/**
Overlay the overlap 1D workspace over the original 1D workspace. overlap shouuld overwrite values on the sum workspace.
@param original : Original 1D workspace to be overwritten only in the region of the overlap.
@param overlap : Overlap 1D workspace to overwrite with
*/
void Stitch1DMD::overlayOverlap(MDHistoWorkspace_sptr original, IMDHistoWorkspace_sptr overlap)
{
const auto targetDim = original->getDimension(0);
const double targetQMax = targetDim->getMaximum();
const double targetQMin = targetDim->getMinimum();
const size_t targetNbins = targetDim->getNBins();
const double targetStep = double(targetNbins) / (targetQMax - targetQMin);
const double targetC = -1 * targetStep * targetQMin;
const auto overlapDim = overlap->getDimension(0);
const double overlapQMax = overlapDim->getMaximum();
const double overlapQMin = overlapDim->getMinimum();
const size_t overlapNBins = overlapDim->getNBins();
const double overlapStep = (overlapQMax - overlapQMin) / double(overlapNBins);
const double overlapC = overlapQMin;
for(size_t i = 0; i < overlapNBins; ++i)
{
// Calculate the q value for each index in the overlap region.
const double q = (overlapStep * double(i)) + overlapC;
// Find the target index by recentering (adding 0.5) and then truncating to an integer.
size_t targetIndex = size_t((targetStep * q) + targetC + 0.5) ;
// Overwrite signal
original->setSignalAt(targetIndex, overlap->signalAt(i));
// Overwrite error
original->setErrorSquaredAt(targetIndex, overlap->errorSquaredAt(i));
}
}
void SliceMDHisto::cutData(Mantid::API::IMDHistoWorkspace_sptr inWS,
Mantid::API::IMDHistoWorkspace_sptr outWS,
Mantid::coord_t *sourceDim,
Mantid::coord_t *targetDim, std::vector<int> start,
std::vector<int> end, unsigned int dim) {
int length;
boost::shared_ptr<const IMDDimension> inDim = inWS->getDimension(dim);
boost::shared_ptr<const IMDDimension> outDim = outWS->getDimension(dim);
length = end[dim] - start[dim];
if (dim == m_rank - 1) {
MDHistoWorkspace_sptr outWSS =
boost::dynamic_pointer_cast<MDHistoWorkspace>(outWS);
for (int i = 0; i < length; i++) {
sourceDim[dim] = inDim->getX(start[dim] + i);
signal_t val = inWS->getSignalAtCoord(
sourceDim, static_cast<Mantid::API::MDNormalization>(0));
targetDim[dim] = outDim->getX(i);
size_t idx = outWSS->getLinearIndexAtCoord(targetDim);
outWS->setSignalAt(idx, val);
outWS->setErrorSquaredAt(idx, val);
}
} else {
for (int i = 0; i < length; i++) {
sourceDim[dim] = inDim->getX(start[dim] + i);
targetDim[dim] = outDim->getX(i);
cutData(inWS, outWS, sourceDim, targetDim, start, end, dim + 1);
}
}
}
/** Execute the algorithm.
*/
void CreateMDHistoWorkspace::exec()
{
MDHistoWorkspace_sptr ws = this->createEmptyOutputWorkspace();
double* signals = ws->getSignalArray();
double* errors = ws->getErrorSquaredArray();
std::vector<double> signalValues = getProperty("SignalInput");
std::vector<double> errorValues = getProperty("ErrorInput");
size_t binProduct = this->getBinProduct();
std::stringstream stream;
stream << binProduct;
if(binProduct != signalValues.size())
{
throw std::invalid_argument("Expected size of the SignalInput is: " + stream.str() );
}
if(binProduct != errorValues.size())
{
throw std::invalid_argument("Expected size of the ErrorInput is: " + stream.str() );
}
//Copy from property
std::copy(signalValues.begin(), signalValues.end(), signals);
std::vector<double> empty;
//Clean up.
signalValues.swap(empty);
//Copy from property
std::for_each(errorValues.begin(), errorValues.end(), Square());
std::copy(errorValues.begin(), errorValues.end(), errors);
//Clean up
errorValues.swap(empty);
setProperty("OutputWorkspace", ws);
}
/** Execute the algorithm.
*/
void TransformMD::exec() {
Mantid::API::IMDWorkspace_sptr inWS;
Mantid::API::IMDWorkspace_sptr outWS;
inWS = getProperty("InputWorkspace");
outWS = getProperty("OutputWorkspace");
if (boost::dynamic_pointer_cast<MatrixWorkspace>(inWS))
throw std::runtime_error("TransformMD can only transform a "
"MDHistoWorkspace or a MDEventWorkspace.");
if (outWS != inWS) {
// NOT in-place. So first we clone inWS into outWS
IAlgorithm_sptr clone =
this->createChildAlgorithm("CloneMDWorkspace", 0.0, 0.5, true);
clone->setProperty("InputWorkspace", inWS);
clone->executeAsChildAlg();
outWS = clone->getProperty("OutputWorkspace");
}
if (!outWS)
throw std::runtime_error("Invalid output workspace.");
size_t nd = outWS->getNumDims();
m_scaling = getProperty("Scaling");
m_offset = getProperty("Offset");
// Replicate single values
if (m_scaling.size() == 1)
m_scaling = std::vector<double>(nd, m_scaling[0]);
if (m_offset.size() == 1)
m_offset = std::vector<double>(nd, m_offset[0]);
// Check the size
if (m_scaling.size() != nd)
throw std::invalid_argument("Scaling argument must be either length 1 or "
"match the number of dimensions.");
if (m_offset.size() != nd)
throw std::invalid_argument("Offset argument must be either length 1 or "
"match the number of dimensions.");
// Transform the dimensions
outWS->transformDimensions(m_scaling, m_offset);
MDHistoWorkspace_sptr histo =
boost::dynamic_pointer_cast<MDHistoWorkspace>(outWS);
IMDEventWorkspace_sptr event =
boost::dynamic_pointer_cast<IMDEventWorkspace>(outWS);
if (histo) {
// Recalculate all the values since the dimensions changed.
histo->cacheValues();
} else if (event) {
// Call the method for this type of MDEventWorkspace.
CALL_MDEVENT_FUNCTION(this->doTransform, outWS);
}
this->setProperty("OutputWorkspace", outWS);
}
/**
* Load a slab of double data into a bare array.
* Checks that the size is correct.
* @param name
* @param data bare pointer to double array
* @param ws
* @param dataType
*/
void LoadMD::loadSlab(std::string name, void *data, MDHistoWorkspace_sptr ws,
NeXus::NXnumtype dataType) {
m_file->openData(name);
if (m_file->getInfo().type != dataType)
throw std::runtime_error("Unexpected data type for '" + name +
"' data set.'");
int nPoints = 1;
size_t numDims = m_file->getInfo().dims.size();
std::vector<int> size(numDims);
for (size_t d = 0; d < numDims; d++) {
nPoints *= static_cast<int>(m_file->getInfo().dims[d]);
size[d] = static_cast<int>(m_file->getInfo().dims[d]);
}
if (nPoints != static_cast<int>(ws->getNPoints()))
throw std::runtime_error(
"Inconsistency between the number of points in '" + name +
"' and the number of bins defined by the dimensions.");
std::vector<int> start(numDims, 0);
try {
m_file->getSlab(data, start, size);
} catch (...) {
std::cout << " start: " << start[0] << " size: " << size[0] << '\n';
}
m_file->closeData();
}
void SINQHMListener::recurseDim(int *data, IMDHistoWorkspace_sptr ws,
int currentDim, coord_t *idx) {
if (currentDim == rank) {
int Cindex = calculateCAddress(idx);
int val = data[Cindex];
MDHistoWorkspace_sptr mdws =
boost::dynamic_pointer_cast<MDHistoWorkspace>(ws);
size_t F77index = mdws->getLinearIndexAtCoord(idx);
mdws->setSignalAt(F77index, signal_t(val));
mdws->setErrorSquaredAt(F77index, signal_t(val));
} else {
for (int i = 0; i < dim[currentDim]; i++) {
idx[currentDim] = static_cast<coord_t>(i);
recurseDim(data, ws, currentDim + 1, idx);
}
}
}
void SINQTranspose3D::doTRICS(IMDHistoWorkspace_sptr inWS)
{
double *inVal, *inErr, *outVal, *outErr;
size_t idxIn, idxOut;
unsigned int xdim, ydim, zdim;
boost::shared_ptr<const IMDDimension> x,y,z;
x = inWS->getXDimension();
y = inWS->getYDimension();
z = inWS->getZDimension();
std::vector<IMDDimension_sptr> dimensions;
dimensions.push_back(boost::const_pointer_cast<IMDDimension>(x));
dimensions.push_back(boost::const_pointer_cast<IMDDimension>(z));
dimensions.push_back(boost::const_pointer_cast<IMDDimension>(y));
MDHistoWorkspace_sptr outWS (new MDHistoWorkspace(dimensions));
outWS->setTo(.0,.0,.0);
inVal = inWS->getSignalArray();
inErr = inWS->getErrorSquaredArray();
outVal = outWS->getSignalArray();
outErr = outWS->getErrorSquaredArray();
xdim = static_cast<unsigned int>(x->getNBins());
ydim = static_cast<unsigned int>(y->getNBins());
zdim = static_cast<unsigned int>(z->getNBins());
for(unsigned int xx = 0; xx < xdim; xx++){
for(unsigned int yy= 0; yy < ydim; yy++){
for(unsigned int zz = 0; zz < zdim; zz++){
idxIn = ydim*zdim*xx + zdim*yy + zz; // this works for TRICS
idxOut = outWS->getLinearIndex(xx,zz,yy);
outVal[idxOut] = inVal[idxIn];
outErr[idxOut] = inErr[idxIn];
}
}
}
copyMetaData(inWS, outWS);
// assign the workspace
setProperty("OutputWorkspace",outWS);
}
void SINQTranspose3D::doYXZ(IMDHistoWorkspace_sptr inWS)
{
double *inVal, *inErr, *outVal, *outErr;
size_t idxIn, idxOut;
boost::shared_ptr<const IMDDimension> x,y,z;
x = inWS->getXDimension();
y = inWS->getYDimension();
z = inWS->getZDimension();
std::vector<IMDDimension_sptr> dimensions;
dimensions.push_back(boost::const_pointer_cast<IMDDimension>(y));
dimensions.push_back(boost::const_pointer_cast<IMDDimension>(x));
dimensions.push_back(boost::const_pointer_cast<IMDDimension>(z));
MDHistoWorkspace_sptr outWS (new MDHistoWorkspace(dimensions));
inVal = inWS->getSignalArray();
inErr = inWS->getErrorSquaredArray();
outVal = outWS->getSignalArray();
outErr = outWS->getErrorSquaredArray();
for(unsigned int xx = 0; xx < x->getNBins(); xx++){
for(unsigned int yy= 0; yy < y->getNBins(); yy++){
for(unsigned int zz = 0; zz < z->getNBins(); zz++){
idxIn = inWS->getLinearIndex(xx,yy,zz);
idxOut = outWS->getLinearIndex(yy,xx,zz);
outVal[idxOut] = inVal[idxIn];
outErr[idxOut] = inErr[idxIn];
}
}
}
copyMetaData(inWS, outWS);
// assign the workspace
setProperty("OutputWorkspace",outWS);
}
void SINQTranspose3D::doAMOR(IMDHistoWorkspace_sptr inWS)
{
double val, *inVal;
unsigned int xdim, ydim, zdim, idx;
boost::shared_ptr<const IMDDimension> x,y,z;
x = inWS->getXDimension();
y = inWS->getYDimension();
z = inWS->getZDimension();
std::vector<IMDDimension_sptr> dimensions;
dimensions.push_back(boost::const_pointer_cast<IMDDimension>(y));
dimensions.push_back(boost::const_pointer_cast<IMDDimension>(x));
dimensions.push_back(boost::const_pointer_cast<IMDDimension>(z));
MDHistoWorkspace_sptr outWS (new MDHistoWorkspace(dimensions));
outWS->setTo(.0,.0,.0);
xdim = static_cast<unsigned int>(x->getNBins());
ydim = static_cast<unsigned int>(y->getNBins());
zdim = static_cast<unsigned int>(z->getNBins());
inVal = inWS->getSignalArray();
for(unsigned int xx = 0; xx < xdim; xx++){
for(unsigned int yy = 0; yy < ydim; yy++){
for(unsigned zz = 0; zz < zdim; zz++){
//idx = ydim*zdim*xx + zdim*yy + zz;
idx = ydim*zdim*xx + zdim*yy + zz;
val = inVal[idx];
outWS->setSignalAt(outWS->getLinearIndex(yy,xx,zz),val);
outWS->setErrorSquaredAt(outWS->getLinearIndex(yy,xx,zz),val);
}
}
}
copyMetaData(inWS, outWS);
// assign the workspace
setProperty("OutputWorkspace",outWS);
}
/** Execute the algorithm.
*/
void TransformMD::exec() {
Mantid::API::IMDWorkspace_sptr inWS;
Mantid::API::IMDWorkspace_sptr outWS;
inWS = getProperty("InputWorkspace");
outWS = getProperty("OutputWorkspace");
std::string outName = getPropertyValue("OutputWorkspace");
if (boost::dynamic_pointer_cast<MatrixWorkspace>(inWS))
throw std::runtime_error("TransformMD can only transform a "
"MDHistoWorkspace or a MDEventWorkspace.");
if (outWS != inWS) {
// NOT in-place. So first we clone inWS into outWS
IAlgorithm_sptr clone =
this->createChildAlgorithm("CloneMDWorkspace", 0.0, 0.5, true);
clone->setProperty("InputWorkspace", inWS);
clone->executeAsChildAlg();
outWS = clone->getProperty("OutputWorkspace");
}
if (!outWS)
throw std::runtime_error("Invalid output workspace.");
size_t nd = outWS->getNumDims();
m_scaling = getProperty("Scaling");
m_offset = getProperty("Offset");
// Replicate single values
if (m_scaling.size() == 1)
m_scaling = std::vector<double>(nd, m_scaling[0]);
if (m_offset.size() == 1)
m_offset = std::vector<double>(nd, m_offset[0]);
// Check the size
if (m_scaling.size() != nd)
throw std::invalid_argument("Scaling argument must be either length 1 or "
"match the number of dimensions.");
if (m_offset.size() != nd)
throw std::invalid_argument("Offset argument must be either length 1 or "
"match the number of dimensions.");
// Transform the dimensions
outWS->transformDimensions(m_scaling, m_offset);
MDHistoWorkspace_sptr histo =
boost::dynamic_pointer_cast<MDHistoWorkspace>(outWS);
IMDEventWorkspace_sptr event =
boost::dynamic_pointer_cast<IMDEventWorkspace>(outWS);
if (histo) {
// Recalculate all the values since the dimensions changed.
histo->cacheValues();
// Expect first 3 dimensions to be -1 for changing conventions
for (int i = 0; i < static_cast<int>(m_scaling.size()); i++)
if (m_scaling[i] < 0) {
std::vector<int> axes(m_scaling.size()); // vector with ints.
std::iota(std::begin(axes), std::end(axes), 0); // Fill with 0, 1, ...
axes[0] = i;
axes[i] = 0;
if (i > 0)
histo = transposeMD(histo, axes);
signal_t *signals = histo->getSignalArray();
signal_t *errorsSq = histo->getErrorSquaredArray();
signal_t *numEvents = histo->getNumEventsArray();
// Find the extents
size_t nPoints =
static_cast<size_t>(histo->getDimension(0)->getNBins());
size_t mPoints = 1;
for (size_t k = 1; k < histo->getNumDims(); k++) {
mPoints *= static_cast<size_t>(histo->getDimension(k)->getNBins());
}
// other dimensions
for (size_t j = 0; j < mPoints; j++) {
this->reverse(signals + j * nPoints, nPoints);
this->reverse(errorsSq + j * nPoints, nPoints);
this->reverse(numEvents + j * nPoints, nPoints);
}
histo = transposeMD(histo, axes);
}
// Pass on the display normalization from the input workspace
histo->setDisplayNormalization(inWS->displayNormalizationHisto());
this->setProperty("OutputWorkspace", histo);
} else if (event) {
// Call the method for this type of MDEventWorkspace.
CALL_MDEVENT_FUNCTION(this->doTransform, outWS);
Progress *prog2 = nullptr;
ThreadScheduler *ts = new ThreadSchedulerFIFO();
ThreadPool tp(ts, 0, prog2);
event->splitAllIfNeeded(ts);
// prog2->resetNumSteps( ts->size(), 0.4, 0.6);
tp.joinAll();
event->refreshCache();
// Set the special coordinate system.
IMDEventWorkspace_sptr inEvent =
boost::dynamic_pointer_cast<IMDEventWorkspace>(inWS);
event->setCoordinateSystem(inEvent->getSpecialCoordinateSystem());
if (m_scaling[0] < 0) {
// Only need these 2 algorithms for transforming with negative number
std::vector<double> extents;
std::vector<std::string> names, units;
for (size_t d = 0; d < nd; d++) {
Geometry::IMDDimension_const_sptr dim = event->getDimension(d);
// Find the extents
extents.push_back(dim->getMinimum());
extents.push_back(dim->getMaximum());
names.push_back(std::string(dim->getName()));
units.push_back(dim->getUnits());
}
Algorithm_sptr create_alg = createChildAlgorithm("CreateMDWorkspace");
create_alg->setProperty("Dimensions", static_cast<int>(nd));
create_alg->setProperty("EventType", event->getEventTypeName());
create_alg->setProperty("Extents", extents);
create_alg->setProperty("Names", names);
create_alg->setProperty("Units", units);
create_alg->setPropertyValue("OutputWorkspace", "__none");
create_alg->executeAsChildAlg();
Workspace_sptr none = create_alg->getProperty("OutputWorkspace");
AnalysisDataService::Instance().addOrReplace(outName, event);
AnalysisDataService::Instance().addOrReplace("__none", none);
Mantid::API::BoxController_sptr boxController = event->getBoxController();
std::vector<int> splits;
for (size_t d = 0; d < nd; d++) {
splits.push_back(static_cast<int>(boxController->getSplitInto(d)));
}
Algorithm_sptr merge_alg = createChildAlgorithm("MergeMD");
merge_alg->setPropertyValue("InputWorkspaces", outName + ",__none");
merge_alg->setProperty("SplitInto", splits);
merge_alg->setProperty(
"SplitThreshold",
static_cast<int>(boxController->getSplitThreshold()));
merge_alg->setProperty("MaxRecursionDepth", 13);
merge_alg->executeAsChildAlg();
event = merge_alg->getProperty("OutputWorkspace");
AnalysisDataService::Instance().remove("__none");
}
this->setProperty("OutputWorkspace", event);
}
}
/** Perform loading for a MDHistoWorkspace.
* The entry should be open already.
*/
void LoadMD::loadHisto() {
// Create the initial MDHisto.
MDHistoWorkspace_sptr ws;
// If display normalization has been provided. Use that.
if (m_visualNormalization) {
ws = boost::make_shared<MDHistoWorkspace>(m_dims,
m_visualNormalization.get());
} else {
ws = boost::make_shared<MDHistoWorkspace>(
m_dims); // Whatever MDHistoWorkspace defaults to.
}
// Now the ExperimentInfo
MDBoxFlatTree::loadExperimentInfos(m_file.get(), m_filename, ws);
// Coordinate system
ws->setCoordinateSystem(m_coordSystem);
// Load the WorkspaceHistory "process"
if (this->getProperty("LoadHistory")) {
ws->history().loadNexus(m_file.get());
}
this->loadAffineMatricies(boost::dynamic_pointer_cast<IMDWorkspace>(ws));
if (m_saveMDVersion == 2)
m_file->openGroup("data", "NXdata");
// Load each data slab
this->loadSlab("signal", ws->getSignalArray(), ws, ::NeXus::FLOAT64);
this->loadSlab("errors_squared", ws->getErrorSquaredArray(), ws,
::NeXus::FLOAT64);
this->loadSlab("num_events", ws->getNumEventsArray(), ws, ::NeXus::FLOAT64);
this->loadSlab("mask", ws->getMaskArray(), ws, ::NeXus::INT8);
m_file->close();
// Check if a MDFrame adjustment is required
checkForRequiredLegacyFixup(ws);
if (m_requiresMDFrameCorrection) {
setMDFrameOnWorkspaceFromLegacyFile(ws);
}
// Write out the Qconvention
// ki-kf for Inelastic convention; kf-ki for Crystallography convention
std::string pref_QConvention =
Kernel::ConfigService::Instance().getString("Q.convention");
g_log.information() << "Convention for Q in Preferences is "
<< pref_QConvention
<< "; Convention of Q in NeXus file is " << m_QConvention
<< '\n';
if (pref_QConvention != m_QConvention) {
std::vector<double> scaling(m_numDims);
scaling = qDimensions(ws);
g_log.information() << "Transforming Q\n";
Algorithm_sptr transform_alg = createChildAlgorithm("TransformMD");
transform_alg->setProperty("InputWorkspace",
boost::dynamic_pointer_cast<IMDWorkspace>(ws));
transform_alg->setProperty("Scaling", scaling);
transform_alg->executeAsChildAlg();
IMDWorkspace_sptr tmp = transform_alg->getProperty("OutputWorkspace");
ws = boost::dynamic_pointer_cast<MDHistoWorkspace>(tmp);
}
// Save to output
setProperty("OutputWorkspace", boost::dynamic_pointer_cast<IMDWorkspace>(ws));
}