/** Calculates the rebin parameters in the case where the bins of the two
* workspaces intersect.
* 'Intersect' is used in the sense of two intersecting sets.
* @param X1 :: The bin boundaries from the first workspace
* @param i :: Indicates the index in X1 immediately before the overlap
* region starts
* @param X2 :: The bin boundaries from the second workspace
* @param params :: A reference to the vector of rebinning parameters
*/
void MergeRuns::intersectionParams(const MantidVec &X1, int64_t &i,
const MantidVec &X2,
std::vector<double> ¶ms) const {
// First calculate the number of bins in each workspace that are in the
// overlap region
int64_t overlapbins1, overlapbins2;
overlapbins1 = X1.size() - i;
for (overlapbins2 = 0; X2[overlapbins2] < X1.back(); ++overlapbins2) {
}
// We want to use whichever one has the larger bins (on average)
if (overlapbins1 < overlapbins2) {
// In this case we want the rest of the bins from the first workspace.....
for (; i < static_cast<int64_t>(X1.size()); ++i) {
params.push_back(X1[i] - X1[i - 1]);
params.push_back(X1[i]);
}
// Now remove the last bin & boundary
params.pop_back();
params.pop_back();
// ....and then the non-overlap ones from the second workspace
for (size_t j = overlapbins2; j < X2.size(); ++j) {
params.push_back(X2[j] - params.back());
params.push_back(X2[j]);
}
} else {
// In this case we just have to add all the bins from the second workspace
for (size_t j = 1; j < X2.size(); ++j) {
params.push_back(X2[j] - params.back());
params.push_back(X2[j]);
}
}
}
/** Deals with the (rare) case where the flightpath is longer than the reference
* Note that in this case both T1 & T2 will be greater than Tmax
*/
std::pair<int, int>
UnwrapMonitor::handleFrameOverlapped(const MantidVec &xdata, const double &Ld,
std::vector<double> &tempX) {
// Calculate the interval to exclude
const double Dt = (m_Tmax - m_Tmin) * (1 - (m_LRef / Ld));
// This gives us new minimum & maximum tof values
const double minT = m_Tmin + Dt;
const double maxT = m_Tmax - Dt;
// Can have situation where Ld is so much larger than Lref that everything
// would be excluded.
// This is an invalid input - warn and leave spectrum unwrapped
if (minT > maxT) {
g_log.warning() << "Invalid input, Ld (" << Ld << ") >> Lref (" << m_LRef
<< "). Current spectrum will not be unwrapped.\n";
return std::make_pair(0, static_cast<int>(xdata.size() - 1));
}
int min = 0, max = static_cast<int>(xdata.size());
for (unsigned int j = 0; j < m_XSize; ++j) {
const double T = xdata[j];
if (T < minT) {
min = j + 1;
tempX.erase(tempX.begin());
} else if (T > maxT) {
tempX.erase(tempX.end() - (max - j), tempX.end());
max = j - 1;
break;
}
}
return std::make_pair(min, max);
}
/**
* Find the overlap of the inputWS with the given polygon
* @param oldAxis1 :: Axis 1 bin boundaries from the input grid
* @param oldAxis2 :: Axis 2 bin boundaries from the input grid
* @param newPoly :: The new polygon to test
* @returns A list of intersection locations with weights of the overlap
*/
std::vector<Rebin2D::BinWithWeight>
Rebin2D::findIntersections(const MantidVec & oldAxis1, const MantidVec & oldAxis2,
const Geometry::ConvexPolygon & newPoly) const
{
std::vector<BinWithWeight> overlaps;
overlaps.reserve(5); // Have a guess at a posible limit
const size_t nxpoints(oldAxis1.size()-1), nypoints(oldAxis2.size()-1);
const double yn_lo(newPoly[0].Y()), yn_hi(newPoly[1].Y());
const double xn_lo(newPoly[0].X()), xn_hi(newPoly[2].X());
for(size_t i = 0; i < nypoints; ++i)
{
const double yo_lo(oldAxis2[i]), yo_hi(oldAxis2[i+1]);
// Check if there is a possibility of overlap
if( yo_hi < yn_lo || yo_lo > yn_hi ) continue;
for(size_t j = 0; j < nxpoints; ++j)
{
const double xo_lo(oldAxis1[j]), xo_hi(oldAxis1[j+1]);
// Check if there is a possibility of overlap
if( xo_hi < xn_lo || xo_lo > xn_hi ) continue;
ConvexPolygon oldPoly(xo_lo, xo_hi, yo_lo, yo_hi);
try
{
ConvexPolygon overlap = intersectionByLaszlo(newPoly, oldPoly);
overlaps.push_back(BinWithWeight(i,j,overlap.area()/oldPoly.area()));
}
catch(Geometry::NoIntersectionException &)
{}
}
}
return overlaps;
}
int UnwrapSNS::unwrapX(const MantidVec &datain, MantidVec &dataout,
const double &Ld) {
MantidVec tempX_L; // lower half - to be frame wrapped
tempX_L.reserve(m_XSize);
tempX_L.clear();
MantidVec tempX_U; // upper half - to not be frame wrapped
tempX_U.reserve(m_XSize);
tempX_U.clear();
double filterVal = m_Tmin * Ld / m_LRef;
dataout.clear();
int specialBin = 0;
for (int bin = 0; bin < m_XSize; ++bin) {
// This is the time-of-flight value under consideration in the current
// iteration of the loop
const double tof = datain[bin];
if (tof < filterVal) {
tempX_L.push_back(tof + m_frameWidth);
// Record the bins that fall in this range for copying over the data &
// errors
if (specialBin < bin)
specialBin = bin;
} else {
tempX_U.push_back(tof);
}
} // loop over X values
// now put it back into the vector supplied
dataout.clear();
dataout.insert(dataout.begin(), tempX_U.begin(), tempX_U.end());
dataout.insert(dataout.end(), tempX_L.begin(), tempX_L.end());
assert(datain.size() == dataout.size());
return specialBin;
}
/** Calculates the rebin parameters in the case where the range of the second
* workspace is
* entirely within that of the first workspace.
* 'Inclusion' is used in the sense of a set being included in anothre.
* @param X1 :: The bin boundaries from the first workspace
* @param i :: Indicates the index in X1 immediately before the overlap
* region starts
* @param X2 :: The bin boundaries from the second workspace
* @param params :: A reference to the vector of rebinning parameters
*/
void MergeRuns::inclusionParams(const MantidVec &X1, int64_t &i,
const MantidVec &X2,
std::vector<double> ¶ms) const {
// First calculate the number of bins in each workspace that are in the
// overlap region
int64_t overlapbins1, overlapbins2;
for (overlapbins1 = 1; X1[i + overlapbins1] < X2.back(); ++overlapbins1) {
}
//++overlapbins1;
overlapbins2 = X2.size() - 1;
// In the overlap region, we want to use whichever one has the larger bins (on
// average)
if (overlapbins1 + 1 <= overlapbins2) {
// In the case where the first workspace has larger bins it's easy
// - just add the rest of X1's bins
for (; i < static_cast<int64_t>(X1.size()); ++i) {
params.push_back(X1[i] - X1[i - 1]);
params.push_back(X1[i]);
}
} else {
// In this case we want all of X2's bins first (without the first and last
// boundaries)
for (size_t j = 1; j < X2.size() - 1; ++j) {
params.push_back(X2[j] - params.back());
params.push_back(X2[j]);
}
// And now those from X1 that lie above the overlap region
i += overlapbins1;
for (; i < static_cast<int64_t>(X1.size()); ++i) {
params.push_back(X1[i] - params.back());
params.push_back(X1[i]);
}
}
}
/**
* Create workspace to store the structure factor.
* First spectrum is the real part, second spectrum is the imaginary part
* X values are the modulus of the Q-vectors
* @param h5file file identifier
* @param gws pointer to WorkspaceGroup being filled
* @param setName string name of dataset
* @param qvmod vector of Q-vectors' moduli
* @param sorting_indexes permutation of qvmod indexes to render it in increasing order of momemtum transfer
*/
void LoadSassena::loadFQ(const hid_t& h5file, API::WorkspaceGroup_sptr gws, const std::string setName, const MantidVec &qvmod, const std::vector<int> &sorting_indexes)
{
const std::string gwsName = this->getPropertyValue("OutputWorkspace");
int nq = static_cast<int>( qvmod.size() ); //number of q-vectors
DataObjects::Workspace2D_sptr ws = boost::dynamic_pointer_cast<DataObjects::Workspace2D>(API::WorkspaceFactory::Instance().create("Workspace2D", 2, nq, nq));
const std::string wsName = gwsName + std::string("_") + setName;
ws->setTitle(wsName);
double* buf = new double[nq*2];
this->dataSetDouble(h5file,setName,buf);
MantidVec& re = ws->dataY(0); // store the real part
ws->dataX(0) = qvmod; //X-axis values are the modulus of the q vector
MantidVec& im = ws->dataY(1); // store the imaginary part
ws->dataX(1) = qvmod;
double *curr = buf;
for(int iq=0; iq<nq; iq++){
const int index=sorting_indexes[iq];
re[index]=curr[0];
im[index]=curr[1];
curr+=2;
}
delete[] buf;
// Set the Units
ws->getAxis(0)->unit() = Kernel::UnitFactory::Instance().create("MomentumTransfer");
this->registerWorkspace(gws,wsName,ws, "X-axis: Q-vector modulus; Y-axis: intermediate structure factor");
}
void Divide::performBinaryOperation(const MantidVec &lhsX,
const MantidVec &lhsY,
const MantidVec &lhsE, const double rhsY,
const double rhsE, MantidVec &YOut,
MantidVec &EOut) {
(void)lhsX; // Avoid compiler warning
if (rhsY == 0 && m_warnOnZeroDivide)
g_log.warning() << "Division by zero: the RHS is a single-valued vector "
"with value zero."
<< "\n";
// Do the right-hand part of the error calculation just once
const double rhsFactor = pow(rhsE / rhsY, 2);
const int bins = static_cast<int>(lhsE.size());
for (int j = 0; j < bins; ++j) {
// Get reference to input Y
const double leftY = lhsY[j];
// see comment in the function above for the error formula
EOut[j] = sqrt(pow(lhsE[j], 2) + pow(leftY, 2) * rhsFactor) / fabs(rhsY);
// Copy the result last in case one of the input workspaces is also any
// output
YOut[j] = leftY / rhsY;
}
}
/**
* @param xValues The X data for the fitted spectrum
*/
void ComptonScatteringCountRate::createPositivityCM(const MantidVec &xValues) {
// -- Constraint matrix for J(y) > 0 --
// The first N columns are filled with J(y) for each mass + N_h for the first
// mass hermite
// terms included + (n+1) for each termn the background of order n
// The background columns are filled with x^j/error where j=(1,n+1)
const size_t nrows(xValues.size());
size_t nColsCMatrix(m_fixedParamIndices.size());
m_cmatrix = Kernel::DblMatrix(nrows, nColsCMatrix);
// Fill background values as they don't change at all
if (m_bkgdPolyN > 0) {
size_t polyStartCol = nColsCMatrix - m_bkgdPolyN - 1;
for (size_t i = 0; i < nrows; ++i) // rows
{
double *row = m_cmatrix[i];
const double &xi = xValues[i];
const double &erri = m_errors[i];
size_t polyN = m_bkgdPolyN;
for (size_t j = polyStartCol; j < nColsCMatrix; ++j) // cols
{
row[j] = std::pow(xi, static_cast<double>(polyN)) / erri;
--polyN;
}
}
}
}
void WeightedMean::performBinaryOperation(const MantidVec& lhsX, const MantidVec& lhsY, const MantidVec& lhsE,
const double rhsY, const double rhsE, MantidVec& YOut, MantidVec& EOut)
{
UNUSED_ARG(lhsX);
assert( lhsX.size() == 1 );
// If we get here we've got two single column workspaces so it's easy.
if (lhsE[0] > 0.0 && rhsE > 0.0)
{
const double err1 = lhsE[0]*lhsE[0];
const double err2 = rhsE*rhsE;
YOut[0] = (lhsY[0]/err1)+(rhsY/err2);
EOut[0] = (err1*err2)/(err1+err2);
YOut[0] *= EOut[0];
EOut[0] = sqrt(EOut[0]);
}
else if (lhsE[0] > 0.0 && rhsE <= 0.0)
{
YOut[0] = lhsY[0];
EOut[0] = lhsE[0];
}
else if (lhsE[0] <= 0.0 && rhsE > 0.0)
{
YOut[0] = rhsY;
EOut[0] = rhsE;
}
else
{
YOut[0] = 0.0;
EOut[0] = 0.0;
}
}
/// Retrieve and check the Start/EndX parameters, if set
void Linear::setRange(const MantidVec& X, const MantidVec& Y)
{
//read in the values that the user selected
double startX = getProperty("StartX");
double endX = getProperty("EndX");
//If the user didn't a start default to the start of the data
if ( isEmpty(startX) ) startX = X.front();
//the default for the end is the end of the data
if ( isEmpty(endX) ) endX = X.back();
// Check the validity of startX
if ( startX < X.front() )
{
g_log.warning("StartX out of range! Set to start of frame.");
startX = X.front();
}
// Now get the corresponding bin boundary that comes before (or coincides with) this value
for (m_minX = 0; X[m_minX+1] < startX; ++m_minX) {}
// Check the validity of endX and get the bin boundary that come after (or coincides with) it
if ( endX >= X.back() || endX < startX )
{
if ( endX != X.back() )
{
g_log.warning("EndX out of range! Set to end of frame");
endX = X.back();
}
m_maxX = static_cast<int>(Y.size());
}
else
{
for (m_maxX = m_minX; X[m_maxX] < endX; ++m_maxX) {}
}
}
void Divide::performBinaryOperation(const MantidVec &lhsX,
const MantidVec &lhsY,
const MantidVec &lhsE,
const MantidVec &rhsY,
const MantidVec &rhsE, MantidVec &YOut,
MantidVec &EOut) {
(void)lhsX; // Avoid compiler warning
const int bins = static_cast<int>(lhsE.size());
for (int j = 0; j < bins; ++j) {
// Get references to the input Y's
const double leftY = lhsY[j];
const double rightY = rhsY[j];
// error dividing two uncorrelated numbers, re-arrange so that you don't
// get infinity if leftY==0 (when rightY=0 the Y value and the result will
// both be infinity)
// (Sa/a)2 + (Sb/b)2 = (Sc/c)2
// (Sa c/a)2 + (Sb c/b)2 = (Sc)2
// = (Sa 1/b)2 + (Sb (a/b2))2
// (Sc)2 = (1/b)2( (Sa)2 + (Sb a/b)2 )
EOut[j] =
sqrt(pow(lhsE[j], 2) + pow(leftY * rhsE[j] / rightY, 2)) / fabs(rightY);
// Copy the result last in case one of the input workspaces is also any
// output
YOut[j] = leftY / rightY;
;
}
}
MantidVec
operator()(const MantidVec &_Left,
const MantidVec &_Right) const { // apply operator+ to operands
MantidVec v(_Left.size());
std::transform(_Left.begin(), _Left.end(), _Right.begin(), v.begin(),
SumGaussError<double>());
return (v);
}
/** Calculates the rebin paramters in the case where the two input workspaces do
* not overlap at all.
* @param X1 :: The bin boundaries from the first workspace
* @param X2 :: The bin boundaries from the second workspace
* @param params :: A reference to the vector of rebinning parameters
*/
void MergeRuns::noOverlapParams(const MantidVec &X1, const MantidVec &X2,
std::vector<double> ¶ms) const {
// Add all the bins from the first workspace
for (size_t i = 1; i < X1.size(); ++i) {
params.push_back(X1[i - 1]);
params.push_back(X1[i] - X1[i - 1]);
}
// Put a single bin in the 'gap' (but check first the 'gap' isn't zero)
if (X1.back() < X2.front()) {
params.push_back(X1.back());
params.push_back(X2.front() - X1.back());
}
// Now add all the bins from the second workspace
for (size_t j = 1; j < X2.size(); ++j) {
params.push_back(X2[j - 1]);
params.push_back(X2[j] - X2[j - 1]);
}
params.push_back(X2.back());
}
/// Returns vector with x-values of spectrum if MatrixWorkspace does not contain
/// histogram data.
MantidVec FunctionDomain1DSpectrumCreator::getVectorNonHistogram() const {
const MantidVec wsXData = m_matrixWorkspace->readX(m_workspaceIndex);
size_t wsXSize = wsXData.size();
if (wsXSize < 1) {
throw std::invalid_argument(
"Workspace2D with less than one x-value cannot be processed.");
}
return MantidVec(wsXData);
}
/**
* Returns the phase shift to apply
* If "AutoShift" is set, calculates this automatically as -X[N/2]
* Otherwise, returns user-supplied "Shift" (or zero if none set)
* @param xValues :: [input] Reference to X values of input workspace
* @returns :: Phase shift
*/
double FFT::getPhaseShift(const MantidVec &xValues) {
double shift = 0.0;
const bool autoshift = getProperty("AutoShift");
if (autoshift) {
const size_t mid = xValues.size() / 2;
shift = -xValues[mid];
} else {
shift = getProperty("Shift");
}
shift *= 2 * M_PI;
return shift;
}
void PoissonErrors::performBinaryOperation(const MantidVec& lhsX, const MantidVec& lhsY, const MantidVec& lhsE,
const double rhsY, const double rhsE, MantidVec& YOut, MantidVec& EOut)
{
(void) lhsE; (void) lhsX; //Avoid compiler warning
assert( lhsX.size() == 1 );
// If we get here we've got two single column workspaces so it's easy.
YOut[0] = lhsY[0];
const double fractional = rhsY ? rhsE/rhsY : 0.0;
EOut[0] = fractional*lhsY[0];
}
/** Zeroes data (Y/E) at the end of a spectrum
* @param start :: The index to start zeroing at
* @param end :: The index to end zeroing at
* @param Y :: The data vector
* @param E :: The error vector
*/
void RemoveBins::RemoveFromEnds(int start, int end, MantidVec& Y, MantidVec& E)
{
if ( start ) --start;
int size = static_cast<int>(Y.size());
if ( end > size ) end = size;
for (int j = start; j < end; ++j)
{
Y[j] = 0.0;
E[j] = 0.0;
}
return;
}
/** Divides the number of counts in each output Q bin by the wrighting ("number that would expected to arrive")
* The errors are propogated using the uncorrolated error estimate for multiplication/division
* @param[in] normSum the weighting for each bin
* @param[in] normError2 square of the error on the normalization
* @param[in, out] counts counts in each bin
* @param[in, out] errors input the _square_ of the error on each bin, output the total error (unsquared)
*/
void Q1D2::normalize(const MantidVec & normSum, const MantidVec & normError2, MantidVec & counts, MantidVec & errors) const
{
for (size_t k = 0; k < counts.size(); ++k)
{
// the normalisation is a = b/c where b = counts c =normalistion term
const double c = normSum[k];
const double a = counts[k] /= c;
// when a = b/c, the formula for Da, the error on a, in terms of Db, etc. is (Da/a)^2 = (Db/b)^2 + (Dc/c)^2
//(Da)^2 = ((Db/b)^2 + (Dc/c)^2)*(b^2/c^2) = ((Db/c)^2 + (b*Dc/c^2)^2) = (Db^2 + (b*Dc/c)^2)/c^2 = (Db^2 + (Dc*a)^2)/c^2
//this will work as long as c>0, but then the above formula above can't deal with 0 either
const double aOverc = a/c;
errors[k] = std::sqrt(errors[k]/(c*c) + normError2[k]*aOverc*aOverc);
}
}
/**
* Get the start and end of the x-interval.
* @param X :: The x-vector of a spectrum.
* @param isHistogram :: Is the x-vector comming form a histogram? If it's true
* the bin
* centres are used.
* @return :: A pair of start x and end x.
*/
std::pair<double, double> WienerSmooth::getStartEnd(const MantidVec &X,
bool isHistogram) const {
const size_t n = X.size();
if (n < 3) {
// 3 is the smallest number for this method to work without breaking
throw std::runtime_error(
"Number of bins/data points cannot be smaller than 3.");
}
if (isHistogram) {
return std::make_pair((X[0] + X[1]) / 2, (X[n - 1] + X[n - 2]) / 2);
}
// else
return std::make_pair(X.front(), X.back());
}
/** Execute the algorithm.
*/
void WeightedMeanOfWorkspace::exec()
{
MatrixWorkspace_sptr inputWS = this->getProperty("InputWorkspace");
// Check if it is an event workspace
EventWorkspace_const_sptr eventW = boost::dynamic_pointer_cast<const EventWorkspace>(inputWS);
if (eventW != NULL)
{
throw std::runtime_error("WeightedMeanOfWorkspace cannot handle EventWorkspaces!");
}
// Create the output workspace
MatrixWorkspace_sptr singleValued = WorkspaceFactory::Instance().create("WorkspaceSingleValue", 1, 1, 1);
// Calculate weighted mean
std::size_t numHists = inputWS->getNumberHistograms();
double averageValue = 0.0;
double weightSum = 0.0;
for (std::size_t i = 0; i < numHists; ++i)
{
try
{
IDetector_const_sptr det = inputWS->getDetector(i);
if( det->isMonitor() || det->isMasked() )
{
continue;
}
}
catch (...)
{
// Swallow these if no instrument is found
;
}
MantidVec y = inputWS->dataY(i);
MantidVec e = inputWS->dataE(i);
double weight = 0.0;
for (std::size_t j = 0; j < y.size(); ++j)
{
if (!boost::math::isnan(y[j]) && !boost::math::isinf(y[j]) &&
!boost::math::isnan(e[j]) && !boost::math::isinf(e[j]))
{
weight = 1.0 / (e[j] * e[j]);
averageValue += (y[j] * weight);
weightSum += weight;
}
}
}
singleValued->dataX(0)[0] = 0.0;
singleValued->dataY(0)[0] = averageValue / weightSum;
singleValued->dataE(0)[0] = std::sqrt(weightSum);
this->setProperty("OutputWorkspace", singleValued);
}
/** Returns the number of background points
*
* Given a list of peaks and a vector with spectrum count data, this method returns the number of background points
* contained in this spectrum. It is used for extraction of the background in order to allocate the correct vector
* size before filling it.
*
* @param peakPositions :: Peak positions.
* @param correlationCounts :: Data vector the peak positions refer to.
* @return Number of background points.
*/
size_t PoldiPeakSearch::getNumberOfBackgroundPoints(std::list<MantidVec::const_iterator> peakPositions, const MantidVec &correlationCounts) const
{
/* subtracting 2, to match original algorithm, where
* the first and the last point of the spectrum are not
* considered in this calculation.
*/
size_t totalDataPoints = correlationCounts.size() - 2;
size_t occupiedByPeaks = peakPositions.size() * (m_doubleMinimumDistance + 1);
if(occupiedByPeaks > totalDataPoints) {
throw(std::runtime_error("More data points occupied by peaks than existing data points - not possible."));
}
return totalDataPoints - occupiedByPeaks;
}
void SaveGSS::writeRALFdata(const int bank, const bool MultiplyByBinWidth,
std::stringstream &out, const MantidVec &X,
const MantidVec &Y, const MantidVec &E) const {
const size_t datasize = Y.size();
double bc1 = X[0] * 32;
double bc2 = (X[1] - X[0]) * 32;
// Logarithmic step
double bc4 = (X[1] - X[0]) / X[0];
if (boost::math::isnan(fabs(bc4)) || boost::math::isinf(bc4))
bc4 = 0; // If X is zero for BANK
// Write out the data header
writeBankLine(out, "RALF", bank, datasize);
out << std::fixed << " " << std::setprecision(0) << std::setw(8) << bc1
<< std::fixed << " " << std::setprecision(0) << std::setw(8) << bc2
<< std::fixed << " " << std::setprecision(0) << std::setw(8) << bc1
<< std::fixed << " " << std::setprecision(5) << std::setw(7) << bc4
<< " FXYE" << std::endl;
// Do each Y entry
for (size_t j = 0; j < datasize; j++) {
// Calculate the error
double Epos;
if (MultiplyByBinWidth)
Epos = E[j] * (X[j + 1] - X[j]); // E[j]*X[j]*bc4;
else
Epos = E[j];
Epos = fixErrorValue(Epos);
// The center of the X bin.
out << std::fixed << std::setprecision(5) << std::setw(15)
<< 0.5 * (X[j] + X[j + 1]);
// The Y value
if (MultiplyByBinWidth)
out << std::fixed << std::setprecision(8) << std::setw(18)
<< Y[j] * (X[j + 1] - X[j]);
else
out << std::fixed << std::setprecision(8) << std::setw(18) << Y[j];
// The error
out << std::fixed << std::setprecision(8) << std::setw(18) << Epos << "\n";
}
return;
}
void Multiply::performBinaryOperation(const MantidVec& lhsX, const MantidVec& lhsY, const MantidVec& lhsE,
const double rhsY, const double rhsE, MantidVec& YOut, MantidVec& EOut)
{
UNUSED_ARG(lhsX);
const size_t bins = lhsE.size();
for (size_t j=0; j<bins; ++j)
{
// Get reference to input Y
const double leftY = lhsY[j];
// see comment in the function above for the error formula
EOut[j] = sqrt(pow(lhsE[j]*rhsY, 2) + pow(rhsE*leftY, 2));
// Copy the result last in case one of the input workspaces is also any output
YOut[j] = leftY*rhsY;
}
}
/// Returns vector with x-values of spectrum if MatrixWorkspace contains
/// histogram data.
MantidVec FunctionDomain1DSpectrumCreator::getVectorHistogram() const {
const MantidVec wsXData = m_matrixWorkspace->readX(m_workspaceIndex);
size_t wsXSize = wsXData.size();
if (wsXSize < 2) {
throw std::invalid_argument("Histogram Workspace2D with less than two "
"x-values cannot be processed.");
}
MantidVec x(wsXSize - 1);
for (size_t i = 0; i < x.size(); ++i) {
x[i] = (wsXData[i] + wsXData[i + 1]) / 2.0;
}
return x;
}
void Divide::performBinaryOperation(const MantidVec& lhsX, const MantidVec& lhsY, const MantidVec& lhsE,
const double rhsY, const double rhsE, MantidVec& YOut, MantidVec& EOut)
{
(void) lhsX; //Avoid compiler warning
// Do the right-hand part of the error calculation just once
const double rhsFactor = pow(rhsE/rhsY,2);
const int bins = static_cast<int>(lhsE.size());
for (int j=0; j<bins; ++j)
{
// Get reference to input Y
const double leftY = lhsY[j];
// see comment in the function above for the error formula
EOut[j] = sqrt( pow(lhsE[j], 2)+pow( leftY, 2)*rhsFactor )/rhsY;
// Copy the result last in case one of the input workspaces is also any output
YOut[j] = leftY/rhsY;
}
}
/** Write data in SLOG format
*/
void SaveGSS::writeSLOGdata(const int bank, const bool MultiplyByBinWidth,
std::stringstream &out, const MantidVec &X,
const MantidVec &Y, const MantidVec &E) const {
const size_t datasize = Y.size();
double bc1 = X.front(); // minimum TOF in microseconds
if (bc1 <= 0.) {
throw std::runtime_error(
"Cannot write out logarithmic data starting at zero");
}
double bc2 = 0.5 * (*(X.rbegin()) +
*(X.rbegin() + 1)); // maximum TOF (in microseconds?)
double bc3 = (*(X.begin() + 1) - bc1) / bc1; // deltaT/T
g_log.debug() << "SaveGSS(): Min TOF = " << bc1 << std::endl;
writeBankLine(out, "SLOG", bank, datasize);
out << std::fixed << " " << std::setprecision(0) << std::setw(10) << bc1
<< std::fixed << " " << std::setprecision(0) << std::setw(10) << bc2
<< std::fixed << " " << std::setprecision(7) << std::setw(10) << bc3
<< std::fixed << " 0 FXYE" << std::endl;
for (size_t i = 0; i < datasize; i++) {
double y = Y[i];
double e = E[i];
if (MultiplyByBinWidth) {
// Multiple by bin width as
double delta = X[i + 1] - X[i];
y *= delta;
e *= delta;
}
e = fixErrorValue(e);
out << " " << std::fixed << std::setprecision(9) << std::setw(20)
<< 0.5 * (X[i] + X[i + 1]) << " " << std::fixed << std::setprecision(9)
<< std::setw(20) << y << " " << std::fixed << std::setprecision(9)
<< std::setw(20) << e << std::setw(12) << " "
<< "\n"; // let it flush its own buffer
}
out << std::flush;
return;
}
/**
* Calculate detector efficiency given a formula, the efficiency at the elastic line,
* and a vector with energies.
* Efficiency = f(Ei-DeltaE) / f(Ei)
* Hope all compilers supports the NRVO (otherwise will copy the output vector)
* @param eff0 :: calculated eff0
* @param formula :: formula to calculate efficiency (parsed from IDF)
* @param xIn :: Energy bins vector (X axis)
* @return a vector with the efficiencies
*/
MantidVec DetectorEfficiencyCorUser::calculateEfficiency(double eff0,
const std::string& formula, const MantidVec& xIn) {
MantidVec effOut(xIn.size() - 1); // x are bins and have more one value than y
try {
double e;
mu::Parser p;
p.DefineVar("e", &e);
p.SetExpr(formula);
// copied from Jaques Ollivier Code
bool conditionForEnergy = std::min( std::abs( *std::min_element(xIn.begin(), xIn.end()) ) , m_Ei) < m_Ei;
MantidVec::const_iterator xIn_it = xIn.begin(); // DeltaE
MantidVec::iterator effOut_it = effOut.begin();
for (; effOut_it != effOut.end(); ++xIn_it, ++effOut_it) {
if (conditionForEnergy ) {
// cppcheck cannot see that this is used by reference by muparser
e = std::fabs(m_Ei + *xIn_it);
}
else {
// cppcheck cannot see that this is used by reference by muparser
// cppcheck-suppress unreadVariable
e = std::fabs(m_Ei - *xIn_it);
}
double eff = p.Eval();
*effOut_it = eff / eff0;
}
return effOut;
} catch (mu::Parser::exception_type &e) {
throw Kernel::Exception::InstrumentDefinitionError(
"Error calculating formula from string. Muparser error message is: "
+ e.GetMsg());
}
}
/**
* Copy over the metadata from the input matrix workspace to output MDEventWorkspace
* @param mdEventWS :: The output MDEventWorkspace where metadata are copied to. The source of the metadata is the input matrix workspace
*
*/
void ConvertToMD::copyMetaData(API::IMDEventWorkspace_sptr &mdEventWS) const
{
// found detector which is not a monitor to get proper bin boundaries.
size_t spectra_index(0);
bool dector_found(false);
for(size_t i=0;i<m_InWS2D->getNumberHistograms(); ++i)
{
try
{
auto det=m_InWS2D->getDetector(i);
if (!det->isMonitor())
{
spectra_index=i;
dector_found = true;
g_log.debug()<<"Using spectra N "<<i<< " as the source of the bin boundaries for the resolution corrections \n";
break;
}
}
catch(...)
{}
}
if (!dector_found)
g_log.warning()<<"No detectors in the workspace are associated with spectra. Using spectrum 0 trying to retrieve the bin boundaries \n";
// retrieve representative bin boundaries
MantidVec binBoundaries = m_InWS2D->readX(spectra_index);
// check if the boundaries transformation is necessary
if (m_Convertor->getUnitConversionHelper().isUnitConverted())
{
if( !dynamic_cast<DataObjects::EventWorkspace *>(m_InWS2D.get()))
{
g_log.information()<<" ConvertToMD converts input workspace units, but the bin boundaries are copied from the first workspace spectra. The resolution estimates can be incorrect if unit conversion depends on spectra number.\n";
UnitsConversionHelper &unitConv = m_Convertor->getUnitConversionHelper();
unitConv.updateConversion(spectra_index);
for(size_t i=0;i<binBoundaries.size();i++)
{
binBoundaries[i] =unitConv.convertUnits(binBoundaries[i]);
}
}
// sort bin boundaries in case if unit transformation have swapped them.
if (binBoundaries[0]>binBoundaries[binBoundaries.size()-1])
{
g_log.information()<<"Bin boundaries are not arranged monotonously. Sorting performed\n";
std::sort(binBoundaries.begin(),binBoundaries.end());
}
}
// Replacement for SpectraDetectorMap::createIDGroupsMap using the ISpectrum objects instead
auto mapping = boost::make_shared<det2group_map>();
for ( size_t i = 0; i < m_InWS2D->getNumberHistograms(); ++i )
{
const auto& dets = m_InWS2D->getSpectrum(i)->getDetectorIDs();
if(!dets.empty())
{
std::vector<detid_t> id_vector;
std::copy(dets.begin(), dets.end(), std::back_inserter(id_vector));
mapping->insert(std::make_pair(id_vector.front(), id_vector));
}
}
uint16_t nexpts = mdEventWS->getNumExperimentInfo();
for(uint16_t i = 0; i < nexpts; ++i)
{
ExperimentInfo_sptr expt = mdEventWS->getExperimentInfo(i);
expt->mutableRun().storeHistogramBinBoundaries(binBoundaries);
expt->cacheDetectorGroupings(*mapping);
}
}
/** Corrects a spectra for the detector efficiency calculated from detector information
Gets the detector information and uses this to calculate its efficiency
* @param spectraIn :: index of the spectrum to get the efficiency for
* @throw invalid_argument if the shape of a detector is isn't a cylinder aligned along one axis
* @throw runtime_error if the SpectraDetectorMap has not been filled
* @throw NotFoundError if the detector or its gas pressure or wall thickness were not found
*/
void DetectorEfficiencyCor::correctForEfficiency(int64_t spectraIn)
{
IDetector_const_sptr det = m_inputWS->getDetector(spectraIn);
if( det->isMonitor() || det->isMasked() )
{
return;
}
MantidVec & yout = m_outputWS->dataY(spectraIn);
MantidVec & eout = m_outputWS->dataE(spectraIn);
// Need the original values so this is not a reference
const MantidVec yValues = m_inputWS->readY(spectraIn);
const MantidVec eValues = m_inputWS->readE(spectraIn);
// get a pointer to the detectors that created the spectrum
const std::set<detid_t> dets = m_inputWS->getSpectrum(spectraIn)->getDetectorIDs();
std::set<detid_t>::const_iterator it = dets.begin();
std::set<detid_t>::const_iterator iend = dets.end();
if ( it == iend )
{
throw Exception::NotFoundError("No detectors found", spectraIn);
}
// Storage for the reciprocal wave vectors that are calculated as the
//correction proceeds
std::vector<double> oneOverWaveVectors(yValues.size());
for( ; it != iend ; ++it )
{
IDetector_const_sptr det_member = m_inputWS->getInstrument()->getDetector(*it);
Parameter_sptr par = m_paraMap->get(det_member.get(),"3He(atm)");
if ( !par )
{
throw Exception::NotFoundError("3He(atm)", spectraIn);
}
const double atms = par->value<double>();
par = m_paraMap->get(det_member.get(),"wallT(m)");
if ( !par )
{
throw Exception::NotFoundError("wallT(m)", spectraIn);
}
const double wallThickness = par->value<double>();
double detRadius(0.0);
V3D detAxis;
getDetectorGeometry(det_member, detRadius, detAxis);
// now get the sin of the angle, it's the magnitude of the cross product of unit vector along the detector tube axis and a unit vector directed from the sample to the detector centre
V3D vectorFromSample = det_member->getPos() - m_samplePos;
vectorFromSample.normalize();
Quat rot = det_member->getRotation();
// rotate the original cylinder object axis to get the detector axis in the actual instrument
rot.rotate(detAxis);
detAxis.normalize();
// Scalar product is quicker than cross product
double cosTheta = detAxis.scalar_prod(vectorFromSample);
double sinTheta = std::sqrt(1.0 - cosTheta*cosTheta);
// Detector constant
const double det_const = g_helium_prefactor*(detRadius - wallThickness)*atms/sinTheta;
MantidVec::const_iterator yinItr = yValues.begin();
MantidVec::const_iterator einItr = eValues.begin();
MantidVec::iterator youtItr = yout.begin();
MantidVec::iterator eoutItr = eout.begin();
MantidVec::const_iterator xItr = m_inputWS->readX(spectraIn).begin();
std::vector<double>::iterator wavItr = oneOverWaveVectors.begin();
for( ; youtItr != yout.end(); ++youtItr, ++eoutItr)
{
if( it == dets.begin() )
{
*youtItr = 0.0;
*eoutItr = 0.0;
*wavItr = calculateOneOverK(*xItr, *(xItr + 1 ));
}
const double oneOverWave = *wavItr;
const double factor = 1.0/detectorEfficiency(det_const*oneOverWave);
*youtItr += (*yinItr)*factor;
*eoutItr += (*einItr)*factor;
++yinItr; ++einItr;
++xItr; ++wavItr;
}
}
}
void TOFSANSResolutionByPixel::exec() {
MatrixWorkspace_sptr inOutWS = getProperty("Workspace");
double deltaR = getProperty("DeltaR");
double R1 = getProperty("SourceApertureRadius");
double R2 = getProperty("SampleApertureRadius");
// Convert to meters
deltaR /= 1000.0;
R1 /= 1000.0;
R2 /= 1000.0;
const MatrixWorkspace_sptr sigmaModeratorVSwavelength =
getProperty("SigmaModerator");
// create interpolation table from sigmaModeratorVSwavelength
Kernel::Interpolation lookUpTable;
const MantidVec xInterpolate = sigmaModeratorVSwavelength->readX(0);
const MantidVec yInterpolate = sigmaModeratorVSwavelength->readY(0);
// prefer the input to be a pointworkspace and create interpolation function
if (sigmaModeratorVSwavelength->isHistogramData()) {
g_log.notice() << "mid-points of SigmaModerator histogram bins will be "
"used for interpolation.";
for (size_t i = 0; i < xInterpolate.size() - 1; ++i) {
const double midpoint = xInterpolate[i + 1] - xInterpolate[i];
lookUpTable.addPoint(midpoint, yInterpolate[i]);
}
} else {
for (size_t i = 0; i < xInterpolate.size(); ++i) {
lookUpTable.addPoint(xInterpolate[i], yInterpolate[i]);
}
}
const V3D samplePos = inOutWS->getInstrument()->getSample()->getPos();
const V3D sourcePos = inOutWS->getInstrument()->getSource()->getPos();
const V3D SSD = samplePos - sourcePos;
const double L1 = SSD.norm();
const int numberOfSpectra = static_cast<int>(inOutWS->getNumberHistograms());
Progress progress(this, 0.0, 1.0, numberOfSpectra);
for (int i = 0; i < numberOfSpectra; i++) {
IDetector_const_sptr det;
try {
det = inOutWS->getDetector(i);
} catch (Exception::NotFoundError &) {
g_log.information() << "Spectrum index " << i
<< " has no detector assigned to it - discarding"
<< std::endl;
}
// If no detector found or if it's masked or a monitor, skip onto the next
// spectrum
if (!det || det->isMonitor() || det->isMasked())
continue;
// Get the flight path from the sample to the detector pixel
const V3D scatteredFlightPathV3D = det->getPos() - samplePos;
const double L2 = scatteredFlightPathV3D.norm();
const double Lsum = L1 + L2;
// calculate part that is wavelenght independent
const double dTheta2 = (4.0 * M_PI * M_PI / 12.0) *
(3.0 * R1 * R1 / (L1 * L1) +
3.0 * R2 * R2 * Lsum * Lsum / (L1 * L1 * L2 * L2) +
(deltaR * deltaR) / (L2 * L2));
// Multiplicative factor to go from lambda to Q
// Don't get fooled by the function name...
const double theta = inOutWS->detectorTwoTheta(det);
const double factor = 4.0 * M_PI * sin(theta / 2.0);
const MantidVec &xIn = inOutWS->readX(i);
MantidVec &yIn = inOutWS->dataY(i);
const size_t xLength = xIn.size();
// for each wavelenght bin of each pixel calculate a q-resolution
for (size_t j = 0; j < xLength - 1; j++) {
// use the midpoint of each bin
const double wl = (xIn[j + 1] + xIn[j]) / 2.0;
// Calculate q. Alternatively q could be calculated using ConvertUnit
const double q = factor / wl;
// wavelenght spread from bin assumed to be
const double sigmaSpreadFromBin = xIn[j + 1] - xIn[j];
// wavelenght spread from moderatorm, converted from microseconds to
// wavelengths
const double sigmaModerator =
lookUpTable.value(wl) * 3.9560 / (1000.0 * Lsum);
// calculate wavelenght resolution from moderator and histogram time bin
const double sigmaLambda =
std::sqrt(sigmaSpreadFromBin * sigmaSpreadFromBin / 12.0 +
sigmaModerator * sigmaModerator);
// calculate sigmaQ for a given lambda and pixel
const double sigmaOverLambdaTimesQ = q * sigmaLambda / wl;
const double sigmaQ = std::sqrt(
dTheta2 / (wl * wl) + sigmaOverLambdaTimesQ * sigmaOverLambdaTimesQ);
// update inout workspace with this sigmaQ
yIn[j] = sigmaQ;
}
progress.report("Computing Q resolution");
}
}
