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Simon Heybrock authored
Pending targets: `AllTests`.
Simon Heybrock authoredPending targets: `AllTests`.
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MDNormSCD.cpp 29.21 KiB
#include "MantidMDAlgorithms/MDNormSCD.h"
#include "MantidAPI/CommonBinsValidator.h"
#include "MantidAPI/InstrumentValidator.h"
#include "MantidAPI/Run.h"
#include "MantidAPI/WorkspaceUnitValidator.h"
#include "MantidDataObjects/EventWorkspace.h"
#include "MantidDataObjects/MDEventWorkspace.h"
#include "MantidDataObjects/MDHistoWorkspace.h"
#include "MantidGeometry/Instrument.h"
#include "MantidKernel/CompositeValidator.h"
#include "MantidKernel/ConfigService.h"
#include "MantidKernel/TimeSeriesProperty.h"
#include "MantidKernel/VectorHelper.h"
namespace Mantid {
namespace MDAlgorithms {
using Mantid::Kernel::Direction;
using Mantid::API::WorkspaceProperty;
using namespace Mantid::DataObjects;
using namespace Mantid::API;
using namespace Mantid::Kernel;
namespace {
// function to compare two intersections (h,k,l,Momentum) by Momentum
bool compareMomentum(const Mantid::Kernel::VMD &v1,
const Mantid::Kernel::VMD &v2) {
return (v1[3] < v2[3]);
}
}
// Register the algorithm into the AlgorithmFactory
DECLARE_ALGORITHM(MDNormSCD)
/**
* Constructor
*/
MDNormSCD::MDNormSCD()
: m_normWS(), m_inputWS(), m_hmin(0.0f), m_hmax(0.0f), m_kmin(0.0f),
m_kmax(0.0f), m_lmin(0.0f), m_lmax(0.0f), m_hIntegrated(true),
m_kIntegrated(true), m_lIntegrated(true), m_rubw(3, 3), m_kiMin(0.0),
m_kiMax(EMPTY_DBL()), m_hIdx(-1), m_kIdx(-1), m_lIdx(-1), m_hX(), m_kX(),
m_lX(), m_samplePos(), m_beamDir() {}
/// Algorithm's version for identification. @see Algorithm::version
int MDNormSCD::version() const { return 1; }
/// Algorithm's category for identification. @see Algorithm::category
const std::string MDNormSCD::category() const {
return "MDAlgorithms\\Normalisation";
}
/// Algorithm's summary for use in the GUI and help. @see Algorithm::summary
const std::string MDNormSCD::summary() const {
return "Calculate normalization for an MDEvent workspace for single crystal "
"diffraction.";
}
/// Algorithm's name for use in the GUI and help. @see Algorithm::name
const std::string MDNormSCD::name() const { return "MDNormSCD"; }
/**
* Initialize the algorithm's properties.
*/
void MDNormSCD::init() {
declareProperty(make_unique<WorkspaceProperty<IMDEventWorkspace>>(
"InputWorkspace", "", Direction::Input),
"An input MDWorkspace.");
std::string dimChars = getDimensionChars();
// --------------- Axis-aligned properties
// ---------------------------------------
for (size_t i = 0; i < dimChars.size(); i++) {
std::string dim(" ");
dim[0] = dimChars[i];
std::string propName = "AlignedDim" + dim;
declareProperty(
Kernel::make_unique<PropertyWithValue<std::string>>(propName, "",
Direction::Input),
"Binning parameters for the " + Strings::toString(i) +
"th dimension.\n"
"Enter it as a comma-separated list of values with the format: "
"'name,minimum,maximum,number_of_bins'. Leave blank for NONE.");
}
auto fluxValidator = boost::make_shared<CompositeValidator>();
fluxValidator->add<WorkspaceUnitValidator>("Momentum");
fluxValidator->add<InstrumentValidator>();
fluxValidator->add<CommonBinsValidator>();
auto solidAngleValidator = fluxValidator->clone();
declareProperty(make_unique<WorkspaceProperty<>>(
"FluxWorkspace", "", Direction::Input, fluxValidator),
"An input workspace containing momentum dependent flux.");
declareProperty(make_unique<WorkspaceProperty<>>("SolidAngleWorkspace", "",
Direction::Input,
solidAngleValidator),
"An input workspace containing momentum integrated vanadium "
"(a measure of the solid angle).");
declareProperty(make_unique<WorkspaceProperty<Workspace>>(
"OutputWorkspace", "", Direction::Output),
"A name for the output data MDHistoWorkspace.");
declareProperty(make_unique<WorkspaceProperty<Workspace>>(
"OutputNormalizationWorkspace", "", Direction::Output),
"A name for the output normalization MDHistoWorkspace.");
}
/**
* Execute the algorithm.
*/
void MDNormSCD::exec() {
cacheInputs();
auto outputWS = binInputWS();
convention = Kernel::ConfigService::Instance().getString("Q.convention");
setProperty<Workspace_sptr>("OutputWorkspace", outputWS);
createNormalizationWS(*outputWS);
setProperty("OutputNormalizationWorkspace", m_normWS);
// Check for other dimensions if we could measure anything in the original
// data
bool skipNormalization = false;
const std::vector<coord_t> otherValues =
getValuesFromOtherDimensions(skipNormalization);
const auto affineTrans =
findIntergratedDimensions(otherValues, skipNormalization);
cacheDimensionXValues();
if (!skipNormalization) {
calculateNormalization(otherValues, affineTrans);
} else {
g_log.warning("Binning limits are outside the limits of the MDWorkspace. "
"Not applying normalization.");
}
}
/**
* Set up starting values for cached variables
*/void MDNormSCD::cacheInputs() {
m_inputWS = getProperty("InputWorkspace");
if (inputEnergyMode() != "Elastic") {
throw std::invalid_argument("Invalid energy transfer mode. Algorithm "
"currently only supports elastic data.");
}
// Min/max dimension values
const auto hdim(m_inputWS->getDimension(0)), kdim(m_inputWS->getDimension(1)),
ldim(m_inputWS->getDimension(2));
m_hmin = hdim->getMinimum();
m_kmin = kdim->getMinimum();
m_lmin = ldim->getMinimum();
m_hmax = hdim->getMaximum();
m_kmax = kdim->getMaximum();
m_lmax = ldim->getMaximum();
const auto &exptInfoZero = *(m_inputWS->getExperimentInfo(0));
auto source = exptInfoZero.getInstrument()->getSource();
auto sample = exptInfoZero.getInstrument()->getSample();
if (source == nullptr || sample == nullptr) {
throw Kernel::Exception::InstrumentDefinitionError(
"Instrument not sufficiently defined: failed to get source and/or "
"sample");
}
m_samplePos = sample->getPos();
m_beamDir = m_samplePos - source->getPos();
m_beamDir.normalize();
}
/**
* Currently looks for the ConvertToMD algorithm in the history
* @return A string donating the energy transfer mode of the input workspace
*/
std::string MDNormSCD::inputEnergyMode() const {
const auto &hist = m_inputWS->getHistory();
const size_t nalgs = hist.size();
const auto &lastAlgorithm = hist.lastAlgorithm();
std::string emode;
if (lastAlgorithm->name() == "ConvertToMD") {
emode = lastAlgorithm->getPropertyValue("dEAnalysisMode");
} else if ((lastAlgorithm->name() == "Load" ||
hist.lastAlgorithm()->name() == "LoadMD") &&
hist.getAlgorithmHistory(nalgs - 2)->name() == "ConvertToMD") {
// get dEAnalysisMode
PropertyHistories histvec =
hist.getAlgorithmHistory(nalgs - 2)->getProperties();
for (auto &hist : histvec) {
if (hist->name() == "dEAnalysisMode") {
emode = hist->value();
break;
}
}
} else {
throw std::invalid_argument("The last algorithm in the history of the "
"input workspace is not ConvertToMD");
}
return emode;
}
/**
* Runs the BinMD algorithm on the input to provide the output workspace
* All slicing algorithm properties are passed along
* @return MDHistoWorkspace as a result of the binning
*/
MDHistoWorkspace_sptr MDNormSCD::binInputWS() {
const auto &props = getProperties();
IAlgorithm_sptr binMD = createChildAlgorithm("BinMD", 0.0, 0.3);
binMD->setPropertyValue("AxisAligned", "1");
for (auto prop : props) { const auto &propName = prop->name();
if (propName != "FluxWorkspace" && propName != "SolidAngleWorkspace" &&
propName != "OutputNormalizationWorkspace") {
binMD->setPropertyValue(propName, prop->value());
}
}
binMD->executeAsChildAlg();
Workspace_sptr outputWS = binMD->getProperty("OutputWorkspace");
return boost::dynamic_pointer_cast<MDHistoWorkspace>(outputWS);
}
/**
* Create & cached the normalization workspace
* @param dataWS The binned workspace that will be used for the data
*/
void MDNormSCD::createNormalizationWS(const MDHistoWorkspace &dataWS) {
// Copy the MDHisto workspace, and change signals and errors to 0.
m_normWS = dataWS.clone();
m_normWS->setTo(0., 0., 0.);
}
/**
* Retrieve logged values from non-HKL dimensions
* @param skipNormalization [InOut] Updated to false if any values are outside
* range measured by input workspace
* @return A vector of values from other dimensions to be include in normalized
* MD position calculation
*/
std::vector<coord_t>
MDNormSCD::getValuesFromOtherDimensions(bool &skipNormalization) const {
const auto &runZero = m_inputWS->getExperimentInfo(0)->run();
std::vector<coord_t> otherDimValues;
for (size_t i = 3; i < m_inputWS->getNumDims(); i++) {
const auto dimension = m_inputWS->getDimension(i);
float dimMin = static_cast<float>(dimension->getMinimum());
float dimMax = static_cast<float>(dimension->getMaximum());
auto *dimProp = dynamic_cast<Kernel::TimeSeriesProperty<double> *>(
runZero.getProperty(dimension->getName()));
if (dimProp) {
coord_t value = static_cast<coord_t>(dimProp->firstValue());
otherDimValues.push_back(value);
// in the original MD data no time was spent measuring between dimMin and
// dimMax
if (value < dimMin || value > dimMax) {
skipNormalization = true;
}
}
}
return otherDimValues;
}
/**
* Checks the normalization workspace against the indices of the original
* dimensions.
* If not found, the corresponding dimension is integrated
* @param otherDimValues Values from non-HKL dimensions
* @param skipNormalization [InOut] Sets the flag true if normalization values
* are outside of original inputs
* @return Affine trasform matrix
*/
Kernel::Matrix<coord_t>
MDNormSCD::findIntergratedDimensions(const std::vector<coord_t> &otherDimValues,
bool &skipNormalization) {
// Get indices of the original dimensions in the output workspace,
// and if not found, the corresponding dimension is integrated
Kernel::Matrix<coord_t> affineMat =
m_normWS->getTransformFromOriginal(0)->makeAffineMatrix();
const size_t nrm1 = affineMat.numRows() - 1; const size_t ncm1 = affineMat.numCols() - 1;
for (size_t row = 0; row < nrm1; row++) // affine matrix, ignore last row
{
const auto dimen = m_normWS->getDimension(row);
const auto dimMin(dimen->getMinimum()), dimMax(dimen->getMaximum());
if (affineMat[row][0] == 1.) {
m_hIntegrated = false;
m_hIdx = row;
if (m_hmin < dimMin)
m_hmin = dimMin;
if (m_hmax > dimMax)
m_hmax = dimMax;
if (m_hmin > dimMax || m_hmax < dimMin) {
skipNormalization = true;
}
}
if (affineMat[row][1] == 1.) {
m_kIntegrated = false;
m_kIdx = row;
if (m_kmin < dimMin)
m_kmin = dimMin;
if (m_kmax > dimMax)
m_kmax = dimMax;
if (m_kmin > dimMax || m_kmax < dimMin) {
skipNormalization = true;
}
}
if (affineMat[row][2] == 1.) {
m_lIntegrated = false;
m_lIdx = row;
if (m_lmin < dimMin)
m_lmin = dimMin;
if (m_lmax > dimMax)
m_lmax = dimMax;
if (m_lmin > dimMax || m_lmax < dimMin) {
skipNormalization = true;
}
}
for (size_t col = 3; col < ncm1; col++) // affine matrix, ignore last column
{
if (affineMat[row][col] == 1.) {
double val = otherDimValues.at(col - 3);
if (val > dimMax || val < dimMin) {
skipNormalization = true;
}
}
}
}
return affineMat;
}
/**
* Stores the X values from each H,K,L dimension as member variables
*/
void MDNormSCD::cacheDimensionXValues() {
if (!m_hIntegrated) {
auto &hDim = *m_normWS->getDimension(m_hIdx);
m_hX.resize(hDim.getNBins());
for (size_t i = 0; i < m_hX.size(); ++i) {
m_hX[i] = hDim.getX(i);
}
}
if (!m_kIntegrated) {
auto &kDim = *m_normWS->getDimension(m_kIdx);
m_kX.resize(kDim.getNBins());
for (size_t i = 0; i < m_kX.size(); ++i) {
m_kX[i] = kDim.getX(i);
} }
if (!m_lIntegrated) {
auto &lDim = *m_normWS->getDimension(m_lIdx);
m_lX.resize(lDim.getNBins());
for (size_t i = 0; i < m_lX.size(); ++i) {
m_lX[i] = lDim.getX(i);
}
}
}
/**
* Computed the normalization for the input workspace. Results are stored in
* m_normWS
* @param otherValues
* @param affineTrans
*/
void MDNormSCD::calculateNormalization(
const std::vector<coord_t> &otherValues,
const Kernel::Matrix<coord_t> &affineTrans) {
API::MatrixWorkspace_const_sptr integrFlux = getProperty("FluxWorkspace");
integrFlux->getXMinMax(m_kiMin, m_kiMax);
API::MatrixWorkspace_const_sptr solidAngleWS =
getProperty("SolidAngleWorkspace");
const auto &exptInfoZero = *(m_inputWS->getExperimentInfo(0));
typedef Kernel::PropertyWithValue<std::vector<double>> VectorDoubleProperty;
auto *rubwLog =
dynamic_cast<VectorDoubleProperty *>(exptInfoZero.getLog("RUBW_MATRIX"));
if (!rubwLog) {
throw std::runtime_error(
"Wokspace does not contain a log entry for the RUBW matrix."
"Cannot continue.");
} else {
Kernel::DblMatrix rubwValue(
(*rubwLog)()); // includes the 2*pi factor but not goniometer for now :)
m_rubw = exptInfoZero.run().getGoniometerMatrix() * rubwValue;
m_rubw.Invert();
}
const double protonCharge = exptInfoZero.run().getProtonCharge();
auto instrument = exptInfoZero.getInstrument();
std::vector<detid_t> detIDs = instrument->getDetectorIDs(true);
// Prune out those that are part of a group and simply leave the head of the
// group
detIDs = removeGroupedIDs(exptInfoZero, detIDs);
// Mappings
const int64_t ndets = static_cast<int64_t>(detIDs.size());
const detid2index_map fluxDetToIdx =
integrFlux->getDetectorIDToWorkspaceIndexMap();
const detid2index_map solidAngDetToIdx =
solidAngleWS->getDetectorIDToWorkspaceIndexMap();
auto prog = make_unique<API::Progress>(this, 0.3, 1.0, ndets);
PARALLEL_FOR_IF(Kernel::threadSafe(*integrFlux))
for (int64_t i = 0; i < ndets; i++) {
PARALLEL_START_INTERUPT_REGION
const auto detID = detIDs[i];
double theta(0.0), phi(0.0);
bool skip(false);
try {
auto spectrum = getThetaPhi(detID, exptInfoZero, theta, phi);
if (spectrum->isMonitor() || spectrum->isMasked())
continue;
} catch (
std::exception &) // detector might not exist or has no been included
// in grouping
{
skip = true; // Intel compiler has a problem with continue inside a catch // inside openmp...
}
if (skip)
continue;
// Intersections
auto intersections = calculateIntersections(theta, phi);
if (intersections.empty())
continue;
// get the flux spetrum number
size_t wsIdx = fluxDetToIdx.find(detID)->second;
// Get solid angle for this contribution
double solid =
solidAngleWS->readY(solidAngDetToIdx.find(detID)->second)[0] *
protonCharge;
// -- calculate integrals for the intersection --
// momentum values at intersections
auto intersectionsBegin = intersections.begin();
std::vector<double> xValues(intersections.size()),
yValues(intersections.size());
{
// copy momenta to xValues
auto x = xValues.begin();
for (auto it = intersectionsBegin; it != intersections.end(); ++it, ++x) {
*x = (*it)[3];
}
}
// calculate integrals at momenta from xValues by interpolating between
// points in spectrum sp
// of workspace integrFlux. The result is stored in yValues
calcIntegralsForIntersections(xValues, *integrFlux, wsIdx, yValues);
// Compute final position in HKL
const size_t vmdDims = intersections.front().size();
// pre-allocate for efficiency and copy non-hkl dim values into place
std::vector<coord_t> pos(vmdDims + otherValues.size());
std::copy(otherValues.begin(), otherValues.end(),
pos.begin() + vmdDims - 1);
pos.push_back(1.);
for (auto it = intersectionsBegin + 1; it != intersections.end(); ++it) {
const auto &curIntSec = *it;
const auto &prevIntSec = *(it - 1);
// the full vector isn't used so compute only what is necessary
double delta = curIntSec[3] - prevIntSec[3];
if (delta < 1e-07)
continue; // Assume zero contribution if difference is small
// Average between two intersections for final position
std::transform(curIntSec.getBareArray(),
curIntSec.getBareArray() + vmdDims - 1,
prevIntSec.getBareArray(), pos.begin(),
VectorHelper::SimpleAverage<coord_t>());
std::vector<coord_t> posNew = affineTrans * pos;
size_t linIndex = m_normWS->getLinearIndexAtCoord(posNew.data());
if (linIndex == size_t(-1))
continue;
// index of the current intersection
size_t k = static_cast<size_t>(std::distance(intersectionsBegin, it));
// signal = integral between two consecutive intersections
double signal = (yValues[k] - yValues[k - 1]) * solid;
PARALLEL_CRITICAL(updateMD) {
signal += m_normWS->getSignalAt(linIndex);
m_normWS->setSignalAt(linIndex, signal);
}
} prog->report();
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
}
/**
* Linearly interpolate between the points in integrFlux at xValues and save the
* results in yValues.
* @param xValues :: X-values at which to interpolate
* @param integrFlux :: A workspace with the spectra to interpolate
* @param sp :: A workspace index for a spectrum in integrFlux to interpolate.
* @param yValues :: A vector to save the results.
*/
void MDNormSCD::calcIntegralsForIntersections(
const std::vector<double> &xValues, const API::MatrixWorkspace &integrFlux,
size_t sp, std::vector<double> &yValues) const {
assert(xValues.size() == yValues.size());
// the x-data from the workspace
const auto &xData = integrFlux.readX(sp);
const double xStart = xData.front();
const double xEnd = xData.back();
// the values in integrFlux are expected to be integrals of a non-negative
// function
// ie they must make a non-decreasing function
const auto &yData = integrFlux.readY(sp);
size_t spSize = yData.size();
const double yMin = 0.0;
const double yMax = yData.back();
size_t nData = xValues.size();
// all integrals below xStart must be 0
if (xValues[nData - 1] < xStart) {
std::fill(yValues.begin(), yValues.end(), yMin);
return;
}
// all integrals above xEnd must be equal tp yMax
if (xValues[0] > xEnd) {
std::fill(yValues.begin(), yValues.end(), yMax);
return;
}
size_t i = 0;
// integrals below xStart must be 0
while (i < nData - 1 && xValues[i] < xStart) {
yValues[i] = yMin;
i++;
}
size_t j = 0;
for (; i < nData; i++) {
// integrals above xEnd must be equal tp yMax
if (j >= spSize - 1) {
yValues[i] = yMax;
} else {
double xi = xValues[i];
while (j < spSize - 1 && xi > xData[j])
j++;
// if x falls onto an interpolation point return the corresponding y
if (xi == xData[j]) {
yValues[i] = yData[j];
} else if (j == spSize - 1) {
// if we get above xEnd it's yMax
yValues[i] = yMax;
} else if (j > 0) {
// interpolate between the consecutive points double x0 = xData[j - 1];
double x1 = xData[j];
double y0 = yData[j - 1];
double y1 = yData[j];
yValues[i] = y0 + (y1 - y0) * (xi - x0) / (x1 - x0);
} else // j == 0
{
yValues[i] = yMin;
}
}
}
}
/**
* Checks for IDs that are actually part of the same group and just keeps one
* from the group.
* For a 1:1 map, none will be removed.
* @param exptInfo An ExperimentInfo object that defines the grouping
* @param detIDs A list of existing IDs
* @return A new list of IDs
*/
std::vector<detid_t>
MDNormSCD::removeGroupedIDs(const ExperimentInfo &exptInfo,
const std::vector<detid_t> &detIDs) {
const size_t ntotal = detIDs.size();
std::vector<detid_t> singleIDs;
singleIDs.reserve(ntotal / 2); // reserve half. In the case of 1:1 it will
// double to the correct size once
std::set<detid_t> groupedIDs;
for (auto curID : detIDs) {
if (groupedIDs.count(curID) == 1)
continue; // Already been processed
try {
const auto &members = exptInfo.getGroupMembers(curID);
singleIDs.push_back(members.front());
std::copy(members.begin() + 1, members.end(),
std::inserter(groupedIDs, groupedIDs.begin()));
} catch (std::runtime_error &) {
singleIDs.push_back(curID);
}
}
g_log.debug() << "Found " << singleIDs.size() << " spectra from "
<< detIDs.size() << " IDs\n";
return singleIDs;
}
/**
* Get the theta and phi angles for the given ID. If the detector was part of a
* group,
* as defined in the ExperimentInfo object, then the theta/phi are for the whole
* set.
* @param detID A reference to a single ID
* @param exptInfo A reference to the ExperimentInfo that defines that
* spectrum->detector mapping
* @param theta [Output] Set to the theta angle for the detector (set)
* @param phi [Output] Set to the phi angle for the detector (set)
* @return A poiner to the Detector object for this spectrum as a whole
* (may be a single pixel or group)
*/
Geometry::IDetector_const_sptr
MDNormSCD::getThetaPhi(const detid_t detID, const ExperimentInfo &exptInfo,
double &theta, double &phi) {
const auto spectrum = exptInfo.getDetectorByID(detID);
theta = spectrum->getTwoTheta(m_samplePos, m_beamDir);
phi = spectrum->getPhi();
return spectrum;
}
/**
* Calculate the points of intersection for the given detector with cuboid
* surrounding the
* detector position in HKL
* @param theta Polar angle withd detector
* @param phi Azimuthal angle with detector
* @return A list of intersections in HKL space
*/
std::vector<Kernel::VMD> MDNormSCD::calculateIntersections(const double theta,
const double phi) {
V3D q(-sin(theta) * cos(phi), -sin(theta) * sin(phi), 1. - cos(theta));
q = m_rubw * q;
if (convention == "Crystallography") {
q *= -1;
}
double hStart = q.X() * m_kiMin, hEnd = q.X() * m_kiMax;
double kStart = q.Y() * m_kiMin, kEnd = q.Y() * m_kiMax;
double lStart = q.Z() * m_kiMin, lEnd = q.Z() * m_kiMax;
double eps = 1e-7;
auto hNBins = m_hX.size();
auto kNBins = m_kX.size();
auto lNBins = m_lX.size();
std::vector<Kernel::VMD> intersections;
intersections.reserve(hNBins + kNBins + lNBins + 8);
// calculate intersections with planes perpendicular to h
if (fabs(hStart - hEnd) > eps) {
double fmom = (m_kiMax - m_kiMin) / (hEnd - hStart);
double fk = (kEnd - kStart) / (hEnd - hStart);
double fl = (lEnd - lStart) / (hEnd - hStart);
if (!m_hIntegrated) {
for (size_t i = 0; i < hNBins; i++) {
double hi = m_hX[i];
if ((hi >= m_hmin) && (hi <= m_hmax) &&
((hStart - hi) * (hEnd - hi) < 0)) {
// if hi is between hStart and hEnd, then ki and li will be between
// kStart, kEnd and lStart, lEnd and momi will be between m_kiMin and
// KnincidemtmMax
double ki = fk * (hi - hStart) + kStart;
double li = fl * (hi - hStart) + lStart;
if ((ki >= m_kmin) && (ki <= m_kmax) && (li >= m_lmin) &&
(li <= m_lmax)) {
double momi = fmom * (hi - hStart) + m_kiMin;
Mantid::Kernel::VMD v(hi, ki, li, momi);
intersections.push_back(v);
}
}
}
}
double momhMin = fmom * (m_hmin - hStart) + m_kiMin;
if ((momhMin > m_kiMin) && (momhMin < m_kiMax)) {
// khmin and lhmin
double khmin = fk * (m_hmin - hStart) + kStart;
double lhmin = fl * (m_hmin - hStart) + lStart;
if ((khmin >= m_kmin) && (khmin <= m_kmax) && (lhmin >= m_lmin) &&
(lhmin <= m_lmax)) {
Mantid::Kernel::VMD v(m_hmin, khmin, lhmin, momhMin);
intersections.push_back(v);
}
}
double momhMax = fmom * (m_hmax - hStart) + m_kiMin;
if ((momhMax > m_kiMin) && (momhMax < m_kiMax)) {
// khmax and lhmax
double khmax = fk * (m_hmax - hStart) + kStart;
double lhmax = fl * (m_hmax - hStart) + lStart; if ((khmax >= m_kmin) && (khmax <= m_kmax) && (lhmax >= m_lmin) &&
(lhmax <= m_lmax)) {
Mantid::Kernel::VMD v(m_hmax, khmax, lhmax, momhMax);
intersections.push_back(v);
}
}
}
// calculate intersections with planes perpendicular to k
if (fabs(kStart - kEnd) > eps) {
double fmom = (m_kiMax - m_kiMin) / (kEnd - kStart);
double fh = (hEnd - hStart) / (kEnd - kStart);
double fl = (lEnd - lStart) / (kEnd - kStart);
if (!m_kIntegrated) {
for (size_t i = 0; i < kNBins; i++) {
double ki = m_kX[i];
if ((ki >= m_kmin) && (ki <= m_kmax) &&
((kStart - ki) * (kEnd - ki) < 0)) {
// if ki is between kStart and kEnd, then hi and li will be between
// hStart, hEnd and lStart, lEnd
double hi = fh * (ki - kStart) + hStart;
double li = fl * (ki - kStart) + lStart;
if ((hi >= m_hmin) && (hi <= m_hmax) && (li >= m_lmin) &&
(li <= m_lmax)) {
double momi = fmom * (ki - kStart) + m_kiMin;
Mantid::Kernel::VMD v(hi, ki, li, momi);
intersections.push_back(v);
}
}
}
}
double momkMin = fmom * (m_kmin - kStart) + m_kiMin;
if ((momkMin > m_kiMin) && (momkMin < m_kiMax)) {
// hkmin and lkmin
double hkmin = fh * (m_kmin - kStart) + hStart;
double lkmin = fl * (m_kmin - kStart) + lStart;
if ((hkmin >= m_hmin) && (hkmin <= m_hmax) && (lkmin >= m_lmin) &&
(lkmin <= m_lmax)) {
Mantid::Kernel::VMD v(hkmin, m_kmin, lkmin, momkMin);
intersections.push_back(v);
}
}
double momkMax = fmom * (m_kmax - kStart) + m_kiMin;
if ((momkMax > m_kiMin) && (momkMax < m_kiMax)) {
// hkmax and lkmax
double hkmax = fh * (m_kmax - kStart) + hStart;
double lkmax = fl * (m_kmax - kStart) + lStart;
if ((hkmax >= m_hmin) && (hkmax <= m_hmax) && (lkmax >= m_lmin) &&
(lkmax <= m_lmax)) {
Mantid::Kernel::VMD v(hkmax, m_kmax, lkmax, momkMax);
intersections.push_back(v);
}
}
}
// calculate intersections with planes perpendicular to l
if (fabs(lStart - lEnd) > eps) {
double fmom = (m_kiMax - m_kiMin) / (lEnd - lStart);
double fh = (hEnd - hStart) / (lEnd - lStart);
double fk = (kEnd - kStart) / (lEnd - lStart);
if (!m_lIntegrated) {
for (size_t i = 0; i < lNBins; i++) {
double li = m_lX[i];
if ((li >= m_lmin) && (li <= m_lmax) &&
((lStart - li) * (lEnd - li) < 0)) {
// if li is between lStart and lEnd, then hi and ki will be between
// hStart, hEnd and kStart, kEnd
double hi = fh * (li - lStart) + hStart;
double ki = fk * (li - lStart) + kStart; if ((hi >= m_hmin) && (hi <= m_hmax) && (ki >= m_kmin) &&
(ki <= m_kmax)) {
double momi = fmom * (li - lStart) + m_kiMin;
Mantid::Kernel::VMD v(hi, ki, li, momi);
intersections.push_back(v);
}
}
}
}
double momlMin = fmom * (m_lmin - lStart) + m_kiMin;
if ((momlMin > m_kiMin) && (momlMin < m_kiMax)) {
// hlmin and klmin
double hlmin = fh * (m_lmin - lStart) + hStart;
double klmin = fk * (m_lmin - lStart) + kStart;
if ((hlmin >= m_hmin) && (hlmin <= m_hmax) && (klmin >= m_kmin) &&
(klmin <= m_kmax)) {
Mantid::Kernel::VMD v(hlmin, klmin, m_lmin, momlMin);
intersections.push_back(v);
}
}
double momlMax = fmom * (m_lmax - lStart) + m_kiMin;
if ((momlMax > m_kiMin) && (momlMax < m_kiMax)) {
// khmax and lhmax
double hlmax = fh * (m_lmax - lStart) + hStart;
double klmax = fk * (m_lmax - lStart) + kStart;
if ((hlmax >= m_hmin) && (hlmax <= m_hmax) && (klmax >= m_kmin) &&
(klmax <= m_kmax)) {
Mantid::Kernel::VMD v(hlmax, klmax, m_lmax, momlMax);
intersections.push_back(v);
}
}
}
// add endpoints
if ((hStart >= m_hmin) && (hStart <= m_hmax) && (kStart >= m_kmin) &&
(kStart <= m_kmax) && (lStart >= m_lmin) && (lStart <= m_lmax)) {
Mantid::Kernel::VMD v(hStart, kStart, lStart, m_kiMin);
intersections.push_back(v);
}
if ((hEnd >= m_hmin) && (hEnd <= m_hmax) && (kEnd >= m_kmin) &&
(kEnd <= m_kmax) && (lEnd >= m_lmin) && (lEnd <= m_lmax)) {
Mantid::Kernel::VMD v(hEnd, kEnd, lEnd, m_kiMax);
intersections.push_back(v);
}
// sort intersections by momentum
typedef std::vector<Mantid::Kernel::VMD>::iterator IterType;
std::stable_sort<IterType, bool (*)(const Mantid::Kernel::VMD &,
const Mantid::Kernel::VMD &)>(
intersections.begin(), intersections.end(), compareMomentum);
return intersections;
}
} // namespace MDAlgorithms
} // namespace Mantid