 * root2 + a2) * root2 + a1) * root2 + a0; // never used
+ }
+
+ p = ((a3 * root3 + a2) * root3 + a1) * root3 + a0;
+ pprime = (THREE * a3 * root3 + TWO * a2) * root3 + a1;
+ if (pprime != ZERO) {
+ root3 = root3 - p / pprime;
+ // p = ((a3 * root3 + a2) * root3 + a1) * root3 + a0; // never used
+ }
+ }
+}
+
+/** Compute pi_beta = ||x||^beta and its derivatives
+* Extracted wholesale from module RAL_NLLS_RQS
+*
+* @param max_order :: Maximum order of derivative.
+* @param beta :: Power.
+* @param x_norm2 :: (0) value of ||x||^2,
+* (i) ith derivative of ||x||^2, i = 1, max_order
+* @param pi_beta :: (0) value of ||x||^beta,
+* (i) ith derivative of ||x||^beta, i = 1, max_order
+*/
+void PiBetaDerivs(int max_order, double beta,
+ const DoubleFortranVector &x_norm2,
+ DoubleFortranVector &pi_beta) {
+ double hbeta = HALF * beta;
+ pi_beta(0) = pow(x_norm2(0), hbeta);
+ pi_beta(1) = hbeta * (pow(x_norm2(0), (hbeta - ONE))) * x_norm2(1);
+ if (max_order == 1)
+ return;
+ pi_beta(2) = hbeta * (pow(x_norm2(0), (hbeta - TWO))) *
+ ((hbeta - ONE) * pow(x_norm2(1), 2) + x_norm2(0) * x_norm2(2));
+ if (max_order == 2)
+ return;
+ pi_beta(3) = hbeta * (pow(x_norm2(0), (hbeta - THREE))) *
+ (x_norm2(3) * pow(x_norm2(0), 2) +
+ (hbeta - ONE) * (THREE * x_norm2(0) * x_norm2(1) * x_norm2(2) +
+ (hbeta - TWO) * pow(x_norm2(1), 3)));
+}
+
+/** Set initial values for the TRS control parameters
+*
+* @param control :: A structure containing control information.
+*/
+void intitializeControl(control_type &control) {
+ control.stop_normal = pow(EPSILON_MCH, 0.75);
+ control.stop_absolute_normal = pow(EPSILON_MCH, 0.75);
+}
+
+/** Solve the trust-region subproblem
+*
+* minimize 1/2 <x, H x> + <c, x> + f
+* subject to ||x||_2 <= radius or ||x||_2 = radius
+*
+* where H is diagonal, using a secular iteration
+*
+* @param n :: The number of unknowns.
+* @param radius :: The trust-region radius.
+* @param f :: The value of constant term for the quadratic function
+* @param c :: A vector of values for the linear term c.
+* @param h :: A vector of values for the diagonal matrix H.
+* @param x :: The required solution vector x.
+* @param control :: A structure containing control information.
+* @param inform :: A structure containing information.
+*/
+void solveSubproblemMain(int n, double radius, double f,
+ const DoubleFortranVector &c,
+ const DoubleFortranVector &h, DoubleFortranVector &x,
+ const control_type &control, inform_type &inform) {
+
+ // set initial values
+
+ if (x.len() != n) {
+ x.allocate(n);
+ }
+ x.zero();
+ inform.x_norm = ZERO;
+ inform.obj = f;
+ inform.hard_case = false;
+ double delta_lambda = ZERO;
+
+ // Check that arguments are OK
+ if (n < 0) {
+ throw std::runtime_error(
+ "Number of unknowns for trust-region subproblem is negative.");
+ }
+ if (radius < 0) {
+ throw std::runtime_error(
+ "Trust-region radius for trust-region subproblem is negative");
+ }
+
+ DoubleFortranVector x_norm2(0, MAX_DEGREE), pi_beta(0, MAX_DEGREE);
+
+ // compute the two-norm of c and the extreme eigenvalues of H
+
+ double c_norm = twoNorm(c);
+ double lambda_min = 0.0;
+ double lambda_max = 0.0;
+ std::tie(lambda_min, lambda_max) = minMaxValues(h);
+
+ double lambda = 0.0;
+ //! check for the trivial case
+ if (c_norm == ZERO && lambda_min >= ZERO) {
+ if (control.equality_problem) {
+ int i_hard = 1; // TODO: is init value of 1 correct?
+ for (int i = 1; i <= n; ++i) { // do i = 1, n
+ if (h(i) == lambda_min) {
+ i_hard = i;
+ break;
+ }
+ }
+ x(i_hard) = ONE / radius;
+ inform.x_norm = radius;
+ inform.obj = f + lambda_min * radius * radius;
+ }
+ return;
+ }
+
+ // construct values lambda_l and lambda_u for which lambda_l <=
+ // lambda_optimal
+ // <= lambda_u, and ensure that all iterates satisfy lambda_l <= lambda
+ // <= lambda_u
+
+ double c_norm_over_radius = c_norm / radius;
+ double lambda_l = 0.0, lambda_u = 0.0;
+ if (control.equality_problem) {
+ lambda_l =
+ biggest(control.lower, -lambda_min, c_norm_over_radius - lambda_max);
+ lambda_u = std::min(control.upper, c_norm_over_radius - lambda_min);
+ } else {
+ lambda_l = biggest(control.lower, ZERO, -lambda_min,
+ c_norm_over_radius - lambda_max);
+ lambda_u = std::min(control.upper,
+ std::max(ZERO, c_norm_over_radius - lambda_min));
+ }
+ lambda = lambda_l;
+
+ // check for the "hard case"
+ if (lambda == -lambda_min) {
+ int i_hard = 1; // TODO: is init value of 1 correct?
+ double c2 = ZERO;
+ inform.hard_case = true;
+ for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
+ if (h(i) == lambda_min) {
+ if (fabs(c(i)) > EPSILON_MCH * c_norm) {
+ inform.hard_case = false;
+ c2 = c2 + pow(c(i), 2);
+ } else {
+ i_hard = i;
+ }
+ }
+ }
+
+ // the hard case may occur
+ if (inform.hard_case) {
+ for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
+ if (h(i) != lambda_min) {
+ x(i) = -c(i) / (h(i) + lambda);
+ } else {
+ x(i) = ZERO;
+ }
+ }
+ inform.x_norm = twoNorm(x);
+
+ // the hard case does occur
+
+ if (inform.x_norm <= radius) {
+ if (inform.x_norm < radius) {
+
+ // compute the step alpha so that x + alpha e_i_hard lies on the
+ // trust-region
+ // boundary and gives the smaller value of q
+
+ auto utx = x(i_hard) / radius;
+ auto distx =
+ (radius - inform.x_norm) * ((radius + inform.x_norm) / radius);
+ auto alpha = sign(
+ distx / (fabs(utx) + sqrt(pow(utx, 2) + distx / radius)), utx);
+
+ // record the optimal values
+
+ x(i_hard) = x(i_hard) + alpha;
+ }
+ inform.x_norm = twoNorm(x);
+ inform.obj = f + HALF * (dotProduct(c, x) - lambda * pow(radius, 2));
+ return;
+
+ // the hard case didn't occur after all
+ } else {
+ inform.hard_case = false;
+
+ // compute the first derivative of ||x|(lambda)||^2 - radius^2
+ auto w_norm2 = ZERO;
+ for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
+ if (h(i) != lambda_min)
+ w_norm2 = w_norm2 + pow(c(i), 2) / pow((h(i) + lambda), 3);
+ }
+ x_norm2(1) = -TWO * w_norm2;
+
+ // compute the newton correction
+
+ lambda = lambda + (pow(inform.x_norm, 2) - pow(radius, 2)) / x_norm2(1);
+ lambda_l = std::max(lambda_l, lambda);
+ }
+
+ // there is a singularity at lambda. compute the point for which the
+ // sum of squares of the singular terms is equal to radius^2
+ } else {
+ lambda = lambda + std::max(sqrt(c2) / radius, lambda * EPSILON_MCH);
+ lambda_l = std::max(lambda_l, lambda);
+ }
+ }
+
+ // the iterates will all be in the L region. Prepare for the main loop
+ auto max_order = std::max(1, std::min(MAX_DEGREE, control.taylor_max_degree));
+
+ // start the main loop
+ for (;;) {
+
+ // if h(lambda) is positive definite, solve h(lambda) x = - c
+
+ for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
+ x(i) = -c(i) / (h(i) + lambda);
+ }
+
+ // compute the two-norm of x
+ inform.x_norm = twoNorm(x);
+ x_norm2(0) = pow(inform.x_norm, 2);
+
+ // if the newton step lies within the trust region, exit
+
+ if (lambda == ZERO && inform.x_norm <= radius) {
+ inform.obj = f + HALF * dotProduct(c, x);
+ return;
+ }
+
+ //! the current estimate gives a good approximation to the required
+ //! root
+
+ if (fabs(inform.x_norm - radius) <=
+ std::max(control.stop_normal * radius, control.stop_absolute_normal)) {
+ break;
+ }
+
+ lambda_l = std::max(lambda_l, lambda);
+
+ // record, for the future, values of lambda which give small ||x||
+ if (inform.len_history < HISTORY_MAX) {
+ history_type history_item;
+ history_item.lambda = lambda;
+ history_item.x_norm = inform.x_norm;
+ inform.history.push_back(history_item);
+ inform.len_history = inform.len_history + 1;
+ }
+
+ // a lambda in L has been found. It is now simply a matter of applying
+ // a variety of Taylor-series-based methods starting from this lambda
+
+ // precaution against rounding producing lambda outside L
+
+ if (lambda > lambda_u) {
+ throw std::runtime_error(
+ "Lambda for trust-region subproblem is ill conditioned");
+ }
+
+ // compute first derivatives of x^T M x
+
+ // form ||w||^2 = x^T H^-1(lambda) x
+
+ double w_norm2 = ZERO;
+ for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
+ w_norm2 = w_norm2 + pow(c(i), 2) / pow(h(i) + lambda, 3);
+ }
+
+ // compute the first derivative of x_norm2 = x^T M x
+ x_norm2(1) = -TWO * w_norm2;
+
+ // compute pi_beta = ||x||^beta and its first derivative when beta = - 1
+ double beta = -ONE;
+ PiBetaDerivs(1, beta, x_norm2, pi_beta);
+
+ // compute the Newton correction (for beta = - 1)
+
+ delta_lambda = -(pi_beta(0) - pow((radius), beta)) / pi_beta(1);
+
+ DoubleFortranVector lambda_new(3);
+ int n_lambda = 1;
+ lambda_new(n_lambda) = lambda + delta_lambda;
+
+ if (max_order >= 3) {
+
+ // compute the second derivative of x^T x
+
+ double z_norm2 = ZERO;
+ for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
+ z_norm2 = z_norm2 + pow(c(i), 2) / pow((h(i) + lambda), 4);
+ }
+ x_norm2(2) = SIX * z_norm2;
+
+ // compute the third derivatives of x^T x
+
+ double v_norm2 = ZERO;
+ for (int i = 1; i <= n; ++i) { // for_do(i, 1, n)
+ v_norm2 = v_norm2 + pow(c(i), 2) / pow((h(i) + lambda), 5);
+ }
+ x_norm2(3) = -TWENTY_FOUR * v_norm2;
+
+ // compute pi_beta = ||x||^beta and its derivatives when beta = 2
+
+ beta = TWO;
+ PiBetaDerivs(max_order, beta, x_norm2, pi_beta);
+
+ // compute the "cubic Taylor approximaton" step (beta = 2)
+
+ auto a_0 = pi_beta(0) - pow((radius), beta);
+ auto a_1 = pi_beta(1);
+ auto a_2 = HALF * pi_beta(2);
+ auto a_3 = SIXTH * pi_beta(3);
+ auto a_max = biggest(fabs(a_0), fabs(a_1), fabs(a_2), fabs(a_3));
+ if (a_max > ZERO) {
+ a_0 = a_0 / a_max;
+ a_1 = a_1 / a_max;
+ a_2 = a_2 / a_max;
+ a_3 = a_3 / a_max;
+ }
+ int nroots = 0;
+ double root1 = 0, root2 = 0, root3 = 0;
+
+ rootsCubic(a_0, a_1, a_2, a_3, ROOTS_TOL, nroots, root1, root2, root3);
+ n_lambda = n_lambda + 1;
+ if (nroots == 3) {
+ lambda_new(n_lambda) = lambda + root3;
+ } else {
+ lambda_new(n_lambda) = lambda + root1;
+ }
+
+ // compute pi_beta = ||x||^beta and its derivatives when beta = - 0.4
+
+ beta = -POINT4;
+ PiBetaDerivs(max_order, beta, x_norm2, pi_beta);
+
+ // compute the "cubic Taylor approximaton" step (beta = - 0.4)
+
+ a_0 = pi_beta(0) - pow((radius), beta);
+ a_1 = pi_beta(1);
+ a_2 = HALF * pi_beta(2);
+ a_3 = SIXTH * pi_beta(3);
+ a_max = biggest(fabs(a_0), fabs(a_1), fabs(a_2), fabs(a_3));
+ if (a_max > ZERO) {
+ a_0 = a_0 / a_max;
+ a_1 = a_1 / a_max;
+ a_2 = a_2 / a_max;
+ a_3 = a_3 / a_max;
+ }
+ rootsCubic(a_0, a_1, a_2, a_3, ROOTS_TOL, nroots, root1, root2, root3);
+ n_lambda = n_lambda + 1;
+ if (nroots == 3) {
+ lambda_new(n_lambda) = lambda + root3;
+ } else {
+ lambda_new(n_lambda) = lambda + root1;
+ }
+ }
+
+ // compute the best Taylor improvement
+
+ auto lambda_plus = maxVal(lambda_new, n_lambda);
+ delta_lambda = lambda_plus - lambda;
+ lambda = lambda_plus;
+
+ // improve the lower bound if possible
+
+ lambda_l = std::max(lambda_l, lambda_plus);
+
+ // check that the best Taylor improvement is significant
+
+ if (fabs(delta_lambda) < EPSILON_MCH * std::max(ONE, fabs(lambda))) {
+ break;
+ }
+
+ } // for(;;)
+}
+
+/** Solve the trust-region subproblem
+*
+* minimize q(x) = 1/2 <x, H x> + <c, x> + f
+* subject to ||x||_2 <= radius or ||x||_2 = radius
+*
+* where H is diagonal, using a secular iteration
+*
+* @param n :: The number of unknowns.
+* @param radius :: The trust-region radius.
+* @param f :: The value of constant term for the quadratic function.
+* @param c :: A vector of values for the linear term c.
+* @param h :: A vector of values for the diagonal matrix H.
+* @param x :: The required solution vector x.
+* @param control :: A structure containing control information.
+* @param inform :: A structure containing information.
+*/
+void solveSubproblem(int n, double radius, double f,
+ const DoubleFortranVector &c, const DoubleFortranVector &h,
+ DoubleFortranVector &x, const control_type &control,
+ inform_type &inform) {
+ // scale the problem to solve instead
+ // minimize q_s(x_s) = 1/2 <x_s, H_s x_s> + <c_s, x_s> + f_s
+ // subject to ||x_s||_2 <= radius_s or ||x_s||_2 = radius_s
+
+ // where H_s = H / s_h and c_s = c / s_c for scale factors s_h and s_c
+
+ // This corresponds to
+ // radius_s = ( s_h / s_c ) radius,
+ // f_s = ( s_h / s_c^2 ) f
+ // and the solution may be recovered as
+ // x = ( s_c / s_h ) x_s
+ // lambda = s_h lambda_s
+ // q(x) = ( s_c^2 / s_ h ) q_s(x_s)
+
+ // scale H by the largest H and remove relatively tiny H
+
+ DoubleFortranVector h_scale(n);
+ auto scale_h = maxAbsVal(h); // MAXVAL( ABS( H ) )
+ if (scale_h > ZERO) {
+ for (int i = 1; i <= n; ++i) { // do i = 1, n
+ if (fabs(h(i)) >= control.h_min * scale_h) {
+ h_scale(i) = h(i) / scale_h;
+ } else {
+ h_scale(i) = ZERO;
+ }
+ }
+ } else {
+ scale_h = ONE;
+ h_scale.zero();
+ }
+
+ // scale c by the largest c and remove relatively tiny c
+
+ DoubleFortranVector c_scale(n);
+ auto scale_c = maxAbsVal(c); // maxval( abs( c ) )
+ if (scale_c > ZERO) {
+ for (int i = 1; i <= n; ++i) { // do i = 1, n
+ if (fabs(c(i)) >= control.h_min * scale_c) {
+ c_scale(i) = c(i) / scale_c;
+ } else {
+ c_scale(i) = ZERO;
+ }
+ }
+ } else {
+ scale_c = ONE;
+ c_scale.zero();
+ }
+
+ double radius_scale = (scale_h / scale_c) * radius;
+ double f_scale = (scale_h / pow(scale_c, 2)) * f;
+
+ auto control_scale = control;
+ if (control_scale.lower != LOWER_DEFAULT) {
+ control_scale.lower = control_scale.lower / scale_h;
+ }
+ if (control_scale.upper != UPPER_DEFAULT) {
+ control_scale.upper = control_scale.upper / scale_h;
+ }
+
+ // solve the scaled problem
+
+ solveSubproblemMain(n, radius_scale, f_scale, c_scale, h_scale, x,
+ control_scale, inform);
+
+ // unscale the solution, function value, multiplier and related values
+
+ // x = ( scale_c / scale_h ) * x
+ x *= scale_c / scale_h;
+ inform.obj *= pow(scale_c, 2) / scale_h;
+ inform.multiplier *= scale_h;
+ inform.pole *= scale_h;
+ for (size_t i = 0; i < inform.history.size();
+ ++i) { // do i = 1, inform.len_history
+ inform.history[i].lambda *= scale_h;
+ inform.history[i].x_norm *= scale_c / scale_h;
+ }
+}
+
+} // namespace
+
+/** Solve the trust-region subproblem using
+* the DTRS method from Galahad
+*
+* This method needs H to be diagonal, so we need to
+* pre-process
+*
+* main output d, the soln to the TR subproblem
+* @param J :: The Jacobian.
+* @param f :: The residuals.
+* @param hf :: The Hessian (sort of).
+* @param Delta :: The raduis of the trust region.
+* @param d :: The output vector of corrections to the parameters giving the
+* solution to the TR subproblem.
+* @param normd :: The 2-norm of d.
+* @param options :: The options.
+*/
+void TrustRegionMinimizer::calculateStep(const DoubleFortranMatrix &J,
+ const DoubleFortranVector &f,
+ const DoubleFortranMatrix &hf,
+ double Delta, DoubleFortranVector &d,
+ double &normd,
+ const NLLS::nlls_options &options) {
+
+ control_type controlOptions;
+ inform_type inform;
+
+ // The code finds
+ // d = arg min_p w^T p + 0.5 * p^T D p
+ // s.t. ||p|| \leq Delta
+ //
+ // where D is diagonal
+ //
+ // our probem in naturally in the form
+ //
+ // d = arg min_p v^T p + 0.5 * p^T H p
+ // s.t. ||p|| \leq Delta
+ //
+ // first, find the matrix H and vector v
+ // Set A = J^T J
+ NLLS::matmultInner(J, m_A);
+ // add any second order information...
+ // so A = J^T J + HF
+ m_A += hf;
+
+ // now form v = J^T f
+ NLLS::multJt(J, f, m_v);
+
+ // if scaling needed, do it
+ if (options.scale != 0) {
+ applyScaling(J, m_A, m_v, m_scale, options);
+ }
+
+ // Now that we have the unprocessed matrices, we need to get an
+ // eigendecomposition to make A diagonal
+ //
+ NLLS::allEigSymm(m_A, m_ew, m_ev);
+
+ // We can now change variables, setting y = Vp, getting
+ // Vd = arg min_(Vx) v^T p + 0.5 * (Vp)^T D (Vp)
+ // s.t. ||x|| \leq Delta
+ // <=>
+ // Vd = arg min_(Vx) V^Tv^T (Vp) + 0.5 * (Vp)^T D (Vp)
+ // s.t. ||x|| \leq Delta
+ // <=>
+ // we need to get the transformed vector v
+ NLLS::multJt(m_ev, m_v, m_v_trans);
+
+ // we've now got the vectors we need, pass to solveSubproblem
+ intitializeControl(controlOptions);
+
+ auto n = J.len2();
+ if (m_v_trans.len() != n) {
+ m_v_trans.allocate(n);
+ }
+
+ for (int ii = 1; ii <= n; ++ii) { // for_do(ii, 1,n)
+ if (fabs(m_v_trans(ii)) < EPSILON_MCH) {
+ m_v_trans(ii) = ZERO;
+ }
+ if (fabs(m_ew(ii)) < EPSILON_MCH) {
+ m_ew(ii) = ZERO;
+ }
+ }
+
+ solveSubproblem(n, Delta, ZERO, m_v_trans, m_ew, m_d_trans, controlOptions,
+ inform);
+
+ // and return the un-transformed vector
+ NLLS::multJ(m_ev, m_d_trans, d);
+
+ normd = NLLS::norm2(d); // ! ||d||_D
+
+ if (options.scale != 0) {
+ for (int ii = 1; ii <= n; ++ii) { // for_do(ii, 1, n)
+ d(ii) = d(ii) / m_scale(ii);
+ }
+ }
+
+} // calculateStep
+
/** Return the current value of the cost function.
*/
double TrustRegionMinimizer::costFunctionVal() { return m_leastSquares->val(); }
diff --git a/Framework/CurveFitting/test/FuncMinimizers/MoreSorensenTest.h b/Framework/CurveFitting/test/FuncMinimizers/MoreSorensenTest.h
deleted file mode 100644
index 5d4265a6da5b158951c5137a3083972abe210cc5..0000000000000000000000000000000000000000
--- a/Framework/CurveFitting/test/FuncMinimizers/MoreSorensenTest.h
+++ /dev/null
@@ -1,329 +0,0 @@
-#ifndef CURVEFITTING_MORESORNSENTTEST_H_
-#define CURVEFITTING_MORESORNSENTTEST_H_
-
-#include <cxxtest/TestSuite.h>
-
-#include "MantidCurveFitting/CostFunctions/CostFuncLeastSquares.h"
-#include "MantidCurveFitting/FuncMinimizers/MoreSorensenMinimizer.h"
-#include "MantidCurveFitting/Functions/UserFunction.h"
-#include "MantidAPI/FunctionDomain1D.h"
-#include "MantidAPI/FunctionValues.h"
-#include "MantidCurveFitting/Constraints/BoundaryConstraint.h"
-
-#include <sstream>
-
-using namespace Mantid;
-using namespace Mantid::CurveFitting;
-using namespace Mantid::CurveFitting::FuncMinimisers;
-using namespace Mantid::CurveFitting::CostFunctions;
-using namespace Mantid::CurveFitting::Constraints;
-using namespace Mantid::CurveFitting::Functions;
-using namespace Mantid::API;
-
-class MoreSorensenTest : public CxxTest::TestSuite {
-public:
- // This pair of boilerplate methods prevent the suite being created statically
- // This means the constructor isn't called when running other tests
- static MoreSorensenTest *createSuite() { return new MoreSorensenTest(); }
- static void destroySuite(MoreSorensenTest *suite) { delete suite; }
-
- void test_Linear() {
- API::FunctionDomain1D_sptr domain(
- new API::FunctionDomain1DVector(0.0, 10.0, 20));
- API::FunctionValues mockData(*domain);
- UserFunction dataMaker;
- dataMaker.setAttributeValue("Formula", "a*x+b");
- dataMaker.setParameter("a", 1.1);
- dataMaker.setParameter("b", 2.2);
- dataMaker.function(*domain, mockData);
-
- API::FunctionValues_sptr values(new API::FunctionValues(*domain));
- values->setFitDataFromCalculated(mockData);
- values->setFitWeights(1.0);
-
- boost::shared_ptr<UserFunction> fun = boost::make_shared<UserFunction>();
- fun->setAttributeValue("Formula", "a*x+b");
- fun->setParameter("a", 1.);
- fun->setParameter("b", 2.);
-
- boost::shared_ptr<CostFuncLeastSquares> costFun =
- boost::make_shared<CostFuncLeastSquares>();
- costFun->setFittingFunction(fun, domain, values);
- TS_ASSERT_EQUALS(costFun->nParams(), 2);
-
- MoreSorensenMinimizer s;
- s.initialize(costFun);
- TS_ASSERT(s.minimize());
-
- TS_ASSERT_DELTA(fun->getParameter("a"), 1.1, 0.01);
- TS_ASSERT_DELTA(fun->getParameter("b"), 2.2, 0.01);
- TS_ASSERT_EQUALS(s.getError(), "success");
- }
-
- void test_Gaussian() {
- API::FunctionDomain1D_sptr domain(
- new API::FunctionDomain1DVector(0.0, 10.0, 20));
- API::FunctionValues mockData(*domain);
- UserFunction dataMaker;
- dataMaker.setAttributeValue("Formula", "a*x+b+h*exp(-s*x^2)");
- dataMaker.setParameter("a", 1.1);
- dataMaker.setParameter("b", 2.2);
- dataMaker.setParameter("h", 3.3);
- dataMaker.setParameter("s", 0.2);
- dataMaker.function(*domain, mockData);
-
- API::FunctionValues_sptr values(new API::FunctionValues(*domain));
- values->setFitDataFromCalculated(mockData);
- values->setFitWeights(1.0);
-
- boost::shared_ptr<UserFunction> fun = boost::make_shared<UserFunction>();
- fun->setAttributeValue("Formula", "a*x+b+h*exp(-s*x^2)");
- fun->setParameter("a", 1.);
- fun->setParameter("b", 2.);
- fun->setParameter("h", 3.);
- fun->setParameter("s", 0.1);
-
- boost::shared_ptr<CostFuncLeastSquares> costFun =
- boost::make_shared<CostFuncLeastSquares>();
- costFun->setFittingFunction(fun, domain, values);
-
- MoreSorensenMinimizer s;
- s.initialize(costFun);
- TS_ASSERT(s.minimize());
- TS_ASSERT_DELTA(costFun->val(), 0.0, 0.0001);
- TS_ASSERT_DELTA(fun->getParameter("a"), 1.1, 0.001);
- TS_ASSERT_DELTA(fun->getParameter("b"), 2.2, 0.001);
- TS_ASSERT_DELTA(fun->getParameter("h"), 3.3, 0.001);
- TS_ASSERT_DELTA(fun->getParameter("s"), 0.2, 0.001);
- TS_ASSERT_EQUALS(s.getError(), "success");
- }
-
- void test_Gaussian_fixed() {
- API::FunctionDomain1D_sptr domain(
- new API::FunctionDomain1DVector(0.0, 10.0, 20));
- API::FunctionValues mockData(*domain);
- UserFunction dataMaker;
- dataMaker.setAttributeValue("Formula", "a*x+b+h*exp(-s*x^2)");
- dataMaker.setParameter("a", 1.1);
- dataMaker.setParameter("b", 2.2);
- dataMaker.setParameter("h", 3.3);
- dataMaker.setParameter("s", 0.2);
- dataMaker.function(*domain, mockData);
-
- API::FunctionValues_sptr values(new API::FunctionValues(*domain));
- values->setFitDataFromCalculated(mockData);
- values->setFitWeights(1.0);
-
- boost::shared_ptr<UserFunction> fun = boost::make_shared<UserFunction>();
- fun->setAttributeValue("Formula", "a*x+b+h*exp(-s*x^2)");
- fun->setParameter("a", 1.);
- fun->setParameter("b", 2.5);
- fun->setParameter("h", 3.);
- fun->setParameter("s", 0.1);
- fun->fix(0);
-
- boost::shared_ptr<CostFuncLeastSquares> costFun =
- boost::make_shared<CostFuncLeastSquares>();
- costFun->setFittingFunction(fun, domain, values);
- TS_ASSERT_EQUALS(costFun->nParams(), 3);
-
- MoreSorensenMinimizer s;
- s.initialize(costFun);
- TS_ASSERT(s.minimize());
- TS_ASSERT_DELTA(costFun->val(), 0.2, 0.01);
- TS_ASSERT_DELTA(fun->getParameter("a"), 1., 0.000001);
- TS_ASSERT_DELTA(fun->getParameter("b"), 2.90, 0.01);
- TS_ASSERT_DELTA(fun->getParameter("h"), 2.67, 0.01);
- TS_ASSERT_DELTA(fun->getParameter("s"), 0.27, 0.01);
- TS_ASSERT_EQUALS(s.getError(), "success");
- }
-
- void test_Gaussian_tied() {
- API::FunctionDomain1D_sptr domain(
- new API::FunctionDomain1DVector(0.0, 10.0, 20));
- API::FunctionValues mockData(*domain);
- UserFunction dataMaker;
- dataMaker.setAttributeValue("Formula", "a*x+b+h*exp(-s*x^2)");
- dataMaker.setParameter("a", 1.1);
- dataMaker.setParameter("b", 2.2);
- dataMaker.setParameter("h", 3.3);
- dataMaker.setParameter("s", 0.2);
- dataMaker.function(*domain, mockData);
-
- API::FunctionValues_sptr values(new API::FunctionValues(*domain));
- values->setFitDataFromCalculated(mockData);
- values->setFitWeights(1.0);
-
- boost::shared_ptr<UserFunction> fun = boost::make_shared<UserFunction>();
- fun->setAttributeValue("Formula", "a*x+b+h*exp(-s*x^2)");
- fun->setParameter("a", 1.);
- fun->setParameter("b", 2.5);
- fun->setParameter("h", 3.);
- fun->setParameter("s", 0.1);
- fun->tie("a", "1");
-
- boost::shared_ptr<CostFuncLeastSquares> costFun =
- boost::make_shared<CostFuncLeastSquares>();
- costFun->setFittingFunction(fun, domain, values);
- TS_ASSERT_EQUALS(costFun->nParams(), 3);
-
- MoreSorensenMinimizer s;
- s.initialize(costFun);
- TS_ASSERT(s.minimize());
- TS_ASSERT_DELTA(costFun->val(), 0.2, 0.01);
- TS_ASSERT_DELTA(fun->getParameter("a"), 1., 0.000001);
- TS_ASSERT_DELTA(fun->getParameter("b"), 2.90, 0.01);
- TS_ASSERT_DELTA(fun->getParameter("h"), 2.67, 0.01);
- TS_ASSERT_DELTA(fun->getParameter("s"), 0.27, 0.01);
- TS_ASSERT_EQUALS(s.getError(), "success");
- }
-
- void xtest_Gaussian_tied_with_formula() {
- API::FunctionDomain1D_sptr domain(
- new API::FunctionDomain1DVector(0.0, 10.0, 20));
- API::FunctionValues mockData(*domain);
- UserFunction dataMaker;
- dataMaker.setAttributeValue("Formula", "a*x+b+h*exp(-s*x^2)");
- dataMaker.setParameter("a", 1.1);
- dataMaker.setParameter("b", 2.2);
- dataMaker.setParameter("h", 3.3);
- dataMaker.setParameter("s", 0.2);
- dataMaker.function(*domain, mockData);
-
- API::FunctionValues_sptr values(new API::FunctionValues(*domain));
- values->setFitDataFromCalculated(mockData);
- values->setFitWeights(1.0);
-
- boost::shared_ptr<UserFunction> fun = boost::make_shared<UserFunction>();
- fun->setAttributeValue("Formula", "a*x+b+h*exp(-s*x^2)");
- fun->setParameter("a", 1.);
- fun->setParameter("b", 2.);
- fun->setParameter("h", 3.);
- fun->setParameter("s", 0.1);
- fun->tie("b", "2*a+0.1");
-
- boost::shared_ptr<CostFuncLeastSquares> costFun =
- boost::make_shared<CostFuncLeastSquares>();
- costFun->setFittingFunction(fun, domain, values);
- TS_ASSERT_EQUALS(costFun->nParams(), 3);
-
- MoreSorensenMinimizer s;
- s.initialize(costFun);
- TS_ASSERT(s.minimize());
- TS_ASSERT_DELTA(costFun->val(), 0.002, 0.01);
-
- double a = fun->getParameter("a");
- TS_ASSERT_DELTA(a, 1.0895, 0.01);
- TS_ASSERT_DELTA(fun->getParameter("b"), 2 * a + 0.1, 0.0001);
- TS_ASSERT_DELTA(fun->getParameter("h"), 3.23, 0.01);
- TS_ASSERT_DELTA(fun->getParameter("s"), 0.207, 0.001);
- TS_ASSERT_EQUALS(s.getError(), "success");
- }
-
- void xtest_Linear_constrained() {
- API::FunctionDomain1D_sptr domain(
- new API::FunctionDomain1DVector(0.0, 10.0, 20));
- API::FunctionValues mockData(*domain);
- UserFunction dataMaker;
- dataMaker.setAttributeValue("Formula", "a*x+b");
- dataMaker.setParameter("a", 1.1);
- dataMaker.setParameter("b", 2.2);
- dataMaker.function(*domain, mockData);
-
- API::FunctionValues_sptr values(new API::FunctionValues(*domain));
- values->setFitDataFromCalculated(mockData);
- values->setFitWeights(1.0);
-
- boost::shared_ptr<UserFunction> fun = boost::make_shared<UserFunction>();
- fun->setAttributeValue("Formula", "a*x+b");
- fun->setParameter("a", 1.);
- fun->setParameter("b", 2.);
-
- fun->addConstraint(
- Kernel::make_unique<BoundaryConstraint>(fun.get(), "a", 0, 0.5));
-
- boost::shared_ptr<CostFuncLeastSquares> costFun =
- boost::make_shared<CostFuncLeastSquares>();
- costFun->setFittingFunction(fun, domain, values);
- TS_ASSERT_EQUALS(costFun->nParams(), 2);
-
- MoreSorensenMinimizer s;
- s.initialize(costFun);
- TS_ASSERT(s.minimize());
-
- TS_ASSERT_DELTA(fun->getParameter("a"), 0.5, 0.1);
- TS_ASSERT_DELTA(fun->getParameter("b"), 5.2, 0.2);
- TS_ASSERT_EQUALS(s.getError(), "success");
- }
-
- void xtest_Linear_constrained1() {
- API::FunctionDomain1D_sptr domain(
- new API::FunctionDomain1DVector(0.0, 10.0, 20));
- API::FunctionValues mockData(*domain);
- UserFunction dataMaker;
- dataMaker.setAttributeValue("Formula", "a^2*x+b");
- dataMaker.setParameter("a", 1);
- dataMaker.setParameter("b", 2);
- dataMaker.function(*domain, mockData);
-
- API::FunctionValues_sptr values(new API::FunctionValues(*domain));
- values->setFitDataFromCalculated(mockData);
- values->setFitWeights(1.0);
-
- boost::shared_ptr<UserFunction> fun = boost::make_shared<UserFunction>();
- fun->setAttributeValue("Formula", "a^2*x+b");
- fun->setParameter("a", -0.5);
- fun->setParameter("b", 2.2);
-
- // lower bound is made > 0 because function's derivative over "a" at a=0 is
- // 0
- fun->addConstraint(
- Kernel::make_unique<BoundaryConstraint>(fun.get(), "a", 0.001, 2.0));
-
- boost::shared_ptr<CostFuncLeastSquares> costFun =
- boost::make_shared<CostFuncLeastSquares>();
- costFun->setFittingFunction(fun, domain, values);
- TS_ASSERT_EQUALS(costFun->nParams(), 2);
-
- MoreSorensenMinimizer s;
- s.initialize(costFun);
- TS_ASSERT(s.minimize());
-
- // std::cerr << "a=" << fun->getParameter("a") << '\n';
- // std::cerr << "b=" << fun->getParameter("b") << '\n';
-
- TS_ASSERT_DELTA(costFun->val(), 0.00, 0.0001);
- TS_ASSERT_DELTA(fun->getParameter("a"), 1.0, 0.01);
- TS_ASSERT_DELTA(fun->getParameter("b"), 2.0, 0.01);
- TS_ASSERT_EQUALS(s.getError(), "success");
- }
-
- void xtest_cannot_reach_tolerance() {
- API::FunctionDomain1D_sptr domain(
- new API::FunctionDomain1DVector(0.0, 1.0, 10));
- API::FunctionValues mockData(*domain);
- UserFunction dataMaker;
- dataMaker.setAttributeValue("Formula", "a*x");
- dataMaker.setParameter("a", 1.0);
- dataMaker.function(*domain, mockData);
-
- API::FunctionValues_sptr values(new API::FunctionValues(*domain));
- values->setFitDataFromCalculated(mockData);
- values->setFitWeights(1.0);
-
- boost::shared_ptr<UserFunction> fun = boost::make_shared<UserFunction>();
- fun->setAttributeValue("Formula", "a+b+0*x");
-
- boost::shared_ptr<CostFuncLeastSquares> costFun =
- boost::make_shared<CostFuncLeastSquares>();
- costFun->setFittingFunction(fun, domain, values);
-
- MoreSorensenMinimizer s;
- s.initialize(costFun);
- TS_ASSERT(!s.minimize());
-
- TS_ASSERT_EQUALS(s.getError(), "cannot reach the specified tolerance in F");
- }
-};
-
-#endif /*CURVEFITTING_MORESORNSENTTEST_H_*/
diff --git a/Framework/CurveFitting/test/FuncMinimizers/DTRSMinimizerTest.h b/Framework/CurveFitting/test/FuncMinimizers/TrustRegionMinimizerTest.h
similarity index 93%
rename from Framework/CurveFitting/test/FuncMinimizers/DTRSMinimizerTest.h
rename to Framework/CurveFitting/test/FuncMinimizers/TrustRegionMinimizerTest.h
index 7712495c097799f9350ff12651c135d3776e6cc3..84dc5edc84b21210b4aeabdff0cc76e45d3f986d 100644
--- a/Framework/CurveFitting/test/FuncMinimizers/DTRSMinimizerTest.h
+++ b/Framework/CurveFitting/test/FuncMinimizers/TrustRegionMinimizerTest.h
@@ -1,10 +1,10 @@
-#ifndef CURVEFITTING_DTRSMINIMIZERTTEST_H_
-#define CURVEFITTING_DTRSMINIMIZERTTEST_H_
+#ifndef CURVEFITTING_TRUSTREGIONMINIMIZERTTEST_H_
+#define CURVEFITTING_TRUSTREGIONMINIMIZERTTEST_H_
#include <cxxtest/TestSuite.h>
#include "MantidCurveFitting/CostFunctions/CostFuncLeastSquares.h"
-#include "MantidCurveFitting/FuncMinimizers/DTRSMinimizer.h"
+#include "MantidCurveFitting/FuncMinimizers/TrustRegionMinimizer.h"
#include "MantidCurveFitting/Functions/UserFunction.h"
#include "MantidAPI/FunctionDomain1D.h"
#include "MantidAPI/FunctionValues.h"
@@ -20,12 +20,14 @@ using namespace Mantid::CurveFitting::Constraints;
using namespace Mantid::CurveFitting::Functions;
using namespace Mantid::API;
-class DTRSMinimizerTest : public CxxTest::TestSuite {
+class TrustRegionMinimizerTest : public CxxTest::TestSuite {
public:
// This pair of boilerplate methods prevent the suite being created statically
// This means the constructor isn't called when running other tests
- static DTRSMinimizerTest *createSuite() { return new DTRSMinimizerTest(); }
- static void destroySuite(DTRSMinimizerTest *suite) { delete suite; }
+ static TrustRegionMinimizerTest *createSuite() {
+ return new TrustRegionMinimizerTest();
+ }
+ static void destroySuite(TrustRegionMinimizerTest *suite) { delete suite; }
void test_Linear() {
API::FunctionDomain1D_sptr domain(
@@ -51,7 +53,7 @@ public:
costFun->setFittingFunction(fun, domain, values);
TS_ASSERT_EQUALS(costFun->nParams(), 2);
- DTRSMinimizer s;
+ TrustRegionMinimizer s;
s.initialize(costFun);
TS_ASSERT(s.minimize());
@@ -87,7 +89,7 @@ public:
boost::make_shared<CostFuncLeastSquares>();
costFun->setFittingFunction(fun, domain, values);
- DTRSMinimizer s;
+ TrustRegionMinimizer s;
s.initialize(costFun);
TS_ASSERT(s.minimize());
TS_ASSERT_DELTA(costFun->val(), 0.0, 0.0001);
@@ -127,7 +129,7 @@ public:
costFun->setFittingFunction(fun, domain, values);
TS_ASSERT_EQUALS(costFun->nParams(), 3);
- DTRSMinimizer s;
+ TrustRegionMinimizer s;
s.initialize(costFun);
TS_ASSERT(s.minimize()); //
TS_ASSERT_DELTA(costFun->val(), 0.2, 0.01);
@@ -167,7 +169,7 @@ public:
costFun->setFittingFunction(fun, domain, values);
TS_ASSERT_EQUALS(costFun->nParams(), 3);
- DTRSMinimizer s;
+ TrustRegionMinimizer s;
s.initialize(costFun);
TS_ASSERT(s.minimize()); //
TS_ASSERT_DELTA(costFun->val(), 0.2, 0.01);
@@ -205,7 +207,7 @@ public:
costFun->setFittingFunction(fun, domain, values);
TS_ASSERT_EQUALS(costFun->nParams(), 2);
- DTRSMinimizer s;
+ TrustRegionMinimizer s;
s.initialize(costFun);
TS_ASSERT(s.minimize());
@@ -243,7 +245,7 @@ public:
costFun->setFittingFunction(fun, domain, values);
TS_ASSERT_EQUALS(costFun->nParams(), 2);
- DTRSMinimizer s;
+ TrustRegionMinimizer s;
s.initialize(costFun);
TS_ASSERT(s.minimize());
@@ -254,4 +256,4 @@ public:
}
};
-#endif /*CURVEFITTING_DTRSMINIMIZERTTEST_H_*/
+#endif /*CURVEFITTING_TRUSTREGIONMINIMIZERTTEST_H_*/
diff --git a/Framework/CurveFitting/test/RalNlls/NLLSTest.h b/Framework/CurveFitting/test/RalNlls/NLLSTest.h
index 94337fb13bf1564c746c5be59f78579c007ca852..ae6dc165970b3004d3af2cbe5efd2ea14a01010e 100644
--- a/Framework/CurveFitting/test/RalNlls/NLLSTest.h
+++ b/Framework/CurveFitting/test/RalNlls/NLLSTest.h
@@ -16,19 +16,6 @@ using namespace Mantid::API;
class NLLSTest : public CxxTest::TestSuite {
public:
- void test_More_Sorensen_ExpDecay() {
- auto ws = make_exp_decay_workspace();
- Fit fit;
- fit.initialize();
- fit.setPropertyValue("Function", "name=ExpDecay");
- fit.setProperty("InputWorkspace", ws);
- fit.setProperty("Minimizer", "More-Sorensen");
- fit.execute();
- IFunction_sptr fun = fit.getProperty("Function");
- TS_ASSERT_DELTA(fun->getParameter(0), 60.195, 0.001);
- TS_ASSERT_DELTA(fun->getParameter(1), 2.16815, 0.00001);
- }
-
void test_Galahad_ExpDecay() {
auto ws = make_exp_decay_workspace();
Fit fit;
diff --git a/Framework/DataObjects/inc/MantidDataObjects/PeaksWorkspace.h b/Framework/DataObjects/inc/MantidDataObjects/PeaksWorkspace.h
index 9d122261e5cbac7c2551c1ab99ab934c88b1c919..2bdbd533ff90e4c116fa85a5fb295ed050095792 100644
--- a/Framework/DataObjects/inc/MantidDataObjects/PeaksWorkspace.h
+++ b/Framework/DataObjects/inc/MantidDataObjects/PeaksWorkspace.h
@@ -283,11 +283,6 @@ private:
/// Coordinates
Kernel::SpecialCoordinateSystem m_coordSystem;
-
- // adapter for logs() function, which create reference to this class itself
- // and does not allow to delete the shared pointers,
- // returned by logs() function when they go out of scope
- API::LogManager_sptr m_logCash;
};
/// Typedef for a shared pointer to a peaks workspace.
diff --git a/Framework/DataObjects/inc/MantidDataObjects/WorkspaceCreation.h b/Framework/DataObjects/inc/MantidDataObjects/WorkspaceCreation.h
index 572cc2c8032cc9cbc1b8e48234faf1c4fb0d9c5c..7a3d895a65962c561b7996c1fcbf5202b00bcabf 100644
--- a/Framework/DataObjects/inc/MantidDataObjects/WorkspaceCreation.h
+++ b/Framework/DataObjects/inc/MantidDataObjects/WorkspaceCreation.h
@@ -145,10 +145,6 @@ fixDistributionFlag(API::MatrixWorkspace &workspace,
MANTID_DATAOBJECTS_DLL void
initializeFromParent(const API::MatrixWorkspace &parent,
API::MatrixWorkspace &ws);
-
-MANTID_DATAOBJECTS_DLL void
-initializeFromParentWithoutLogs(const API::MatrixWorkspace &parent,
- API::MatrixWorkspace &ws);
}
/** This is the create() method that all the other create() methods call.
@@ -193,46 +189,6 @@ std::unique_ptr<T> create(const P &parent, const IndexArg &indexArg,
return ws;
}
-/** create a new workspace with empty run, i.e., without logs
- * this is for initializeFromParentWithoutLogs
- */
-template <class T, class P, class IndexArg, class HistArg,
- class = typename std::enable_if<
- std::is_base_of<API::MatrixWorkspace, P>::value>::type>
-std::unique_ptr<T> createWithoutLogs(const P &parent, const IndexArg &indexArg,
- const HistArg &histArg) {
- // Figure out (dynamic) target type:
- // - Type is same as parent if T is base of parent
- // - If T is not base of parent, conversion may occur. Currently only
- // supported for EventWorkspace
- std::unique_ptr<T> ws;
- if (std::is_base_of<API::HistoWorkspace, T>::value &&
- parent.id() == "EventWorkspace") {
- // Drop events, create Workspace2D or T whichever is more derived.
- ws = detail::createHelper<T>();
- } else {
- try {
- // If parent is more derived than T: create type(parent)
- ws = dynamic_cast<const T &>(parent).cloneEmpty();
- } catch (std::bad_cast &) {
- // If T is more derived than parent: create T
- ws = detail::createConcreteHelper<T>();
- }
- }
-
- // The instrument is also copied by initializeFromParentWithoutLogs,
- // but if indexArg is
- // IndexInfo and contains non-empty spectrum definitions the initialize call
- // will fail due to invalid indices in the spectrum definitions. Therefore, we
- // copy the instrument first. This should be cleaned up once we figure out the
- // future of WorkspaceFactory.
- ws->setInstrument(parent.getInstrument());
- ws->initialize(indexArg, HistogramData::Histogram(histArg));
- detail::initializeFromParentWithoutLogs(parent, *ws);
- detail::fixDistributionFlag(*ws, histArg);
- return ws;
-}
-
template <class T, class IndexArg, class HistArg,
typename std::enable_if<
!std::is_base_of<API::MatrixWorkspace, IndexArg>::value>::type * =
@@ -269,19 +225,6 @@ std::unique_ptr<T> create(const P &parent) {
return ws;
}
-template <class T, class P,
- typename std::enable_if<std::is_base_of<API::MatrixWorkspace,
- P>::value>::type * = nullptr>
-std::unique_ptr<T> createWithoutLogs(const P &parent) {
- const auto numHistograms = parent.getNumberHistograms();
- auto ws = createWithoutLogs<T>(parent, numHistograms,
- detail::stripData(parent.histogram(0)));
- for (size_t i = 0; i < numHistograms; ++i) {
- ws->setSharedX(i, parent.sharedX(i));
- }
- return ws;
-}
-
// Templating with HistArg clashes with the IndexArg template above. Could be
// fixed with many enable_if cases, but for now we simply provide 3 variants
// (Histogram, BinEdges, Points) by hand.
diff --git a/Framework/DataObjects/src/PeaksWorkspace.cpp b/Framework/DataObjects/src/PeaksWorkspace.cpp
index d38c71e134721f311ab3efe3b8022464955b96ca..301c714e2c6f5a474e161fe5bc73a93c2e900315 100644
--- a/Framework/DataObjects/src/PeaksWorkspace.cpp
+++ b/Framework/DataObjects/src/PeaksWorkspace.cpp
@@ -877,15 +877,9 @@ PeaksWorkspace::getSpecialCoordinateSystem() const {
struct NullDeleter {
template <typename T> void operator()(T *) {}
};
-/**Get access to shared pointer containing workspace porperties, cashes the
- shared pointer
- into internal class variable to not allow shared pointer being deleted */
+/**Get access to shared pointer containing workspace porperties */
API::LogManager_sptr PeaksWorkspace::logs() {
- if (m_logCash)
- return m_logCash;
-
- m_logCash = API::LogManager_sptr(&(this->mutableRun()), NullDeleter());
- return m_logCash;
+ return API::LogManager_sptr(&(this->mutableRun()), NullDeleter());
}
/** Get constant access to shared pointer containing workspace porperties;
diff --git a/Framework/DataObjects/src/WorkspaceCreation.cpp b/Framework/DataObjects/src/WorkspaceCreation.cpp
index ee7eec6e4da2548fd14374624570d646ea2e19f1..92ecff01b8353a8025e330d6a02b29052576f128 100644
--- a/Framework/DataObjects/src/WorkspaceCreation.cpp
+++ b/Framework/DataObjects/src/WorkspaceCreation.cpp
@@ -52,24 +52,6 @@ void initializeFromParent(const API::MatrixWorkspace &parent,
static_cast<void>(ws.mutableX(0));
}
-/** Initialize a MatrixWorkspace from its parent including instrument, unit,
- * number of spectra but without Run (i.e., logs)
- * @brief initializeFromParentWithoutLogs
- * @param parent
- * @param ws
- */
-void initializeFromParentWithoutLogs(const API::MatrixWorkspace &parent,
- API::MatrixWorkspace &ws) {
- bool differentSize = (parent.x(0).size() != ws.x(0).size()) ||
- (parent.y(0).size() != ws.y(0).size());
- API::WorkspaceFactory::Instance().initializeFromParentWithoutLogs(
- parent, ws, differentSize);
- // For EventWorkspace, `ws.y(0)` put entry 0 in the MRU. However, clients
- // would typically expect an empty MRU and fail to clear it. This dummy call
- // removes the entry from the MRU.
- static_cast<void>(ws.mutableX(0));
-}
-
template <>
void fixDistributionFlag(API::MatrixWorkspace &workspace,
const HistogramData::Histogram &histArg) {
diff --git a/Framework/DataObjects/test/WorkspaceCreationTest.h b/Framework/DataObjects/test/WorkspaceCreationTest.h
index 7aba97e764b0e0ff9746a0ec22625d3d908b95ba..dccc28d59ee2daf4cd37e614521de4aaf4094033 100644
--- a/Framework/DataObjects/test/WorkspaceCreationTest.h
+++ b/Framework/DataObjects/test/WorkspaceCreationTest.h
@@ -265,7 +265,9 @@ public:
const std::string &name1 = "Log4";
const std::string &value1 = "6.4a";
parent->mutableRun().addProperty(name1, value1);
- const auto ws = createWithoutLogs<Workspace2D>(*parent);
+ const auto ws = create<Workspace2D>(*parent);
+ TS_ASSERT_EQUALS(&parent->run(), &ws->run());
+ ws->setSharedRun(Kernel::make_cow<Run>());
check_indices(*ws);
check_zeroed_data(*ws);
check_instrument(*ws);
diff --git a/Framework/Indexing/CMakeLists.txt b/Framework/Indexing/CMakeLists.txt
index b3d274a33d63b6a6b30f0c1f0f9e465b38956e95..e5b69e1a9de4cb53c493f6632026201e14b6fb41 100644
--- a/Framework/Indexing/CMakeLists.txt
+++ b/Framework/Indexing/CMakeLists.txt
@@ -9,6 +9,7 @@ set ( SRC_FILES
)
set ( INC_FILES
+ inc/MantidIndexing/Conversion.h
inc/MantidIndexing/DetectorID.h
inc/MantidIndexing/DllConfig.h
inc/MantidIndexing/Extract.h
@@ -27,6 +28,7 @@ set ( INC_FILES
)
set ( TEST_FILES
+ ConversionTest.h
DetectorIDTest.h
ExtractTest.h
GlobalSpectrumIndexTest.h
diff --git a/Framework/Indexing/inc/MantidIndexing/Conversion.h b/Framework/Indexing/inc/MantidIndexing/Conversion.h
new file mode 100644
index 0000000000000000000000000000000000000000..01a24ac96ee6b30db13af350acf4eb613a3058ca
--- /dev/null
+++ b/Framework/Indexing/inc/MantidIndexing/Conversion.h
@@ -0,0 +1,79 @@
+#ifndef MANTID_INDEXING_CONVERSION_H_
+#define MANTID_INDEXING_CONVERSION_H_
+
+#include "MantidIndexing/DllConfig.h"
+#include "MantidIndexing/GlobalSpectrumIndex.h"
+#include "MantidIndexing/SpectrumNumber.h"
+
+namespace Mantid {
+namespace Indexing {
+
+/** Conversion helpers from and to (vectors of) integer types such as
+ SpectrumNumber and GlobalSpectrumIndex.
+
+ @author Simon Heybrock
+ @date 2017
+
+ Copyright © 2017 ISIS Rutherford Appleton Laboratory, NScD Oak Ridge
+ National Laboratory & European Spallation Source
+
+ This file is part of Mantid.
+
+ Mantid is free software; you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation; either version 3 of the License, or
+ (at your option) any later version.
+
+ Mantid is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see <http://www.gnu.org/licenses/>.
+
+ File change history is stored at: <https://github.com/mantidproject/mantid>
+ Code Documentation is available at: <http://doxygen.mantidproject.org>
+*/
+
+/** Convert std::vector<In> to std::vector<Out> by static-casting all elements.
+ *
+ * `In` must be an integral type and `Out` can be any type inheriting
+ * Indexing::IndexType, such as SpectrumNumber or GlobalSpectrumIndex. The
+ * conversion is done using static_cast without any range check. It is the
+ * responsibility of the caller to not pass any vectors containing elements that
+ * suffer from loss of data in a static_cast. */
+template <
+ class Out, class In,
+ typename std::enable_if<std::is_integral<In>::value>::type * = nullptr>
+std::vector<Out> castVector(const std::vector<In> &indices) {
+ std::vector<Out> converted;
+ converted.reserve(indices.size());
+ for (const auto index : indices)
+ converted.push_back(static_cast<typename Out::underlying_type>(index));
+ return converted;
+}
+
+/** Convert std::vector<In> to std::vector<Out> by static-casting all elements.
+ *
+ * `Out` must be an integral type and `In` can be any type inheriting
+ * Indexing::IndexType, such as SpectrumNumber or GlobalSpectrumIndex. The
+ * conversion is done using static_cast without any range check. It is the
+ * responsibility of the caller to not pass any vectors containing elements that
+ * suffer from loss of data in a static_cast. */
+template <
+ class Out, class In,
+ typename std::enable_if<!std::is_integral<In>::value>::type * = nullptr>
+std::vector<Out> castVector(const std::vector<In> &indices) {
+ std::vector<Out> converted;
+ converted.reserve(indices.size());
+ for (const auto index : indices)
+ converted.push_back(
+ static_cast<Out>(static_cast<typename In::underlying_type>(index)));
+ return converted;
+}
+
+} // namespace Indexing
+} // namespace Mantid
+
+#endif /* MANTID_INDEXING_CONVERSION_H_ */
diff --git a/Framework/Indexing/inc/MantidIndexing/IndexInfo.h b/Framework/Indexing/inc/MantidIndexing/IndexInfo.h
index a9e3267c6cf46d4e2c80e344ae3814dea4b905b3..ded7d80947676efd3964bfb915c3ced210242a57 100644
--- a/Framework/Indexing/inc/MantidIndexing/IndexInfo.h
+++ b/Framework/Indexing/inc/MantidIndexing/IndexInfo.h
@@ -114,6 +114,9 @@ public:
SpectrumIndexSet
makeIndexSet(const std::vector<GlobalSpectrumIndex> &globalIndices) const;
+ std::vector<GlobalSpectrumIndex> globalSpectrumIndicesFromDetectorIndices(
+ const std::vector<size_t> &detectorIndices) const;
+
bool isOnThisPartition(GlobalSpectrumIndex globalIndex) const;
Parallel::StorageMode storageMode() const;
diff --git a/Framework/Indexing/inc/MantidIndexing/IndexType.h b/Framework/Indexing/inc/MantidIndexing/IndexType.h
index 0920f29b6b2c3cb7a2d681b364268db96e07bd35..3778d2036e468801181bc85327e8bd4223ad1ae6 100644
--- a/Framework/Indexing/inc/MantidIndexing/IndexType.h
+++ b/Framework/Indexing/inc/MantidIndexing/IndexType.h
@@ -37,6 +37,7 @@ template <class Derived, class Int,
class = typename std::enable_if<std::is_integral<Int>::value>::type>
class IndexType {
public:
+ using underlying_type = Int;
IndexType() noexcept : m_data(0) {}
IndexType(Int data) noexcept : m_data(data) {}
explicit operator Int() const noexcept { return m_data; }
diff --git a/Framework/Indexing/src/IndexInfo.cpp b/Framework/Indexing/src/IndexInfo.cpp
index ed94a21c0f3ea752281ea0bb409c97a9d6f27f84..0f27f32d743d749a200521fbba012f08cbba6cee 100644
--- a/Framework/Indexing/src/IndexInfo.cpp
+++ b/Framework/Indexing/src/IndexInfo.cpp
@@ -193,6 +193,55 @@ SpectrumIndexSet IndexInfo::makeIndexSet(
return m_spectrumNumberTranslator->makeIndexSet(globalIndices);
}
+/** Map a vector of detector indices to a vector of global spectrum indices.
+ *
+ * The mapping is based on the held spectrum definitions. Throws if any spectrum
+ * maps to more than one detectors. Throws if there is no 1:1 mapping from
+ * detectors to spectra, such as when some of the detectors have no matching
+ * spectrum. */
+std::vector<GlobalSpectrumIndex>
+IndexInfo::globalSpectrumIndicesFromDetectorIndices(
+ const std::vector<size_t> &detectorIndices) const {
+ if (!m_spectrumDefinitions)
+ throw std::runtime_error("IndexInfo::"
+ "globalSpectrumIndicesFromDetectorIndices -- no "
+ "spectrum definitions available");
+ std::vector<char> detectorMap;
+ for (const auto &index : detectorIndices) {
+ // IndexInfo has no knowledge of the maximum detector index so we workaround
+ // this knowledge gap by assuming below that any index beyond the end of the
+ // map is 0.
+ if (index >= detectorMap.size())
+ detectorMap.resize(index + 1, 0);
+ detectorMap[index] = 1;
+ }
+
+ std::vector<GlobalSpectrumIndex> spectrumIndices;
+ for (size_t i = 0; i < size(); ++i) {
+ const auto &spectrumDefinition = m_spectrumDefinitions->operator[](i);
+ if (spectrumDefinition.size() == 1) {
+ const auto detectorIndex = spectrumDefinition[0].first;
+ if (detectorMap.size() > detectorIndex &&
+ detectorMap[detectorIndex] != 0) {
+ if (detectorMap[detectorIndex] > 1)
+ throw std::runtime_error(
+ "Multiple spectra correspond to the same detector");
+ // Increment flag to catch two spectra mapping to same detector.
+ ++detectorMap[detectorIndex];
+ spectrumIndices.push_back(i);
+ }
+ }
+ if (spectrumDefinition.size() > 1)
+ throw std::runtime_error("SpectrumDefinition contains multiple entries. "
+ "No unique mapping from detector to spectrum "
+ "possible");
+ }
+ if (detectorIndices.size() != spectrumIndices.size())
+ throw std::runtime_error(
+ "Some of the requested detectors do not have a corresponding spectrum");
+ return spectrumIndices;
+}
+
/// Returns true if the given global index is on this partition.
bool IndexInfo::isOnThisPartition(GlobalSpectrumIndex globalIndex) const {
// A map from global index to partition might be faster, consider adding this
diff --git a/Framework/Indexing/test/ConversionTest.h b/Framework/Indexing/test/ConversionTest.h
new file mode 100644
index 0000000000000000000000000000000000000000..c84c095f2aa21c32769426aed290e8f13d01750f
--- /dev/null
+++ b/Framework/Indexing/test/ConversionTest.h
@@ -0,0 +1,57 @@
+#ifndef MANTID_INDEXING_CONVERSIONTEST_H_
+#define MANTID_INDEXING_CONVERSIONTEST_H_
+
+#include <cxxtest/TestSuite.h>
+
+#include "MantidIndexing/Conversion.h"
+#include "MantidIndexing/GlobalSpectrumIndex.h"
+#include "MantidIndexing/SpectrumNumber.h"
+
+using namespace Mantid::Indexing;
+
+class ConversionTest : public CxxTest::TestSuite {
+public:
+ // This pair of boilerplate methods prevent the suite being created statically
+ // This means the constructor isn't called when running other tests
+ static ConversionTest *createSuite() { return new ConversionTest(); }
+ static void destroySuite(ConversionTest *suite) { delete suite; }
+
+ void test_just_a_static_cast() {
+ std::vector<SpectrumNumber> in{-1};
+ TS_ASSERT_EQUALS(castVector<size_t>(in),
+ (std::vector<size_t>{18446744073709551615ul}));
+ }
+
+ void test_GlobalSpectrumIndex() {
+ std::vector<GlobalSpectrumIndex> in{0, 1, 2};
+ TS_ASSERT_EQUALS(castVector<size_t>(in), (std::vector<size_t>{0, 1, 2}));
+ TS_ASSERT_EQUALS(castVector<int64_t>(in), (std::vector<int64_t>{0, 1, 2}));
+ TS_ASSERT_EQUALS(castVector<int32_t>(in), (std::vector<int32_t>{0, 1, 2}));
+ }
+
+ void test_to_GlobalSpectrumIndex() {
+ std::vector<int64_t> in{0, 1, 2};
+ TS_ASSERT_EQUALS(castVector<GlobalSpectrumIndex>(in),
+ (std::vector<GlobalSpectrumIndex>{0, 1, 2}));
+ std::vector<size_t> in2{0, 1, 2};
+ TS_ASSERT_EQUALS(castVector<GlobalSpectrumIndex>(in2),
+ (std::vector<GlobalSpectrumIndex>{0, 1, 2}));
+ }
+
+ void test_SpectrumNumber() {
+ std::vector<SpectrumNumber> in{-1, 1, 2};
+ TS_ASSERT_EQUALS(castVector<int64_t>(in), (std::vector<int64_t>{-1, 1, 2}));
+ TS_ASSERT_EQUALS(castVector<int32_t>(in), (std::vector<int32_t>{-1, 1, 2}));
+ }
+
+ void test_to_SpectrumNumber() {
+ std::vector<int32_t> in{-1, 1, 2};
+ TS_ASSERT_EQUALS(castVector<SpectrumNumber>(in),
+ (std::vector<SpectrumNumber>{-1, 1, 2}));
+ std::vector<int64_t> in2{-1, 1, 2};
+ TS_ASSERT_EQUALS(castVector<SpectrumNumber>(in2),
+ (std::vector<SpectrumNumber>{-1, 1, 2}));
+ }
+};
+
+#endif /* MANTID_INDEXING_CONVERSIONTEST_H_ */
diff --git a/Framework/Indexing/test/IndexInfoTest.h b/Framework/Indexing/test/IndexInfoTest.h
index 0b5434423faf6cf5f578e5259c938497ca2cee88..7e16ef641f317550f9d78c9cb4fc31629f3c6ae8 100644
--- a/Framework/Indexing/test/IndexInfoTest.h
+++ b/Framework/Indexing/test/IndexInfoTest.h
@@ -187,6 +187,90 @@ public:
TS_ASSERT_EQUALS(info.spectrumDefinitions().get(), defs.get());
}
+ void test_globalSpectrumIndicesFromDetectorIndices_fails_without_spec_defs() {
+ IndexInfo info(3);
+ std::vector<size_t> detectorIndices{6, 8};
+ TS_ASSERT_THROWS_EQUALS(
+ info.globalSpectrumIndicesFromDetectorIndices(detectorIndices),
+ const std::runtime_error &e, std::string(e.what()),
+ "IndexInfo::globalSpectrumIndicesFromDetectorIndices -- no spectrum "
+ "definitions available");
+ }
+
+ void test_globalSpectrumIndicesFromDetectorIndices_fails_multiple() {
+ IndexInfo info(3);
+ std::vector<size_t> detectorIndices{6, 8};
+ std::vector<SpectrumDefinition> specDefs(3);
+ specDefs[0].add(6);
+ specDefs[1].add(7);
+ specDefs[1].add(77);
+ specDefs[2].add(8);
+ info.setSpectrumDefinitions(specDefs);
+ TS_ASSERT_THROWS_EQUALS(
+ info.globalSpectrumIndicesFromDetectorIndices(detectorIndices),
+ const std::runtime_error &e, std::string(e.what()),
+ "SpectrumDefinition contains multiple entries. No unique mapping from "
+ "detector to spectrum possible");
+ }
+
+ void test_globalSpectrumIndicesFromDetectorIndices_fails_missing() {
+ IndexInfo info(3);
+ std::vector<size_t> detectorIndices{6, 8};
+ std::vector<SpectrumDefinition> specDefs(3);
+ // Nothing maps to 8
+ specDefs[0].add(6);
+ specDefs[1].add(7);
+ info.setSpectrumDefinitions(specDefs);
+ TS_ASSERT_THROWS_EQUALS(
+ info.globalSpectrumIndicesFromDetectorIndices(detectorIndices),
+ const std::runtime_error &e, std::string(e.what()),
+ "Some of the requested detectors do not have a corresponding spectrum");
+ }
+
+ void test_globalSpectrumIndicesFromDetectorIndices_fails_conflict() {
+ IndexInfo info(3);
+ std::vector<size_t> detectorIndices{6, 8};
+ std::vector<SpectrumDefinition> specDefs(3);
+ // Two indices map to same detector.
+ specDefs[0].add(6);
+ specDefs[1].add(6);
+ specDefs[2].add(8);
+ info.setSpectrumDefinitions(specDefs);
+ TS_ASSERT_THROWS_EQUALS(
+ info.globalSpectrumIndicesFromDetectorIndices(detectorIndices),
+ const std::runtime_error &e, std::string(e.what()),
+ "Multiple spectra correspond to the same detector");
+ }
+
+ void test_globalSpectrumIndicesFromDetectorIndices_fails_conflict_miss() {
+ IndexInfo info(3);
+ std::vector<size_t> detectorIndices{6, 8};
+ std::vector<SpectrumDefinition> specDefs(3);
+ // Two indices map to same detector, but additionally one is missing.
+ specDefs[0].add(6);
+ specDefs[1].add(6);
+ info.setSpectrumDefinitions(specDefs);
+ TS_ASSERT_THROWS_EQUALS(
+ info.globalSpectrumIndicesFromDetectorIndices(detectorIndices),
+ const std::runtime_error &e, std::string(e.what()),
+ "Multiple spectra correspond to the same detector");
+ }
+
+ void test_globalSpectrumIndicesFromDetectorIndices() {
+ IndexInfo info(3);
+ std::vector<size_t> detectorIndices{6, 8};
+ std::vector<SpectrumDefinition> specDefs(3);
+ specDefs[0].add(6);
+ specDefs[1].add(7);
+ specDefs[2].add(8);
+ info.setSpectrumDefinitions(specDefs);
+ const auto &indices =
+ info.globalSpectrumIndicesFromDetectorIndices(detectorIndices);
+ TS_ASSERT_EQUALS(indices.size(), detectorIndices.size());
+ TS_ASSERT_EQUALS(indices[0], 0);
+ TS_ASSERT_EQUALS(indices[1], 2);
+ }
+
void test_StorageMode_Cloned() {
runParallel(run_StorageMode_Cloned);
// Trivial: Run with one partition.
diff --git a/Framework/PythonInterface/plugins/algorithms/EnggFocus.py b/Framework/PythonInterface/plugins/algorithms/EnggFocus.py
index 7e658088f19150698b68417007aa4537b38f98ac..28ecf993a48d5403c04f3ac7fa2bba021ee4fa61 100644
--- a/Framework/PythonInterface/plugins/algorithms/EnggFocus.py
+++ b/Framework/PythonInterface/plugins/algorithms/EnggFocus.py
@@ -62,7 +62,7 @@ class EnggFocus(PythonAlgorithm):
self.declareProperty(self.INDICES_PROP_NAME, '', direction=Direction.Input,
doc='Sets the spectrum numbers for the detectors '
- 'that should be considered in the focussing operation (all others will be '
+ 'that should be considered in the focusing operation (all others will be '
'ignored). This option cannot be used together with Bank, as they overlap. '
'You can give multiple ranges, for example: "0-99", or "0-9, 50-59, 100-109".')
@@ -160,8 +160,28 @@ class EnggFocus(PythonAlgorithm):
# converting units), so I guess that's what users will expect
self._convert_to_distribution(input_ws)
+ if bank:
+ self._add_bank_number(input_ws, bank)
+
self.setProperty("OutputWorkspace", input_ws)
+ def _bank_to_int(self, bank):
+ if bank == "North":
+ return "1"
+ if bank == "South":
+ return "2"
+ if bank in ("1", "2"):
+ return bank
+ raise RuntimeError("Invalid value for bank: \"{}\" of type {}".format(bank, type(bank)))
+
+ def _add_bank_number(self, ws, bank):
+ alg = self.createChildAlgorithm("AddSampleLog")
+ alg.setProperty("Workspace", ws)
+ alg.setProperty("LogName", "bankid")
+ alg.setProperty("LogText", self._bank_to_int(bank))
+ alg.setProperty("LogType", "Number")
+ alg.execute()
+
def _mask_bins(self, wks, min_bins, max_bins):
"""
Mask multiple ranges of bins, given multiple pairs min-max
diff --git a/Testing/Data/SystemTest/ISIS_Powder/input/PEARL00098494.nxs.md5 b/Testing/Data/SystemTest/ISIS_Powder/input/PEARL00098494.nxs.md5
new file mode 100644
index 0000000000000000000000000000000000000000..bb209053d4c2864afe53af5a6f21b89dd8721439
--- /dev/null
+++ b/Testing/Data/SystemTest/ISIS_Powder/input/PEARL00098494.nxs.md5
@@ -0,0 +1 @@
+c13f59f8155dc56e59d0412511b80b5d
\ No newline at end of file
diff --git a/Testing/SystemTests/tests/analysis/ISIS_PowderPearlTest.py b/Testing/SystemTests/tests/analysis/ISIS_PowderPearlTest.py
index 12eba9b03a1fccf20ec220cd46884c632d8a35b0..1b3731a5357d07a680ea3bad2742901ab1ce33df 100644
--- a/Testing/SystemTests/tests/analysis/ISIS_PowderPearlTest.py
+++ b/Testing/SystemTests/tests/analysis/ISIS_PowderPearlTest.py
@@ -122,9 +122,34 @@ class FocusTest(stresstesting.MantidStressTest):
mantid.mtd.clear()
+class CreateCalTest(stresstesting.MantidStressTest):
+
+ calibration_results = None
+ existing_config = config["datasearch.directories"]
+
+ def requiredFiles(self):
+ return _gen_required_files()
+
+ def runTest(self):
+ setup_mantid_paths()
+ self.calibration_results = run_create_cal()
+
+ def valid(self):
+ return ceria_validator(self.calibration_results)
+
+ def cleanup(self):
+ try:
+ _try_delete(spline_path)
+ _try_delete(output_dir)
+ finally:
+ config['datasearch.directories'] = self.existing_config
+ mantid.mtd.clear()
+
+
def _gen_required_files():
required_run_numbers = ["98472", "98485", # create_van
- "98507", "98472_splined"] # Focus (Si)
+ "98507", "98472_splined", # Focus (Si)
+ "98494"] # create_cal (Ce)
# Generate file names of form "INSTxxxxx.nxs" - PEARL requires 000 padding
input_files = [os.path.join(input_dir, (inst_name + "000" + number + ".nxs")) for number in required_run_numbers]
@@ -132,6 +157,12 @@ def _gen_required_files():
return input_files
+def run_create_cal():
+ ceria_run = 98494
+ inst_obj = setup_inst_object(tt_mode="tt88", focus_mode="all")
+ return inst_obj.create_cal(run_number=ceria_run)
+
+
def run_vanadium_calibration(focus_mode):
vanadium_run = 98507 # Choose arbitrary run in the cycle 17_1
@@ -162,6 +193,11 @@ def focus_validation(results):
return _compare_ws(reference_file_name=reference_file_name, results=results)
+def ceria_validator(results):
+ reference_file_name = "ISIS_Powder-PEARL00098494_grouped.nxs"
+ return _compare_ws(reference_file_name=reference_file_name, results=results)
+
+
def _compare_ws(reference_file_name, results):
ref_ws = mantid.Load(Filename=reference_file_name)
diff --git a/Testing/SystemTests/tests/analysis/reference/ISIS_Powder-PEARL98494_grouped.nxs.md5 b/Testing/SystemTests/tests/analysis/reference/ISIS_Powder-PEARL98494_grouped.nxs.md5
new file mode 100644
index 0000000000000000000000000000000000000000..85159fd3ae5819d82f207365d911baf49b3d05a1
--- /dev/null
+++ b/Testing/SystemTests/tests/analysis/reference/ISIS_Powder-PEARL98494_grouped.nxs.md5
@@ -0,0 +1 @@
+b957a6b0928e12a8c86284ea010df429
\ No newline at end of file
diff --git a/docs/source/release/v3.12.0/diffraction.rst b/docs/source/release/v3.12.0/diffraction.rst
index 5de79b4872045e64e6092cf0a641cb8a82d6aced..79174ecb3939e6ada94c7ff15821a054b6fecc3b 100644
--- a/docs/source/release/v3.12.0/diffraction.rst
+++ b/docs/source/release/v3.12.0/diffraction.rst
@@ -13,6 +13,7 @@ Powder Diffraction
------------------
- Some new functionality for POLARIS in the ISIS Powder scripts. Adjusted some default parameters and output unsplined vanadium workspace by default
+- ISIS_Powder scripts for PEARL now support creation of grouping .cal files from ceria run(s)
- The ``CalibrationFile`` is now optional in :ref:`SNSPowderReduction <algm-SNSPowderReduction>`. In this case time focussing will use :ref:`ConvertUnits <algm-ConvertUnits>` and the instrument geometry. Care must be taken to supply a ``GroupingFile`` otherwise all of the spectra will be kept separate.
- New algorithm :ref:`algm-EstimateDivergence` estimates the beam divergence due to finite slit size
- :ref:`PDCalibration <algm-PDCalibration>` returns three more diagnostic workspaces: one for the fitted peak heights, one for the fitted peak widths, and one for observed resolution.
diff --git a/docs/source/release/v3.12.0/framework.rst b/docs/source/release/v3.12.0/framework.rst
index b6bc937cb3b1db9a97698e9d71c8b81c05f267b7..6b6eed76cd9adb64b0492a33f27d810a460cab79 100644
--- a/docs/source/release/v3.12.0/framework.rst
+++ b/docs/source/release/v3.12.0/framework.rst
@@ -38,6 +38,7 @@ Performance
-----------
- Improved performance for second and consecutive loads of instrument geometry, particularly for instruments with many detector pixels. This affects :ref:`LoadEmptyInstrument <algm-LoadEmptyInstrument>` and load algorithms that are using it.
+- Up to 30% performance improvement for :ref:`CropToComponent <algm-CropToComponent>` based on ongoing work on Instrument-2.0.
Python
------
diff --git a/docs/source/release/v3.12.0/indirect_inelastic.rst b/docs/source/release/v3.12.0/indirect_inelastic.rst
index e4d374817645fff48b81eb22fd105102e3e38583..6759792bee11b44c4a2c2cfa8e89ca33c6649c2c 100644
--- a/docs/source/release/v3.12.0/indirect_inelastic.rst
+++ b/docs/source/release/v3.12.0/indirect_inelastic.rst
@@ -37,6 +37,7 @@ New
Improved
########
- The Plot Guess Feature in the ConvFit Interface is now enabled for the diffusion functions.
+- The Plot Guess Feature in the MSDFit Interface is now implemented for the three models introduced in release v3.11 (MsdGauss, MsdPeters and MsdYi).
Bugfixes
########
diff --git a/docs/source/techniques/ISISPowder-Pearl-v1.rst b/docs/source/techniques/ISISPowder-Pearl-v1.rst
index 76d56a89537ef4ddf6eaafc95f80d397b6f512fb..404a1e8f8328e79ee45d53439a66c5d8b45118b7 100644
--- a/docs/source/techniques/ISISPowder-Pearl-v1.rst
+++ b/docs/source/techniques/ISISPowder-Pearl-v1.rst
@@ -55,6 +55,7 @@ The following methods can be executed on a PEARL object:
- :ref:`create_vanadium_pearl_isis-powder-diffraction-ref`
- :ref:`focus_pearl_isis-powder-diffraction-ref`
+- :ref:`create_cal_pearl_isis-powder-diffraction-ref`
For information on creating a PEARL object see:
:ref:`creating_pearl_object-isis-powder-diffraction-ref`
@@ -113,7 +114,7 @@ The following parameter is required if
The following parameter may also be optionally set:
- :ref:`file_ext_pearl_isis-powder-diffraction-ref`
-
+
Example
=======
@@ -131,6 +132,32 @@ Example
run_number="100-110", tt_mode="tt88",
vanadium_normalisation=True)
+.. _create_cal_pearl_isis-powder-diffraction-ref:
+
+create_cal
+^^^^^^^^^^
+The *create_cal* method creates the offset calibration file for PEARL
+scripts. The following parameters are required:
+
+- :ref:`calibration_mapping_file_pearl_isis-powder-diffraction-ref`
+- :ref:`focus_mode_pearl_isis-powder-diffraction-ref`
+- :ref:`long_mode_pearl_isis-powder-diffraction-ref`
+- :ref:`run_number_pearl_isis-powder-diffraction-ref`
+
+Example
+=======
+
+.. code-block:: python
+
+ # Notice how the filename ends with .yaml
+ cal_mapping_file = r"C:\path\to\cal_mapping.yaml"
+
+ pearl_example.create_cal(run_number=95671,
+ tt_mode="tt70",
+ long_mode=True,
+ calibration_mapping_file=cal_mapping_file)
+
+
.. _calibration_mapping_pearl_isis-powder-diffraction-ref:
Calibration Mapping File
@@ -462,7 +489,8 @@ Example Input:
run_number
^^^^^^^^^^
Specifies the run number(s) to process when calling the
-:ref:`focus_pearl_isis-powder-diffraction-ref` method.
+:ref:`focus_pearl_isis-powder-diffraction-ref` and
+:ref:`create_cal_isis-powder-diffraction-ref` methods.
This parameter accepts a single value or a range
of values with the following syntax:
@@ -573,6 +601,104 @@ requires the user to restart Mantid for the new values to take effect.
Please read :ref:`instrument_advanced_properties_isis-powder-diffraction-ref`
before proceeding to change values within the advanced configuration file.
+.. _create_cal_rebin_1_params_pearl_isis-powder-diffraction-ref:
+
+create_cal_rebin_1_params
+^^^^^^^^^^^^^^^^^^^^^^^^^
+The rebin parameters to use in the first rebin operation in
+:ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL this is
+set to the following:
+
+.. code-block:: python
+
+ # Long mode OFF:
+ create_cal_rebin_1_params: "100,-0.0006,19950"
+
+ # Long mode ON:
+ create_cal_rebin_1_params: "20300,-0.0006,39990"
+
+
+.. _create_cal_rebin_2_params_pearl_isis-powder-diffraction-ref:
+
+create_cal_rebin_2_params
+^^^^^^^^^^^^^^^^^^^^^^^^^
+The rebin parameters to use in the second rebin operation in
+:ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL this is
+set to the following:
+
+.. code-block:: python
+
+ create_cal_rebin_2_params: "1.8,0.002,2.1"
+
+
+.. _cross_corr_reference_spectra_pearl_isis-powder-diffraction-ref:
+
+cross_corr_reference_spectra
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+The Workspace Index of the spectra to correlate all other spectra
+against in the cross-correlation step of
+:ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL this is
+set to the following:
+
+.. code-block:: python
+
+ cross_corr_reference_spectra: 20
+
+
+.. _cross_corr_ws_index_max_pearl_isis-powder-diffraction-ref:
+
+cross_corr_ws_index_max
+^^^^^^^^^^^^^^^^^^^^^^^
+The workspace index of the last member of the range of spectra to
+cross-correlate against in
+:ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL this is
+set to the following:
+
+.. code-block:: python
+
+ cross_corr_ws_index_max: 1063
+
+
+.. _cross_corr_ws_index_min_pearl_isis-powder-diffraction-ref:
+
+cross_corr_ws_index_min
+^^^^^^^^^^^^^^^^^^^^^^^
+The workspace index of the first member of the range of spectra to
+cross-correlate against in
+:ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL this is
+set to the following:
+
+.. code-block:: python
+
+ cross_corr_ws_index_min: 9
+
+
+.. _cros_cor_x_max_pearl_isis-powder-diffraction-ref:
+
+cross_cor_x_max
+^^^^^^^^^^^^^^^
+The ending point of the region to be cross correlated in
+:ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL this is
+set to the following:
+
+.. code-block:: python
+
+ cross_corr_x_max: 2.1
+
+
+.. _cros_corr_x_min_pearl_isis-powder-diffraction-ref:
+
+cross_cor_x_min
+^^^^^^^^^^^^^^^
+The starting point of the region to be cross correlated in
+:ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL this is
+set to the following:
+
+.. code-block:: python
+
+ cross_corr_x_min: 1.8
+
+
.. _focused_cropping_values_pearl_isis-powder-diffraction-ref:
focused_cropping_values
@@ -630,6 +756,58 @@ On PEARL this is set to the following TOF windows:
]
+.. _get_det_offsets_d_ref_pearl_isis-powder-diffraction-ref:
+
+get_det_offsets_d_ref
+^^^^^^^^^^^^^^^^^^^^^
+Center of reference peak in d-space for GetDetectorOffsets in
+:ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL this is
+set to the following:
+
+.. code-block:: python
+
+ get_det_offsets_d_ref: 1.912795
+
+
+.. _get_det_offsets_step_pearl_isis-powder-diffraction-ref:
+
+get_det_offsets_step
+^^^^^^^^^^^^^^^^^^^^
+Step size used to bin d-spacing data in GetDetectorOffsets when
+running :ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL
+this is set to the following:
+
+.. code-block:: python
+
+ get_det_offsets_step: 0.002
+
+
+.. _get_det_offsets_x_max_pearl_isis-powder-diffraction-ref:
+
+get_det_offsets_x_max
+^^^^^^^^^^^^^^^^^^^^^
+Maximum of CrossCorrelation data to search for peak, usually negative,
+in :ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL this
+is set to the following:
+
+.. code-block:: python
+
+ get_det_offsets_x_max: -200
+
+
+.. _get_det_offsets_x_min_pearl_isis-powder-diffraction-ref:
+
+get_det_offsets_x_min
+^^^^^^^^^^^^^^^^^^^^^
+Minimum of CrossCorrelation data to search for peak, usually negative,
+in :ref:`create_cal_pearl_isis-powder-diffraction-ref`. On PEARL this
+is set to the following:
+
+.. code-block:: python
+
+ get_det_offsets_x_min: -200
+
+
.. _monitor_lambda_crop_range_pearl_isis-powder-diffraction-ref:
monitor_lambda_crop_range
diff --git a/instrument/Facilities.xml b/instrument/Facilities.xml
index b218298efb24d2994ad442ec7f41235c8731dfab..061fd364bd169b7259d6a12d23059867425af0ab 100644
--- a/instrument/Facilities.xml
+++ b/instrument/Facilities.xml
@@ -799,14 +799,14 @@
<instrument name="ISIS_Histogram">
<technique>Test Listener</technique>
<livedata>
- <connection name="histo" address="localhost:56789" listener="ISISHistoDataListener" />
+ <connection name="histo" address="127.0.0.1:56789" listener="ISISHistoDataListener" />
</livedata>
</instrument>
<instrument name="ISIS_Event">
<technique>Test Listener</technique>
<livedata>
- <connection name="event" address="localhost:59876" listener="ISISLiveEventDataListener" />
+ <connection name="event" address="127.0.0.1:59876" listener="ISISLiveEventDataListener" />
</livedata>
</instrument>
diff --git a/instrument/SEQUOIA_Definition-20120404-20171113.xml b/instrument/SEQUOIA_Definition-20120404-20171113.xml
new file mode 100644
index 0000000000000000000000000000000000000000..c2e6b15bc303f5afc3df1adc4cc0f067899bb3f0
--- /dev/null
+++ b/instrument/SEQUOIA_Definition-20120404-20171113.xml
@@ -0,0 +1,1826 @@
+<?xml version='1.0' encoding='ASCII'?>
+<!-- For help on the notation used to specify an Instrument Definition File
+ see http://www.mantidproject.org/IDF -->
+<instrument xmlns="http://www.mantidproject.org/IDF/1.0"
+ xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+ xsi:schemaLocation="http://www.mantidproject.org/IDF/1.0 http://schema.mantidproject.org/IDF/1.0/IDFSchema.xsd"
+ valid-to="2017-11-13 23:59:59" name="SEQUOIA" valid-from="2012-04-04 14:15:46.929098">
+ <!--For runs after 19889 -->
+ <defaults>
+ <length unit="metre"/>
+ <angle unit="degree"/>
+ <reference-frame>
+ <along-beam axis="z"/>
+ <pointing-up axis="y"/>
+ <handedness val="right"/>
+ </reference-frame>
+ </defaults>
+ <!--SOURCE AND SAMPLE POSITION-->
+ <component type="moderator">
+ <location z="-20.0114"/>
+ </component>
+ <type is="Source" name="moderator"/>
+ <component type="sample-position">
+ <location y="0.0" x="0.0" z="0.0"/>
+ </component>
+ <type is="SamplePos" name="sample-position"/>
+ <!--MONITORS-->
+ <component type="monitors" idlist="monitors">
+ <location/>
+ </component>
+ <type name="monitors">
+ <component type="monitor">
+ <location z="-1.77808" name="monitor1"/>
+ <location z="8.99184" name="monitor2"/>
+ </component>
+ </type>
+ <component type="B row" idlist="B row">
+ <location/>
+ </component>
+ <type name="B row">
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+ <id start="73728" end="74751"/>
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+ </idlist>
+ <idlist idname="C row">
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+ <id start="112640" end="113663"/>
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+ <id start="114688" end="115711"/>
+ </idlist>
+ <idlist idname="D row">
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+ <id start="117760" end="118783"/>
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+ <id start="150528" end="151551"/>
+ <id start="151552" end="152575"/>
+ <id start="152576" end="153599"/>
+ </idlist>
+ <!--MONITOR IDs-->
+ <idlist idname="monitors">
+ <id val="-1"/>
+ <id val="-2"/>
+ </idlist>
+ <!--DETECTOR PARAMETERS-->
+ <component-link name="B row">
+ <parameter name="tube_pressure">
+ <value units="atm" val="10.0"/>
+ </parameter>
+ <parameter name="tube_thickness">
+ <value units="metre" val="0.0008"/>
+ </parameter>
+ <parameter name="tube_temperature">
+ <value units="K" val="290.0"/>
+ </parameter>
+ </component-link>
+ <component-link name="C row">
+ <parameter name="tube_pressure">
+ <value units="atm" val="10.0"/>
+ </parameter>
+ <parameter name="tube_thickness">
+ <value units="metre" val="0.0008"/>
+ </parameter>
+ <parameter name="tube_temperature">
+ <value units="K" val="290.0"/>
+ </parameter>
+ </component-link>
+ <component-link name="D row">
+ <parameter name="tube_pressure">
+ <value units="atm" val="10.0"/>
+ </parameter>
+ <parameter name="tube_thickness">
+ <value units="metre" val="0.0008"/>
+ </parameter>
+ <parameter name="tube_temperature">
+ <value units="K" val="290.0"/>
+ </parameter>
+ </component-link>
+</instrument>
diff --git a/instrument/SEQUOIA_Definition.xml b/instrument/SEQUOIA_Definition.xml
index ae0a7cf3160892b2a4e763b9bc8bb9dfe66fe886..bfc60dbcf2292a9c39c90b8c10c9d06a05964ce6 100644
--- a/instrument/SEQUOIA_Definition.xml
+++ b/instrument/SEQUOIA_Definition.xml
@@ -4,7 +4,7 @@
<instrument xmlns="http://www.mantidproject.org/IDF/1.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://www.mantidproject.org/IDF/1.0 http://schema.mantidproject.org/IDF/1.0/IDFSchema.xsd"
- valid-to="2100-01-31 23:59:59" name="SEQUOIA" valid-from="2012-04-04 14:15:46.929098">
+ valid-to="2100-01-31 23:59:59" name="SEQUOIA" valid-from="2017-11-14 00:00:00">
<!--For runs after 19889 -->
<defaults>
<length unit="metre"/>
@@ -150,265 +150,305 @@
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diff --git a/qt/scientific_interfaces/CMakeLists.txt b/qt/scientific_interfaces/CMakeLists.txt
index e979e681458c44050ef2a469c5abd13d92cd78ac..25a9fa612bf0b3eab71e068b2ce4bf437bbb6835 100644
--- a/qt/scientific_interfaces/CMakeLists.txt
+++ b/qt/scientific_interfaces/CMakeLists.txt
@@ -30,6 +30,7 @@ set ( TEST_FILES
test/ALCLatestFileFinderTest.h
test/ALCPeakFittingModelTest.h
test/ALCPeakFittingPresenterTest.h
+ test/EnggDiffFittingModelTest.h
test/EnggDiffFittingPresenterTest.h
test/EnggDiffractionPresenterTest.h
test/IO_MuonGroupingTest.h
diff --git a/qt/scientific_interfaces/EnggDiffraction/CMakeLists.txt b/qt/scientific_interfaces/EnggDiffraction/CMakeLists.txt
index 985648af0074a208841bb5256b44c65d0f60990f..e5e0b3be88254d266056ec745716c1e6405d0117 100644
--- a/qt/scientific_interfaces/EnggDiffraction/CMakeLists.txt
+++ b/qt/scientific_interfaces/EnggDiffraction/CMakeLists.txt
@@ -1,4 +1,5 @@
set ( SRC_FILES
+ EnggDiffFittingModel.cpp
EnggDiffFittingPresenter.cpp
EnggDiffFittingViewQtWidget.cpp
EnggDiffractionPresenter.cpp
@@ -9,6 +10,7 @@ set ( SRC_FILES
# IMPORTANT: Include files are required in the MOC_FILES set. Scroll down to find it.
set ( INC_FILES
EnggDiffCalibSettings.h
+ EnggDiffFittingModel.h
EnggDiffFittingPresWorker.h
EnggDiffFittingPresenter.h
EnggDiffFittingViewQtWidget.h
@@ -21,6 +23,7 @@ set ( INC_FILES
)
set ( MOC_FILES
+ EnggDiffFittingModel.h
EnggDiffFittingPresenter.h
EnggDiffFittingPresWorker.h
EnggDiffFittingViewQtWidget.h
diff --git a/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingModel.cpp b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingModel.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..6c9cd5cedc9430afbbe35531f3efaf034bc8f7be
--- /dev/null
+++ b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingModel.cpp
@@ -0,0 +1,133 @@
+#include "EnggDiffFittingModel.h"
+
+#include "MantidAPI/AlgorithmManager.h"
+#include "MantidAPI/AnalysisDataService.h"
+#include "MantidAPI/MatrixWorkspace.h"
+#include "MantidAPI/MatrixWorkspace_fwd.h"
+#include "MantidAPI/Run.h"
+#include "MantidAPI/WorkspaceGroup.h"
+#include "MantidKernel/PropertyWithValue.h"
+
+#include <algorithm>
+#include <numeric>
+
+using namespace Mantid;
+
+namespace {
+
+template <typename T> void insertInOrder(const T &item, std::vector<T> &vec) {
+ vec.insert(std::upper_bound(vec.begin(), vec.end(), item), item);
+}
+
+bool isDigit(const std::string &text) {
+ return std::all_of(text.cbegin(), text.cend(), ::isdigit);
+}
+
+} // anonymous namespace
+
+namespace MantidQT {
+namespace CustomInterfaces {
+
+void EnggDiffFittingModel::addWorkspace(const int runNumber, const size_t bank,
+ const API::MatrixWorkspace_sptr ws) {
+ m_wsMap[bank - 1][runNumber] = ws;
+}
+
+API::MatrixWorkspace_sptr
+EnggDiffFittingModel::getWorkspace(const int runNumber, const size_t bank) {
+ if (bank < 1 || bank > m_wsMap.size()) {
+ return nullptr;
+ }
+ if (m_wsMap[bank - 1].find(runNumber) == m_wsMap[bank - 1].end()) {
+ return nullptr;
+ }
+ return m_wsMap[bank - 1][runNumber];
+}
+
+std::vector<int> EnggDiffFittingModel::getAllRunNumbers() const {
+ std::vector<int> runNumbers;
+
+ for (const auto &workspaces : m_wsMap) {
+ for (const auto &kvPair : workspaces) {
+ const auto runNumber = kvPair.first;
+ if (std::find(runNumbers.begin(), runNumbers.end(), runNumber) ==
+ runNumbers.end()) {
+ insertInOrder(runNumber, runNumbers);
+ }
+ }
+ }
+
+ return runNumbers;
+}
+
+void EnggDiffFittingModel::loadWorkspaces(const std::string &filename) {
+ auto loadAlg = API::AlgorithmManager::Instance().create("Load");
+ loadAlg->initialize();
+
+ loadAlg->setPropertyValue("Filename", filename);
+ loadAlg->setPropertyValue("OutputWorkspace", FOCUSED_WS_NAME);
+ loadAlg->execute();
+
+ API::AnalysisDataServiceImpl &ADS = API::AnalysisDataService::Instance();
+ if (filename.find(",") == std::string::npos) { // Only 1 run loaded
+ const auto ws = ADS.retrieveWS<API::MatrixWorkspace>(FOCUSED_WS_NAME);
+ addWorkspace(ws->getRunNumber(), guessBankID(ws), ws);
+ } else {
+ const auto group_ws = ADS.retrieveWS<API::WorkspaceGroup>(FOCUSED_WS_NAME);
+ for (auto iter = group_ws->begin(); iter != group_ws->end(); ++iter) {
+ const auto ws = boost::dynamic_pointer_cast<API::MatrixWorkspace>(*iter);
+ addWorkspace(ws->getRunNumber(), guessBankID(ws), ws);
+ }
+ }
+}
+
+std::vector<std::pair<int, size_t>>
+EnggDiffFittingModel::getRunNumbersAndBanksIDs() {
+ std::vector<std::pair<int, size_t>> pairs;
+
+ const auto runNumbers = getAllRunNumbers();
+ for (const auto runNumber : runNumbers) {
+ for (size_t i = 0; i < m_wsMap.size(); ++i) {
+ if (m_wsMap[i].find(runNumber) != m_wsMap[i].end()) {
+ pairs.push_back(std::pair<int, size_t>(runNumber, i + 1));
+ }
+ }
+ }
+ return pairs;
+}
+
+size_t
+EnggDiffFittingModel::guessBankID(API::MatrixWorkspace_const_sptr ws) const {
+ if (ws->run().hasProperty("bankid")) {
+ const auto log = dynamic_cast<Kernel::PropertyWithValue<int> *>(
+ ws->run().getLogData("bankid"));
+ return boost::lexical_cast<size_t>(log->value());
+ }
+
+ // couldn't get it from sample logs - try using the old naming convention
+ auto name = ws->getName();
+ std::vector<std::string> chunks;
+ boost::split(chunks, name, boost::is_any_of("_"));
+ bool isNum = isDigit(chunks.back());
+ if (!chunks.empty() && isNum) {
+ try {
+ return boost::lexical_cast<size_t>(chunks.back());
+ } catch (boost::exception &) {
+ // If we get a bad cast or something goes wrong then
+ // the file is probably not what we were expecting
+ // so throw a runtime error
+ throw std::runtime_error(
+ "Failed to fit file: The data was not what is expected. "
+ "Does the file contain a focused workspace?");
+ }
+ }
+
+ throw std::runtime_error("Could not guess run number from input workspace. "
+ "Are you sure it has been focused correctly?");
+}
+
+const std::string EnggDiffFittingModel::FOCUSED_WS_NAME =
+ "engggui_fitting_focused_ws";
+
+} // namespace CustomInterfaces
+} // namespace MantidQT
diff --git a/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingModel.h b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingModel.h
new file mode 100644
index 0000000000000000000000000000000000000000..9993fa1315b0b009a8e8ff0a20f0847a5cb082e6
--- /dev/null
+++ b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingModel.h
@@ -0,0 +1,38 @@
+#ifndef MANTIDQTCUSTOMINTERFACES_ENGGDIFFRACTION_ENGGDIFFFITTINGMODEL_H_
+#define MANTIDQTCUSTOMINTERFACES_ENGGDIFFRACTION_ENGGDIFFFITTINGMODEL_H_
+
+#include "DllConfig.h"
+#include "MantidAPI/MatrixWorkspace_fwd.h"
+
+#include <array>
+#include <unordered_map>
+#include <vector>
+
+using namespace Mantid;
+
+namespace MantidQT {
+namespace CustomInterfaces {
+
+class MANTIDQT_ENGGDIFFRACTION_DLL EnggDiffFittingModel {
+public:
+ API::MatrixWorkspace_sptr getWorkspace(const int runNumber,
+ const size_t bank);
+ std::vector<int> getAllRunNumbers() const;
+ void loadWorkspaces(const std::string &filename);
+ std::vector<std::pair<int, size_t>> getRunNumbersAndBanksIDs();
+ void addWorkspace(const int runNumber, const size_t bank,
+ const API::MatrixWorkspace_sptr ws);
+
+private:
+ static const size_t MAX_BANKS = 2;
+ static const std::string FOCUSED_WS_NAME;
+ std::array<std::unordered_map<int, API::MatrixWorkspace_sptr>, MAX_BANKS>
+ m_wsMap;
+
+ size_t guessBankID(API::MatrixWorkspace_const_sptr) const;
+};
+
+} // namespace CustomInterfaces
+} // namespace MantidQT
+
+#endif // MANTIDQTCUSTOMINTERFACES_ENGGDIFFRACTION_ENGGDIFFFITTINGMODEL_H_
diff --git a/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingPresenter.cpp b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingPresenter.cpp
index 09808dcdff316a764bf5b3de387bdfb1784ce812..385f141bdac433f4b9e83598548e44aad63f594a 100644
--- a/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingPresenter.cpp
+++ b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingPresenter.cpp
@@ -1,6 +1,7 @@
#include "EnggDiffFittingPresenter.h"
#include "MantidAPI/AlgorithmManager.h"
#include "MantidAPI/AnalysisDataService.h"
+#include "MantidAPI/WorkspaceGroup.h"
#include "MantidAPI/ITableWorkspace.h"
#include "MantidAPI/MatrixWorkspace.h"
#include "MantidAPI/Run.h"
@@ -9,6 +10,7 @@
#include "MantidQtWidgets/LegacyQwt/QwtHelper.h"
#include "EnggDiffFittingPresWorker.h"
+#include <boost/algorithm/string.hpp>
#include <boost/lexical_cast.hpp>
#include <cctype>
#include <fstream>
@@ -29,6 +31,7 @@ Mantid::Kernel::Logger g_log("EngineeringDiffractionGUI");
const bool EnggDiffFittingPresenter::g_useAlignDetectors = true;
+// MOVE THIS TO THE MODEL
const std::string EnggDiffFittingPresenter::g_focusedFittingWSName =
"engggui_fitting_focused_ws";
@@ -124,6 +127,10 @@ void EnggDiffFittingPresenter::notify(
case IEnggDiffFittingPresenter::LogMsg:
processLogMsg();
break;
+
+ case IEnggDiffFittingPresenter::selectRun:
+ processSelectRun();
+ break;
}
}
@@ -345,6 +352,16 @@ std::vector<std::string> EnggDiffFittingPresenter::processFullPathInput(
return foundFullFilePaths;
}
+void EnggDiffFittingPresenter::processSelectRun() {
+ const auto workspaceID = m_view->getFittingListWidgetCurrentValue();
+ std::vector<std::string> tokens;
+
+ boost::split(tokens, workspaceID, boost::is_any_of("_"));
+ const auto ws =
+ m_model.getWorkspace(std::stoi(tokens[0]), std::stoi(tokens[1]));
+ plotFocusedFile(false, ws);
+}
+
/**
* Takes the full path of a file which has been selected through
* browse, the run number the user has input and stores the
@@ -703,40 +720,60 @@ EnggDiffFittingPresenter::enableMultiRun(const std::string &firstRun,
void EnggDiffFittingPresenter::processStart() {}
-void EnggDiffFittingPresenter::processLoad() {
- // while file text-area is not empty
- // while directory vector is not empty
- // if loaded here set a global variable true so doesnt load again?
-
- try {
- MatrixWorkspace_sptr focusedWS;
- const std::string focusedFile = m_view->getFittingRunNo();
- Poco::Path selectedfPath(focusedFile);
+size_t EnggDiffFittingPresenter::findBankID(
+ Mantid::API::MatrixWorkspace_sptr ws) const {
+ // MOVE THIS TO THE MODEL
+ size_t bankID = 1;
- if (!focusedFile.empty() && selectedfPath.isFile()) {
- runLoadAlg(focusedFile, focusedWS);
- setDifcTzero(focusedWS);
- convertUnits(g_focusedFittingWSName);
- plotFocusedFile(false);
+ auto name = ws->getName();
+ std::vector<std::string> chunks;
+ boost::split(chunks, name, boost::is_any_of("_"));
+ bool isNum = isDigit(chunks.back());
+ if (!chunks.empty() && isNum) {
+ try {
+ bankID = boost::lexical_cast<size_t>(chunks.back());
+ } catch (boost::exception &) {
+ // If we get a bad cast or something goes wrong then
+ // the file is probably not what we were expecting
+ // so throw a runtime error
+ throw std::runtime_error(
+ "Failed to fit file: The data was not what is expected. "
+ "Does the file contain focused " +
+ m_view->getCurrentInstrument() + " workspace?");
+ }
+ }
+ return bankID;
+}
- m_view->showStatus(
- "Focused file loaded! (Click 'Select "
- "Peak' to activate peak picker tool, hold Shift + Click "
- "Peak, Click 'Add Peak')");
+void EnggDiffFittingPresenter::processLoad() {
+ const std::string filenames = m_view->getFittingRunNo();
- } else {
- m_view->userWarning("No File Found",
- "Please select a focused file to load");
- m_view->showStatus("Error while plotting the focused workspace");
- }
- } catch (std::invalid_argument &ia) {
- m_view->userWarning(
- "Failed to load the selected focus file",
- "The focus file failed to load, please check the logger for more"
- " information.");
- g_log.error("Failed to load file. Error message: ");
- g_log.error(ia.what());
+ try {
+ m_model.loadWorkspaces(filenames);
+ } catch (Poco::PathSyntaxException &ex) {
+ warnFileNotFound(ex);
+ return;
+ } catch (std::invalid_argument &ex) {
+ warnFileNotFound(ex);
+ return;
+ } catch (Mantid::Kernel::Exception::NotFoundError &ex) {
+ warnFileNotFound(ex);
+ return;
}
+
+ const auto runNoBankPairs = m_model.getRunNumbersAndBanksIDs();
+ std::vector<std::string> workspaceIDs;
+ std::transform(
+ runNoBankPairs.begin(), runNoBankPairs.end(),
+ std::back_inserter(workspaceIDs), [](const std::pair<int, size_t> &pair) {
+ return std::to_string(pair.first) + "_" + std::to_string(pair.second);
+ });
+ m_view->enableFittingListWidget(true);
+ m_view->clearFittingListWidget();
+ std::for_each(workspaceIDs.begin(), workspaceIDs.end(),
+ [&](const std::string &workspaceID) {
+ m_view->addRunNoItem(workspaceID);
+ });
}
void EnggDiffFittingPresenter::processShutDown() {
@@ -921,31 +958,7 @@ std::string EnggDiffFittingPresenter::validateFittingexpectedPeaks(
}
void EnggDiffFittingPresenter::setDifcTzero(MatrixWorkspace_sptr wks) const {
- size_t bankID = 1;
- // attempt to guess bankID - this should be done in code that is currently
- // in the view
- auto fittingFilename = m_view->getFittingRunNo();
- Poco::File fittingFile(fittingFilename);
- if (fittingFile.exists()) {
- Poco::Path path(fittingFile.path());
- auto name = path.getBaseName();
- std::vector<std::string> chunks;
- boost::split(chunks, name, boost::is_any_of("_"));
- bool isNum = isDigit(chunks.back());
- if (!chunks.empty() && isNum) {
- try {
- bankID = boost::lexical_cast<size_t>(chunks.back());
- } catch (boost::exception &) {
- // If we get a bad cast or something goes wrong then
- // the file is probably not what we were expecting
- // so throw a runtime error
- throw std::runtime_error(
- "Failed to fit file: The data was not what is expected. "
- "Does the file contain focused " +
- m_view->getCurrentInstrument() + " workspace?");
- }
- }
- }
+ const auto bankID = findBankID(wks);
const std::string units = "none";
auto &run = wks->mutableRun();
@@ -1714,19 +1727,20 @@ bool EnggDiffFittingPresenter::isDigit(const std::string &text) const {
return std::all_of(text.cbegin(), text.cend(), ::isdigit);
}
-void EnggDiffFittingPresenter::plotFocusedFile(bool plotSinglePeaks) {
- AnalysisDataServiceImpl &ADS = Mantid::API::AnalysisDataService::Instance();
+void EnggDiffFittingPresenter::warnFileNotFound(const std::exception &ex) {
+ m_view->showStatus("Error while loading focused run");
+ m_view->userWarning("Invalid file selected",
+ "Mantid could not load the selected file. "
+ "Are you sure it exists? "
+ "See the logger for more information");
+ g_log.error("Failed to load file. Error message: ");
+ g_log.error(ex.what());
+}
- if (!ADS.doesExist(g_focusedFittingWSName)) {
- g_log.error() << "Focused workspace could not be plotted as there is no " +
- g_focusedFittingWSName + " workspace found.\n";
- m_view->showStatus("Error while plotting focused workspace");
- return;
- }
+void EnggDiffFittingPresenter::plotFocusedFile(
+ bool plotSinglePeaks, MatrixWorkspace_sptr focusedPeaksWS) {
try {
- auto focusedPeaksWS =
- ADS.retrieveWS<MatrixWorkspace>(g_focusedFittingWSName);
auto focusedData = QwtHelper::curveDataFromWs(focusedPeaksWS);
// Check that the number of curves to plot isn't excessive
@@ -1774,7 +1788,9 @@ void EnggDiffFittingPresenter::plotFitPeaksCurves() {
m_view->resetCanvas();
// plots focused workspace
- plotFocusedFile(m_fittingFinishedOK);
+ throw new std::runtime_error("Plotting fit not yet implemented");
+ // TODO: sort out what to do here
+ // plotFocusedFile(m_fittingFinishedOK);
if (m_fittingFinishedOK) {
g_log.debug() << "single peaks fitting being plotted now.\n";
diff --git a/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingPresenter.h b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingPresenter.h
index 16a27d250fd3b5584acff3ed512af6568b773d33..a0736a7ff9c3ad763c8f6214084b5b7935e8e6cb 100644
--- a/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingPresenter.h
+++ b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingPresenter.h
@@ -4,6 +4,7 @@
#include "MantidAPI/ITableWorkspace_fwd.h"
#include "MantidAPI/MatrixWorkspace_fwd.h"
#include "DllConfig.h"
+#include "EnggDiffFittingModel.h"
#include "IEnggDiffFittingPresenter.h"
#include "IEnggDiffFittingView.h"
#include "IEnggDiffractionCalibration.h"
@@ -87,7 +88,8 @@ public:
std::string tableName, size_t row, std::string &startX,
std::string &endX);
- void plotFocusedFile(bool plotSinglePeaks);
+ void plotFocusedFile(bool plotSinglePeaks,
+ Mantid::API::MatrixWorkspace_sptr focusedPeaksWS);
void plotFitPeaksCurves();
@@ -145,8 +147,12 @@ protected slots:
void fittingRunNoChanged();
private:
+ size_t findBankID(Mantid::API::MatrixWorkspace_sptr ws) const;
+
bool isDigit(const std::string &text) const;
+ void warnFileNotFound(const std::exception &ex);
+
// Methods related single peak fits
virtual void
startAsyncFittingWorker(const std::vector<std::string> &focusedRunNo,
@@ -225,8 +231,14 @@ private:
/// Associated view for this presenter (MVP pattern)
IEnggDiffFittingView *const m_view;
+ /// Associated model for this presenter
+ MantidQT::CustomInterfaces::EnggDiffFittingModel m_model;
+
/// Holds if the view is in the process of being closed
bool m_viewHasClosed;
+
+ /// Handle the user selecting a different run to plot
+ void processSelectRun();
};
} // namespace CustomInterfaces
diff --git a/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingViewQtWidget.cpp b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingViewQtWidget.cpp
index a24d6a2e1ce8424d48f94a57ced94c48f010caba..cc00e278ccb5ce34fd2ebd59f4a8ae533ba2e82b 100644
--- a/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingViewQtWidget.cpp
+++ b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingViewQtWidget.cpp
@@ -86,11 +86,8 @@ void EnggDiffFittingViewQtWidget::doSetup() {
connect(m_ui.lineEdit_pushButton_run_num, SIGNAL(textEdited(const QString &)),
this, SLOT(resetFittingMode()));
- connect(m_ui.lineEdit_pushButton_run_num, SIGNAL(editingFinished()), this,
- SLOT(FittingRunNo()));
-
connect(m_ui.lineEdit_pushButton_run_num, SIGNAL(returnPressed()), this,
- SLOT(FittingRunNo()));
+ SLOT(loadClicked()));
connect(this, SIGNAL(getBanks()), this, SLOT(FittingRunNo()));
@@ -126,6 +123,10 @@ void EnggDiffFittingViewQtWidget::doSetup() {
connect(m_ui.pushButton_plot_separate_window, SIGNAL(released()),
SLOT(plotSeparateWindow()));
+ connect(m_ui.listWidget_fitting_run_num,
+ SIGNAL(itemClicked(QListWidgetItem *)), this,
+ SLOT(listWidget_fitting_run_num_clicked(QListWidgetItem *)));
+
// Tool-tip button
connect(m_ui.pushButton_tooltip, SIGNAL(released()), SLOT(showToolTipHelp()));
@@ -276,6 +277,12 @@ void EnggDiffFittingViewQtWidget::listViewFittingRun() {
}
}
+void EnggDiffFittingViewQtWidget::listWidget_fitting_run_num_clicked(
+ QListWidgetItem *clickedItem) {
+ const auto label = clickedItem->text();
+ m_presenter->notify(IEnggDiffFittingPresenter::selectRun);
+}
+
void EnggDiffFittingViewQtWidget::resetFittingMode() {
// resets the global variable so the list view widgets
// adds the run number to for single runs too
@@ -459,17 +466,17 @@ void EnggDiffFittingViewQtWidget::browseFitFocusedRun() {
std::string nexusFormat = "Nexus file with calibration table: NXS, NEXUS"
"(*.nxs *.nexus);;";
- QString path(
- QFileDialog::getOpenFileName(this, tr("Open Focused File "), prevPath,
- QString::fromStdString(nexusFormat)));
+ QStringList paths(
+ QFileDialog::getOpenFileNames(this, tr("Open Focused File "), prevPath,
+ QString::fromStdString(nexusFormat)));
- if (path.isEmpty()) {
+ if (paths.isEmpty()) {
return;
}
- MantidQt::API::AlgorithmInputHistory::Instance().setPreviousDirectory(path);
- setFittingRunNo(path.toStdString());
- getBanks();
+ // MantidQt::API::AlgorithmInputHistory::Instance().setPreviousDirectory(paths[0]);
+ setFittingRunNo(paths.join(",").toStdString());
+ // getBanks();
}
void EnggDiffFittingViewQtWidget::setFittingRunNo(const std::string &path) {
@@ -504,6 +511,11 @@ int EnggDiffFittingViewQtWidget::getFittingListWidgetCurrentRow() const {
return m_ui.listWidget_fitting_run_num->currentRow();
}
+std::string
+EnggDiffFittingViewQtWidget::getFittingListWidgetCurrentValue() const {
+ return m_ui.listWidget_fitting_run_num->currentItem()->text().toStdString();
+}
+
void EnggDiffFittingViewQtWidget::setFittingListWidgetCurrentRow(
int idx) const {
m_ui.listWidget_fitting_run_num->setCurrentRow(idx);
diff --git a/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingViewQtWidget.h b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingViewQtWidget.h
index 10c6c31e17dda70ac1e9017f930301e5cd783d00..3cfeef3885e8f1ec32f39b41fac008790c330d2a 100644
--- a/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingViewQtWidget.h
+++ b/qt/scientific_interfaces/EnggDiffraction/EnggDiffFittingViewQtWidget.h
@@ -107,6 +107,8 @@ public:
int getFittingListWidgetCurrentRow() const override;
+ std::string getFittingListWidgetCurrentValue() const override;
+
void setFittingListWidgetCurrentRow(int idx) const override;
std::string fittingPeaksData() const override;
@@ -190,6 +192,7 @@ private slots:
void showToolTipHelp();
void setBankDir(int idx);
void listViewFittingRun();
+ void listWidget_fitting_run_num_clicked(QListWidgetItem *listWidget);
private:
/// Setup the interface (tab UI)
diff --git a/qt/scientific_interfaces/EnggDiffraction/EnggDiffractionQtTabFitting.ui b/qt/scientific_interfaces/EnggDiffraction/EnggDiffractionQtTabFitting.ui
index 6ed8a033782e74f7c3703f23581ba38e5c86d190..7c50ba5e7e6a7d6f0dfc577b33d0a77bd92943df 100644
--- a/qt/scientific_interfaces/EnggDiffraction/EnggDiffractionQtTabFitting.ui
+++ b/qt/scientific_interfaces/EnggDiffraction/EnggDiffractionQtTabFitting.ui
@@ -373,7 +373,7 @@
</property>
<property name="maximumSize">
<size>
- <width>50</width>
+ <width>60</width>
<height>16777215</height>
</size>
</property>
diff --git a/qt/scientific_interfaces/EnggDiffraction/IEnggDiffFittingPresenter.h b/qt/scientific_interfaces/EnggDiffraction/IEnggDiffFittingPresenter.h
index 11f2a885682c810a1d456d34545755602453017a..8c5d25fd1c42f84a9168994e56e7faf43188ea6b 100644
--- a/qt/scientific_interfaces/EnggDiffraction/IEnggDiffFittingPresenter.h
+++ b/qt/scientific_interfaces/EnggDiffraction/IEnggDiffFittingPresenter.h
@@ -52,6 +52,7 @@ public:
savePeaks, ///< Save the peaks list
ShutDown, ///< closing the interface
LogMsg, ///< need to send a message to the Mantid log system
+ selectRun, ///< update plot with new run selected from list widget
};
/**
diff --git a/qt/scientific_interfaces/EnggDiffraction/IEnggDiffFittingView.h b/qt/scientific_interfaces/EnggDiffraction/IEnggDiffFittingView.h
index c1638eaeae7dda02b3dc830d457db61081f731d0..8fe38b27bc9a9a06f2deb04a59e78a1c6d96d857 100644
--- a/qt/scientific_interfaces/EnggDiffraction/IEnggDiffFittingView.h
+++ b/qt/scientific_interfaces/EnggDiffraction/IEnggDiffFittingView.h
@@ -191,6 +191,11 @@ public:
*/
virtual int getFittingListWidgetCurrentRow() const = 0;
+ /**
+ * @return The text on the current selected row of the list widget
+ */
+ virtual std::string getFittingListWidgetCurrentValue() const = 0;
+
/**
* Sets the current row of the fitting list widget
*
diff --git a/qt/scientific_interfaces/Indirect/ConvFit.cpp b/qt/scientific_interfaces/Indirect/ConvFit.cpp
index 457726a04c4205336eaa3bdfd79ab5737fa535a2..f87f091e91fec1da7f2d7e65f97e7fe6ba72eaec 100644
--- a/qt/scientific_interfaces/Indirect/ConvFit.cpp
+++ b/qt/scientific_interfaces/Indirect/ConvFit.cpp
@@ -481,7 +481,7 @@ void ConvFit::algorithmComplete(bool error, const QString &outputWSName) {
updatePlot();
updatePlotRange();
- std::string paramWsName = outputPrefix + "_Parameters";
+ const std::string paramWsName = outputPrefix + "_Parameters";
if (AnalysisDataService::Instance().doesExist(paramWsName)) {
QString prefixPrefix = "f1.f1.";
@@ -828,8 +828,8 @@ CompositeFunction_sptr ConvFit::createFunction(bool tieCentres,
func = FunctionFactory::Instance().createFunction("DeltaFunction");
index = model->addFunction(func);
std::string parName = createParName(index);
- populateFunction(func, model, m_properties["Delta Function"], parName,
- false);
+ populateFunction(func, model, m_properties["Delta Function"], false,
+ parName);
}
// ------------------------------------------------------------
@@ -880,7 +880,7 @@ CompositeFunction_sptr ConvFit::createFunction(bool tieCentres,
index = model->addFunction(product);
prefix1 = createParName(index, subIndex);
- populateFunction(func, model, m_properties["FitFunction1"], prefix1, false);
+ populateFunction(func, model, m_properties["FitFunction1"], false, prefix1);
// Add 2nd Lorentzian
if (fitTypeIndex == 2) {
@@ -898,8 +898,8 @@ CompositeFunction_sptr ConvFit::createFunction(bool tieCentres,
index = model->addFunction(product);
prefix2 = createParName(index, subIndex);
- populateFunction(func, model, m_properties["FitFunction2"], prefix2,
- false);
+ populateFunction(func, model, m_properties["FitFunction2"], false,
+ prefix2);
}
}
@@ -1033,39 +1033,6 @@ QtProperty *ConvFit::createFitType(QtProperty *fitTypeGroup,
return fitTypeGroup;
}
-/**
- * Populates the properties of a function with given values
- * @param func The function currently being added to the composite
- * @param comp A composite function of the previously called functions
- * @param group The QtProperty representing the fit type
- * @param pref The index of the functions eg. (f0.f1)
- * @param tie Bool to state if parameters are to be tied together
- */
-void ConvFit::populateFunction(IFunction_sptr func, IFunction_sptr comp,
- QtProperty *group, const std::string &pref,
- bool tie) {
- // Get sub-properties of group and apply them as parameters on the function
- // object
- QList<QtProperty *> props = group->subProperties();
-
- for (int i = 0; i < props.size(); i++) {
- if (tie || !props[i]->subProperties().isEmpty()) {
- std::string name = pref + props[i]->propertyName().toStdString();
- std::string value = props[i]->valueText().toStdString();
- comp->tie(name, value);
- } else {
- std::string propName = props[i]->propertyName().toStdString();
- double propValue = props[i]->valueText().toDouble();
- if (propValue != 0.0) {
- if (func->hasAttribute(propName))
- func->setAttributeValue(propName, propValue);
- else
- func->setParameter(propName, propValue);
- }
- }
- }
-}
-
/**
* Generate a string to describe the fit type selected by the user.
* Used when naming the resultant workspaces.
@@ -1237,8 +1204,8 @@ void ConvFit::updateProperties(int specNo) {
}
void ConvFit::updateProperties(int specNo, const QString &fitFunction) {
- bool isTwoLorentzian = fitFunction == "Lorentzian 2";
- bool specOutOfBounds =
+ const bool isTwoLorentzian = fitFunction == "Lorentzian 2";
+ const bool specOutOfBounds =
specNo < minimumSpectrum() || maximumSpectrum() < specNo;
for (auto ¶m : getFunctionParameters(fitFunction)) {
@@ -1294,7 +1261,7 @@ void ConvFit::plotGuess() {
// Do nothing if there is not a sample and resolution
if (m_uiForm.dsResInput->isValid() && m_uiForm.ckPlotGuess->isChecked()) {
extendResolutionWorkspace();
- bool tieCentres = (m_uiForm.cbFitType->currentIndex() == 2);
+ const bool tieCentres = (m_uiForm.cbFitType->currentIndex() == 2);
IndirectDataAnalysisTab::plotGuess(m_uiForm.ppPlotTop,
createFunction(tieCentres, true));
} else {
diff --git a/qt/scientific_interfaces/Indirect/ConvFit.h b/qt/scientific_interfaces/Indirect/ConvFit.h
index ec0880e97a052fb1be26c5b948aa63271b9e5f2a..5997d389e80ef443dcc9114fdac067b428d9cfd3 100644
--- a/qt/scientific_interfaces/Indirect/ConvFit.h
+++ b/qt/scientific_interfaces/Indirect/ConvFit.h
@@ -60,9 +60,6 @@ private:
QtProperty *createFitType(QtProperty *, const bool & = true);
void createTemperatureCorrection(Mantid::API::CompositeFunction_sptr product);
- void populateFunction(Mantid::API::IFunction_sptr func,
- Mantid::API::IFunction_sptr comp, QtProperty *group,
- const std::string &pref, bool tie);
QString fitTypeString() const;
QString backgroundString() const;
QString minimizerString(QString outputName) const;
diff --git a/qt/scientific_interfaces/Indirect/IndirectDataAnalysisTab.cpp b/qt/scientific_interfaces/Indirect/IndirectDataAnalysisTab.cpp
index fa7d733233e80703d9df0379cbd45245a5bba92b..5fb5de2db6395b103e62d1f3b0517e929a611aae 100644
--- a/qt/scientific_interfaces/Indirect/IndirectDataAnalysisTab.cpp
+++ b/qt/scientific_interfaces/Indirect/IndirectDataAnalysisTab.cpp
@@ -2,7 +2,9 @@
#include "MantidAPI/AnalysisDataService.h"
#include "MantidAPI/FunctionDomain1D.h"
+#include "MantidAPI/FunctionFactory.h"
#include "MantidAPI/MatrixWorkspace.h"
+#include "MantidAPI/WorkspaceFactory.h"
#include "MantidAPI/WorkspaceGroup.h"
#include "boost/shared_ptr.hpp"
@@ -167,6 +169,9 @@ void IndirectDataAnalysisTab::plotCurrentPreview() {
/**
* Plots the selected spectrum of the input workspace in this indirect data
* analysis tab.
+ *
+ * @param previewPlot The preview plot widget in which to plot the input
+ * input workspace.
*/
void IndirectDataAnalysisTab::plotInput(
MantidQt::MantidWidgets::PreviewPlot *previewPlot) {
@@ -204,6 +209,15 @@ void IndirectDataAnalysisTab::updatePlot(
}
}
+/**
+ * Plots the data in the workspace with the specified name. Plots the
+ * sample and fit spectrum in the specified top preview plot. Plots
+ * the diff spectra in the specified difference preview plot.
+ *
+ * @param workspaceName The name of the workspace to plot.
+ * @param fitPreviewPlot The fit preview plot.
+ * @param diffPreviewPlot The difference preview plot.
+ */
void IndirectDataAnalysisTab::updatePlot(
const std::string &workspaceName,
MantidQt::MantidWidgets::PreviewPlot *fitPreviewPlot,
@@ -228,6 +242,17 @@ void IndirectDataAnalysisTab::updatePlot(
}
}
+/**
+ * Plots the workspace at the index specified by the selected
+ * spectrum, in the specified workspace group. Plots the sample
+ * and fit spectrum in the specified top preview plot. Plots
+ * the diff spectra in the specified difference preview plot.
+ *
+ * @param outputWS The group workspace containing the
+ * workspaced to plot.
+ * @param fitPreviewPlot The fit preview plot.
+ * @param diffPreviewPlot The difference preview plot.
+ */
void IndirectDataAnalysisTab::updatePlot(
WorkspaceGroup_sptr outputWS,
MantidQt::MantidWidgets::PreviewPlot *fitPreviewPlot,
@@ -241,6 +266,15 @@ void IndirectDataAnalysisTab::updatePlot(
}
}
+/**
+ * Plots the data in the specified workspace. Plots the sample
+ * and fit spectrum in the specified top preview plot. Plots
+ * the diff spectra in the specified difference preview plot.
+ *
+ * @param outputWS The workspace to plot.
+ * @param fitPreviewPlot The fit preview plot.
+ * @param diffPreviewPlot The difference preview plot.
+ */
void IndirectDataAnalysisTab::updatePlot(
MatrixWorkspace_sptr outputWS,
MantidQt::MantidWidgets::PreviewPlot *fitPreviewPlot,
@@ -259,6 +293,18 @@ void IndirectDataAnalysisTab::updatePlot(
}
}
+/*
+ * Updates the plot range with the specified name, to match the range of
+ * the sample curve.
+ *
+ * @param rangeName The name of the range to update.
+ * @param previewPlot The preview plot widget, in which the range
+ * is specified.
+ * @param startRangePropName The name of the property specifying the start
+ * value for the range.
+ * @parma endRangePropName The name of the property specifying the end
+ * value for the range.
+ */
void IndirectDataAnalysisTab::updatePlotRange(
const QString &rangeName, MantidQt::MantidWidgets::PreviewPlot *previewPlot,
const QString &startRangePropName, const QString &endRangePropName) {
@@ -273,6 +319,14 @@ void IndirectDataAnalysisTab::updatePlotRange(
}
}
+/*
+ * Plots a guess of the fit for the specified function, in the
+ * specified preview plot widget.
+ *
+ * @param previewPlot The preview plot widget in which to plot
+ * the guess.
+ * @param function The function to fit.
+ */
void IndirectDataAnalysisTab::plotGuess(
MantidQt::MantidWidgets::PreviewPlot *previewPlot,
IFunction_sptr function) {
@@ -280,25 +334,40 @@ void IndirectDataAnalysisTab::plotGuess(
if (inputWorkspace()) {
auto guessWs = createGuessWorkspace(function);
- previewPlot->addSpectrum("Guess", guessWs, 0, Qt::green);
+
+ // Check whether the guess workspace has enough data points
+ // to plot
+ if (guessWs->x(0).size() >= 2) {
+ previewPlot->addSpectrum("Guess", guessWs, 0, Qt::green);
+ }
}
}
+/*
+ * Creates a guess workspace, for approximating a fit with the specified
+ * function on the input workspace.
+ *
+ * @param func The function to fit.
+ * @return A guess workspace containing the guess data for the fit.
+ */
MatrixWorkspace_sptr
IndirectDataAnalysisTab::createGuessWorkspace(IFunction_sptr func) {
const auto inputWS = inputWorkspace();
const auto startX = m_dblManager->value(m_properties["StartX"]);
const auto endX = m_dblManager->value(m_properties["EndX"]);
- const size_t binIndexLow = inputWS->binIndexOf(startX);
- const size_t binIndexHigh = inputWS->binIndexOf(endX);
- const size_t nData = binIndexHigh - binIndexLow;
+ const auto binIndexLow = inputWS->binIndexOf(startX);
+ const auto binIndexHigh = inputWS->binIndexOf(endX);
+ const auto nData = binIndexHigh - binIndexLow;
const auto &xPoints = inputWS->points(0);
std::vector<double> dataX(nData);
std::copy(&xPoints[binIndexLow], &xPoints[binIndexLow + nData],
dataX.begin());
- std::vector<double> dataY = computeOutput(func, dataX);
+ const auto dataY = computeOutput(func, dataX);
+
+ if (dataY.empty())
+ return WorkspaceFactory::Instance().create("Workspace2D", 1, 1, 1);
IAlgorithm_sptr createWsAlg =
createWorkspaceAlgorithm("__GuessAnon", 1, dataX, dataY);
@@ -306,9 +375,21 @@ IndirectDataAnalysisTab::createGuessWorkspace(IFunction_sptr func) {
return createWsAlg->getProperty("OutputWorkspace");
}
+/*
+ * Computes the output vector of applying the specified function to
+ * the specified input vector.
+ *
+ * @param func The function to apply.
+ * @param dataX Vector of input data.
+ * @return Vector containing values calculated from applying
+ * the specified function to the input data.
+ */
std::vector<double>
IndirectDataAnalysisTab::computeOutput(IFunction_sptr func,
const std::vector<double> &dataX) {
+ if (dataX.empty())
+ return std::vector<double>();
+
FunctionDomain1DVector domain(dataX);
FunctionValues outputData(domain);
func->function(domain, outputData);
@@ -320,6 +401,17 @@ IndirectDataAnalysisTab::computeOutput(IFunction_sptr func,
return dataY;
}
+/*
+ * Generates and returns an algorithm for creating a workspace, with
+ * the specified name, number of spectra and containing the specified
+ * x data and y data.
+ *
+ * @param workspaceName The name of the workspace to create.
+ * @param numSpec The number of spectra in the workspace to create.
+ * @param dataX The x data to add to the created workspace.
+ * @param dataY The y data to add to the created workspace.
+ * @return An algorithm for creating the workspace.
+ */
IAlgorithm_sptr IndirectDataAnalysisTab::createWorkspaceAlgorithm(
const std::string &workspaceName, int numSpec,
const std::vector<double> &dataX, const std::vector<double> &dataY) {
@@ -335,6 +427,86 @@ IAlgorithm_sptr IndirectDataAnalysisTab::createWorkspaceAlgorithm(
return createWsAlg;
}
+/**
+ * Create and populates a function with given values
+ * @param funcName The name of the function to create and populate populate
+ * @param group The QtProperty representing the fit type
+ * @param comp A composite function of the previously called functions to
+ * be used in tie
+ * @param tie Bool to state if parameters are to be tied together
+ * @param pref The index of the functions eg. (f0.f1)
+ */
+IFunction_sptr IndirectDataAnalysisTab::createPopulatedFunction(
+ const std::string &funcName, IFunction_sptr comp, QtProperty *group,
+ bool tie, const std::string &pref) {
+ IFunction_sptr func = FunctionFactory::Instance().createFunction(funcName);
+ populateFunction(func, comp, group, tie, pref);
+ return func;
+}
+
+/**
+ * Create and populates a function with given values
+ * @param func The function to populate
+ * @param group The QtProperty representing the fit type
+ * @param tie Bool to state if parameters are to be tied together
+ * @param pref The index of the functions eg. (f0.f1)
+ */
+IFunction_sptr
+IndirectDataAnalysisTab::createPopulatedFunction(const std::string &funcName,
+ QtProperty *group, bool tie,
+ const std::string &pref) {
+ IFunction_sptr func = FunctionFactory::Instance().createFunction(funcName);
+ populateFunction(func, group, tie, pref);
+ return func;
+}
+
+/**
+ * Populates the properties of a function with given values
+ * @param func The function to populate
+ * @param group The QtProperty representing the fit type
+ * @param tie Bool to state if parameters are to be tied together
+ * @param pref The index of the functions eg. (f0.f1)
+ */
+void IndirectDataAnalysisTab::populateFunction(IFunction_sptr func,
+ QtProperty *group, bool tie,
+ const std::string &pref) {
+ populateFunction(func, func, group, tie, pref);
+}
+
+/**
+ * Populates the properties of a function with given values
+ * @param func The function currently being added to the composite
+ * @param comp A composite function of the previously called functions
+ * @param group The QtProperty representing the fit type
+ * @param pref The index of the functions eg. (f0.f1)
+ * @param tie Bool to state if parameters are to be tied together
+ */
+void IndirectDataAnalysisTab::populateFunction(IFunction_sptr func,
+ IFunction_sptr comp,
+ QtProperty *group, bool tie,
+ const std::string &pref) {
+ // Get sub-properties of group and apply them as parameters on the function
+ // object
+ QList<QtProperty *> props = group->subProperties();
+
+ for (const auto &prop : props) {
+ if (tie || !prop->subProperties().isEmpty()) {
+ std::string name = pref + prop->propertyName().toStdString();
+ std::string value = prop->valueText().toStdString();
+ comp->tie(name, value);
+ } else {
+ std::string propName = prop->propertyName().toStdString();
+ double propValue = prop->valueText().toDouble();
+ if (propValue != 0.0) {
+ if (func->hasAttribute(propName))
+ func->setAttributeValue(propName, propValue);
+ else
+ func->setParameter(propName, propValue);
+ }
+ }
+ }
+}
+
} // namespace IDA
} // namespace CustomInterfaces
} // namespace MantidQt
diff --git a/qt/scientific_interfaces/Indirect/IndirectDataAnalysisTab.h b/qt/scientific_interfaces/Indirect/IndirectDataAnalysisTab.h
index a29dd0d2f9fc83b110a28cd76c6f9002e7921225..ccfa93c5b9dd6b33f759bfbb9e49d68a6b2c1771 100644
--- a/qt/scientific_interfaces/Indirect/IndirectDataAnalysisTab.h
+++ b/qt/scientific_interfaces/Indirect/IndirectDataAnalysisTab.h
@@ -118,6 +118,22 @@ protected:
const std::vector<double> &dataX,
const std::vector<double> &dataY);
+ Mantid::API::IFunction_sptr
+ createPopulatedFunction(const std::string &funcName,
+ Mantid::API::IFunction_sptr comp, QtProperty *group,
+ bool tie = false, const std::string &pref = "");
+
+ Mantid::API::IFunction_sptr
+ createPopulatedFunction(const std::string &funcName, QtProperty *group,
+ bool tie = false, const std::string &pref = "");
+
+ void populateFunction(Mantid::API::IFunction_sptr func, QtProperty *group,
+ bool tie = false, const std::string &pref = "");
+
+ void populateFunction(Mantid::API::IFunction_sptr func,
+ Mantid::API::IFunction_sptr comp, QtProperty *group,
+ bool tie = false, const std::string &pref = "");
+
/// DoubleEditorFactory
DoubleEditorFactory *m_dblEdFac;
/// QtCheckBoxFactory
diff --git a/qt/scientific_interfaces/Indirect/IqtFit.cpp b/qt/scientific_interfaces/Indirect/IqtFit.cpp
index 0b5607670ead1534dc13da5f91bf7ae4102af387..0925d7b60de9672e9cc1485c3e18c42cf4472cb8 100644
--- a/qt/scientific_interfaces/Indirect/IqtFit.cpp
+++ b/qt/scientific_interfaces/Indirect/IqtFit.cpp
@@ -426,20 +426,21 @@ CompositeFunction_sptr IqtFit::createFunction(bool tie) {
}
if (fitType == 2) {
- fname = "StretchedExp";
+ result->addFunction(createPopulatedFunction(
+ "StretchExp", m_properties["StretchedExp"], tie));
} else {
- fname = "Exponential1";
+ result->addFunction(
+ createPopulatedFunction("ExpDecay", m_properties["Exponential1"], tie));
}
- result->addFunction(createExponentialFunction(fname, tie));
-
if (fitType == 1 || fitType == 3) {
if (fitType == 1) {
- fname = "Exponential2";
+ result->addFunction(createPopulatedFunction(
+ "ExpDecay", m_properties["Exponential2"], tie));
} else {
- fname = "StretchedExp";
+ result->addFunction(createPopulatedFunction(
+ "StretchExp", m_properties["StretchedExp"], tie));
}
- result->addFunction(createExponentialFunction(fname, tie));
}
// Return CompositeFunction object to caller.
@@ -447,51 +448,11 @@ CompositeFunction_sptr IqtFit::createFunction(bool tie) {
return result;
}
-IFunction_sptr IqtFit::createExponentialFunction(const QString &name,
- bool tie) {
- IFunction_sptr result;
- if (name.startsWith("Exp")) {
- IFunction_sptr result =
- FunctionFactory::Instance().createFunction("ExpDecay");
- result->setParameter(
- "Height", m_dblManager->value(m_properties[name + ".Intensity"]));
- result->setParameter("Lifetime",
- m_dblManager->value(m_properties[name + ".Tau"]));
- if (tie) {
- result->tie("Height",
- m_properties[name + ".Intensity"]->valueText().toStdString());
- result->tie("Lifetime",
- m_properties[name + ".Tau"]->valueText().toStdString());
- }
- result->applyTies();
- return result;
- } else {
- IFunction_sptr result =
- FunctionFactory::Instance().createFunction("StretchExp");
- result->setParameter(
- "Height", m_dblManager->value(m_properties[name + ".Intensity"]));
- result->setParameter("Lifetime",
- m_dblManager->value(m_properties[name + ".Tau"]));
- result->setParameter("Stretching",
- m_dblManager->value(m_properties[name + ".Beta"]));
- if (tie) {
- result->tie("Height",
- m_properties[name + ".Intensity"]->valueText().toStdString());
- result->tie("Lifetime",
- m_properties[name + ".Tau"]->valueText().toStdString());
- result->tie("Stretching",
- m_properties[name + ".Beta"]->valueText().toStdString());
- }
- result->applyTies();
- return result;
- }
-}
-
QtProperty *IqtFit::createExponential(const QString &name) {
QtProperty *expGroup = m_grpManager->addProperty(name);
- m_properties[name + ".Intensity"] = m_dblManager->addProperty("Intensity");
+ m_properties[name + ".Intensity"] = m_dblManager->addProperty("Height");
m_dblManager->setDecimals(m_properties[name + ".Intensity"], NUM_DECIMALS);
- m_properties[name + ".Tau"] = m_dblManager->addProperty("Tau");
+ m_properties[name + ".Tau"] = m_dblManager->addProperty("Lifetime");
m_dblManager->setDecimals(m_properties[name + ".Tau"], NUM_DECIMALS);
expGroup->addSubProperty(m_properties[name + ".Intensity"]);
expGroup->addSubProperty(m_properties[name + ".Tau"]);
@@ -500,9 +461,9 @@ QtProperty *IqtFit::createExponential(const QString &name) {
QtProperty *IqtFit::createStretchedExp(const QString &name) {
QtProperty *prop = m_grpManager->addProperty(name);
- m_properties[name + ".Intensity"] = m_dblManager->addProperty("Intensity");
- m_properties[name + ".Tau"] = m_dblManager->addProperty("Tau");
- m_properties[name + ".Beta"] = m_dblManager->addProperty("Beta");
+ m_properties[name + ".Intensity"] = m_dblManager->addProperty("Height");
+ m_properties[name + ".Tau"] = m_dblManager->addProperty("Lifetime");
+ m_properties[name + ".Beta"] = m_dblManager->addProperty("Stretching");
m_dblManager->setRange(m_properties[name + ".Beta"], 0, 1);
m_dblManager->setDecimals(m_properties[name + ".Intensity"], NUM_DECIMALS);
m_dblManager->setDecimals(m_properties[name + ".Tau"], NUM_DECIMALS);
diff --git a/qt/scientific_interfaces/Indirect/IqtFit.h b/qt/scientific_interfaces/Indirect/IqtFit.h
index e1eb02576977c002ff9da68be9ef28efb53e63bc..86275cde486f8478458c582ce2527d84f795f754 100644
--- a/qt/scientific_interfaces/Indirect/IqtFit.h
+++ b/qt/scientific_interfaces/Indirect/IqtFit.h
@@ -59,8 +59,6 @@ private slots:
private:
boost::shared_ptr<Mantid::API::CompositeFunction>
createFunction(bool tie = false);
- boost::shared_ptr<Mantid::API::IFunction>
- createExponentialFunction(const QString &name, bool tie = false);
QtProperty *createExponential(const QString &);
QtProperty *createStretchedExp(const QString &);
void setDefaultParameters(const QString &name);
diff --git a/qt/scientific_interfaces/Indirect/MSDFit.cpp b/qt/scientific_interfaces/Indirect/MSDFit.cpp
index 3a8abd797cb8ab2eb57b8c204795ab10f1e34e0e..1289fd3a2d748a23b1a56d606750feabfa399fce 100644
--- a/qt/scientific_interfaces/Indirect/MSDFit.cpp
+++ b/qt/scientific_interfaces/Indirect/MSDFit.cpp
@@ -1,6 +1,7 @@
#include "MSDFit.h"
#include "../General/UserInputValidator.h"
#include "MantidAPI/AnalysisDataService.h"
+#include "MantidAPI/FunctionFactory.h"
#include "MantidAPI/WorkspaceGroup.h"
#include "MantidQtWidgets/LegacyQwt/RangeSelector.h"
@@ -36,11 +37,14 @@ void MSDFit::setup() {
m_properties["EndX"] = m_dblManager->addProperty("EndX");
m_dblManager->setDecimals(m_properties["EndX"], NUM_DECIMALS);
- m_properties["Gaussian"] = createModel("Gaussian", {"Intensity", "MSD"});
- m_properties["Peters"] = createModel("Peters", {"Intensity", "MSD", "Beta"});
- m_properties["Yi"] = createModel("Yi", {"Intensity", "MSD", "Sigma"});
+ m_properties["Gaussian"] = createModel("MsdGauss", {"Height", "MSD"});
+ m_properties["Peters"] = createModel("MsdPeters", {"Height", "MSD", "Beta"});
+ m_properties["Yi"] = createModel("MsdYi", {"Height", "MSD", "Sigma"});
auto fitRangeSelector = m_uiForm.ppPlotTop->addRangeSelector("MSDRange");
+ m_dblManager->setValue(m_properties["StartX"],
+ fitRangeSelector->getMinimum());
+ m_dblManager->setValue(m_properties["EndX"], fitRangeSelector->getMaximum());
modelSelection(m_uiForm.cbModelInput->currentIndex());
@@ -64,6 +68,13 @@ void MSDFit::setup() {
connect(m_uiForm.spPlotSpectrum, SIGNAL(valueChanged(int)), this,
SLOT(updatePlot()));
+ connect(m_dblManager, SIGNAL(propertyChanged(QtProperty *)), this,
+ SLOT(plotGuess()));
+ connect(m_uiForm.ckPlotGuess, SIGNAL(stateChanged(int)), this,
+ SLOT(plotGuess()));
+ connect(m_uiForm.cbModelInput, SIGNAL(currentIndexChanged(int)), this,
+ SLOT(plotGuess()));
+
connect(m_uiForm.spSpectraMin, SIGNAL(valueChanged(int)), this,
SLOT(specMinChanged(int)));
connect(m_uiForm.spSpectraMax, SIGNAL(valueChanged(int)), this,
@@ -90,7 +101,8 @@ void MSDFit::run() {
dataName.left(dataName.lastIndexOf("_")).toStdString() + "_s" +
std::to_string(specMin) + "_to_s" + std::to_string(specMax) + "_" +
model.toStdString() + "_msd";
- m_parameterToProperty = createParameterToPropertyMap(model);
+ m_parameterToProperty =
+ createParameterToPropertyMap(m_properties[model]->propertyName());
IAlgorithm_sptr msdAlg =
msdFitAlgorithm(modelToAlgorithmProperty(model), specMin, specMax);
@@ -113,7 +125,8 @@ void MSDFit::singleFit() {
m_pythonExportWsName =
dataName.left(dataName.lastIndexOf("_")).toStdString() + "_s" +
std::to_string(fitSpec) + "_" + model.toStdString() + "_msd";
- m_parameterToProperty = createParameterToPropertyMap(model);
+ m_parameterToProperty =
+ createParameterToPropertyMap(m_properties[model]->propertyName());
IAlgorithm_sptr msdAlg =
msdFitAlgorithm(modelToAlgorithmProperty(model), fitSpec, fitSpec);
@@ -212,6 +225,23 @@ void MSDFit::updatePlot() {
IndirectDataAnalysisTab::updatePlotRange("MSDRange", m_uiForm.ppPlotTop);
}
+void MSDFit::plotGuess() {
+
+ if (m_uiForm.ckPlotGuess->isChecked()) {
+ QString modelName = m_uiForm.cbModelInput->currentText();
+ IndirectDataAnalysisTab::plotGuess(m_uiForm.ppPlotTop,
+ createFunction(modelName));
+ } else {
+ m_uiForm.ppPlotTop->removeSpectrum("Guess");
+ }
+}
+
+IFunction_sptr MSDFit::createFunction(const QString &modelName) {
+ return createPopulatedFunction(
+ m_properties[modelName]->propertyName().toStdString(),
+ m_properties[modelName]);
+}
+
/**
* Called when new data has been loaded by the data selector.
*
@@ -313,12 +343,23 @@ QtProperty *MSDFit::createModel(const QString &modelName,
}
void MSDFit::modelSelection(int selected) {
- QString model = m_uiForm.cbModelInput->itemText(selected);
+ auto model = m_uiForm.cbModelInput->itemText(selected);
m_msdTree->clear();
m_msdTree->addProperty(m_properties["StartX"]);
m_msdTree->addProperty(m_properties["EndX"]);
m_msdTree->addProperty(m_properties[model]);
+
+ if (!m_pythonExportWsName.empty()) {
+ auto idx = m_pythonExportWsName.rfind("_");
+ m_pythonExportWsName = m_pythonExportWsName.substr(0, idx);
+ idx = m_pythonExportWsName.rfind("_");
+ m_pythonExportWsName = m_pythonExportWsName.substr(0, idx);
+ m_pythonExportWsName += "_" + model.toStdString() + "_msd";
+ }
+
+ m_uiForm.ckPlotGuess->setChecked(false);
+ updatePlot();
}
/*
@@ -333,7 +374,7 @@ void MSDFit::modelSelection(int selected) {
QHash<QString, QString>
MSDFit::createParameterToPropertyMap(const QString &model) {
QHash<QString, QString> parameterToProperty;
- parameterToProperty["Height"] = model + ".Intensity";
+ parameterToProperty["Height"] = model + ".Height";
parameterToProperty["MSD"] = model + ".MSD";
if (model == "Peters")
diff --git a/qt/scientific_interfaces/Indirect/MSDFit.h b/qt/scientific_interfaces/Indirect/MSDFit.h
index e9d58afaa3e8e1ba13b211d5180a2dbdadeb2390..d329bec176d3c27167bb71c85efcd37c5b6fc6e8 100644
--- a/qt/scientific_interfaces/Indirect/MSDFit.h
+++ b/qt/scientific_interfaces/Indirect/MSDFit.h
@@ -4,6 +4,8 @@
#include "IndirectDataAnalysisTab.h"
#include "ui_MSDFit.h"
+#include "MantidAPI/IFunction.h"
+
namespace MantidQt {
namespace CustomInterfaces {
namespace IDA {
@@ -33,6 +35,7 @@ private slots:
void modelSelection(int selected);
void updatePlot();
void updateProperties(int specNo);
+ void plotGuess();
private:
Mantid::API::IAlgorithm_sptr msdFitAlgorithm(const std::string &model,
@@ -41,6 +44,7 @@ private:
const std::vector<QString> &modelParameters);
QHash<QString, QString> createParameterToPropertyMap(const QString &model);
std::string modelToAlgorithmProperty(const QString &model);
+ Mantid::API::IFunction_sptr createFunction(const QString &modelName);
Ui::MSDFit m_uiForm;
QtTreePropertyBrowser *m_msdTree;
diff --git a/qt/scientific_interfaces/Indirect/MSDFit.ui b/qt/scientific_interfaces/Indirect/MSDFit.ui
index 20d0a5a06ddc59f4c30fe2d486b2fc4dd424f07c..dfc78073f9d7549b9e2633ad2912a9cfede37194 100644
--- a/qt/scientific_interfaces/Indirect/MSDFit.ui
+++ b/qt/scientific_interfaces/Indirect/MSDFit.ui
@@ -56,9 +56,6 @@
</item>
<item>
<layout class="QHBoxLayout" name="loMSDFit">
- <item>
- <layout class="QVBoxLayout" name="properties"/>
- </item>
<item>
<layout class="QVBoxLayout" name="loMSDPlot">
<item>
diff --git a/qt/scientific_interfaces/test/EnggDiffFittingModelTest.h b/qt/scientific_interfaces/test/EnggDiffFittingModelTest.h
new file mode 100644
index 0000000000000000000000000000000000000000..c9c4837854e491533172322acffa59099f8c24b4
--- /dev/null
+++ b/qt/scientific_interfaces/test/EnggDiffFittingModelTest.h
@@ -0,0 +1,86 @@
+#ifndef MANTID_CUSTOMINTERFACES_ENGGDIFFFITTINGMODELTEST_H_
+#define MANTID_CUSTOMINTERFACES_ENGGDIFFFITTINGMODELTEST_H_
+
+#include <cxxtest/TestSuite.h>
+
+#include "MantidAPI/MatrixWorkspace.h"
+#include "MantidAPI/WorkspaceFactory.h"
+
+#include "../EnggDiffraction/EnggDiffFittingModel.h"
+
+#include <vector>
+
+// Lets us have pairs inside assertion macros
+typedef std::pair<int, size_t> RunBankPair;
+
+using namespace Mantid;
+using namespace MantidQT::CustomInterfaces;
+
+namespace {
+
+void addSampleWorkspaceToModel(const int runNumber, const int bank,
+ EnggDiffFittingModel &model) {
+ API::MatrixWorkspace_sptr ws =
+ API::WorkspaceFactory::Instance().create("Workspace2D", 1, 10, 10);
+ model.addWorkspace(runNumber, bank, ws);
+}
+
+} // anonymous namespace
+
+class EnggDiffFittingModelTest : public CxxTest::TestSuite {
+public:
+ // This pair of boilerplate methods prevent the suite being created statically
+ // This means the constructor isn't called when running other tests
+ static EnggDiffFittingModelTest *createSuite() {
+ return new EnggDiffFittingModelTest();
+ }
+ static void destroySuite(EnggDiffFittingModelTest *suite) { delete suite; }
+
+ void test_addAndGetWorkspace() {
+ auto model = EnggDiffFittingModel();
+ API::MatrixWorkspace_sptr ws =
+ API::WorkspaceFactory::Instance().create("Workspace2D", 1, 10, 10);
+ const int runNumber = 100;
+ const int bank = 1;
+ TS_ASSERT_THROWS_NOTHING(model.addWorkspace(runNumber, bank, ws));
+ const auto retrievedWS = model.getWorkspace(runNumber, bank);
+
+ TS_ASSERT(retrievedWS != nullptr);
+ TS_ASSERT_EQUALS(ws, retrievedWS);
+ }
+
+ void test_getAllRunNumbers() {
+ auto model = EnggDiffFittingModel();
+
+ addSampleWorkspaceToModel(123, 1, model);
+ addSampleWorkspaceToModel(456, 2, model);
+ addSampleWorkspaceToModel(789, 1, model);
+ addSampleWorkspaceToModel(123, 2, model);
+
+ const auto runNumbers = model.getAllRunNumbers();
+
+ TS_ASSERT_EQUALS(runNumbers.size(), 3);
+ TS_ASSERT_EQUALS(runNumbers[0], 123);
+ TS_ASSERT_EQUALS(runNumbers[1], 456);
+ TS_ASSERT_EQUALS(runNumbers[2], 789);
+ }
+
+ void test_getRunNumbersAndBankIDs() {
+ auto model = EnggDiffFittingModel();
+
+ addSampleWorkspaceToModel(123, 1, model);
+ addSampleWorkspaceToModel(456, 2, model);
+ addSampleWorkspaceToModel(789, 1, model);
+ addSampleWorkspaceToModel(123, 2, model);
+
+ const auto runNoBankPairs = model.getRunNumbersAndBanksIDs();
+
+ TS_ASSERT_EQUALS(runNoBankPairs.size(), 4);
+ TS_ASSERT_EQUALS(runNoBankPairs[0], RunBankPair(123, 1));
+ TS_ASSERT_EQUALS(runNoBankPairs[1], RunBankPair(123, 2));
+ TS_ASSERT_EQUALS(runNoBankPairs[2], RunBankPair(456, 2));
+ TS_ASSERT_EQUALS(runNoBankPairs[3], RunBankPair(789, 1));
+ }
+};
+
+#endif
\ No newline at end of file
diff --git a/qt/scientific_interfaces/test/EnggDiffFittingViewMock.h b/qt/scientific_interfaces/test/EnggDiffFittingViewMock.h
index c244b4d9bfa2af4b9a52918c54cebe1e0aa398db..5356e30ee18b5aa36be7ecd517adf151fc3ddbc5 100644
--- a/qt/scientific_interfaces/test/EnggDiffFittingViewMock.h
+++ b/qt/scientific_interfaces/test/EnggDiffFittingViewMock.h
@@ -99,6 +99,9 @@ public:
// sets the current row of the fitting list widget
MOCK_CONST_METHOD1(setFittingListWidgetCurrentRow, void(int idx));
+ // gets current value of the fitting list widget
+ MOCK_CONST_METHOD0(getFittingListWidgetCurrentValue, std::string());
+
// sets the peak list according to the QString given
MOCK_CONST_METHOD1(setPeakList, void(const std::string &peakList));
diff --git a/qt/widgets/common/inc/MantidQtWidgets/Common/HintingLineEdit.h b/qt/widgets/common/inc/MantidQtWidgets/Common/HintingLineEdit.h
index 9f36d636a57b76d7375a3c5994780e198db33dc5..41904b5de4d32db7f000e781c05272c20d17ef06 100644
--- a/qt/widgets/common/inc/MantidQtWidgets/Common/HintingLineEdit.h
+++ b/qt/widgets/common/inc/MantidQtWidgets/Common/HintingLineEdit.h
@@ -64,6 +64,9 @@ protected:
protected slots:
void updateHints(const QString &text);
void hideHints();
+
+private:
+ static QPalette createFixedPalette();
};
} // namespace MantidWidgets
} // namepsace MantidQt
diff --git a/qt/widgets/common/src/HintingLineEdit.cpp b/qt/widgets/common/src/HintingLineEdit.cpp
index a085a2f56797f97cc7b7473e29ccfc900dc01797..ada5ffda61f3bb72bac710f01581a3e5a3a36198 100644
--- a/qt/widgets/common/src/HintingLineEdit.cpp
+++ b/qt/widgets/common/src/HintingLineEdit.cpp
@@ -5,6 +5,7 @@
#include <QLabel>
#include <QStyle>
#include <QToolTip>
+#include <boost/algorithm/string.hpp>
namespace MantidQt {
namespace MantidWidgets {
@@ -20,7 +21,7 @@ HintingLineEdit::HintingLineEdit(
m_hintLabel->setWordWrap(true);
m_hintLabel->setIndent(1);
m_hintLabel->setAutoFillBackground(true);
- m_hintLabel->setPalette(QToolTip::palette());
+ m_hintLabel->setPalette(createFixedPalette());
m_hintLabel->setForegroundRole(QPalette::ToolTipText);
m_hintLabel->setBackgroundRole(QPalette::ToolTipBase);
m_hintLabel->ensurePolished();
@@ -30,6 +31,29 @@ HintingLineEdit::HintingLineEdit(
connect(this, SIGNAL(editingFinished()), this, SLOT(hideHints()));
}
+/** Fixes the colour pallete so that the hints are readable.
+
+ Tooltips use the inactive text colours since they are never 'in focus'.
+ This causes problems on some linux distributions (specifically Fedora 26
+ and Ubuntu 16.04) where the inactive text colours are particularly light
+ and lack contrast with the colour used for the background.
+
+ This method creates a modified tooltip pallete which uses the active
+ window text colour instead.
+
+ @returns A tooltip pallete with contrasting tooltip text and background
+ colours.
+*/
+QPalette HintingLineEdit::createFixedPalette() {
+ auto toolTipPalette = QToolTip::palette();
+
+ auto const activeTextColour =
+ toolTipPalette.color(QPalette::ColorGroup::Active, QPalette::WindowText);
+ toolTipPalette.setColor(QPalette::ColorGroup::Inactive, QPalette::ToolTipText,
+ activeTextColour);
+ return toolTipPalette;
+}
+
HintingLineEdit::~HintingLineEdit() {}
/** Handle a key press event.
diff --git a/scripts/Diffraction/isis_powder/pearl.py b/scripts/Diffraction/isis_powder/pearl.py
index b677f99b10339e40d5ac5ffc0ae05ddfb1047584..e1ac04b9647d9b370561b358d1f22d7f4d49977c 100644
--- a/scripts/Diffraction/isis_powder/pearl.py
+++ b/scripts/Diffraction/isis_powder/pearl.py
@@ -4,7 +4,8 @@ import mantid.simpleapi as mantid
from isis_powder.routines import common, instrument_settings
from isis_powder.abstract_inst import AbstractInst
-from isis_powder.pearl_routines import pearl_algs, pearl_output, pearl_advanced_config, pearl_param_mapping
+from isis_powder.pearl_routines import pearl_advanced_config, pearl_algs, pearl_calibration_algs, pearl_output, \
+ pearl_param_mapping
class Pearl(AbstractInst):
@@ -41,6 +42,31 @@ class Pearl(AbstractInst):
else:
self._run_create_vanadium()
+ def create_cal(self, **kwargs):
+ self._switch_long_mode_inst_settings(kwargs.get("long_mode"))
+ self._inst_settings.update_attributes(kwargs=kwargs)
+ run_details = self._get_run_details(self._inst_settings.run_number)
+
+ cross_correlate_params = {"ReferenceSpectra": self._inst_settings.reference_spectra,
+ "WorkspaceIndexMin": self._inst_settings.cross_corr_ws_min,
+ "WorkspaceIndexMax": self._inst_settings.cross_corr_ws_max,
+ "XMin": self._inst_settings.cross_corr_x_min,
+ "XMax": self._inst_settings.cross_corr_x_max}
+ get_detector_offsets_params = {"DReference": self._inst_settings.d_reference,
+ "Step": self._inst_settings.get_det_offsets_step,
+ "XMin": self._inst_settings.get_det_offsets_x_min,
+ "XMax": self._inst_settings.get_det_offsets_x_max}
+
+ return pearl_calibration_algs.create_calibration(calibration_runs=self._inst_settings.run_number,
+ instrument=self,
+ offset_file_name=run_details.offset_file_path,
+ grouping_file_name=run_details.grouping_file_path,
+ calibration_dir=self._inst_settings.calibration_dir,
+ rebin_1_params=self._inst_settings.cal_rebin_1,
+ rebin_2_params=self._inst_settings.cal_rebin_2,
+ cross_correlate_params=cross_correlate_params,
+ get_det_offset_params=get_detector_offsets_params)
+
def _run_create_vanadium(self):
# Provides a minimal wrapper so if we have tt_mode 'all' we can loop round
return self._create_vanadium(run_number_string=self._inst_settings.run_in_range,
diff --git a/scripts/Diffraction/isis_powder/pearl_routines/pearl_advanced_config.py b/scripts/Diffraction/isis_powder/pearl_routines/pearl_advanced_config.py
index 39341287ba9d8fd04f2dcac2c23c6f58a3bc1b4d..7d7cbe90991a867ebb04b42b1c6672f4f847b5a0 100644
--- a/scripts/Diffraction/isis_powder/pearl_routines/pearl_advanced_config.py
+++ b/scripts/Diffraction/isis_powder/pearl_routines/pearl_advanced_config.py
@@ -9,14 +9,15 @@ general_params = {
"spline_coefficient": 60,
"file_names": {
- "vanadium_absorb_filename": "pearl_absorp_sphere_10mm_newinst2_long.nxs",
- "tt88_grouping_filename": "pearl_group_12_1_TT88.cal",
- "tt70_grouping_filename": "pearl_group_12_1_TT70.cal",
- "tt35_grouping_filename": "pearl_group_12_1_TT35.cal"
+ "vanadium_absorb_filename": "pearl_absorp_sphere_10mm_newinst2_long.nxs",
+ "tt88_grouping_filename": "pearl_group_12_1_TT88.cal",
+ "tt70_grouping_filename": "pearl_group_12_1_TT70.cal",
+ "tt35_grouping_filename": "pearl_group_12_1_TT35.cal"
},
}
long_mode_off_params = {
+ "create_cal_rebin_1_params": "100,-0.0006,19950",
"monitor_lambda_crop_range": (0.03, 6.00),
"monitor_integration_range": (0.6, 5.0),
# This needs to be greater than the bank TOF cropping values or you will get data that divides to 0/inf
@@ -41,6 +42,7 @@ long_mode_off_params = {
}
long_mode_on_params = {
+ "create_cal_rebin_1_params": "20300,-0.0006,39990",
"monitor_lambda_crop_range": (5.9, 12.0),
"monitor_integration_range": (6, 10),
# raw_data_tof_cropping needs to be have smaller/larger values than the bank TOF cropping values or
@@ -65,6 +67,22 @@ long_mode_on_params = {
]
}
+calibration_params = {
+ "create_cal_rebin_2_params": "1.8,0.002,2.1",
+ "create_cal_cross_correlate_params": {
+ "cross_corr_reference_spectra": 20,
+ "cross_corr_ws_index_min": 9,
+ "cross_corr_ws_index_max": 1063,
+ "cross_corr_x_min": 1.8,
+ "cross_corr_x_max": 2.1
+ },
+ "create_cal_get_detector_offsets_params": {
+ "get_det_offsets_step": 0.002,
+ "get_det_offsets_x_min": -200,
+ "get_det_offsets_x_max": 200,
+ "get_det_offsets_d_ref": 1.912795
+ }
+}
variable_help = {
"long_mode_<on/off>_params": {
@@ -100,6 +118,22 @@ variable_help = {
"workspace. This is used to normalise the workspace current.",
"spline_coefficient": "The coefficient to use whilst calculating a spline for each bank during "
"a vanadium calibration."
+ },
+
+ "calibration_params": {
+ "create_cal_rebin_1_params": "The parameters for the first rebin step used to create a calibration file",
+ "create_cal_rebin_2_params": "The parameters for the second rebin step used to create a calibration file",
+ "cross_corr_reference_spectra": "The Workspace Index of the spectra to correlate all other spectra against",
+ "cross_corr_ws_index_min": "The workspace index of the first member of the range of spectra to cross-correlate "
+ "against",
+ "cross_corr_ws_index_max": "The workspace index of the last member of the range of spectra to cross-correlate "
+ "against",
+ "cross_corr_x_min": "The starting point of the region to be cross correlated",
+ "cross_corr_x_max": "The ending point of the region to be cross correlated",
+ "get_det_offsets_step": "Step size used to bin d-spacing data in GetDetectorOffsets",
+ "get_det_offsets_x_min": "Minimum of CrossCorrelation data to search for peak, usually negative",
+ "get_det_offsets_x_max": "Maximum of CrossCorrelation data to search for peak, usually positive",
+ "get_det_offsets_d_ref": "Center of reference peak in d-space"
}
}
@@ -107,6 +141,7 @@ variable_help = {
def get_all_adv_variables(is_long_mode_on=False):
long_mode_params = long_mode_on_params if is_long_mode_on else long_mode_off_params
advanced_config_dict = {}
+ advanced_config_dict.update(calibration_params)
advanced_config_dict.update(general_params)
advanced_config_dict.update(long_mode_params)
return advanced_config_dict
diff --git a/scripts/Diffraction/isis_powder/pearl_routines/pearl_calibration_algs.py b/scripts/Diffraction/isis_powder/pearl_routines/pearl_calibration_algs.py
index 39d0f90d2734f79dee6a1e60bf71413c9ea220f1..d85053d168add6538d7032ec4f7385be882076ec 100644
--- a/scripts/Diffraction/isis_powder/pearl_routines/pearl_calibration_algs.py
+++ b/scripts/Diffraction/isis_powder/pearl_routines/pearl_calibration_algs.py
@@ -3,92 +3,49 @@ from __future__ import (absolute_import, division, print_function)
import os
import mantid.simpleapi as mantid
import isis_powder.routines.common as common
-from isis_powder.routines.common_enums import INPUT_BATCHING
-
-# TODO this entire file needs cleaning and refactoring
-
-
-def create_calibration(self, calibration_runs, offset_file_name, grouping_file_name):
- input_ws_list = common.load_current_normalised_ws_list(run_number_string=calibration_runs, instrument=self,
+from isis_powder.routines.common_enums import INPUT_BATCHING, WORKSPACE_UNITS
+
+
+def create_calibration(calibration_runs, instrument, offset_file_name, grouping_file_name, calibration_dir,
+ rebin_1_params, rebin_2_params, cross_correlate_params, get_det_offset_params):
+ """
+ Create a calibration file from (usually) a ceria run
+ :param calibration_runs: Run number(s) for this run
+ :param instrument: The PEARL instrument object
+ :param offset_file_name: Name of the file to write detector offset information to
+ :param grouping_file_name: Name of grouping calibration file
+ :param calibration_dir: Path to directory containing calibration information
+ :param rebin_1_params: Parameters for the first rebin step (as a string in the usual format)
+ :param rebin_2_params: Parameters for the second rebin step (as a string in the usual format)
+ :param cross_correlate_params: Parameters for CrossCorrelate (as a dictionary PropertyName: PropertyValue)
+ :param get_det_offset_params: Parameters for GetDetectorOffsets (as a dictionary PropertyName: PropertyValue)
+ """
+ input_ws_list = common.load_current_normalised_ws_list(run_number_string=calibration_runs, instrument=instrument,
input_batching=INPUT_BATCHING.Summed)
- input_ws = input_ws_list[0]
- run_details = self._get_run_details(calibration_runs)
-
- if run_details.instrument_version == "new" or run_details.instrument_version == "new2":
- input_ws = mantid.Rebin(InputWorkspace=input_ws, Params="100,-0.0006,19950")
-
- d_spacing_cal = mantid.ConvertUnits(InputWorkspace=input_ws, Target="dSpacing")
- d_spacing_cal = mantid.Rebin(InputWorkspace=d_spacing_cal, Params="1.8,0.002,2.1")
-
- if run_details.instrument_version == "new2":
- cross_cor_ws = mantid.CrossCorrelate(InputWorkspace=d_spacing_cal, ReferenceSpectra=20,
- WorkspaceIndexMin=9, WorkspaceIndexMax=1063, XMin=1.8, XMax=2.1)
-
- elif run_details.instrument_version == "new":
- cross_cor_ws = mantid.CrossCorrelate(InputWorkspace=d_spacing_cal, ReferenceSpectra=20,
- WorkspaceIndexMin=9, WorkspaceIndexMax=943, XMin=1.8, XMax=2.1)
- else:
- cross_cor_ws = mantid.CrossCorrelate(InputWorkspace=d_spacing_cal, ReferenceSpectra=500,
- WorkspaceIndexMin=1, WorkspaceIndexMax=1440, XMin=1.8, XMax=2.1)
- if self._old_api_uses_full_paths: # Workaround for old API setting full paths
- grouping_file_path = grouping_file_name
- offset_file_path = offset_file_name
- else:
- offset_file_path = os.path.join(self.calibration_dir, offset_file_name)
- grouping_file_path = os.path.join(self.calibration_dir, grouping_file_name)
-
- # Ceo Cell refined to 5.4102(3) so 220 is 1.912795
- offset_output_path = mantid.GetDetectorOffsets(InputWorkspace=cross_cor_ws, Step=0.002, DReference=1.912795,
- XMin=-200, XMax=200, GroupingFileName=offset_file_path)
- del offset_output_path # This isn't used so delete it to keep linters happy
- aligned_ws = mantid.AlignDetectors(InputWorkspace=input_ws, CalibrationFile=offset_file_path)
- cal_grouped_ws = mantid.DiffractionFocussing(InputWorkspace=aligned_ws, GroupingFileName=grouping_file_path)
-
- common.remove_intermediate_workspace(d_spacing_cal)
- common.remove_intermediate_workspace(cross_cor_ws)
- common.remove_intermediate_workspace(aligned_ws)
- common.remove_intermediate_workspace(cal_grouped_ws)
+ input_ws = input_ws_list[0]
+ calibration_ws = mantid.Rebin(InputWorkspace=input_ws, Params=rebin_1_params)
-def do_silicon_calibration(self, runs_to_process, cal_file_name, grouping_file_name):
- # TODO fix all of this as the script is too limited to be useful
- create_si_ws = common.load_current_normalised_ws_list(run_number_string=runs_to_process, instrument=self)
- cycle_details = self._get_label_information(runs_to_process)
- instrument_version = cycle_details["instrument_version"]
+ if calibration_ws.getAxis(0).getUnit().unitID() != WORKSPACE_UNITS.d_spacing:
+ calibration_ws = mantid.ConvertUnits(InputWorkspace=calibration_ws, Target="dSpacing")
- if instrument_version == "new" or instrument_version == "new2":
- create_si_ws = mantid.Rebin(InputWorkspace=create_si_ws, Params="100,-0.0006,19950")
+ rebinned = mantid.Rebin(InputWorkspace=calibration_ws, Params=rebin_2_params)
+ cross_correlated = mantid.CrossCorrelate(InputWorkspace=rebinned, **cross_correlate_params)
- create_si_d_spacing_ws = mantid.ConvertUnits(InputWorkspace=create_si_ws, Target="dSpacing")
+ offset_file = os.path.join(calibration_dir, offset_file_name)
+ # Offsets workspace must be referenced as string so it can be deleted, as simpleapi doesn't recognise it as a ws
+ offsets_ws_name = "offsets"
+ mantid.GetDetectorOffsets(InputWorkspace=cross_correlated, GroupingFileName=offset_file,
+ OutputWorkspace=offsets_ws_name, **get_det_offset_params)
- if instrument_version == "new2":
- create_si_d_spacing_rebin_ws = mantid.Rebin(InputWorkspace=create_si_d_spacing_ws, Params="1.71,0.002,2.1")
- create_si_cross_corr_ws = mantid.CrossCorrelate(InputWorkspace=create_si_d_spacing_rebin_ws,
- ReferenceSpectra=20, WorkspaceIndexMin=9,
- WorkspaceIndexMax=1063, XMin=1.71, XMax=2.1)
- elif instrument_version == "new":
- create_si_d_spacing_rebin_ws = mantid.Rebin(InputWorkspace=create_si_d_spacing_ws, Params="1.85,0.002,2.05")
- create_si_cross_corr_ws = mantid.CrossCorrelate(InputWorkspace=create_si_d_spacing_rebin_ws,
- ReferenceSpectra=20, WorkspaceIndexMin=9,
- WorkspaceIndexMax=943, XMin=1.85, XMax=2.05)
- elif instrument_version == "old":
- create_si_d_spacing_rebin_ws = mantid.Rebin(InputWorkspace=create_si_d_spacing_ws, Params="3,0.002,3.2")
- create_si_cross_corr_ws = mantid.CrossCorrelate(InputWorkspace=create_si_d_spacing_rebin_ws,
- ReferenceSpectra=500, WorkspaceIndexMin=1,
- WorkspaceIndexMax=1440, XMin=3, XMax=3.2)
- else:
- raise NotImplementedError("The instrument version is not supported for creating a silicon calibration")
+ rebinned_tof = mantid.ConvertUnits(InputWorkspace=rebinned, Target="TOF")
+ aligned = mantid.AlignDetectors(InputWorkspace=rebinned_tof, CalibrationFile=offset_file)
- common.remove_intermediate_workspace(create_si_d_spacing_ws)
- common.remove_intermediate_workspace(create_si_d_spacing_rebin_ws)
+ grouping_file = os.path.join(calibration_dir, grouping_file_name)
+ focused = mantid.DiffractionFocussing(InputWorkspace=aligned, GroupingFileName=grouping_file,
+ OutputWorkspace=instrument._generate_output_file_name(calibration_runs)
+ + "_grouped")
- calibration_output_path = self.calibration_dir + cal_file_name
- create_si_offsets_ws = mantid.GetDetectorOffsets(InputWorkspace=create_si_cross_corr_ws,
- Step=0.002, DReference=1.920127251, XMin=-200, XMax=200,
- GroupingFileName=calibration_output_path)
- create_si_aligned_ws = mantid.AlignDetectors(InputWorkspace=create_si_ws,
- CalibrationFile=calibration_output_path)
- grouping_output_path = self.calibration_dir + grouping_file_name
- create_si_grouped_ws = mantid.DiffractionFocussing(InputWorkspace=create_si_aligned_ws,
- GroupingFileName=grouping_output_path)
- del create_si_offsets_ws, create_si_grouped_ws
+ common.remove_intermediate_workspace([calibration_ws, rebinned, cross_correlated, rebinned_tof, aligned,
+ offsets_ws_name])
+ return focused
diff --git a/scripts/Diffraction/isis_powder/pearl_routines/pearl_param_mapping.py b/scripts/Diffraction/isis_powder/pearl_routines/pearl_param_mapping.py
index 5c3de085f7b9607beced67d1407b4c99129d4062..cc7902e28d57964fd80280658f4116da6471ad8a 100644
--- a/scripts/Diffraction/isis_powder/pearl_routines/pearl_param_mapping.py
+++ b/scripts/Diffraction/isis_powder/pearl_routines/pearl_param_mapping.py
@@ -6,32 +6,43 @@ from isis_powder.pearl_routines.pearl_enums import PEARL_FOCUS_MODES, PEARL_TT_M
# Maps friendly user name (ext_name) -> script name (int_name)
attr_mapping = \
[
- ParamMapEntry(ext_name="attenuation_file_path", int_name="attenuation_file_path"),
- ParamMapEntry(ext_name="config_file", int_name="config_file_name"),
- ParamMapEntry(ext_name="calibration_mapping_file", int_name="cal_mapping_path"),
- ParamMapEntry(ext_name="calibration_directory", int_name="calibration_dir"),
- ParamMapEntry(ext_name="do_absorb_corrections", int_name="absorb_corrections"),
- ParamMapEntry(ext_name="file_ext", int_name="file_extension", optional=True),
- ParamMapEntry(ext_name="focused_cropping_values", int_name="tof_cropping_values"),
- ParamMapEntry(ext_name="focus_mode", int_name="focus_mode", enum_class=PEARL_FOCUS_MODES),
- ParamMapEntry(ext_name="long_mode", int_name="long_mode"),
- ParamMapEntry(ext_name="monitor_lambda_crop_range", int_name="monitor_lambda"),
- ParamMapEntry(ext_name="monitor_integration_range", int_name="monitor_integration_range"),
- ParamMapEntry(ext_name="monitor_mask_regions", int_name="monitor_mask_regions"),
- ParamMapEntry(ext_name="monitor_spectrum_number", int_name="monitor_spec_no"),
- ParamMapEntry(ext_name="monitor_spline_coefficient", int_name="monitor_spline"),
- ParamMapEntry(ext_name="output_directory", int_name="output_dir"),
- ParamMapEntry(ext_name="perform_attenuation", int_name="perform_atten"),
- ParamMapEntry(ext_name="raw_data_tof_cropping", int_name="raw_data_crop_vals"),
- ParamMapEntry(ext_name="run_in_cycle", int_name="run_in_range"),
- ParamMapEntry(ext_name="run_number", int_name="run_number"),
- ParamMapEntry(ext_name="spline_coefficient", int_name="spline_coefficient"),
- ParamMapEntry(ext_name="tt88_grouping_filename", int_name="tt88_grouping"),
- ParamMapEntry(ext_name="tt70_grouping_filename", int_name="tt70_grouping"),
- ParamMapEntry(ext_name="tt35_grouping_filename", int_name="tt35_grouping"),
- ParamMapEntry(ext_name="tt_mode", int_name="tt_mode", enum_class=PEARL_TT_MODES),
- ParamMapEntry(ext_name="user_name", int_name="user_name"),
- ParamMapEntry(ext_name="vanadium_absorb_filename", int_name="van_absorb_file"),
- ParamMapEntry(ext_name="vanadium_tof_cropping", int_name="van_tof_cropping"),
- ParamMapEntry(ext_name="vanadium_normalisation", int_name="van_norm")
+ ParamMapEntry(ext_name="attenuation_file_path", int_name="attenuation_file_path"),
+ ParamMapEntry(ext_name="config_file", int_name="config_file_name"),
+ ParamMapEntry(ext_name="calibration_mapping_file", int_name="cal_mapping_path"),
+ ParamMapEntry(ext_name="calibration_directory", int_name="calibration_dir"),
+ ParamMapEntry(ext_name="create_cal_rebin_1_params", int_name="cal_rebin_1"),
+ ParamMapEntry(ext_name="create_cal_rebin_2_params", int_name="cal_rebin_2"),
+ ParamMapEntry(ext_name="cross_corr_reference_spectra", int_name="reference_spectra"),
+ ParamMapEntry(ext_name="cross_corr_ws_index_max", int_name="cross_corr_ws_max"),
+ ParamMapEntry(ext_name="cross_corr_ws_index_min", int_name="cross_corr_ws_min"),
+ ParamMapEntry(ext_name="cross_corr_x_min", int_name="cross_corr_x_min"),
+ ParamMapEntry(ext_name="cross_corr_x_max", int_name="cross_corr_x_max"),
+ ParamMapEntry(ext_name="do_absorb_corrections", int_name="absorb_corrections"),
+ ParamMapEntry(ext_name="file_ext", int_name="file_extension", optional=True),
+ ParamMapEntry(ext_name="focused_cropping_values", int_name="tof_cropping_values"),
+ ParamMapEntry(ext_name="focus_mode", int_name="focus_mode", enum_class=PEARL_FOCUS_MODES),
+ ParamMapEntry(ext_name="get_det_offsets_d_ref", int_name="d_reference"),
+ ParamMapEntry(ext_name="get_det_offsets_step", int_name="get_det_offsets_step"),
+ ParamMapEntry(ext_name="get_det_offsets_x_min", int_name="get_det_offsets_x_min"),
+ ParamMapEntry(ext_name="get_det_offsets_x_max", int_name="get_det_offsets_x_max"),
+ ParamMapEntry(ext_name="long_mode", int_name="long_mode"),
+ ParamMapEntry(ext_name="monitor_lambda_crop_range", int_name="monitor_lambda"),
+ ParamMapEntry(ext_name="monitor_integration_range", int_name="monitor_integration_range"),
+ ParamMapEntry(ext_name="monitor_mask_regions", int_name="monitor_mask_regions"),
+ ParamMapEntry(ext_name="monitor_spectrum_number", int_name="monitor_spec_no"),
+ ParamMapEntry(ext_name="monitor_spline_coefficient", int_name="monitor_spline"),
+ ParamMapEntry(ext_name="output_directory", int_name="output_dir"),
+ ParamMapEntry(ext_name="perform_attenuation", int_name="perform_atten"),
+ ParamMapEntry(ext_name="raw_data_tof_cropping", int_name="raw_data_crop_vals"),
+ ParamMapEntry(ext_name="run_in_cycle", int_name="run_in_range"),
+ ParamMapEntry(ext_name="run_number", int_name="run_number"),
+ ParamMapEntry(ext_name="spline_coefficient", int_name="spline_coefficient"),
+ ParamMapEntry(ext_name="tt88_grouping_filename", int_name="tt88_grouping"),
+ ParamMapEntry(ext_name="tt70_grouping_filename", int_name="tt70_grouping"),
+ ParamMapEntry(ext_name="tt35_grouping_filename", int_name="tt35_grouping"),
+ ParamMapEntry(ext_name="tt_mode", int_name="tt_mode", enum_class=PEARL_TT_MODES),
+ ParamMapEntry(ext_name="user_name", int_name="user_name"),
+ ParamMapEntry(ext_name="vanadium_absorb_filename", int_name="van_absorb_file"),
+ ParamMapEntry(ext_name="vanadium_tof_cropping", int_name="van_tof_cropping"),
+ ParamMapEntry(ext_name="vanadium_normalisation", int_name="van_norm")
]
diff --git a/scripts/Diffraction/isis_powder/routines/common.py b/scripts/Diffraction/isis_powder/routines/common.py
index 60378e6b51879c9c45a1d3d3fca28eb1baba9624..61fe1cb7f64e66f0e8f90105d47253c641430414 100644
--- a/scripts/Diffraction/isis_powder/routines/common.py
+++ b/scripts/Diffraction/isis_powder/routines/common.py
@@ -206,8 +206,11 @@ def get_first_run_number(run_number_string):
:return: The first run for the user input of runs
"""
run_numbers = generate_run_numbers(run_number_string=run_number_string)
- if isinstance(run_numbers, list):
- run_numbers = run_numbers[0]
+
+ if not run_numbers:
+ raise RuntimeError("Attempted to load empty set of workspaces. Please input at least one valid run number")
+
+ run_numbers = run_numbers[0]
return run_numbers