/**
* Mask the outlier values to get a better median value.
* @param medianvec The median value calculated from the current counts.
* @param countsWS The counts workspace. Any outliers will be masked here.
* @param indexmap Index map.
* @returns The number failed.
*/
int MedianDetectorTest::maskOutliers(
const std::vector<double> medianvec, API::MatrixWorkspace_sptr countsWS,
std::vector<std::vector<size_t>> indexmap) {
// Fractions of the median
const double out_lo = getProperty("LowOutlier");
const double out_hi = getProperty("HighOutlier");
int numFailed(0);
bool checkForMask = false;
Geometry::Instrument_const_sptr instrument = countsWS->getInstrument();
if (instrument != nullptr) {
checkForMask = ((instrument->getSource() != nullptr) &&
(instrument->getSample() != nullptr));
}
for (size_t i = 0; i < indexmap.size(); ++i) {
std::vector<size_t> &hists = indexmap[i];
double median = medianvec[i];
PARALLEL_FOR_IF(Kernel::threadSafe(*countsWS))
for (int j = 0; j < static_cast<int>(hists.size()); ++j) { // NOLINT
const double value = countsWS->y(hists[j])[0];
if ((value == 0.) && checkForMask) {
const auto &detids = countsWS->getSpectrum(hists[j]).getDetectorIDs();
if (instrument->isDetectorMasked(detids)) {
numFailed -= 1; // it was already masked
}
}
if ((value < out_lo * median) && (value > 0.0)) {
countsWS->maskWorkspaceIndex(hists[j]);
PARALLEL_ATOMIC
++numFailed;
} else if (value > out_hi * median) {
countsWS->maskWorkspaceIndex(hists[j]);
PARALLEL_ATOMIC
++numFailed;
}
}
PARALLEL_CHECK_INTERUPT_REGION
}
return numFailed;
}
/** Create the final output workspace after converting the X axis
* @returns the final output workspace
*
* @param progress :: Progress indicator
* @param targetUnit :: Target conversion unit
* @param inputWS :: Input workspace
* @param nHist :: Stores the number of histograms
*/
MatrixWorkspace_sptr ConvertSpectrumAxis2::createOutputWorkspace(
API::Progress &progress, const std::string &targetUnit,
API::MatrixWorkspace_sptr &inputWS, size_t nHist) {
// Create the output workspace. Can not re-use the input one because the
// spectra are re-ordered.
MatrixWorkspace_sptr outputWorkspace = WorkspaceFactory::Instance().create(
inputWS, m_indexMap.size(), inputWS->x(0).size(), inputWS->y(0).size());
// Now set up a new numeric axis holding the theta values corresponding to
// each spectrum.
auto const newAxis = new NumericAxis(m_indexMap.size());
outputWorkspace->replaceAxis(1, newAxis);
progress.setNumSteps(nHist + m_indexMap.size());
// Set the units of the axis.
if (targetUnit == "theta" || targetUnit == "Theta" ||
targetUnit == "signed_theta" || targetUnit == "SignedTheta") {
newAxis->unit() = boost::make_shared<Units::Degrees>();
} else if (targetUnit == "ElasticQ") {
newAxis->unit() = UnitFactory::Instance().create("MomentumTransfer");
} else if (targetUnit == "ElasticQSquared") {
newAxis->unit() = UnitFactory::Instance().create("QSquared");
}
std::multimap<double, size_t>::const_iterator it;
size_t currentIndex = 0;
for (it = m_indexMap.begin(); it != m_indexMap.end(); ++it) {
// Set the axis value.
newAxis->setValue(currentIndex, it->first);
// Copy over the data.
outputWorkspace->setHistogram(currentIndex, inputWS->histogram(it->second));
// We can keep the spectrum numbers etc.
outputWorkspace->getSpectrum(currentIndex)
.copyInfoFrom(inputWS->getSpectrum(it->second));
++currentIndex;
progress.report("Creating output workspace...");
}
return outputWorkspace;
}
/** Execute the algorithm.
*/
void CreateEPP::exec() {
API::MatrixWorkspace_sptr inputWS =
getProperty(PropertyNames::INPUT_WORKSPACE);
const auto &spectrumInfo = inputWS->spectrumInfo();
API::ITableWorkspace_sptr outputWS =
API::WorkspaceFactory::Instance().createTable("TableWorkspace");
addEPPColumns(outputWS);
const double sigma = getProperty(PropertyNames::SIGMA);
const size_t spectraCount = spectrumInfo.size();
outputWS->setRowCount(spectraCount);
const auto l1 = spectrumInfo.l1();
const double EFixed = inputWS->run().getPropertyAsSingleValue("Ei");
for (size_t i = 0; i < spectraCount; ++i) {
const auto l2 = spectrumInfo.l2(i);
const auto elasticTOF = Kernel::UnitConversion::run(
"Energy", "TOF", EFixed, l1, l2, 0, Kernel::DeltaEMode::Direct, EFixed);
outputWS->getRef<int>(ColumnNames::WS_INDEX, i) = static_cast<int>(i);
outputWS->getRef<double>(ColumnNames::PEAK_CENTRE, i) = elasticTOF;
outputWS->getRef<double>(ColumnNames::PEAK_CENTRE_ERR, i) = 0;
outputWS->getRef<double>(ColumnNames::SIGMA, i) = sigma;
outputWS->getRef<double>(ColumnNames::SIGMA_ERR, i) = 0;
double height = 0;
try {
const auto elasticIndex = inputWS->binIndexOf(elasticTOF, i);
height = inputWS->y(i)[elasticIndex];
} catch (std::out_of_range &) {
std::ostringstream sout;
sout << "EPP out of TOF range for workspace index " << i
<< ". Peak height set to zero.";
g_log.warning() << sout.str();
}
outputWS->getRef<double>(ColumnNames::HEIGHT, i) = height;
outputWS->getRef<double>(ColumnNames::CHI_SQUARED, i) = 1;
outputWS->getRef<std::string>(ColumnNames::STATUS, i) = "success";
}
setProperty(PropertyNames::OUTPUT_WORKSPACE, outputWS);
}
/** Fits each spectrum in the workspace to f(x) = A * sin( w * x + p)
* @param ws :: [input] The workspace to fit
* @param freq :: [input] Hint for the frequency (w)
* @param groupName :: [input] The name of the output workspace group
* @param resTab :: [output] Table workspace storing the asymmetries and phases
* @param resGroup :: [output] Workspace group storing the fitting results
*/
void CalMuonDetectorPhases::fitWorkspace(const API::MatrixWorkspace_sptr &ws,
double freq, std::string groupName,
API::ITableWorkspace_sptr resTab,
API::WorkspaceGroup_sptr &resGroup) {
int nhist = static_cast<int>(ws->getNumberHistograms());
// Create the fitting function f(x) = A * sin ( w * x + p )
// The same function and initial parameters are used for each fit
std::string funcStr = createFittingFunction(freq, true);
// Set up results table
resTab->addColumn("int", "Spectrum number");
resTab->addColumn("double", "Asymmetry");
resTab->addColumn("double", "Phase");
const auto &indexInfo = ws->indexInfo();
// Loop through fitting all spectra individually
const static std::string success = "success";
for (int wsIndex = 0; wsIndex < nhist; wsIndex++) {
reportProgress(wsIndex, nhist);
const auto &yValues = ws->y(wsIndex);
auto emptySpectrum = std::all_of(yValues.begin(), yValues.end(),
[](double value) { return value == 0.; });
if (emptySpectrum) {
g_log.warning("Spectrum " + std::to_string(wsIndex) + " is empty");
TableWorkspace_sptr tab = boost::make_shared<TableWorkspace>();
tab->addColumn("str", "Name");
tab->addColumn("double", "Value");
tab->addColumn("double", "Error");
for (int j = 0; j < 4; j++) {
API::TableRow row = tab->appendRow();
if (j == PHASE_ROW) {
row << "dummy" << 0.0 << 0.0;
} else {
row << "dummy" << ASYMM_ERROR << 0.0;
}
}
extractDetectorInfo(*tab, *resTab, indexInfo.spectrumNumber(wsIndex));
} else {
auto fit = createChildAlgorithm("Fit");
fit->initialize();
fit->setPropertyValue("Function", funcStr);
fit->setProperty("InputWorkspace", ws);
fit->setProperty("WorkspaceIndex", wsIndex);
fit->setProperty("CreateOutput", true);
fit->setPropertyValue("Output", groupName);
fit->execute();
std::string status = fit->getProperty("OutputStatus");
if (!fit->isExecuted()) {
std::ostringstream error;
error << "Fit failed for spectrum at workspace index " << wsIndex;
error << ": " << status;
throw std::runtime_error(error.str());
} else if (status != success) {
g_log.warning("Fit failed for spectrum at workspace index " +
std::to_string(wsIndex) + ": " + status);
}
API::MatrixWorkspace_sptr fitOut = fit->getProperty("OutputWorkspace");
resGroup->addWorkspace(fitOut);
API::ITableWorkspace_sptr tab = fit->getProperty("OutputParameters");
// Now we have our fitting results stored in tab
// but we need to extract the relevant information, i.e.
// the detector phases (parameter 'p') and asymmetries ('A')
extractDetectorInfo(*tab, *resTab, indexInfo.spectrumNumber(wsIndex));
}
}
}
/**
* Takes a single valued histogram workspace and assesses which histograms are
* within the limits.
* Those that are not are masked on the input workspace.
* @param countsWS :: Input/Output Integrated workspace to diagnose.
* @param medianvec The median value calculated from the current counts.
* @param indexmap Index map.
* @param maskWS :: A mask workspace to apply.
* @return The number of detectors that failed the tests, not including those
* skipped.
*/
int MedianDetectorTest::doDetectorTests(
const API::MatrixWorkspace_sptr countsWS,
const std::vector<double> medianvec,
std::vector<std::vector<size_t>> indexmap,
API::MatrixWorkspace_sptr maskWS) {
g_log.debug("Applying the criteria to find failing detectors");
// A spectra can't fail if the statistics show its value is consistent with
// the mean value,
// check the error and how many errorbars we are away
const double minSigma = getProperty("SignificanceTest");
// prepare to report progress
const int numSpec(m_maxWsIndex - m_minWsIndex);
const int progStep = static_cast<int>(ceil(numSpec / 30.0));
int steps(0);
const double deadValue(1.0);
int numFailed(0);
bool checkForMask = false;
Geometry::Instrument_const_sptr instrument = countsWS->getInstrument();
if (instrument != nullptr) {
checkForMask = ((instrument->getSource() != nullptr) &&
(instrument->getSample() != nullptr));
}
PARALLEL_FOR_IF(Kernel::threadSafe(*countsWS, *maskWS))
for (int j = 0; j < static_cast<int>(indexmap.size()); ++j) {
std::vector<size_t> hists = indexmap.at(j);
double median = medianvec.at(j);
const size_t nhist = hists.size();
g_log.debug() << "new component with " << nhist << " spectra.\n";
for (size_t i = 0; i < nhist; ++i) {
g_log.debug() << "Counts workspace index=" << i
<< ", Mask workspace index=" << hists.at(i) << '\n';
PARALLEL_START_INTERUPT_REGION
++steps;
// update the progressbar information
if (steps % progStep == 0) {
progress(advanceProgress(progStep * static_cast<double>(RTMarkDetects) /
numSpec));
}
if (checkForMask) {
const auto &detids =
countsWS->getSpectrum(hists.at(i)).getDetectorIDs();
if (instrument->isDetectorMasked(detids)) {
maskWS->mutableY(hists.at(i))[0] = deadValue;
continue;
}
if (instrument->isMonitor(detids)) {
// Don't include in calculation but don't mask it
continue;
}
}
const double signal = countsWS->y(hists.at(i))[0];
// Mask out NaN and infinite
if (!std::isfinite(signal)) {
maskWS->mutableY(hists.at(i))[0] = deadValue;
PARALLEL_ATOMIC
++numFailed;
continue;
}
const double error = minSigma * countsWS->e(hists.at(i))[0];
if ((signal < median * m_loFrac && (signal - median < -error)) ||
(signal > median * m_hiFrac && (signal - median > error))) {
maskWS->mutableY(hists.at(i))[0] = deadValue;
PARALLEL_ATOMIC
++numFailed;
}
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
// Log finds
g_log.information() << numFailed << " spectra failed the median tests.\n";
}
return numFailed;
}
/** Forms the quadrature phase signal (squashogram)
* @param ws :: [input] workspace containing the measured spectra
* @param phase :: [input] table workspace containing the detector phases
* @param n0 :: [input] vector containing the normalization constants
* @return :: workspace containing the quadrature phase signal
*/
API::MatrixWorkspace_sptr
PhaseQuadMuon::squash(const API::MatrixWorkspace_sptr &ws,
const API::ITableWorkspace_sptr &phase,
const std::vector<double> &n0) {
// Poisson limit: below this number we consider we don't have enough
// statistics
// to apply sqrt(N). This is an arbitrary number used in the original code
// provided by scientists
double poissonLimit = 30.;
size_t nspec = ws->getNumberHistograms();
size_t npoints = ws->blocksize();
// Muon life time in microseconds
double muLife = PhysicalConstants::MuonLifetime * 1e6;
if (n0.size() != nspec) {
throw std::invalid_argument("Invalid normalization constants");
}
// Get the maximum asymmetry
double maxAsym = 0.;
for (size_t h = 0; h < nspec; h++) {
if (phase->Double(h, 1) > maxAsym) {
maxAsym = phase->Double(h, 1);
}
}
if (maxAsym == 0.0) {
throw std::invalid_argument("Invalid detector asymmetries");
}
std::vector<double> aj, bj;
{
// Calculate coefficients aj, bj
double sxx = 0;
double syy = 0;
double sxy = 0;
for (size_t h = 0; h < nspec; h++) {
double asym = phase->Double(h, 1) / maxAsym;
double phi = phase->Double(h, 2);
double X = n0[h] * asym * cos(phi);
double Y = n0[h] * asym * sin(phi);
sxx += X * X;
syy += Y * Y;
sxy += X * Y;
}
double lam1 = 2 * syy / (sxx * syy - sxy * sxy);
double mu1 = 2 * sxy / (sxy * sxy - sxx * syy);
double lam2 = 2 * sxy / (sxy * sxy - sxx * syy);
double mu2 = 2 * sxx / (sxx * syy - sxy * sxy);
for (size_t h = 0; h < nspec; h++) {
double asym = phase->Double(h, 1) / maxAsym;
double phi = phase->Double(h, 2);
double X = n0[h] * asym * cos(phi);
double Y = n0[h] * asym * sin(phi);
aj.push_back((lam1 * X + mu1 * Y) * 0.5);
bj.push_back((lam2 * X + mu2 * Y) * 0.5);
}
}
// First X value
double X0 = ws->x(0).front();
// Create and populate output workspace
API::MatrixWorkspace_sptr ows = API::WorkspaceFactory::Instance().create(
"Workspace2D", 2, npoints + 1, npoints);
// X
ows->setSharedX(0, ws->sharedX(0));
ows->setSharedX(1, ws->sharedX(0));
// Phase quadrature
auto &realY = ows->mutableY(0);
auto &imagY = ows->mutableY(1);
auto &realE = ows->mutableE(0);
auto &imagE = ows->mutableE(1);
for (size_t i = 0; i < npoints; i++) {
for (size_t h = 0; h < nspec; h++) {
// (X,Y,E) with exponential decay removed
const double X = ws->x(h)[i];
const double Y = ws->y(h)[i] - n0[h] * exp(-(X - X0) / muLife);
const double E = (ws->y(h)[i] > poissonLimit)
? ws->e(h)[i]
: sqrt(n0[h] * exp(-(X - X0) / muLife));
realY[i] += aj[h] * Y;
imagY[i] += bj[h] * Y;
realE[i] += aj[h] * aj[h] * E * E;
imagE[i] += bj[h] * bj[h] * E * E;
}
realE[i] = sqrt(realE[i]);
imagE[i] = sqrt(imagE[i]);
// Regain exponential decay
const double X = ws->getSpectrum(0).x()[i];
const double e = exp(-(X - X0) / muLife);
realY[i] /= e;
imagY[i] /= e;
realE[i] /= e;
imagE[i] /= e;
}
return ows;
}
/** Forms the quadrature phase signal (squashogram)
* @param ws :: [input] workspace containing the measured spectra
* @param phase :: [input] table workspace containing the detector phases
* @param n0 :: [input] vector containing the normalization constants
* @return :: workspace containing the quadrature phase signal
*/
API::MatrixWorkspace_sptr
PhaseQuadMuon::squash(const API::MatrixWorkspace_sptr &ws,
const API::ITableWorkspace_sptr &phase,
const std::vector<double> &n0) {
// Poisson limit: below this number we consider we don't have enough
// statistics
// to apply sqrt(N). This is an arbitrary number used in the original code
// provided by scientists
const double poissonLimit = 30.;
// Muon life time in microseconds
const double muLife = PhysicalConstants::MuonLifetime * 1e6;
const size_t nspec = ws->getNumberHistograms();
if (n0.size() != nspec) {
throw std::invalid_argument("Invalid normalization constants");
}
auto names = phase->getColumnNames();
for (auto &name : names) {
std::transform(name.begin(), name.end(), name.begin(), ::tolower);
}
auto phaseIndex = findName(phaseNames, names);
auto asymmetryIndex = findName(asymmNames, names);
// Get the maximum asymmetry
double maxAsym = 0.;
for (size_t h = 0; h < nspec; h++) {
if (phase->Double(h, asymmetryIndex) > maxAsym &&
phase->Double(h, asymmetryIndex) != ASYMM_ERROR) {
maxAsym = phase->Double(h, asymmetryIndex);
}
}
if (maxAsym == 0.0) {
throw std::invalid_argument("Invalid detector asymmetries");
}
std::vector<bool> emptySpectrum;
emptySpectrum.reserve(nspec);
std::vector<double> aj, bj;
{
// Calculate coefficients aj, bj
double sxx = 0.;
double syy = 0.;
double sxy = 0.;
for (size_t h = 0; h < nspec; h++) {
emptySpectrum.push_back(
std::all_of(ws->y(h).begin(), ws->y(h).end(),
[](double value) { return value == 0.; }));
if (!emptySpectrum[h]) {
const double asym = phase->Double(h, asymmetryIndex) / maxAsym;
const double phi = phase->Double(h, phaseIndex);
const double X = n0[h] * asym * cos(phi);
const double Y = n0[h] * asym * sin(phi);
sxx += X * X;
syy += Y * Y;
sxy += X * Y;
}
}
const double lam1 = 2 * syy / (sxx * syy - sxy * sxy);
const double mu1 = 2 * sxy / (sxy * sxy - sxx * syy);
const double lam2 = 2 * sxy / (sxy * sxy - sxx * syy);
const double mu2 = 2 * sxx / (sxx * syy - sxy * sxy);
for (size_t h = 0; h < nspec; h++) {
if (emptySpectrum[h]) {
aj.push_back(0.0);
bj.push_back(0.0);
} else {
const double asym = phase->Double(h, asymmetryIndex) / maxAsym;
const double phi = phase->Double(h, phaseIndex);
const double X = n0[h] * asym * cos(phi);
const double Y = n0[h] * asym * sin(phi);
aj.push_back((lam1 * X + mu1 * Y) * 0.5);
bj.push_back((lam2 * X + mu2 * Y) * 0.5);
}
}
}
const size_t npoints = ws->blocksize();
// Create and populate output workspace
API::MatrixWorkspace_sptr ows =
API::WorkspaceFactory::Instance().create(ws, 2, npoints + 1, npoints);
// X
ows->setSharedX(0, ws->sharedX(0));
ows->setSharedX(1, ws->sharedX(0));
// Phase quadrature
auto &realY = ows->mutableY(0);
auto &imagY = ows->mutableY(1);
auto &realE = ows->mutableE(0);
auto &imagE = ows->mutableE(1);
const auto xPointData = ws->histogram(0).points();
// First X value
const double X0 = xPointData.front();
// calculate exponential decay outside of the loop
std::vector<double> expDecay = xPointData.rawData();
std::transform(expDecay.begin(), expDecay.end(), expDecay.begin(),
[X0, muLife](double x) { return exp(-(x - X0) / muLife); });
for (size_t i = 0; i < npoints; i++) {
for (size_t h = 0; h < nspec; h++) {
if (!emptySpectrum[h]) {
// (X,Y,E) with exponential decay removed
const double X = ws->x(h)[i];
const double exponential = n0[h] * exp(-(X - X0) / muLife);
const double Y = ws->y(h)[i] - exponential;
const double E =
(ws->y(h)[i] > poissonLimit) ? ws->e(h)[i] : sqrt(exponential);
realY[i] += aj[h] * Y;
imagY[i] += bj[h] * Y;
realE[i] += aj[h] * aj[h] * E * E;
imagE[i] += bj[h] * bj[h] * E * E;
}
}
realE[i] = sqrt(realE[i]);
imagE[i] = sqrt(imagE[i]);
// Regain exponential decay
realY[i] /= expDecay[i];
imagY[i] /= expDecay[i];
realE[i] /= expDecay[i];
imagE[i] /= expDecay[i];
}
// New Y axis label
ows->setYUnit("Asymmetry");
return ows;
}
/** Carries out the bin-by-bin normalization
* @param inputWorkspace The input workspace
* @param outputWorkspace The result workspace
*/
void NormaliseToMonitor::normaliseBinByBin(
const API::MatrixWorkspace_sptr &inputWorkspace,
API::MatrixWorkspace_sptr &outputWorkspace) {
EventWorkspace_sptr inputEvent =
boost::dynamic_pointer_cast<EventWorkspace>(inputWorkspace);
// Only create output workspace if different to input one
if (outputWorkspace != inputWorkspace) {
if (inputEvent) {
outputWorkspace = inputWorkspace->clone();
} else
outputWorkspace = WorkspaceFactory::Instance().create(inputWorkspace);
}
auto outputEvent =
boost::dynamic_pointer_cast<EventWorkspace>(outputWorkspace);
// Get hold of the monitor spectrum
const auto &monX = m_monitor->binEdges(0);
auto monY = m_monitor->counts(0);
auto monE = m_monitor->countStandardDeviations(0);
// Calculate the overall normalization just the once if bins are all matching
if (m_commonBins)
this->normalisationFactor(monX, monY, monE);
const size_t numHists = inputWorkspace->getNumberHistograms();
auto specLength = inputWorkspace->blocksize();
// Flag set when a division by 0 is found
bool hasZeroDivision = false;
Progress prog(this, 0.0, 1.0, numHists);
// Loop over spectra
PARALLEL_FOR_IF(
Kernel::threadSafe(*inputWorkspace, *outputWorkspace, *m_monitor))
for (int64_t i = 0; i < int64_t(numHists); ++i) {
PARALLEL_START_INTERUPT_REGION
prog.report();
const auto &X = inputWorkspace->binEdges(i);
// If not rebinning, just point to our monitor spectra, otherwise create new
// vectors
auto Y = (m_commonBins ? monY : Counts(specLength));
auto E = (m_commonBins ? monE : CountStandardDeviations(specLength));
if (!m_commonBins) {
// ConvertUnits can give X vectors of all zeros - skip these, they cause
// problems
if (X.back() == 0.0 && X.front() == 0.0)
continue;
// Rebin the monitor spectrum to match the binning of the current data
// spectrum
VectorHelper::rebinHistogram(
monX.rawData(), monY.mutableRawData(), monE.mutableRawData(),
X.rawData(), Y.mutableRawData(), E.mutableRawData(), false);
// Recalculate the overall normalization factor
this->normalisationFactor(X, Y, E);
}
if (inputEvent) {
// ----------------------------------- EventWorkspace
// ---------------------------------------
EventList &outEL = outputEvent->getSpectrum(i);
outEL.divide(X.rawData(), Y.mutableRawData(), E.mutableRawData());
} else {
// ----------------------------------- Workspace2D
// ---------------------------------------
auto &YOut = outputWorkspace->mutableY(i);
auto &EOut = outputWorkspace->mutableE(i);
const auto &inY = inputWorkspace->y(i);
const auto &inE = inputWorkspace->e(i);
outputWorkspace->mutableX(i) = inputWorkspace->x(i);
// The code below comes more or less straight out of Divide.cpp
for (size_t k = 0; k < specLength; ++k) {
// Get the input Y's
const double leftY = inY[k];
const double rightY = Y[k];
if (rightY == 0.0) {
hasZeroDivision = true;
}
// Calculate result and store in local variable to avoid overwriting
// original data if
// output workspace is same as one of the input ones
const double newY = leftY / rightY;
if (fabs(rightY) > 1.0e-12 && fabs(newY) > 1.0e-12) {
const double lhsFactor = (inE[k] < 1.0e-12 || fabs(leftY) < 1.0e-12)
? 0.0
: pow((inE[k] / leftY), 2);
const double rhsFactor =
E[k] < 1.0e-12 ? 0.0 : pow((E[k] / rightY), 2);
EOut[k] = std::abs(newY) * sqrt(lhsFactor + rhsFactor);
}
// Now store the result
YOut[k] = newY;
} // end Workspace2D case
} // end loop over current spectrum
PARALLEL_END_INTERUPT_REGION
} // end loop over spectra
PARALLEL_CHECK_INTERUPT_REGION
if (hasZeroDivision) {
g_log.warning() << "Division by zero in some of the bins.\n";
}
}
