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DiscusMultipleScatteringCorrection.cpp
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1// Mantid Repository : https://github.com/mantidproject/mantid
2//
3// Copyright © 2020 ISIS Rutherford Appleton Laboratory UKRI,
4// NScD Oak Ridge National Laboratory, European Spallation Source,
5// Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
6// SPDX - License - Identifier: GPL - 3.0 +
8#include "MantidAPI/Axis.h"
10#include "MantidAPI/ISpectrum.h"
13#include "MantidAPI/Sample.h"
36
37#include <boost/algorithm/string.hpp>
38
39using namespace Mantid::API;
40using namespace Mantid::Kernel;
43
44namespace {
45constexpr int DEFAULT_NPATHS = 1000;
46constexpr int DEFAULT_SEED = 123456789;
47constexpr int DEFAULT_NSCATTERINGS = 2;
48constexpr int DEFAULT_LATITUDINAL_DETS = 5;
49constexpr int DEFAULT_LONGITUDINAL_DETS = 10;
50
54inline double toWaveVector(double energy) { return sqrt(energy / PhysicalConstants::E_mev_toNeutronWavenumberSq); }
55
57inline double fromWaveVector(double wavevector) {
58 return PhysicalConstants::E_mev_toNeutronWavenumberSq * wavevector * wavevector;
59}
60
61struct EFixedProvider {
62 explicit EFixedProvider(const ExperimentInfo &expt) : m_expt(expt), m_emode(expt.getEMode()), m_EFixed(0.0) {
63 if (m_emode == DeltaEMode::Direct) {
64 m_EFixed = m_expt.getEFixed();
65 }
66 }
67 inline DeltaEMode::Type emode() const { return m_emode; }
68 inline double value(const Mantid::detid_t detID) const {
69 if (m_emode != DeltaEMode::Indirect)
70 return m_EFixed;
71 else
72 return m_expt.getEFixed(detID);
73 }
74
75private:
76 const ExperimentInfo &m_expt;
77 const DeltaEMode::Type m_emode;
78 double m_EFixed;
79};
80} // namespace
81
82namespace Mantid::Algorithms {
83
84std::unique_ptr<DiscusData2D> DiscusData2D::createCopy(bool clearY) {
85 auto data2DNew = std::make_unique<DiscusData2D>();
86 data2DNew->m_data.resize(m_data.size());
87 for (size_t i = 0; i < m_data.size(); i++) {
88 data2DNew->m_data[i].X = m_data[i].X;
89 data2DNew->m_data[i].Y = clearY ? std::vector<double>(m_data[i].Y.size(), 0.) : m_data[i].Y;
90 }
91 data2DNew->m_specAxis = m_specAxis;
92 return data2DNew;
93}
94
95const std::vector<double> &DiscusData2D::getSpecAxisValues() {
96 if (!m_specAxis)
97 throw std::runtime_error("DiscusData2D::getSpecAxisValues - No spec axis has been defined.");
98 return *m_specAxis;
99}
100
101// Register the algorithm into the AlgorithmFactory
103
104
108 // The input workspace must have an instrument
109 auto wsValidator = std::make_shared<InstrumentValidator>();
110
111 declareProperty(
112 std::make_unique<WorkspaceProperty<>>("InputWorkspace", "", Direction::Input, wsValidator),
113 "The name of the input workspace. The input workspace must have X units of Momentum (k) for elastic "
114 "calculations and units of energy transfer (DeltaE) for inelastic calculations. This is used to "
115 "supply the sample details, the detector positions and the x axis range to calculate corrections for");
116
117 declareProperty(std::make_unique<WorkspaceProperty<Workspace>>("StructureFactorWorkspace", "", Direction::Input),
118 "The name of the workspace containing S'(q) or S'(q, w). For elastic calculations, the input "
119 "workspace must contain a single spectrum and have X units of momentum transfer. A workspace group "
120 "containing one workspace per component can also be supplied if a calculation is being run on a "
121 "workspace with a sample environment specified");
122 declareProperty(std::make_unique<WorkspaceProperty<WorkspaceGroup>>("OutputWorkspace", "", Direction::Output),
123 "Name for the WorkspaceGroup that will be created. Each workspace in the "
124 "group contains a calculated weight for a particular number of "
125 "scattering events. The number of scattering events varies from 1 up to "
126 "the number supplied in the NumberOfScatterings parameter. The group "
127 "will also include an additional workspace for a calculation with a "
128 "single scattering event where the absorption post scattering has been "
129 "set to zero");
130 auto wsKValidator = std::make_shared<WorkspaceUnitValidator>("Momentum");
131 declareProperty(std::make_unique<WorkspaceProperty<>>("ScatteringCrossSection", "", Direction::Input,
132 PropertyMode::Optional, wsKValidator),
133 "A workspace containing the scattering cross section as a function of k, :math:`\\sigma_s(k)`. Note "
134 "- this parameter would normally be left empty which results in the tabulated cross section data "
135 "being used instead which implies no wavelength dependence");
136
137 auto positiveInt = std::make_shared<Kernel::BoundedValidator<int>>();
138 positiveInt->setLower(1);
139 declareProperty("NumberOfSimulationPoints", EMPTY_INT(), positiveInt,
140 "The number of points on the input workspace x axis for which a simulation is attempted");
141
142 declareProperty("NeutronPathsSingle", DEFAULT_NPATHS, positiveInt,
143 "The number of \"neutron\" paths to generate for single scattering");
144 declareProperty("NeutronPathsMultiple", DEFAULT_NPATHS, positiveInt,
145 "The number of \"neutron\" paths to generate for multiple scattering");
146 declareProperty("SeedValue", DEFAULT_SEED, positiveInt, "Seed the random number generator with this value");
147 auto nScatteringsValidator = std::make_shared<Kernel::BoundedValidator<int>>();
148 nScatteringsValidator->setLower(1);
149 nScatteringsValidator->setUpper(5);
150 declareProperty("NumberScatterings", DEFAULT_NSCATTERINGS, nScatteringsValidator, "Number of scatterings");
151
152 auto interpolateOpt = createInterpolateOption();
153 declareProperty(interpolateOpt->property(), interpolateOpt->propertyDoc());
154 declareProperty("SparseInstrument", false,
155 "Enable simulation on special "
156 "instrument with a sparse grid of "
157 "detectors interpolating the "
158 "results to the real instrument.");
159 auto threeOrMore = std::make_shared<Kernel::BoundedValidator<int>>();
160 threeOrMore->setLower(3);
161 declareProperty("NumberOfDetectorRows", DEFAULT_LATITUDINAL_DETS, threeOrMore,
162 "Number of detector rows in the detector grid of the sparse instrument.");
163 setPropertySettings("NumberOfDetectorRows",
164 std::make_unique<EnabledWhenProperty>("SparseInstrument", ePropertyCriterion::IS_NOT_DEFAULT));
165 auto twoOrMore = std::make_shared<Kernel::BoundedValidator<int>>();
166 twoOrMore->setLower(2);
167 declareProperty("NumberOfDetectorColumns", DEFAULT_LONGITUDINAL_DETS, twoOrMore,
168 "Number of detector columns in the detector grid "
169 "of the sparse instrument.");
170 setPropertySettings("NumberOfDetectorColumns",
171 std::make_unique<EnabledWhenProperty>("SparseInstrument", ePropertyCriterion::IS_NOT_DEFAULT));
172 declareProperty("ImportanceSampling", false,
173 "Enable importance sampling on the Q value chosen on multiple scatters based on Q.S(Q)");
174 // Control the number of attempts made to generate a random point in the object
175 declareProperty("MaxScatterPtAttempts", 5000, positiveInt,
176 "Maximum number of tries made to generate a scattering point "
177 "within the sample. Objects with holes in them, e.g. a thin "
178 "annulus can cause problems if this number is too low.\n"
179 "If a scattering point cannot be generated by increasing "
180 "this value then there is most likely a problem with "
181 "the sample geometry.");
182 declareProperty("SimulateEnergiesIndependently", false,
183 "For inelastic calculation, whether the results for adjacent energy transfer bins are simulated "
184 "separately. Currently applies to Direct geometry only");
185 declareProperty("NormalizeStructureFactors", false,
186 "Enable normalization of supplied structure factor(s). May be required when running a calculation "
187 "involving more than one material where the normalization of the default S(Q)=1 structure factor "
188 "doesn't match the normalization of a supplied non-isotropic structure factor");
189 declareProperty("RadialCollimator", false,
190 "Enable use of a radial collimator that assign zero weights to tracks where the final scatter "
191 "is not in a position that allows the final track segment to pass through the collimator corridor "
192 "which spans from the guage volume toward the each detector");
193}
194
199std::map<std::string, std::string> DiscusMultipleScatteringCorrection::validateInputs() {
200 std::map<std::string, std::string> issues;
201 MatrixWorkspace_sptr inputWS = getProperty("InputWorkspace");
202 if (inputWS == nullptr) {
203 // Mainly aimed at groups. Group ws pass the property validation on MatrixWorkspace type if all members are
204 // MatrixWorkspaces. We output a WorkspaceGroup for a single input workspace so can't manage input groups
205 issues["InputWorkspace"] = "Input workspace must be a matrix workspace";
206 return issues;
207 }
208 Geometry::IComponent_const_sptr sample = inputWS->getInstrument()->getSample();
209 if (!sample)
210 issues["InputWorkspace"] = "Input workspace does not have a Sample";
211
212 bool atLeastOneValidShape = inputWS->sample().getShape().hasValidShape();
213 if (!atLeastOneValidShape) {
214 if (inputWS->sample().hasEnvironment()) {
215 auto env = &inputWS->sample().getEnvironment();
216 for (size_t i = 0; i < env->nelements(); i++) {
217 if (env->getComponent(i).hasValidShape()) {
218 atLeastOneValidShape = true;
219 break;
220 }
221 }
222 }
223 }
224 if (!atLeastOneValidShape) {
225 issues["InputWorkspace"] = "Either the Sample or one of the environment parts must have a valid shape.";
226 }
227
228 if (inputWS->sample().getShape().hasValidShape())
229 if (inputWS->sample().getMaterial().numberDensity() == 0)
230 issues["InputWorkspace"] = "Sample must have a material set up with a non-zero number density\n";
231 if (inputWS->sample().hasEnvironment()) {
232 auto env = &inputWS->sample().getEnvironment();
233 for (size_t i = 0; i < env->nelements(); i++)
234 if (env->getComponent(i).hasValidShape())
235 if (env->getComponent(i).material().numberDensity() == 0)
236 issues["InputWorkspace"] = "Sample environment component " + std::to_string(i) +
237 " must have a material set up with a non-zero number density\n";
238 }
239
240 std::vector<MatrixWorkspace_sptr> SQWSs;
241 Workspace_sptr SQWSBase = getProperty("StructureFactorWorkspace");
242 auto SQWSGroup = std::dynamic_pointer_cast<WorkspaceGroup>(SQWSBase);
243 if (SQWSGroup) {
244 auto groupMembers = SQWSGroup->getAllItems();
245 std::set<std::string> materialNames;
246 materialNames.insert(inputWS->sample().getMaterial().name());
247 if (inputWS->sample().hasEnvironment()) {
248 auto nEnvComponents = inputWS->sample().getEnvironment().nelements();
249 for (size_t i = 0; i < nEnvComponents; i++)
250 materialNames.insert(inputWS->sample().getEnvironment().getComponent(i).material().name());
251 }
252
253 for (auto &materialName : materialNames) {
254 auto wsIt = std::find_if(groupMembers.begin(), groupMembers.end(),
255 [materialName](Workspace_sptr &ws) { return ws->getName() == materialName; });
256 if (wsIt == groupMembers.end()) {
257 issues["StructureFactorWorkspace"] =
258 "No workspace for material " + materialName + " found in S(Q,w) workspace group";
259 } else
260 SQWSs.push_back(std::dynamic_pointer_cast<MatrixWorkspace>(*wsIt));
261 }
262 } else
263 SQWSs.push_back(std::dynamic_pointer_cast<MatrixWorkspace>(SQWSBase));
264
265 if (inputWS->getEMode() == Kernel::DeltaEMode::Elastic) {
266 if (inputWS->getAxis(0)->unit()->unitID() != "Momentum")
267 issues["InputWorkspace"] += "Input workspace must have units of Momentum (k) for elastic instrument\n";
268 for (auto &SQWS : SQWSs) {
269 if (SQWS->getNumberHistograms() != 1)
270 issues["StructureFactorWorkspace"] += "S(Q) workspace must contain a single spectrum for elastic mode\n";
271
272 if (SQWS->getAxis(0)->unit()->unitID() != "MomentumTransfer")
273 issues["StructureFactorWorkspace"] += "S(Q) workspace must have units of MomentumTransfer\n";
274 }
275 } else {
276 for (auto &SQWS : SQWSs) {
277 if (inputWS->getAxis(0)->unit()->unitID() != "DeltaE")
278 issues["InputWorkspace"] = "Input workspace must have units of DeltaE for inelastic instrument\n";
279 std::set<std::string> axisUnits;
280 axisUnits.insert(SQWS->getAxis(0)->unit()->unitID());
281 axisUnits.insert(SQWS->getAxis(1)->unit()->unitID());
282 if (axisUnits != std::set<std::string>{"DeltaE", "MomentumTransfer"})
283 issues["StructureFactorWorkspace"] +=
284 "S(Q, w) workspace must have units of Energy Transfer and MomentumTransfer\n";
285
286 if (SQWS->getAxis(1)->isSpectra())
287 issues["StructureFactorWorkspace"] += "S(Q, w) must have a numeric spectrum axis\n";
288 std::vector<double> wValues;
289 if (SQWS->getAxis(0)->unit()->unitID() == "DeltaE") {
290 if (!SQWS->isCommonBins())
291 issues["StructureFactorWorkspace"] += "S(Q,w) must have common w values at all Q";
292 }
293
294 auto checkEqualQBins = [&issues](const MantidVec &qValues) {
295 Kernel::EqualBinsChecker checker(qValues, 1.0E-07, -1);
296 if (!checker.validate().empty())
297 issues["StructureFactorWorkspace"] +=
298 "S(Q,w) must have equal size bins in Q in order to support gaussian interpolation";
299 ;
300 };
301
302 if (SQWS->getAxis(0)->unit()->unitID() == "MomentumTransfer") {
303 for (size_t iHist = 0; iHist < SQWS->getNumberHistograms(); iHist++) {
304 auto qValues = SQWS->dataX(iHist);
305 checkEqualQBins(qValues);
306 }
307 } else if (SQWS->getAxis(1)->unit()->unitID() == "MomentumTransfer") {
308 auto qAxis = dynamic_cast<NumericAxis *>(SQWS->getAxis(1));
309 if (qAxis) {
310 auto qValues = qAxis->getValues();
311 checkEqualQBins(qValues);
312 }
313 }
314 }
315 }
316
317 for (auto &SQWS : SQWSs) {
318 for (size_t i = 0; i < SQWS->getNumberHistograms(); i++) {
319 auto &y = SQWS->y(i);
320 if (std::any_of(y.cbegin(), y.cend(), [](const auto yval) { return yval < 0 || std::isnan(yval); }))
321 issues["StructureFactorWorkspace"] += "S(Q) workspace must have all y >= 0";
322 }
323 }
324
325 const int nSimulationPoints = getProperty("NumberOfSimulationPoints");
326 if (!isEmpty(nSimulationPoints)) {
327 InterpolationOption interpOpt;
328 const std::string interpValue = getPropertyValue("Interpolation");
329 interpOpt.set(interpValue, false, false);
330 const auto nSimPointsIssue = interpOpt.validateInputSize(nSimulationPoints);
331 if (!nSimPointsIssue.empty())
332 issues["NumberOfSimulationPoints"] = nSimPointsIssue;
333 }
334
335 const bool simulateEnergiesIndependently = getProperty("SimulateEnergiesIndependently");
336 if (simulateEnergiesIndependently) {
337 if (inputWS->getEMode() == Kernel::DeltaEMode::Elastic)
338 issues["SimulateEnergiesIndependently"] =
339 "SimulateEnergiesIndependently is only applicable to inelastic direct geometry calculations";
340 if (inputWS->getEMode() == Kernel::DeltaEMode::Indirect)
341 issues["SimulateEnergiesIndependently"] =
342 "SimulateEnergiesIndependently is only applicable to inelastic direct geometry calculations. Different "
343 "energy transfer bins are always simulated separately for indirect geometry";
344 }
345
346 return issues;
347}
356 double &xmax) const {
357 // set to crazy values to start
358 xmin = std::numeric_limits<double>::max();
359 xmax = -1.0 * xmin;
360 size_t numberOfSpectra = ws.getNumberHistograms();
361 const auto &spectrumInfo = ws.spectrumInfo();
362
363 // determine the data range - only return min > 0. Bins with x=0 will be skipped later on
364 for (size_t wsIndex = 0; wsIndex < numberOfSpectra; wsIndex++) {
365 if (spectrumInfo.hasDetectors(wsIndex) && !spectrumInfo.isMonitor(wsIndex) && !spectrumInfo.isMasked(wsIndex)) {
366 const auto &dataX = ws.points(wsIndex);
367 const double xfront = dataX.front();
368 const double xback = dataX.back();
369 if (std::isnormal(xfront) && std::isnormal(xback)) {
370 if (xfront < xmin)
371 xmin = xfront;
372 if (xback > xmax)
373 xmax = xback;
374 }
375 }
376 }
377 if (xmin > xmax)
378 throw std::runtime_error("Unable to determine min and max x values for workspace");
379}
380
382 Workspace_sptr suppliedSQWS = getProperty("StructureFactorWorkspace");
383 auto SQWSGroup = std::dynamic_pointer_cast<WorkspaceGroup>(suppliedSQWS);
384 size_t nEnvComponents = 0;
385 if (m_env)
386 nEnvComponents = m_env->nelements();
387 m_SQWSs.clear();
388 if (SQWSGroup) {
389 std::string matName = m_sampleShape->material().name();
390 auto SQWSGroupMember = std::static_pointer_cast<MatrixWorkspace>(SQWSGroup->getItem(matName));
391 addWorkspaceToDiscus2DData(m_sampleShape, matName, SQWSGroupMember);
392 if (nEnvComponents > 0) {
393 matName = m_env->getContainer().material().name();
394 SQWSGroupMember = std::static_pointer_cast<MatrixWorkspace>(SQWSGroup->getItem(matName));
395 addWorkspaceToDiscus2DData(m_env->getContainer().getShapePtr(), matName, SQWSGroupMember);
396 }
397 for (size_t i = 1; i < nEnvComponents; i++) {
398 matName = m_env->getComponent(i).material().name();
399 SQWSGroupMember = std::static_pointer_cast<MatrixWorkspace>(SQWSGroup->getItem(matName));
400 addWorkspaceToDiscus2DData(m_env->getComponentPtr(i), matName, SQWSGroupMember);
401 }
402 } else {
404 std::dynamic_pointer_cast<MatrixWorkspace>(suppliedSQWS));
405 MatrixWorkspace_sptr isotropicSQ = DataObjects::create<Workspace2D>(
406 *std::dynamic_pointer_cast<MatrixWorkspace>(suppliedSQWS), static_cast<size_t>(1),
407 HistogramData::Histogram(HistogramData::Points{0.}, HistogramData::Frequencies{1.}));
408 if (nEnvComponents > 0) {
409 std::string_view matName = m_env->getContainer().material().name();
410 g_log.information() << "Creating isotropic structure factor for " << matName << std::endl;
411 addWorkspaceToDiscus2DData(m_env->getContainer().getShapePtr(), matName, isotropicSQ);
412 }
413 for (size_t i = 1; i < nEnvComponents; i++) {
414 std::string_view matName = m_env->getComponent(i).material().name();
415 g_log.information() << "Creating isotropic structure factor for " << matName << std::endl;
416 addWorkspaceToDiscus2DData(m_env->getComponentPtr(i), matName, isotropicSQ);
417 }
418 }
419}
420
426 const std::string_view &matName,
428 // avoid repeated conversion of bin edges to points inside loop by converting to point data
430 // if S(Q,w) has been supplied ensure Q is along the x axis of each spectrum (so same as S(Q))
431 if (SQWS->getAxis(1)->unit()->unitID() == "MomentumTransfer") {
432 auto transposeAlgorithm = this->createChildAlgorithm("Transpose");
433 transposeAlgorithm->initialize();
434 transposeAlgorithm->setProperty("InputWorkspace", SQWS);
435 transposeAlgorithm->setProperty("OutputWorkspace", "_");
436 transposeAlgorithm->execute();
437 SQWS = transposeAlgorithm->getProperty("OutputWorkspace");
438 } else if (SQWS->getAxis(1)->isSpectra()) {
439 // for elastic set w=0 on the spectrum axis to align code with inelastic
440 auto newAxis = std::make_unique<NumericAxis>(std::vector<double>{0.});
441 newAxis->setUnit("DeltaE");
442 SQWS->replaceAxis(1, std::move(newAxis));
443 }
444 auto specAxis = dynamic_cast<NumericAxis *>(SQWS->getAxis(1));
445 std::vector<DiscusData1D> data;
446 for (size_t i = 0; i < SQWS->getNumberHistograms(); i++) {
447 data.emplace_back(SQWS->x(i).rawData(), SQWS->y(i).rawData());
448 }
449 ComponentWorkspaceMapping SQWSMapping{
450 shape, matName,
451 std::make_shared<DiscusData2D>(data, std::make_shared<std::vector<double>>(specAxis->getValues()))};
452 SQWSMapping.logSQ = SQWSMapping.SQ->createCopy();
453 convertToLogWorkspace(SQWSMapping.logSQ);
454 m_SQWSs.push_back(SQWSMapping);
455}
456
463 if (ws->isHistogramData()) {
465 auto pointDataAlgorithm = this->createChildAlgorithm("ConvertToPointData");
466 pointDataAlgorithm->initialize();
467 pointDataAlgorithm->setProperty("InputWorkspace", ws);
468 pointDataAlgorithm->setProperty("OutputWorkspace", "_");
469 pointDataAlgorithm->execute();
470 ws = pointDataAlgorithm->getProperty("OutputWorkspace");
471 } else {
472 // flat interpolation is later used on S(Q) so convert to points by assigning Y value to LH bin edge
473 MatrixWorkspace_sptr SQWSPoints =
474 API::WorkspaceFactory::Instance().create(ws, ws->getNumberHistograms(), ws->blocksize(), ws->blocksize());
475 SQWSPoints->setSharedY(0, ws->sharedY(0));
476 SQWSPoints->setSharedE(0, ws->sharedE(0));
477 std::vector<double> newX = ws->histogram(0).dataX();
478 newX.pop_back();
479 SQWSPoints->setSharedX(0, HistogramData::Points(newX).cowData());
480 ws = SQWSPoints;
481 }
482 }
483 auto binAxis = dynamic_cast<BinEdgeAxis *>(ws->getAxis(1));
484 if (binAxis) {
485 auto edges = binAxis->getValues();
486 std::vector<double> centres;
487 VectorHelper::convertToBinCentre(edges, centres);
488 auto newAxis = std::make_unique<NumericAxis>(centres);
489 newAxis->setUnit(ws->getAxis(1)->unit()->unitID());
490 ws->replaceAxis(1, std::move(newAxis));
491 }
492}
493
498 if (!getAlwaysStoreInADS())
499 throw std::runtime_error("This algorithm explicitly stores named output workspaces in the ADS so must be run with "
500 "AlwaysStoreInADS set to true");
501 const MatrixWorkspace_sptr inputWS = getProperty("InputWorkspace");
502
506
507 MatrixWorkspace_sptr sigmaSSWS = getProperty("ScatteringCrossSection");
508 if (sigmaSSWS)
509 m_sigmaSS = std::make_shared<DiscusData1D>(sigmaSSWS->x(0).rawData(), sigmaSSWS->y(0).rawData());
510
511 // for inelastic we could calculate the qmax based on the min\max w in the S(Q,w) but that
512 // would bake as assumption that S(Q,w)=0 beyond the limits of the supplied data
513 double qmax = std::numeric_limits<float>::max();
514 EFixedProvider efixed(*inputWS);
515 m_EMode = efixed.emode();
516 g_log.information("EMode=" + DeltaEMode::asString(m_EMode) + " detected");
518 double kmin, kmax;
519 getXMinMax(*inputWS, kmin, kmax);
520 qmax = 2 * kmax;
521 }
522 prepareQSQ(qmax);
523
524 m_simulateEnergiesIndependently = getProperty("SimulateEnergiesIndependently");
525 // call this function with dummy efixed to determine total possible simulation points
526 const auto inputNbins = generateInputKOutputWList(-1.0, inputWS->points(0).rawData()).size();
527
528 int nSimulationPointsInt = getProperty("NumberOfSimulationPoints");
529 size_t nSimulationPoints = static_cast<size_t>(nSimulationPointsInt);
530
531 if (isEmpty(nSimulationPoints)) {
532 nSimulationPoints = inputNbins;
533 } else if (nSimulationPoints > inputNbins) {
534 g_log.warning() << "The requested number of simulation points is larger "
535 "than the maximum number of simulations per spectra. "
536 "Defaulting to "
537 << inputNbins << ".\n ";
538 nSimulationPoints = inputNbins;
539 }
540
541 m_NormalizeSQ = getProperty("NormalizeStructureFactors");
542
543 const bool useSparseInstrument = getProperty("SparseInstrument");
544 SparseWorkspace_sptr sparseWS;
545 if (useSparseInstrument) {
546 const int latitudinalDets = getProperty("NumberOfDetectorRows");
547 const int longitudinalDets = getProperty("NumberOfDetectorColumns");
548 sparseWS = createSparseWorkspace(*inputWS, nSimulationPoints, latitudinalDets, longitudinalDets);
549 }
550 const int nScatters = getProperty("NumberScatterings");
551 m_maxScatterPtAttempts = getProperty("MaxScatterPtAttempts");
552 std::vector<MatrixWorkspace_sptr> simulationWSs;
553 std::vector<MatrixWorkspace_sptr> outputWSs;
554
555 auto noAbsOutputWS = createOutputWorkspace(*inputWS);
556 auto noAbsSimulationWS = useSparseInstrument ? sparseWS->clone() : noAbsOutputWS;
557 for (int i = 0; i < nScatters; i++) {
558 auto outputWS = createOutputWorkspace(*inputWS);
559 MatrixWorkspace_sptr simulationWS = useSparseInstrument ? sparseWS->clone() : outputWS;
560 simulationWSs.emplace_back(simulationWS);
561 outputWSs.emplace_back(outputWS);
562 }
563 const MatrixWorkspace &instrumentWS = useSparseInstrument ? *sparseWS : *inputWS;
564 const auto nhists = useSparseInstrument ? sparseWS->getNumberHistograms() : inputWS->getNumberHistograms();
565
566 const int nSingleScatterEvents = getProperty("NeutronPathsSingle");
567 const int nMultiScatterEvents = getProperty("NeutronPathsMultiple");
568
569 const int seed = getProperty("SeedValue");
570
571 InterpolationOption interpolateOpt;
572 bool independentErrors = (m_EMode == DeltaEMode::Direct) ? m_simulateEnergiesIndependently : true;
573 interpolateOpt.set(getPropertyValue("Interpolation"), true, independentErrors);
574
575 m_importanceSampling = getProperty("ImportanceSampling");
576
577 // add one extra progress step per hist for the wavelength interpolation
578 Progress prog(this, 0.0, 1.0, nhists * (nSimulationPoints + 1));
579 prog.setNotifyStep(0.1);
580 const std::string reportMsg = "Computing corrections";
581
582 bool enableParallelFor = true;
583 enableParallelFor = std::all_of(simulationWSs.cbegin(), simulationWSs.cend(),
584 [](const MatrixWorkspace_sptr &ws) { return Kernel::threadSafe(*ws); });
585
586 enableParallelFor = enableParallelFor && Kernel::threadSafe(*noAbsOutputWS);
587
588 const auto &spectrumInfo = instrumentWS.spectrumInfo();
589 const auto &detectorInfo = instrumentWS.detectorInfo();
590
591 PARALLEL_FOR_IF(enableParallelFor)
592 for (int64_t i = 0; i < static_cast<int64_t>(nhists); ++i) { // signed int for openMP loop
594
595 auto &spectrum = instrumentWS.getSpectrum(i);
596 Mantid::specnum_t specNo = spectrum.getSpectrumNo();
597 MersenneTwister rng(seed + specNo);
598 // no two theta for monitors
599
600 if (spectrumInfo.hasDetectors(i) && !spectrumInfo.isMonitor(i) && !spectrumInfo.isMasked(i)) {
601
602 const double eFixedValue = efixed.value(spectrumInfo.detector(i).getID());
603 auto xPoints = instrumentWS.points(i).rawData();
604
605 auto kInW = generateInputKOutputWList(eFixedValue, xPoints);
606
607 const auto nbins = kInW.size();
608 // step size = index range / number of steps requested
609 const size_t nsteps = std::max(static_cast<size_t>(1), nSimulationPoints - 1);
610 const size_t xStepSize = nbins == 1 ? 1 : (nbins - 1) / nsteps;
611
612 // create copy of the SQ workspaces vector and fully copy any members that will be modified
613 auto componentWorkspaces = m_SQWSs;
614
616 // prep invPOfQ outside the bin loop to avoid costly construction\destruction
617 createInvPOfQWorkspaces(componentWorkspaces, 2);
618
619 std::vector<double> kValues;
620 std::transform(kInW.begin(), kInW.end(), std::back_inserter(kValues),
621 [](std::tuple<double, int, double> t) { return std::get<0>(t); });
622 calculateQSQIntegralAsFunctionOfK(componentWorkspaces, kValues);
623
624 for (size_t bin = 0; bin < nbins; bin += xStepSize) {
625 const double kinc = std::get<0>(kInW[bin]);
626 if ((kinc <= 0) || std::isnan(kinc)) {
627 g_log.warning("Skipping calculation for bin with invalid x, workspace index=" + std::to_string(i) +
628 " bin index=" + std::to_string(std::get<1>(kInW[bin])));
629 continue;
630 }
631 std::vector<double> wValues = std::get<1>(kInW[bin]) == -1 ? xPoints : std::vector{std::get<2>(kInW[bin])};
632
634 prepareCumulativeProbForQ(kinc, componentWorkspaces);
635
636 auto [weights, weightsErrors] =
637 simulatePaths(nSingleScatterEvents, 1, rng, componentWorkspaces, kinc, wValues, true, detectorInfo, i);
638 if (std::get<1>(kInW[bin]) == -1) {
639 noAbsSimulationWS->getSpectrum(i).mutableY() += weights;
640 noAbsSimulationWS->getSpectrum(i).mutableE() += weightsErrors;
641 } else {
642 noAbsSimulationWS->getSpectrum(i).mutableY()[std::get<1>(kInW[bin])] = weights[0];
643 noAbsSimulationWS->getSpectrum(i).mutableE()[std::get<1>(kInW[bin])] = weightsErrors[0];
644 }
645
646 for (int ne = 0; ne < nScatters; ne++) {
647 int nEvents = ne == 0 ? nSingleScatterEvents : nMultiScatterEvents;
648
649 std::tie(weights, weightsErrors) =
650 simulatePaths(nEvents, ne + 1, rng, componentWorkspaces, kinc, wValues, false, detectorInfo, i);
651 if (std::get<1>(kInW[bin]) == -1.0) {
652 simulationWSs[ne]->getSpectrum(i).mutableY() += weights;
653 simulationWSs[ne]->getSpectrum(i).mutableE() += weightsErrors;
654 } else {
655 simulationWSs[ne]->getSpectrum(i).mutableY()[std::get<1>(kInW[bin])] = weights[0];
656 simulationWSs[ne]->getSpectrum(i).mutableE()[std::get<1>(kInW[bin])] = weightsErrors[0];
657 }
658 }
659
660 prog.report(reportMsg);
661
662 // Ensure we have the last point for the interpolation
663 if (xStepSize > 1 && bin + xStepSize >= nbins && bin + 1 != nbins) {
664 bin = nbins - xStepSize - 1;
665 }
666 } // bins
667
668 // interpolate through points not simulated. Simulation WS only has
669 // reduced X values if using sparse instrument so no interpolation
670 // required
671 if (!useSparseInstrument && xStepSize > 1) {
672 auto histNoAbs = noAbsSimulationWS->histogram(i);
673 if (xStepSize < nbins) {
674 interpolateOpt.applyInplace(histNoAbs, xStepSize);
675 } else {
676 std::fill(histNoAbs.mutableY().begin() + 1, histNoAbs.mutableY().end(), histNoAbs.y()[0]);
677 }
678 noAbsOutputWS->setHistogram(i, histNoAbs);
679
680 for (size_t ne = 0; ne < static_cast<size_t>(nScatters); ne++) {
681 auto histnew = simulationWSs[ne]->histogram(i);
682 if (xStepSize < nbins) {
683 interpolateOpt.applyInplace(histnew, xStepSize);
684 } else {
685 std::fill(histnew.mutableY().begin() + 1, histnew.mutableY().end(), histnew.y()[0]);
686 }
687 outputWSs[ne]->setHistogram(i, histnew);
688 }
689 }
690 prog.report(reportMsg);
691 }
692
694 }
696
697 if (useSparseInstrument) {
698 Poco::Thread::sleep(200); // to ensure prog message changes
699 const std::string reportMsgSpatialInterpolation = "Spatial Interpolation";
700 prog.report(reportMsgSpatialInterpolation);
701 interpolateFromSparse(*noAbsOutputWS, *std::dynamic_pointer_cast<SparseWorkspace>(noAbsSimulationWS),
702 interpolateOpt);
703 for (size_t ne = 0; ne < static_cast<size_t>(nScatters); ne++) {
704 interpolateFromSparse(*outputWSs[ne], *std::dynamic_pointer_cast<SparseWorkspace>(simulationWSs[ne]),
705 interpolateOpt);
706 }
707 }
708
709 // Create workspace group that holds output workspaces
710 auto wsgroup = std::make_shared<WorkspaceGroup>();
711 auto outputGroupWSName = getPropertyValue("OutputWorkspace");
712 if (AnalysisDataService::Instance().doesExist(outputGroupWSName))
713 API::AnalysisDataService::Instance().deepRemoveGroup(outputGroupWSName);
714
715 const std::string wsNamePrefix = outputGroupWSName + "_Scatter_";
716 std::string wsName = wsNamePrefix + "1_NoAbs";
717 setWorkspaceName(noAbsOutputWS, wsName);
718 wsgroup->addWorkspace(noAbsOutputWS);
719
720 for (size_t i = 0; i < outputWSs.size(); i++) {
721 wsName = wsNamePrefix + std::to_string(i + 1);
722 setWorkspaceName(outputWSs[i], wsName);
723 wsgroup->addWorkspace(outputWSs[i]);
724
725 auto integratedWorkspace = integrateWS(outputWSs[i]);
726 setWorkspaceName(integratedWorkspace, wsName + "_Integrated");
727 wsgroup->addWorkspace(integratedWorkspace);
728 }
729
730 if (outputWSs.size() > 1) {
731 // create sum of multiple scatter workspaces for use in subtraction method
732 auto summedMScatOutput = createOutputWorkspace(*inputWS);
733 summedMScatOutput = std::accumulate(outputWSs.cbegin() + 1, outputWSs.cend(), summedMScatOutput);
734 wsName = wsNamePrefix + "2_" + std::to_string(outputWSs.size()) + "_Summed";
735 setWorkspaceName(summedMScatOutput, wsName);
736 wsgroup->addWorkspace(summedMScatOutput);
737 // create sum of all scattering order workspaces for use in ratio method
738 auto summedAllScatOutput = createOutputWorkspace(*inputWS);
739 summedAllScatOutput = summedMScatOutput + outputWSs[0];
740 wsName = wsNamePrefix + "1_" + std::to_string(outputWSs.size()) + "_Summed";
741 setWorkspaceName(summedAllScatOutput, wsName);
742 wsgroup->addWorkspace(summedAllScatOutput);
743 // create ratio of single to all scatter
744 auto ratioOutput = createOutputWorkspace(*inputWS);
745 ratioOutput = outputWSs[0] / summedAllScatOutput;
746 wsName = outputGroupWSName + "_Ratio_Single_To_All";
747 setWorkspaceName(ratioOutput, wsName);
748 wsgroup->addWorkspace(ratioOutput);
749
750 // ConvFit method being investigated by Spencer for inelastic currently uses the opposite ratio
752 auto invRatioOutput = 1 / ratioOutput;
753 auto replaceNans = this->createChildAlgorithm("ReplaceSpecialValues");
754 replaceNans->setChild(true);
755 replaceNans->initialize();
756 replaceNans->setProperty("InputWorkspace", invRatioOutput);
757 replaceNans->setProperty("OutputWorkspace", invRatioOutput);
758 replaceNans->setProperty("NaNValue", 0.0);
759 replaceNans->setProperty("InfinityValue", 0.0);
760 replaceNans->execute();
761 wsName = outputGroupWSName + "_Ratio_All_To_Single";
762 setWorkspaceName(invRatioOutput, wsName);
763 wsgroup->addWorkspace(invRatioOutput);
764 }
765 }
766
767 // set the output property
768 setProperty("OutputWorkspace", wsgroup);
769
770 if (g_log.is(Kernel::Logger::Priority::PRIO_INFORMATION)) {
771 g_log.information() << "Total simulation points=" << nhists * nSimulationPoints << "\n";
772 for (const auto &kv : m_attemptsToGenerateInitialTrack)
773 g_log.information() << "Generating initial track required " << kv.first << " attempts on " << kv.second
774 << " occasions.\n";
775 g_log.information() << "Calls to interceptSurface=" << m_callsToInterceptSurface << "\n";
776 g_log.information() << "Total I(k) calculations=" << m_IkCalculations << ", average per simulation point="
777 << static_cast<double>(m_IkCalculations) / static_cast<double>(nhists * nSimulationPoints)
778 << "\n";
779 if (g_log.is(Kernel::Logger::Priority::PRIO_DEBUG))
780 for (size_t i = 0; i < m_SQWSs.size(); i++)
781 g_log.information() << "Scatters in component " << i << ": " << *(m_SQWSs[i].scatterCount) << "\n";
782 }
783}
784
793std::vector<std::tuple<double, int, double>>
794DiscusMultipleScatteringCorrection::generateInputKOutputWList(const double efixed, const std::vector<double> &xPoints) {
795 std::vector<std::tuple<double, int, double>> kInW;
796 const double kFixed = toWaveVector(efixed);
798 int index = 0;
799 std::transform(xPoints.begin(), xPoints.end(), std::back_inserter(kInW), [&index](double d) {
800 auto t = std::make_tuple(d, index, 0.);
801 index++;
802 return t;
803 });
804 } else {
806 kInW.emplace_back(std::make_tuple(kFixed, -1, 0.));
807 else {
808 for (int i = 0; i < static_cast<int>(xPoints.size()); i++) {
810 kInW.emplace_back(std::make_tuple(kFixed, i, xPoints[i]));
811 else if (m_EMode == DeltaEMode::Indirect) {
812 const double initialE = efixed + xPoints[i];
813 if (initialE > 0) {
814 const double kin = toWaveVector(initialE);
815 kInW.emplace_back(std::make_tuple(kin, i, xPoints[i]));
816 } else
817 // negative kinc is filtered out later
818 kInW.emplace_back(std::make_tuple(-1.0, i, xPoints[i]));
819 }
820 }
821 }
822 }
823 return kInW;
824}
825
832 for (auto &SQWSMapping : m_SQWSs) {
833 auto &SQWS = SQWSMapping.SQ;
834 std::shared_ptr<DiscusData2D> outputWS = SQWS->createCopy(true);
835 std::vector<double> IOfQYFull;
836 // loop through the S(Q) spectra for the different energy transfer values
837 for (size_t iW = 0; iW < SQWS->getNumberHistograms(); iW++) {
838 std::vector<double> qValues = SQWS->histogram(iW).X;
839 std::vector<double> SQValues = SQWS->histogram(iW).Y;
840 // add terminating points at 0 and qmax before multiplying by Q so no extrapolation problems
841 if (qValues.front() > 0.) {
842 qValues.insert(qValues.begin(), 0.);
843 SQValues.insert(SQValues.begin(), SQValues.front());
844 }
845 if (qValues.back() < qmax) {
846 qValues.push_back(qmax);
847 SQValues.push_back(SQValues.back());
848 }
849 // add some extra points to help the Q.S(Q) integral get the right answer
850 for (size_t i = 1; i < qValues.size(); i++) {
851 if (std::abs(SQValues[i] - SQValues[i - 1]) >
852 std::numeric_limits<double>::epsilon() * std::min(SQValues[i - 1], SQValues[i])) {
853 qValues.insert(qValues.begin() + i, std::nextafter(qValues[i], -DBL_MAX));
854 SQValues.insert(SQValues.begin() + i, SQValues[i - 1]);
855 i++;
856 }
857 }
858
859 std::vector<double> QSQValues;
860 std::transform(SQValues.begin(), SQValues.end(), qValues.begin(), std::back_inserter(QSQValues),
861 std::multiplies<double>());
862
863 outputWS->histogram(iW).X.resize(qValues.size());
864 outputWS->histogram(iW).X = qValues;
865 outputWS->histogram(iW).Y.resize(QSQValues.size());
866 outputWS->histogram(iW).Y = QSQValues;
867 }
868 SQWSMapping.QSQ = outputWS;
869 }
870}
871
882std::tuple<std::vector<double>, std::vector<double>, std::vector<double>>
883DiscusMultipleScatteringCorrection::integrateQSQ(const std::shared_ptr<DiscusData2D> &QSQ, double kinc,
884 const bool returnCumulative) {
885 std::vector<double> IOfQYFull, qValuesFull, wIndices;
886 double IOfQMaxPreviousRow = 0.;
887
888 auto &wValues = QSQ->getSpecAxisValues();
889 std::vector<double> wWidths;
890 if (wValues.size() == 1) {
891 // convertToBinBoundary currently gives width of 1 for single point but because this is essential for the maths
892 // set the width to 1 explicitly
893 wWidths.push_back(1.);
894 } else {
895 std::vector<double> wBinEdges;
896 wBinEdges.reserve(wValues.size() + 1);
897 VectorHelper::convertToBinBoundary(wValues, wBinEdges);
898 std::adjacent_difference(wBinEdges.begin(), wBinEdges.end(), std::back_inserter(wWidths));
899 wWidths.erase(wWidths.begin()); // first element returned by adjacent_difference isn't a diff so delete it
900 }
901
902 double wMax = fromWaveVector(kinc);
903 auto it = std::lower_bound(wValues.begin(), wValues.end(), wMax);
904 size_t iFirstInaccessibleW = std::distance(wValues.begin(), it);
905 auto nAccessibleWPoints = iFirstInaccessibleW;
906
907 // loop through the S(Q) spectra for the different energy transfer values
908 std::vector<double> IOfQX, IOfQY;
909 // reserve minimum space required for performance
910 IOfQYFull.reserve(nAccessibleWPoints);
911 qValuesFull.reserve(nAccessibleWPoints);
912 wIndices.reserve(nAccessibleWPoints);
913 //}
914 for (size_t iW = 0; iW < nAccessibleWPoints; iW++) {
915 auto kf = getKf((wValues)[iW], kinc);
916 auto [qmin, qrange] = getKinematicRange(kf, kinc);
917 IOfQX.clear();
918 IOfQY.clear();
919 integrateCumulative(QSQ->histogram(iW), qmin, qmin + qrange, IOfQX, IOfQY, returnCumulative);
920 // w bin width for elastic will equal 1
921 double wBinWidth = wWidths[iW];
922 std::transform(IOfQY.begin(), IOfQY.end(), IOfQY.begin(),
923 [IOfQMaxPreviousRow, wBinWidth](double d) -> double { return d * wBinWidth + IOfQMaxPreviousRow; });
924 IOfQMaxPreviousRow = IOfQY.back();
925 IOfQYFull.insert(IOfQYFull.end(), IOfQY.begin(), IOfQY.end());
926 qValuesFull.insert(qValuesFull.end(), IOfQX.begin(), IOfQX.end());
927 wIndices.insert(wIndices.end(), IOfQX.size(), static_cast<double>(iW));
928 }
930 return {IOfQYFull, qValuesFull, wIndices};
931}
932
941 double kinc, const ComponentWorkspaceMappings &materialWorkspaces) {
942 for (size_t iMat = 0; iMat < materialWorkspaces.size(); iMat++) {
943 auto QSQ = materialWorkspaces[iMat].QSQ;
944 auto [IOfQYFull, qValuesFull, wIndices] = integrateQSQ(QSQ, kinc, true);
945 auto IOfQYAtQMax = IOfQYFull.empty() ? 0. : IOfQYFull.back();
946 if (IOfQYAtQMax == 0.)
947 throw std::runtime_error("Integral of Q * S(Q) is zero so can't generate probability distribution");
948 // normalise probability range to 0-1
949 std::vector<double> IOfQYNorm;
950 std::transform(IOfQYFull.begin(), IOfQYFull.end(), std::back_inserter(IOfQYNorm),
951 [IOfQYAtQMax](double d) -> double { return d / IOfQYAtQMax; });
952 // Store the normalized integral (= cumulative probability) on the x axis
953 // The y values in the two spectra store Q, w (or w index to be precise)
954 auto &InvPOfQ = materialWorkspaces[iMat].InvPOfQ;
955 for (size_t i = 0; i < InvPOfQ->getNumberHistograms(); i++) {
956 InvPOfQ->histogram(i).X.resize(IOfQYNorm.size());
957 InvPOfQ->histogram(i).X = IOfQYNorm;
958 }
959 InvPOfQ->histogram(0).Y.resize(qValuesFull.size());
960 InvPOfQ->histogram(0).Y = qValuesFull;
961 InvPOfQ->histogram(1).Y.resize(wIndices.size());
962 InvPOfQ->histogram(1).Y = wIndices;
963 }
964}
965
966void DiscusMultipleScatteringCorrection::convertToLogWorkspace(const std::shared_ptr<DiscusData2D> &SOfQ) {
967 // generate log of the structure factor to support gaussian interpolation
968
969 for (size_t i = 0; i < SOfQ->getNumberHistograms(); i++) {
970 auto &ySQ = SOfQ->histogram(i).Y;
971
972 std::transform(ySQ.begin(), ySQ.end(), ySQ.begin(), [](double d) -> double {
973 const double exp_that_gives_close_to_zero = -20.0;
974 if (d == 0.)
975 return exp_that_gives_close_to_zero;
976 else
977 return std::log(d);
978 });
979 }
980}
981
994 const std::vector<double> &specialKs) {
995 for (auto &SQWSMapping : matWSs) {
996 std::vector<double> finalkValues, QSQIntegrals;
998 // Optimize performance by doing cumulative integral first at each q in S(Q) and then calculate integral for each
999 // k by topping up those results
1000 double kMax = specialKs.back();
1001 std::vector<double> IOfQYFull, qValuesFull;
1002 std::tie(IOfQYFull, qValuesFull, std::ignore) = integrateQSQ(SQWSMapping.QSQ, kMax, true);
1003 for (auto k : specialKs) {
1004 auto qUpperLimit = 2 * k;
1005 auto iterPrevIntegral = std::upper_bound(qValuesFull.begin(), qValuesFull.end(), qUpperLimit) - 1;
1006 auto idxPrevIntegral = static_cast<size_t>(std::distance(qValuesFull.begin(), iterPrevIntegral));
1007 std::vector<double> ignoreVector, topUpIntegral;
1008 integrateCumulative(SQWSMapping.QSQ->histogram(0), *iterPrevIntegral, qUpperLimit, ignoreVector, topUpIntegral,
1009 false);
1010 double IOfQY = IOfQYFull[idxPrevIntegral] + topUpIntegral[0];
1011 if (IOfQY > 0) {
1012 double normalisedIntegral = IOfQY / (2 * k * k);
1013 finalkValues.push_back(k);
1014 QSQIntegrals.push_back(normalisedIntegral);
1015 }
1016 }
1017 } else {
1018 // Calculate the integral for a range of k values. Not massively important which k values but choose them here
1019 // based on the q points in the S(Q) profile and the initial k values incident on the sample
1020 std::set<double> kValues(specialKs.begin(), specialKs.end());
1021 const std::vector<double> &qValues = SQWSMapping.SQ->histogram(0).X;
1022 for (auto q : qValues) {
1023 if (q > 0)
1024 kValues.insert(q / 2);
1025 }
1026
1027 // add a few extra points beyond supplied q range to ensure capture asymptotic value of integral/2*k*k.
1028 // Useful when doing a flat interpolation on m_QSQIntegral during inelastic calculation where k not known up front
1029 double maxSuppliedQ = qValues.back();
1030 if (maxSuppliedQ > 0.) {
1031 kValues.insert(maxSuppliedQ);
1032 kValues.insert(2 * maxSuppliedQ);
1033 }
1034
1035 for (auto k : kValues) {
1036 std::vector<double> IOfQYFull;
1037 std::tie(IOfQYFull, std::ignore, std::ignore) = integrateQSQ(SQWSMapping.QSQ, k, false);
1038 auto IOfQYAtQMax = IOfQYFull.empty() ? 0. : IOfQYFull.back();
1039 // going to divide by this so storing zero results not useful - and don't want to interpolate a zero value
1040 // into a k region where the integral is actually non-zero
1041 if (IOfQYAtQMax > 0) {
1042 double normalisedIntegral = IOfQYAtQMax / (2 * k * k);
1043 finalkValues.push_back(k);
1044 QSQIntegrals.push_back(normalisedIntegral);
1045 }
1046 }
1047 }
1048 auto QSQScaleFactor = std::make_shared<DiscusData1D>(finalkValues, QSQIntegrals);
1049 SQWSMapping.QSQScaleFactor = QSQScaleFactor;
1050 }
1051}
1052
1068 const double xmax, std::vector<double> &resultX,
1069 std::vector<double> &resultY,
1070 const bool returnCumulative) {
1071 assert(h.X.size() == h.Y.size());
1072 const std::vector<double> &xValues = h.X;
1073 const std::vector<double> &yValues = h.Y;
1074
1075 // set the integral to zero at xmin
1076 if (returnCumulative) {
1077 resultX.emplace_back(xmin);
1078 resultY.emplace_back(0.);
1079 }
1080 double sum = 0;
1081
1082 // ensure there's a point at xmin
1083 if (xValues.front() > xmin)
1084 throw std::runtime_error("Distribution doesn't extend as far as lower integration limit, x=" +
1085 std::to_string(xmin));
1086 // ...and a terminating point. Q.S(Q) generally not flat so assuming flat extrapolation not v useful
1087 if (xValues.back() < xmax)
1088 throw std::runtime_error("Distribution doesn't extend as far as upper integration limit, x=" +
1089 std::to_string(xmax));
1090
1091 auto iter = std::upper_bound(xValues.cbegin(), xValues.cend(), xmin);
1092 auto iRight = static_cast<size_t>(std::distance(xValues.cbegin(), iter));
1093
1094 auto linearInterp = [&xValues, &yValues](const double x, const size_t lIndex, const size_t rIndex) -> double {
1095 return (yValues[lIndex] * (xValues[rIndex] - x) + yValues[rIndex] * (x - xValues[lIndex])) /
1096 (xValues[rIndex] - xValues[lIndex]);
1097 };
1098 double yToUse;
1099
1100 // deal with partial initial segments
1101 if (xmin > xValues[iRight - 1]) {
1102 if (xmax >= xValues[iRight]) {
1103 double interpY = linearInterp(xmin, iRight - 1, iRight);
1104 yToUse = 0.5 * (interpY + yValues[iRight]);
1105 sum += yToUse * (xValues[iRight] - xmin);
1106 if (returnCumulative) {
1107 resultX.push_back(xValues[iRight]);
1108 resultY.push_back(sum);
1109 }
1110 iRight++;
1111 } else {
1112 double interpY1 = linearInterp(xmin, iRight - 1, iRight);
1113 double interpY2 = linearInterp(xmax, iRight - 1, iRight);
1114 yToUse = 0.5 * (interpY1 + interpY2);
1115 sum += yToUse * (xmax - xmin);
1116 if (returnCumulative) {
1117 resultX.push_back(xmax);
1118 resultY.push_back(sum);
1119 }
1120 iRight++;
1121 }
1122 }
1123
1124 // integrate the intervals between each pair of points. Do this until right point is at end of vector or > xmax
1125 for (; iRight < xValues.size() && xValues[iRight] <= xmax; iRight++) {
1126 yToUse = 0.5 * (yValues[iRight - 1] + yValues[iRight]);
1127 double xLeft = xValues[iRight - 1];
1128 double xRight = xValues[iRight];
1129 sum += yToUse * (xRight - xLeft);
1130 if (returnCumulative) {
1131 if (xRight > std::nextafter(xLeft, DBL_MAX)) {
1132 resultX.emplace_back(xRight);
1133 resultY.emplace_back(sum);
1134 }
1135 }
1136 }
1137
1138 // integrate a partial final interval if xmax is between points
1139 if ((xmax > xValues[iRight - 1]) && (xmin <= xValues[iRight - 1])) {
1140 double interpY = linearInterp(xmax, iRight - 1, iRight);
1141 yToUse = 0.5 * (yValues[iRight - 1] + interpY);
1142 sum += yToUse * (xmax - xValues[iRight - 1]);
1143 if (returnCumulative) {
1144 resultX.emplace_back(xmax);
1145 resultY.emplace_back(sum);
1146 }
1147 }
1148 if (!returnCumulative) {
1149 resultX.emplace_back(xmax);
1150 resultY.emplace_back(sum);
1151 }
1152}
1153
1160 // don't call integrateCumulative function because want error calculation and support for bin edges
1161 auto integrateAlgorithm = this->createChildAlgorithm("Integration");
1162 integrateAlgorithm->initialize();
1163 integrateAlgorithm->setProperty("InputWorkspace", ws);
1164 integrateAlgorithm->setProperty("OutputWorkspace", "_");
1165 integrateAlgorithm->execute();
1166 MatrixWorkspace_sptr wsIntegrals = integrateAlgorithm->getProperty("OutputWorkspace");
1167 for (size_t i = 0; i < wsIntegrals->getNumberHistograms(); i++)
1168 wsIntegrals->setPoints(i, std::vector<double>{0.});
1169 return wsIntegrals;
1170}
1171
1182std::tuple<double, double> DiscusMultipleScatteringCorrection::new_vector(const Material &material, double k,
1183 bool specialSingleScatterCalc) {
1184 double scatteringXSection, absorbXsection;
1185 if (specialSingleScatterCalc) {
1186 absorbXsection = 0;
1187 } else {
1188 const double wavelength = 2 * M_PI / k;
1189 absorbXsection = material.absorbXSection(wavelength);
1190 }
1191 if (m_sigmaSS) {
1192 scatteringXSection = interpolateFlat(*m_sigmaSS, k);
1193 } else {
1194 scatteringXSection = material.totalScatterXSection();
1195 }
1196
1197 const auto sig_total = scatteringXSection + absorbXsection;
1198 return {sig_total, scatteringXSection};
1199}
1200
1208std::tuple<double, int>
1209DiscusMultipleScatteringCorrection::sampleQW(const std::shared_ptr<DiscusData2D> &CumulativeProb, double x) {
1210 return {interpolateSquareRoot(CumulativeProb->histogram(0), x),
1211 static_cast<int>(interpolateFlat(CumulativeProb->histogram(1), x))};
1212}
1213
1220 const auto &histx = histToInterpolate.X;
1221 const auto &histy = histToInterpolate.Y;
1222 assert(histToInterpolate.X.size() == histToInterpolate.Y.size());
1223 if (x > histx.back()) {
1224 return histy.back();
1225 }
1226 if (x < histx.front()) {
1227 return histy.front();
1228 }
1229 const auto iter = std::upper_bound(histx.cbegin(), histx.cend(), x);
1230 const auto idx = static_cast<size_t>(std::distance(histx.cbegin(), iter) - 1);
1231 const double x0 = histx[idx];
1232 const double x1 = histx[idx + 1];
1233 const double asq = (pow(histy[idx + 1], 2) - pow(histy[idx], 2)) / (x1 - x0);
1234 if (asq == 0.) {
1235 throw std::runtime_error("Cannot perform square root interpolation on supplied distribution");
1236 }
1237 const double b = x0 - pow(histy[idx], 2) / asq;
1238 return sqrt(asq * (x - b));
1239}
1240
1248 auto &xHisto = histToInterpolate.X;
1249 auto &yHisto = histToInterpolate.Y;
1250 if (x > xHisto.back()) {
1251 return yHisto.back();
1252 }
1253 if (x < xHisto.front()) {
1254 return yHisto.front();
1255 }
1256 // may be useful at some point to introduce a tolerance here in case x is just below a step change but seems to behave
1257 // OK for now
1258 auto iter = std::upper_bound(xHisto.cbegin(), xHisto.cend(), x);
1259 auto idx = static_cast<size_t>(std::distance(xHisto.cbegin(), iter) - 1);
1260 return yHisto[idx];
1261}
1262
1271 // could have written using points() method so it also worked on histogram data but found that the points
1272 // method was bottleneck on multithreaded code due to cow_ptr atomic_load
1273 assert(histToInterpolate.X.size() == histToInterpolate.Y.size());
1274 if (x > histToInterpolate.X.back()) {
1275 return exp(histToInterpolate.Y.back());
1276 }
1277 if (x < histToInterpolate.X.front()) {
1278 return exp(histToInterpolate.Y.front());
1279 }
1280 // assume log(cross section) is quadratic in k
1281 auto deltax = histToInterpolate.X[1] - histToInterpolate.X[0];
1282
1283 auto iter = std::upper_bound(histToInterpolate.X.cbegin(), histToInterpolate.X.cend(), x);
1284 auto idx = static_cast<size_t>(std::distance(histToInterpolate.X.cbegin(), iter) - 1);
1285
1286 // need at least two points to the right of the x value for the quadratic
1287 // interpolation to work
1288 auto ny = histToInterpolate.Y.size();
1289 if (ny < 3) {
1290 throw std::runtime_error("Need at least 3 y values to perform quadratic interpolation");
1291 }
1292 if (idx > ny - 3) {
1293 idx = ny - 3;
1294 }
1295 // this interpolation assumes the set of 3 bins\point have the same width
1296 // U=0 on point or bin edge to the left of where x lies
1297 const auto U = (x - histToInterpolate.X[idx]) / deltax;
1298 const auto &y = histToInterpolate.Y;
1299 const auto A = (y[idx] - 2 * y[idx + 1] + y[idx + 2]) / 2;
1300 const auto B = (-3 * y[idx] + 4 * y[idx + 1] - y[idx + 2]) / 2;
1301 const auto C = y[idx];
1302 return exp(A * U * U + B * U + C);
1303}
1304
1315 double w) {
1316 double SQ = 0.;
1317 int iW = -1;
1318 auto &wValues = SQWSMapping.SQ->getSpecAxisValues();
1319 if (wValues.size() == 1) {
1320 // don't use indexOfValue here because for single point it invents a bin width of +/-0.5
1321 if (w == (wValues)[0])
1322 iW = 0;
1323 } else
1324 try {
1325 // required w values will often equal the points in the S(Q,w) distribution so pick nearest value
1326 iW = static_cast<int>(Kernel::VectorHelper::indexOfValueFromCentersNoThrow(wValues, w));
1327 } catch (std::out_of_range &) {
1328 }
1329 if (iW >= 0) {
1331 // the square root interpolation used to look up Q, w in InvPOfQ is based on flat interpolation of S(Q) so use
1332 // same interpolation here for consistency
1333 SQ = interpolateFlat(SQWSMapping.SQ->histogram(iW), q);
1334 else
1335 SQ = interpolateGaussian(SQWSMapping.logSQ->histogram(iW), q);
1336 }
1337
1338 return SQ;
1339}
1340
1341GNU_DIAG_OFF("free-nonheap-object")
1342
1343
1361std::tuple<std::vector<double>, std::vector<double>> DiscusMultipleScatteringCorrection::simulatePaths(
1362 const int nPaths, const int nScatters, Kernel::PseudoRandomNumberGenerator &rng,
1363 const ComponentWorkspaceMappings &componentWorkspaces, const double kinc, const std::vector<double> &wValues,
1364 bool specialSingleScatterCalc, const Mantid::Geometry::DetectorInfo &detectorInfo, const size_t &histogramIndex) {
1365 // countZeroWeights for debugging and analysis of where importance sampling may help
1366 std::vector<int> countZeroWeights(wValues.size(), 0);
1367 std::vector<double> sumOfWeights(wValues.size(), 0.);
1368 std::vector<double> weightsMeans(wValues.size(), 0.), deltas(wValues.size(), 0.), weightsM2(wValues.size(), 0.),
1369 weightsErrors(wValues.size(), 0.);
1370
1371 for (int ie = 0; ie < nPaths; ie++) {
1372 auto [success, weights] = scatter(nScatters, rng, componentWorkspaces, kinc, wValues, specialSingleScatterCalc,
1373 detectorInfo, histogramIndex);
1374 if (success) {
1375 std::transform(weights.begin(), weights.end(), sumOfWeights.begin(), sumOfWeights.begin(), std::plus<double>());
1376 std::transform(weights.begin(), weights.end(), countZeroWeights.begin(), countZeroWeights.begin(),
1377 [](double d, int count) { return d > 0. ? count : count + 1; });
1378
1379 // increment standard deviation using Welford algorithm
1380 for (size_t i = 0; i < wValues.size(); i++) {
1381 deltas[i] = weights[i] - weightsMeans[i];
1382 weightsMeans[i] += deltas[i] / static_cast<double>(ie + 1);
1383 weightsM2[i] += deltas[i] * (weights[i] - weightsMeans[i]);
1384 // calculate sample SD (M2/n-1)
1385 // will give NaN for m_events=1, but that's correct
1386 weightsErrors[i] = sqrt(weightsM2[i] / static_cast<double>(ie));
1387 }
1388
1389 } else
1390 ie--;
1391 }
1392 for (size_t i = 0; i < wValues.size(); i++) {
1393 sumOfWeights[i] = sumOfWeights[i] / nPaths;
1394 weightsErrors[i] = weightsErrors[i] / sqrt(nPaths);
1395 }
1396
1397 return {sumOfWeights, weightsErrors};
1398}
1399
1400GNU_DIAG_ON("free-nonheap-object")
1401
1402
1420std::tuple<bool, std::vector<double>> DiscusMultipleScatteringCorrection::scatter(
1421 const int nScatters, Kernel::PseudoRandomNumberGenerator &rng,
1422 const ComponentWorkspaceMappings &componentWorkspaces, const double kinc, const std::vector<double> &wValues,
1423 bool specialSingleScatterCalc, const Mantid::Geometry::DetectorInfo &detectorInfo, const size_t &histogramIndex) {
1424
1425 double weight = 1;
1426
1427 auto track = start_point(rng);
1428 auto shapeObjectWithScatter =
1429 updateWeightAndPosition(track, weight, kinc, rng, specialSingleScatterCalc, componentWorkspaces);
1430 double scatteringXSection;
1431 std::tie(std::ignore, scatteringXSection) =
1432 new_vector(shapeObjectWithScatter->material(), kinc, specialSingleScatterCalc);
1433
1434 auto currentComponentWorkspaces = componentWorkspaces;
1435 double k = kinc;
1436 for (int iScat = 0; iScat < nScatters - 1; iScat++) {
1437 if ((k != kinc)) {
1438 if (m_importanceSampling) {
1439 auto newComponentWorkspaces = componentWorkspaces;
1440 for (auto &SQWSMapping : currentComponentWorkspaces)
1441 SQWSMapping.InvPOfQ = SQWSMapping.InvPOfQ->createCopy();
1442 prepareCumulativeProbForQ(k, newComponentWorkspaces);
1443 currentComponentWorkspaces = std::move(newComponentWorkspaces);
1444 }
1445 }
1446 auto trackStillAlive =
1447 q_dir(track, shapeObjectWithScatter, currentComponentWorkspaces, k, scatteringXSection, rng, weight);
1448 if (!trackStillAlive)
1449 return {true, std::vector<double>(wValues.size(), 0.)};
1450 int nlinks = m_sampleShape->interceptSurface(track);
1451 if (m_env) {
1452 nlinks += m_env->interceptSurfaces(track);
1453 m_callsToInterceptSurface += m_env->nelements();
1454 }
1455 m_callsToInterceptSurface++;
1456 if (nlinks == 0) {
1457 return {false, {0.}};
1458 }
1459 shapeObjectWithScatter =
1460 updateWeightAndPosition(track, weight, k, rng, specialSingleScatterCalc, componentWorkspaces);
1461 std::tie(std::ignore, scatteringXSection) =
1462 new_vector(shapeObjectWithScatter->material(), k, specialSingleScatterCalc);
1463 }
1464
1465 bool considerCollimator = getProperty("RadialCollimator");
1466 if (considerCollimator) {
1467 const auto &samplePos = detectorInfo.samplePosition();
1468 auto hexahedron = createCollimatorHexahedronShape(samplePos, detectorInfo, histogramIndex);
1469 // zero the paths if the final scatter point is not inside the collimatorCorridor shape or the collimator shape is
1470 // not as expected
1471 if ((!hexahedron) || (!hexahedron->isValid(track.startPoint())))
1472 return {true, std::vector<double>(wValues.size(), 0.)};
1473 }
1474
1475 const auto &detPos = detectorInfo.position(histogramIndex);
1476 Kernel::V3D directionToDetector = detPos - track.startPoint();
1477 Kernel::V3D prevDirection = track.direction();
1478 directionToDetector.normalize();
1479 track.reset(track.startPoint(), directionToDetector);
1480 int nlinks = m_sampleShape->interceptSurface(track);
1481 m_callsToInterceptSurface++;
1482 if (m_env) {
1483 nlinks += m_env->interceptSurfaces(track);
1484 m_callsToInterceptSurface += m_env->nelements();
1485 }
1486 // due to VALID_INTERCEPT_POINT_SHIFT some tracks that skim the surface
1487 // of a CSGObject sample may not generate valid tracks. Start over again
1488 // for this event
1489 if (nlinks == 0) {
1490 return {false, {0.}};
1491 }
1492 std::vector<double> weights;
1493 auto scatteringXSectionFull = shapeObjectWithScatter->material().totalScatterXSection();
1494 // Step through required overall energy transfer (w) values and work out what
1495 // w that means for the final scatter. There will be a single w value for elastic
1496 // Slightly different approach to original DISCUS code. It stepped through the w values
1497 // in the supplied S(Q,w) distribution and applied each one to the final scatter. If
1498 // this resulted in an overall w that equalled one of the required w values it was output.
1499 // That approach implicitly assumed S(Q,w)=0 where not specified and that no interpolation
1500 // on w would be needed - this may be what's required but seems possible it might not always be
1501 for (auto &w : wValues) {
1502 const double finalE = fromWaveVector(kinc) - w;
1503 if (finalE > 0) {
1504 const double kout = toWaveVector(finalE);
1505 const auto qVector = directionToDetector * kout - prevDirection * k;
1506 const double q = qVector.norm();
1507 const double finalW = fromWaveVector(k) - finalE;
1508 auto componentWSIt = findMatchingComponent(componentWorkspaces, shapeObjectWithScatter);
1509 auto &componentWSMapping = *componentWSIt; // to help debugging
1510 double SQ = Interpolate2D(componentWSMapping, q, finalW);
1511 scatteringXSection = m_NormalizeSQ ? scatteringXSection / interpolateFlat(*(componentWSMapping.QSQScaleFactor), k)
1512 : scatteringXSectionFull;
1513
1514 double AT2 = 1;
1515 for (auto it = track.cbegin(); it != track.cend(); it++) {
1516 double sigma_total;
1517 auto &materialPassingThrough = it->object->material();
1518 std::tie(sigma_total, std::ignore) = new_vector(materialPassingThrough, kout, specialSingleScatterCalc);
1519 double numberDensity = materialPassingThrough.numberDensityEffective();
1520 double vmu = 100 * numberDensity * sigma_total;
1521 if (specialSingleScatterCalc)
1522 vmu = 0;
1523 const double dl = it->distInsideObject;
1524 AT2 *= exp(-dl * vmu);
1525 }
1526 weights.emplace_back(weight * AT2 * SQ * scatteringXSection / (4 * M_PI));
1527 } else {
1528 weights.emplace_back(0.);
1529 }
1530 }
1531 return {true, weights};
1532}
1533
1534/*
1535 * Construct a hexahedron shape extending from the detector's front face across the collimator openning window toward
1536 the sample with a legth as twice the distance from sample to detector.
1537 */
1539 const Kernel::V3D &samplePos, const Mantid::Geometry::DetectorInfo &detectorInfo, const size_t &histogramIndex) {
1540 const auto shape = detectorInfo.detector(histogramIndex).shape();
1541 if (!shape || (shape->shape() != Mantid::Geometry::detail::ShapeInfo::GeometryShape::CUBOID)) {
1542 return nullptr;
1543 }
1544
1545 try {
1546 shape->shapeInfo();
1547 } catch (std::exception &) {
1548 return nullptr;
1549 }
1550
1551 const auto colCorridorShape = readFromCollimatorCorridorCache(histogramIndex);
1552 if (colCorridorShape) {
1553 return colCorridorShape;
1554 }
1555
1556 const auto &detectorId = detectorInfo.detector(histogramIndex).getID();
1557 const auto &detectorAbsolPos = detectorInfo.position(detectorInfo.indexOf(detectorId));
1558 const auto cuboidGeometry = shape->shapeInfo().cuboidGeometry();
1559
1560 // Positions of the detector's front face
1561 const auto &detLeftFrontBottomPos = detectorAbsolPos + cuboidGeometry.leftFrontBottom;
1562 const auto &detLeftFrontTopPos = detectorAbsolPos + cuboidGeometry.leftFrontTop;
1563 const auto &detRightFrontBottomPos = detectorAbsolPos + cuboidGeometry.rightFrontBottom;
1564 const auto detRightFrontTopPos = detLeftFrontTopPos + detRightFrontBottomPos - detLeftFrontBottomPos;
1565
1566 const auto detCentrePos =
1567 (detLeftFrontBottomPos + detLeftFrontTopPos + detRightFrontBottomPos + detRightFrontTopPos) / 4.0;
1568 const auto detTopMiddlePos = (detLeftFrontTopPos + detRightFrontTopPos) / 2.0;
1569
1570 // Sanity check to avoid dividing by zero
1571 if ((detRightFrontTopPos == detLeftFrontTopPos) || (detTopMiddlePos == detCentrePos) || (detCentrePos == samplePos)) {
1572 return nullptr;
1573 }
1574
1575 // Define the unit vectors needed for calculations
1576 const auto unitVecSampleToDet = Kernel::normalize(detCentrePos - samplePos);
1577 const auto unitVecLeftToRight = Kernel::normalize(
1578 V3D(-1.0 * unitVecSampleToDet.Z(), 0,
1579 -1.0 * unitVecSampleToDet.X())); // this is a vector normal to unitVecSampleToDet on XZ plane
1580
1581 const auto colOpenningLeftTopPos =
1582 (unitVecSampleToDet * m_collimatorInfo->m_innerRadius * cos(m_collimatorInfo->m_halfAngularExtent)) + samplePos +
1583 (m_collimatorInfo->m_axisVec * (m_collimatorInfo->m_plateHeight / 2.0)) -
1584 (unitVecLeftToRight * m_collimatorInfo->m_innerRadius * sin(m_collimatorInfo->m_halfAngularExtent));
1585 const auto colOpenningRightTopPos =
1586 (unitVecSampleToDet * m_collimatorInfo->m_innerRadius * cos(m_collimatorInfo->m_halfAngularExtent)) + samplePos +
1587 (m_collimatorInfo->m_axisVec * (m_collimatorInfo->m_plateHeight / 2.0)) +
1588 (unitVecLeftToRight * m_collimatorInfo->m_innerRadius * sin(m_collimatorInfo->m_halfAngularExtent));
1589 const auto colOpenningLeftBottomPos =
1590 (unitVecSampleToDet * m_collimatorInfo->m_innerRadius * cos(m_collimatorInfo->m_halfAngularExtent)) + samplePos -
1591 (m_collimatorInfo->m_axisVec * (m_collimatorInfo->m_plateHeight / 2.0)) -
1592 (unitVecLeftToRight * m_collimatorInfo->m_innerRadius * sin(m_collimatorInfo->m_halfAngularExtent));
1593 const auto colOpenningRightBottomPos =
1594 (unitVecSampleToDet * m_collimatorInfo->m_innerRadius * cos(m_collimatorInfo->m_halfAngularExtent)) + samplePos -
1595 (m_collimatorInfo->m_axisVec * (m_collimatorInfo->m_plateHeight / 2.0)) +
1596 (unitVecLeftToRight * m_collimatorInfo->m_innerRadius * sin(m_collimatorInfo->m_halfAngularExtent));
1597
1598 // Sanity check to avoid dividing by zero
1599 if ((colOpenningLeftTopPos == detLeftFrontTopPos) || (colOpenningLeftBottomPos == detLeftFrontBottomPos) ||
1600 (colOpenningRightTopPos == detRightFrontTopPos) || (colOpenningRightBottomPos == detRightFrontBottomPos)) {
1601 return nullptr;
1602 }
1603
1604 // Unit vectors along the sides of hexahedron shape
1605 const auto unitVecAlongLeftTopLeg = Kernel::normalize(colOpenningLeftTopPos - detLeftFrontTopPos);
1606 const auto unitVecAlongLeftBottomLeg = Kernel::normalize(colOpenningLeftBottomPos - detLeftFrontBottomPos);
1607 const auto unitVecAlongRightTopLeg = Kernel::normalize(colOpenningRightTopPos - detRightFrontTopPos);
1608 const auto unitVecAlongRightBottomLeg = Kernel::normalize(colOpenningRightBottomPos - detRightFrontBottomPos);
1609
1610 // Positions of the hexahedron extended towards the sample for each of its legs to have a length twice the lenght of
1611 // sample to detector
1612 double sampleCentreToDetDistance = (detCentrePos - samplePos).norm();
1613 const auto leftFrontBottomPoint = detRightFrontTopPos + unitVecAlongRightTopLeg * sampleCentreToDetDistance * 2.0;
1614 const auto hexaHedronLegsLenRatio =
1615 (leftFrontBottomPoint - detRightFrontTopPos).norm() / (colOpenningRightTopPos - detRightFrontTopPos).norm();
1616 const auto leftBackBottomPoint = detLeftFrontTopPos + unitVecAlongLeftTopLeg * hexaHedronLegsLenRatio *
1617 (colOpenningLeftTopPos - detLeftFrontTopPos).norm();
1618 const auto rightFrontBottomPoint =
1619 detRightFrontBottomPos +
1620 unitVecAlongRightBottomLeg * hexaHedronLegsLenRatio * (colOpenningRightBottomPos - detRightFrontBottomPos).norm();
1621 const auto rightBackBottomPoint =
1622 detLeftFrontBottomPos +
1623 unitVecAlongLeftBottomLeg * hexaHedronLegsLenRatio * (colOpenningLeftBottomPos - detLeftFrontBottomPos).norm();
1624 std::ostringstream xmlShapeStream;
1625 xmlShapeStream << "<hexahedron id=\"corridor-shape\" >"
1626 << "<left-back-bottom-point x=\"" << leftBackBottomPoint.X() << "\""
1627 << " y=\"" << leftBackBottomPoint.Y() << "\""
1628 << " z=\"" << leftBackBottomPoint.Z() << "\" />"
1629 << "<left-front-bottom-point x=\"" << leftFrontBottomPoint.X() << "\""
1630 << " y=\"" << leftFrontBottomPoint.Y() << "\""
1631 << " z=\"" << leftFrontBottomPoint.Z() << "\" />"
1632 << "<right-front-bottom-point x=\"" << rightFrontBottomPoint.X() << "\""
1633 << " y=\"" << rightFrontBottomPoint.Y() << "\""
1634 << " z=\"" << rightFrontBottomPoint.Z() << "\" />"
1635 << "<right-back-bottom-point x=\"" << rightBackBottomPoint.X() << "\""
1636 << " y=\"" << rightBackBottomPoint.Y() << "\""
1637 << " z=\"" << rightBackBottomPoint.Z() << "\" />"
1638 << "<left-back-top-point x=\"" << detLeftFrontTopPos.X() << "\""
1639 << " y=\"" << detLeftFrontTopPos.Y() << "\""
1640 << " z=\"" << detLeftFrontTopPos.Z() << "\" />"
1641 << "<left-front-top-point x=\"" << detRightFrontTopPos.X() << "\""
1642 << " y=\"" << detRightFrontTopPos.Y() << "\""
1643 << " z=\"" << detRightFrontTopPos.Z() << "\" />"
1644 << "<right-front-top-point x=\"" << detRightFrontBottomPos.X() << "\""
1645 << " y=\"" << detRightFrontBottomPos.Y() << "\""
1646 << " z=\"" << detRightFrontBottomPos.Z() << "\" />"
1647 << "<right-back-top-point x=\"" << detLeftFrontBottomPos.X() << "\""
1648 << " y=\"" << detLeftFrontBottomPos.Y() << "\""
1649 << " z=\"" << detLeftFrontBottomPos.Z() << "\" />"
1650 << "</hexahedron>";
1651 Geometry::ShapeFactory shapeMaker;
1652 const auto collimatorCorridorCsgObj = shapeMaker.createShape(xmlShapeStream.str());
1653 writeToCollimatorCorridorCache(histogramIndex, collimatorCorridorCsgObj);
1654 return collimatorCorridorCsgObj;
1655}
1656
1657const std::shared_ptr<Geometry::CSGObject>
1659 std::shared_lock<std::shared_mutex> guard(m_mutexCorridorCache);
1660 const auto itCollimatorCorridor = m_collimatorCorridorCache.find(histogramIndex);
1661 if (itCollimatorCorridor != m_collimatorCorridorCache.end()) {
1662 return itCollimatorCorridor->second;
1663 }
1664 return nullptr;
1665}
1666
1668 const std::size_t &histogramIndex, const std::shared_ptr<Geometry::CSGObject> &collimatorCorridorCsgObj) {
1669 std::unique_lock<std::shared_mutex> guard(m_mutexCorridorCache);
1670 m_collimatorCorridorCache[histogramIndex] = collimatorCorridorCsgObj;
1671}
1672
1674 m_collimatorCorridorCache.clear(); // Clear the cache for collimator corridor shapes
1675 const bool radialCollimator = getProperty("RadialCollimator");
1676 if (radialCollimator) {
1677 m_collimatorInfo = std::make_unique<CollimatorInfo>();
1678 // Collimator inner radius
1679 m_collimatorInfo->m_innerRadius = getDoubleParamFromIDF("col-radius");
1680 // Half of the angular extent of the collimator seen from the sample
1681 m_collimatorInfo->m_halfAngularExtent = 0.5 * getDoubleParamFromIDF("col-angular-extent");
1682 // Height of collimator plate
1683 m_collimatorInfo->m_plateHeight = getDoubleParamFromIDF("col-plate-height");
1684 m_collimatorInfo->m_axisVec = getV3DParamFromIDF("col-axis");
1685 }
1686}
1687
1689 if (!m_instrument->hasParameter(paramName)) {
1690 throw std::runtime_error("Cannot find parameter:" + paramName + " from instrument parameter file");
1691 }
1692 std::vector<double> val_vec = m_instrument->getNumberParameter(paramName, true);
1693 if (val_vec.empty()) {
1694 throw std::runtime_error("No value specified for:" + paramName + " in the instrument parameter file");
1695 }
1696
1697 return static_cast<double>(val_vec.front());
1698}
1699
1701 if (!m_instrument->hasParameter(paramName)) {
1702 throw std::runtime_error("Cannot find parameter:" + paramName + " from instrument parameter file");
1703 }
1704
1705 std::string paramValStr = m_instrument->getStringParameter(paramName)[0];
1706 std::vector<std::string> v3dStrComponent;
1707 boost::split(v3dStrComponent, paramValStr, boost::is_any_of(","));
1708 if (v3dStrComponent.size() != 3) {
1709 throw std::runtime_error("Invalid number of coordinates given for parameter:" + paramName +
1710 " in instrument parameter file");
1711 }
1712 std::vector<double> v3dComponents(3);
1713 std::transform(v3dStrComponent.begin(), v3dStrComponent.end(), v3dComponents.begin(),
1714 [](const std::string &str) -> double { return std::stod(str); });
1715
1716 return Kernel::V3D(v3dComponents[0], v3dComponents[1], v3dComponents[2]);
1717}
1718
1719double DiscusMultipleScatteringCorrection::getKf(const double deltaE, const double kinc) {
1720 double kf;
1721 if (deltaE == 0.) {
1722 kf = kinc; // avoid costly sqrt
1723 } else {
1724 // slightly concerned that rounding errors moving between k and E may mean we take the sqrt of
1725 // a negative number in here. deltaE was capped using a threshold calculated using fromWaveVector so
1726 // hopefully any rounding will affect fromWaveVector(kinc) in same direction
1727 kf = toWaveVector(fromWaveVector(kinc) - deltaE);
1728 assert(!std::isnan(kf));
1729 }
1730 return kf;
1731} // namespace Mantid::Algorithms
1732
1745std::tuple<double, double> DiscusMultipleScatteringCorrection::getKinematicRange(double kf, double ki) {
1746 const double qmin = abs(kf - ki);
1747 const double qrange = 2 * std::min(ki, kf);
1748 return {qmin, qrange};
1749}
1757std::tuple<double, double, int, double>
1759 Kernel::PseudoRandomNumberGenerator &rng, const double kinc) {
1760
1761 // in order to keep integration limits constant sample full range of w even if some not kinematically accessible
1762 // Note - Discus took different approach where it sampled q,w from kinematically accessible range only but it
1763 // only calculated for double scattering and easier to normalise in that case
1764 double wRange;
1765 /*
1766 // The rectangular integration region could be restricted further by limiting w range by calculating max possible w
1767 // TO DO: validate the results for this optimisation
1768 // the energy transfer must always be less than the positive value corresponding to energy going from ki to 0
1769 // Note - this is still the case for indirect because on a multiple scatter the kf isn't kfixed
1770 double wMax = fromWaveVector(kinc);
1771 // find largest w bin centre that is < wmax and then sample w up to the next bin edge
1772 auto it = std::lower_bound(wValues.begin(), wValues.end(), wMax);
1773 int iWMax = static_cast<int>(std::distance(wValues.begin(), it) - 1);*/
1774 int iW = 0;
1775 if (wValues.size() == 1) {
1776 iW = 0;
1777 wRange = 1;
1778 } else {
1779 std::vector<double> wBinEdges;
1780 wBinEdges.reserve(wValues.size() + 1);
1781 VectorHelper::convertToBinBoundary(wValues, wBinEdges);
1782 // w bins not necessarily equal so don't just sample w index
1783 wRange = /*std::min(wMax, wBinEdges[iWMax + 1])*/ wBinEdges.back() - wBinEdges.front();
1784 double w = wBinEdges.front() + rng.nextValue() * wRange;
1785 iW = static_cast<int>(Kernel::VectorHelper::indexOfValueFromCentersNoThrow(wValues, w));
1786 }
1787 double maxkf = toWaveVector(fromWaveVector(kinc) - wValues.front());
1788 double qRange = kinc + maxkf;
1789 double q = qRange * rng.nextValue();
1790 return {q, qRange, iW, wRange};
1791}
1792
1802 // the QSQIntegrals were divided by k^2 so in theory they should be ~flat
1803 return interpolateFlat(QSQScaleFactor, k) * 2 * k * k;
1804}
1805
1818 const ComponentWorkspaceMappings &componentWorkspaces, double &k,
1819 const double scatteringXSection,
1820 Kernel::PseudoRandomNumberGenerator &rng, double &weight) {
1821 const double kinc = k;
1822 double QQ;
1823 int iW;
1824 auto componentWSIt = findMatchingComponent(componentWorkspaces, shapePtr);
1826 std::tie(QQ, iW) = sampleQW(componentWSIt->InvPOfQ, rng.nextValue());
1827 k = getKf(componentWSIt->SQ->getSpecAxisValues()[iW], kinc);
1828 weight = weight * scatteringXSection;
1829 } else {
1830 double qrange, wRange;
1831 auto &wValues = componentWSIt->SQ->getSpecAxisValues();
1832 std::tie(QQ, qrange, iW, wRange) = sampleQWUniform(wValues, rng, kinc);
1833 // if w inaccessible return (ie treat as zero weight) rather than retry so that integration stays over full w
1834 // range
1835 if (fromWaveVector(kinc) - wValues[iW] <= 0)
1836 return false;
1837 k = getKf(wValues[iW], kinc);
1838 double SQ = interpolateGaussian(componentWSIt->logSQ->histogram(iW), QQ);
1839 // integrate over rectangular area of qw space
1840 weight = weight * scatteringXSection * SQ * QQ * qrange * wRange;
1841 if (SQ > 0) {
1842 double integralQSQ = getQSQIntegral(*componentWSIt->QSQScaleFactor, kinc);
1843 assert(integralQSQ != 0.);
1844 weight = weight / integralQSQ;
1845 } else
1846 return false;
1847 }
1848 // T = 2theta
1849 const double cosT = (kinc * kinc + k * k - QQ * QQ) / (2 * kinc * k);
1850 // if q not accessible return rather than retry so that integration stays over rectangular area
1851 if (std::abs(cosT) > 1.0)
1852 return false;
1853
1854 updateTrackDirection(track, cosT, rng.nextValue() * 2 * M_PI);
1855 return true;
1856}
1857
1865 const double phi) {
1866 const auto B3 = sqrt(1 - cosT * cosT);
1867 const auto B2 = cosT;
1868 // possible to do this using the Quat class instead??
1869 // Quat(const double _deg, const V3D &_axis);
1870 // Quat(acos(cosT)*180/M_PI,
1871 // Kernel::V3D(track.direction()[],track.direction()[],0))
1872
1873 // Rodrigues formula with final term equal to zero
1874 // v_rot = cosT * v + sinT(k x v)
1875 // with rotation axis k orthogonal to v
1876 // Define k by first creating two vectors orthogonal to v:
1877 // (vy, -vx, 0) by inspection
1878 // and then (-vz * vx, -vy * vz, vx * vx + vy * vy) as cross product
1879 // Then define k as combination of these:
1880 // sin(phi) * (vy, -vx, 0) + cos(phi) * (-vx * vz, -vy * vz, 1 - vz * vz)
1881 // ...with division by normalisation factor of sqrt(vx * vx + vy * vy)
1882 // Note: xyz convention here isn't the standard Mantid one. x=beam, z=up
1883 const auto vy = track.direction()[0];
1884 const auto vz = track.direction()[1];
1885 const auto vx = track.direction()[2];
1886 double UKX, UKY, UKZ;
1887 if (vz * vz < 1.0) {
1888 // calculate A2 from vx^2 + vy^2 rather than 1-vz^2 to reduce floating point rounding error when vz close to
1889 // 1
1890 auto A2 = sqrt(vx * vx + vy * vy);
1891 auto UQTZ = cos(phi) * A2;
1892 auto UQTX = -cos(phi) * vz * vx / A2 + sin(phi) * vy / A2;
1893 auto UQTY = -cos(phi) * vz * vy / A2 - sin(phi) * vx / A2;
1894 UKX = B2 * vx + B3 * UQTX;
1895 UKY = B2 * vy + B3 * UQTY;
1896 UKZ = B2 * vz + B3 * UQTZ;
1897 } else {
1898 // definition of phi in general formula is dependent on v. So may see phi "redefinition" as vx and vy tend
1899 // to zero and you move from general formula to this special case
1900 UKX = B3 * cos(phi);
1901 UKY = B3 * sin(phi);
1902 UKZ = B2 * vz;
1903 }
1904 track.reset(track.startPoint(), Kernel::V3D(UKY, UKZ, UKX));
1905}
1906
1915 for (int i = 0; i < m_maxScatterPtAttempts; i++) {
1916 auto t = generateInitialTrack(rng);
1917 int nlinks = m_sampleShape->interceptSurface(t);
1919 if (m_env) {
1920 nlinks += m_env->interceptSurfaces(t);
1922 }
1923 if (nlinks > 0) {
1924 if (i > 0) {
1925 if (g_log.is(Kernel::Logger::Priority::PRIO_WARNING)) {
1927 }
1928 }
1929 return t;
1930 }
1931 }
1932 throw std::runtime_error(
1933 "DiscusMultipleScatteringCorrection::start_point() - Unable to generate entry point into sample after " +
1934 std::to_string(m_maxScatterPtAttempts) + " attempts. Try increasing MaxScatterPtAttempts");
1935}
1936
1949 Geometry::Track &track, double &weight, const double k, Kernel::PseudoRandomNumberGenerator &rng,
1950 bool specialSingleScatterCalc, const ComponentWorkspaceMappings &componentWorkspaces) {
1951 double totalMuL = 0.;
1952 auto nlinks = track.count();
1953 // Set default size to 5 (same as in LineIntersectVisit.h)
1954 boost::container::small_vector<std::tuple<const Geometry::IObject *, double, double, double>, 5> geometryObjects;
1955 geometryObjects.reserve(nlinks);
1956 // loop through all the track segments calculating some useful quantities for later
1957 for (auto it = track.cbegin(); it != track.cend(); it++) {
1958 const double trackSegLength = it->distInsideObject;
1959 const auto geometryObj = it->object;
1960 double sigma_total;
1961 std::tie(sigma_total, std::ignore) = new_vector(geometryObj->material(), k, specialSingleScatterCalc);
1962 double vmu = 100 * geometryObj->material().numberDensityEffective() * sigma_total;
1963 double muL = trackSegLength * vmu;
1964 totalMuL += muL;
1965 // some overlap between the quantities stored here but since calculated them all may as well store them all
1966 geometryObjects.emplace_back(geometryObj, vmu, muL, sigma_total);
1967 }
1968
1969 // randomly sample distance travelled across a total muL and work out which component this sits in
1970 double b4Overall = (1.0 - exp(-totalMuL));
1971 double muL = -log(1 - rng.nextValue() * b4Overall);
1972 double vl = 0.;
1973 double newWeight = 0.;
1974 double prevExpTerms = 1.;
1975 std::tuple<const Geometry::IObject *, double, double, double> geometryObjectDetails;
1976 for (size_t i = 0; i < geometryObjects.size(); i++) {
1977 geometryObjectDetails = geometryObjects[i];
1978 auto muL_i = std::get<2>(geometryObjectDetails);
1979 auto vmu_i = std::get<1>(geometryObjectDetails);
1980 if (muL - muL_i > 0) {
1981 vl += muL_i / vmu_i;
1982 muL = muL - muL_i;
1983 prevExpTerms *= exp(-muL_i);
1984 } else {
1985 vl += muL / vmu_i;
1986 double b4 = (1.0 - exp(-muL_i)) * prevExpTerms;
1987 auto sigma_total = std::get<3>(geometryObjectDetails);
1988 newWeight = b4 / sigma_total;
1989 break;
1990 }
1991 }
1992 weight = weight * newWeight;
1993 // At the moment this doesn't cope if sample shape is concave eg if track has more than one segment inside the
1994 // sample with segment outside sample in between
1995 // Note - this clears the track intersections but the sample\environment shapes live on
1996 inc_xyz(track, vl);
1997 auto geometryObject = std::get<0>(geometryObjectDetails);
1998 if (g_log.is(Kernel::Logger::Priority::PRIO_DEBUG)) {
1999 auto componentIt = findMatchingComponent(componentWorkspaces, geometryObject);
2000 (*(componentIt->scatterCount))++;
2001 }
2002 return geometryObject;
2003}
2004
2012 // generate random point on front surface of sample bounding box
2013 // The change of variables from length to t1 means this still samples the points fairly in the integration
2014 // volume even in shapes like cylinders where the depth varies across xy
2015 auto neutron = m_beamProfile->generatePoint(rng, m_activeRegion);
2016 auto ptx = neutron.startPos.X();
2017 auto pty = neutron.startPos.Y();
2018
2019 auto ptOnBeamProfile = Kernel::V3D();
2020 ptOnBeamProfile[m_refframe->pointingHorizontal()] = ptx;
2021 ptOnBeamProfile[m_refframe->pointingUp()] = pty;
2022 ptOnBeamProfile[m_refframe->pointingAlongBeam()] = m_sourcePos[m_refframe->pointingAlongBeam()];
2023 auto toSample = Kernel::V3D();
2024 toSample[m_refframe->pointingAlongBeam()] = 1.;
2025 return Geometry::Track(ptOnBeamProfile, toSample);
2026}
2027
2036 Kernel::V3D position = track.front().entryPoint;
2037 Kernel::V3D direction = track.direction();
2038 const auto x = position[0] + vl * direction[0];
2039 const auto y = position[1] + vl * direction[1];
2040 const auto z = position[2] + vl * direction[2];
2041 const auto startPoint = V3D(x, y, z);
2043 track.reset(startPoint, track.direction());
2044}
2045
2055std::shared_ptr<SparseWorkspace>
2057 const size_t rows, const size_t columns) {
2058 auto sparseWS = std::make_shared<SparseWorkspace>(modelWS, nXPoints, rows, columns);
2059 return sparseWS;
2060}
2061
2063 for (auto &SQWSMapping : matWSs) {
2064 auto &QSQ = SQWSMapping.QSQ;
2065 size_t expectedMaxSize =
2066 std::accumulate(QSQ->histograms().cbegin(), QSQ->histograms().cend(), static_cast<size_t>(0),
2067 [](const size_t value, const DiscusData1D &histo) { return value + histo.Y.size(); });
2068 auto ws = std::make_shared<DiscusData2D>(std::vector<DiscusData1D>(nhists), nullptr);
2069 ws->histogram(0).X.reserve(expectedMaxSize);
2070 for (size_t i = 0; i < nhists; i++)
2071 ws->histogram(i).Y.reserve(expectedMaxSize);
2072 SQWSMapping.InvPOfQ = ws;
2073 }
2074}
2075
2077 MatrixWorkspace_uptr outputWS = DataObjects::create<Workspace2D>(inputWS);
2078 // The algorithm computes the signal values at bin centres so they should
2079 // be treated as a distribution
2080 outputWS->setDistribution(true);
2081 outputWS->setYUnit("");
2082 outputWS->setYUnitLabel("Scattered Weight");
2083 return outputWS;
2084}
2085
2092 auto interpolationOpt = std::make_unique<InterpolationOption>();
2093 return interpolationOpt;
2094}
2095
2097 MatrixWorkspace &targetWS, const SparseWorkspace &sparseWS,
2098 const Mantid::Algorithms::InterpolationOption &interpOpt) {
2099 const auto &spectrumInfo = targetWS.spectrumInfo();
2100 const auto refFrame = targetWS.getInstrument()->getReferenceFrame();
2101 PARALLEL_FOR_IF(Kernel::threadSafe(targetWS, sparseWS))
2102 for (int64_t i = 0; i < static_cast<decltype(i)>(spectrumInfo.size()); ++i) {
2104 if (spectrumInfo.hasDetectors(i) && !spectrumInfo.isMonitor(i)) {
2105 double lat, lon;
2106 std::tie(lat, lon) = spectrumInfo.geographicalAngles(i);
2107 const auto spatiallyInterpHisto = sparseWS.bilinearInterpolateFromDetectorGrid(lat, lon);
2108 if (spatiallyInterpHisto.size() > 1) {
2109 auto targetHisto = targetWS.histogram(i);
2110 interpOpt.applyInPlace(spatiallyInterpHisto, targetHisto);
2111 targetWS.setHistogram(i, targetHisto);
2112 } else {
2113 targetWS.mutableY(i) = spatiallyInterpHisto.y().front();
2114 }
2115 }
2117 }
2119}
2120
2128 bool noClash(false);
2129
2130 for (int i = 0; !noClash; ++i) {
2131 std::string wsIndex; // dont use an index if there is no other
2132 // workspace
2133 if (i > 0) {
2134 wsIndex = "_" + std::to_string(i);
2135 }
2136
2137 bool wsExists = AnalysisDataService::Instance().doesExist(wsName + wsIndex);
2138 if (!wsExists) {
2139 wsName += wsIndex;
2140 noClash = true;
2141 }
2142 }
2143}
2144
2153 API::AnalysisDataService::Instance().addOrReplace(wsName, ws);
2154}
2155
2164 const Geometry::IObject *shapeObjectWithScatter) {
2165 // Currently look up based on the raw pointer value. Did consider looking up based on something more human readable
2166 // such as the component id or name but this isn't guaranteed to be set and a string key may be longer than the
2167 // pointer which is probably 8 bytes
2168 auto componentWSIt = std::find_if(componentWorkspaces.begin(), componentWorkspaces.end(),
2169 [shapeObjectWithScatter](const ComponentWorkspaceMapping &SQWS) {
2170 return SQWS.ComponentPtr.get() == shapeObjectWithScatter;
2171 });
2172 assert(componentWSIt != componentWorkspaces.end());
2173 // can't return iterator because boost have moved vec_iterator into a different namespace post v1.65.1 so won't
2174 // build on all platforms
2175 return &(*componentWSIt);
2176}
2177
2179 m_sampleShape = inputWS->sample().getShapePtr();
2180 try {
2181 m_env = &inputWS->sample().getEnvironment();
2182 } catch (std::runtime_error &) {
2183 // swallow this as no defined environment from getEnvironment
2184 }
2185 // generate the bounding box before the multithreaded section
2186 m_activeRegion = m_sampleShape->getBoundingBox();
2187 if (m_env) {
2188 const auto &envBox = m_env->boundingBox();
2189 m_activeRegion.grow(envBox);
2190 }
2191 m_instrument = inputWS->getInstrument();
2193 m_refframe = m_instrument->getReferenceFrame();
2194 m_sourcePos = m_instrument->getSource()->getPos();
2195}
2196
2197} // namespace Mantid::Algorithms
#define DECLARE_ALGORITHM(classname)
Definition Algorithm.h:542
double value
The value of the point.
Definition FitMW.cpp:51
double energy
Definition GetAllEi.cpp:157
double position
Definition GetAllEi.cpp:154
std::map< DeltaEMode::Type, std::string > index
int count
counter
Definition Matrix.cpp:37
#define PARALLEL_START_INTERRUPT_REGION
Begins a block to skip processing is the algorithm has been interupted Note the end of the block if n...
#define PARALLEL_END_INTERRUPT_REGION
Ends a block to skip processing is the algorithm has been interupted Note the start of the block if n...
#define PARALLEL_FOR_IF(condition)
Empty definitions - to enable set your complier to enable openMP.
#define PARALLEL_CHECK_INTERRUPT_REGION
Adds a check after a Parallel region to see if it was interupted.
#define GNU_DIAG_ON(x)
#define GNU_DIAG_OFF(x)
This is a collection of macros for turning compiler warnings off in a controlled manner.
std::string getPropertyValue(const std::string &name) const override
Get the value of a property as a string.
TypedValue getProperty(const std::string &name) const override
Get the value of a property.
virtual std::shared_ptr< Algorithm > createChildAlgorithm(const std::string &name, const double startProgress=-1., const double endProgress=-1., const bool enableLogging=true, const int &version=-1)
Create a Child Algorithm.
Kernel::Logger & g_log
Definition Algorithm.h:423
bool getAlwaysStoreInADS() const override
Returns true if we always store in the AnalysisDataService.
static bool isEmpty(const NumT toCheck)
checks that the value was not set by users, uses the value in empty double/int.
Stores numeric values that are assumed to be bin edge values.
Definition BinEdgeAxis.h:20
This class is shared by a few Workspace types and holds information related to a particular experimen...
const SpectrumInfo & spectrumInfo() const
Return a reference to the SpectrumInfo object.
const Geometry::DetectorInfo & detectorInfo() const
Return a const reference to the DetectorInfo object.
Geometry::Instrument_const_sptr getInstrument() const
Returns the parameterized instrument.
specnum_t getSpectrumNo() const
Base MatrixWorkspace Abstract Class.
virtual ISpectrum & getSpectrum(const size_t index)=0
Return the underlying ISpectrum ptr at the given workspace index.
HistogramData::Points points(const size_t index) const
virtual std::size_t getNumberHistograms() const =0
Returns the number of histograms in the workspace.
void setHistogram(const size_t index, T &&...data) &
HistogramData::Histogram histogram(const size_t index) const
Returns the Histogram at the given workspace index.
HistogramData::HistogramY & mutableY(const size_t index) &
Class to represent a numeric axis of a workspace.
Definition NumericAxis.h:29
virtual const std::vector< double > & getValues() const
Return a const reference to the values.
Helper class for reporting progress from algorithms.
Definition Progress.h:25
A property class for workspaces.
static std::unique_ptr< IBeamProfile > createBeamProfile(const Geometry::Instrument &instrument, const API::Sample &sample)
std::shared_ptr< std::vector< double > > m_specAxis
std::unique_ptr< DiscusData2D > createCopy(bool clearY=false)
Calculates a multiple scattering correction Based on Muscat Fortran code provided by Spencer Howells.
void setWorkspaceName(const API::MatrixWorkspace_sptr &ws, std::string wsName)
Set the name on a workspace, adjusting for potential clashes in the ADS.
void addWorkspaceToDiscus2DData(const Geometry::IObject_const_sptr &shape, const std::string_view &matName, API::MatrixWorkspace_sptr ws)
Function to convert between a Matrix workspace and the internal simplified 2D data structure.
void convertWsBothAxesToPoints(API::MatrixWorkspace_sptr &ws)
Convert x axis of a workspace to points if it's bin edges.
void convertToLogWorkspace(const std::shared_ptr< DiscusData2D > &SOfQ)
void createInvPOfQWorkspaces(ComponentWorkspaceMappings &matWSs, size_t nhists)
std::tuple< double, double > getKinematicRange(double kf, double ki)
Get the range of q values accessible for a particular kinc and kf.
std::tuple< double, double, int, double > sampleQWUniform(const std::vector< double > &wValues, Kernel::PseudoRandomNumberGenerator &rng, const double kinc)
Sample the q and w value for a scattering event without importance sampling.
void updateTrackDirection(Geometry::Track &track, const double cosT, const double phi)
Update the track's direction following a scatter event given theta and phi angles.
std::vector< std::tuple< double, int, double > > generateInputKOutputWList(const double efixed, const std::vector< double > &xPoints)
Generate a list of the k and w points where calculation results are required.
std::tuple< double, double > new_vector(const Kernel::Material &material, double k, bool specialSingleScatterCalc)
Calculate a total cross section using a k-specific scattering cross section Note - a separate tabulat...
std::map< std::size_t, std::shared_ptr< Geometry::CSGObject > > m_collimatorCorridorCache
Geometry::Track generateInitialTrack(Kernel::PseudoRandomNumberGenerator &rng)
Generate an initial track starting at the source and entering the sample/sample environment at a rand...
std::tuple< double, int > sampleQW(const std::shared_ptr< DiscusData2D > &CumulativeProb, double x)
Use importance sampling to choose a Q and w value for the scatter.
std::map< std::string, std::string > validateInputs() override
Validate the input properties.
API::MatrixWorkspace_sptr integrateWS(const API::MatrixWorkspace_sptr &ws)
Create new workspace with y equal to integral across the bins.
const Geometry::IObject * updateWeightAndPosition(Geometry::Track &track, double &weight, const double k, Kernel::PseudoRandomNumberGenerator &rng, bool specialSingleScatterCalc, const ComponentWorkspaceMappings &componentWorkspaces)
update track start point and weight.
void integrateCumulative(const DiscusData1D &h, const double xmin, const double xmax, std::vector< double > &resultX, std::vector< double > &resultY, const bool returnCumulative)
Integrate a distribution between the supplied xmin and xmax values using trapezoid rule without any e...
void calculateQSQIntegralAsFunctionOfK(ComponentWorkspaceMappings &matWSs, const std::vector< double > &specialKs)
This is a generalised version of the normalisation done in the original Discus algorithm The original...
API::MatrixWorkspace_sptr createOutputWorkspace(const API::MatrixWorkspace &inputWS) const
virtual std::unique_ptr< InterpolationOption > createInterpolateOption()
Factory method to return an instance of the required InterpolationOption class.
double interpolateSquareRoot(const DiscusData1D &histToInterpolate, double x)
Interpolate function of the form y = a * sqrt(x - b) ie inverse of a quadratic Used to lookup value i...
bool q_dir(Geometry::Track &track, const Geometry::IObject *shapePtr, const ComponentWorkspaceMappings &invPOfQs, double &k, const double scatteringXSection, Kernel::PseudoRandomNumberGenerator &rng, double &weight)
Update track direction and weight as a result of a scatter.
void writeToCollimatorCorridorCache(const std::size_t &histogramIndex, const std::shared_ptr< Geometry::CSGObject > &collimatorCorridorCsgObj)
void prepareSampleBeamGeometry(const API::MatrixWorkspace_sptr &inputWS)
virtual std::shared_ptr< SparseWorkspace > createSparseWorkspace(const API::MatrixWorkspace &modelWS, const size_t nXPoints, const size_t rows, const size_t columns)
Factory method to return an instance of the required SparseInstrument class.
const std::shared_ptr< Geometry::CSGObject > readFromCollimatorCorridorCache(const std::size_t &histogramIndex)
void correctForWorkspaceNameClash(std::string &wsName)
Adjust workspace name in case of clash in the ADS.
const std::shared_ptr< Geometry::CSGObject > createCollimatorHexahedronShape(const Kernel::V3D &samplePos, const Mantid::Geometry::DetectorInfo &detectorInfo, const size_t &histogramIndex)
const ComponentWorkspaceMapping * findMatchingComponent(const ComponentWorkspaceMappings &componentWorkspaces, const Geometry::IObject *shapeObjectWithScatter)
Lookup a sample or sample environment component in the supplied list.
double interpolateGaussian(const DiscusData1D &histToInterpolate, double x)
Interpolate a value from a spectrum containing Gaussian peaks.
double Interpolate2D(const ComponentWorkspaceMapping &SQWSMapping, double q, double w)
Interpolate value on S(Q,w) surface given a Q and w.
Geometry::Track start_point(Kernel::PseudoRandomNumberGenerator &rng)
Repeatedly attempt to generate an initial track starting at the source and entering the sample at a r...
void inc_xyz(Geometry::Track &track, double vl)
Update the x, y, z position of the neutron (or dV volume element to integrate over).
std::tuple< std::vector< double >, std::vector< double > > simulatePaths(const int nEvents, const int nScatters, Kernel::PseudoRandomNumberGenerator &rng, const ComponentWorkspaceMappings &componentWorkspaces, const double kinc, const std::vector< double > &wValues, bool specialSingleScatterCalc, const Mantid::Geometry::DetectorInfo &detectorInfo, const size_t &histogramIndex)
Simulates a set of neutron paths through the sample to a specific detector position with each path co...
void prepareCumulativeProbForQ(double kinc, const ComponentWorkspaceMappings &PInvOfQs)
Calculate a cumulative probability distribution for use in importance sampling.
boost::container::small_vector< ComponentWorkspaceMapping, 5 > ComponentWorkspaceMappings
double getQSQIntegral(const DiscusData1D &QSQScaleFactor, double k)
This is a generalised version of the normalisation done in the original Discus algorithm The original...
void interpolateFromSparse(API::MatrixWorkspace &targetWS, const SparseWorkspace &sparseWS, const Mantid::Algorithms::InterpolationOption &interpOpt)
std::shared_ptr< const Geometry::ReferenceFrame > m_refframe
void prepareQSQ(double kinc)
Prepare a profile of Q*S(Q) that will later be used to calculate a cumulative probability distributio...
void getXMinMax(const Mantid::API::MatrixWorkspace &ws, double &xmin, double &xmax) const
This is a variation on the function MatrixWorkspace::getXMinMax with some additional logic eg if x va...
std::tuple< std::vector< double >, std::vector< double >, std::vector< double > > integrateQSQ(const std::shared_ptr< DiscusData2D > &QSQ, double kinc, const bool returnCumulative)
Integrate QSQ over Q and w over the kinematic range accessible for a given kinc.
double interpolateFlat(const DiscusData1D &histToInterpolate, double x)
Interpolate function using flat interpolation from previous point.
Class to provide a consistent interface to an interpolation option on algorithms.
std::string validateInputSize(const size_t size) const
Validate the size of input histogram.
void applyInPlace(const HistogramData::Histogram &in, HistogramData::Histogram &out) const
Apply the interpolation method to the output histogram.
void set(const Value &kind, const bool calculateErrors, const bool independentErrors)
Set the interpolation option.
void applyInplace(HistogramData::Histogram &inOut, size_t stepSize) const
Apply the interpolation method to the given histogram.
Defines functions and utilities to create and deal with sparse instruments.
virtual HistogramData::Histogram bilinearInterpolateFromDetectorGrid(const double lat, const double lon) const
Spatially interpolate a single histogram from nearby detectors using bilinear interpolation method.
Concrete workspace implementation.
Definition Workspace2D.h:29
void grow(const BoundingBox &other)
Grow the bounding box so that it also encompasses the given box.
const IObject_sptr getShapePtr() const
Definition Container.h:43
const Kernel::Material & material() const override
Definition Container.h:93
Geometry::DetectorInfo is an intermediate step towards a DetectorInfo that is part of Instrument-2....
Kernel::V3D position(const size_t index) const
Returns the position of the detector with given index.
const Geometry::IDetector & detector(const size_t index) const
Return a const reference to the detector with given index.
size_t indexOf(const detid_t id) const
Returns the index of the detector with the given detector ID.
virtual detid_t getID() const =0
Get the detector ID.
virtual const std::shared_ptr< const IObject > shape() const =0
Returns the shape of the Object.
IObject : Interface for geometry objects.
Definition IObject.h:42
virtual const Kernel::Material & material() const =0
const Container & getContainer() const
const IObject & getComponent(const size_t index) const
Returns the requested IObject.
Geometry::BoundingBox boundingBox() const
int interceptSurfaces(Track &track) const
Update the given track with intersections within the environment.
const IObject_const_sptr getComponentPtr(const size_t index) const
Class originally intended to be used with the DataHandling 'LoadInstrument' algorithm.
std::shared_ptr< CSGObject > createShape(Poco::XML::Element *pElem)
Creates a geometric object from a DOM-element-node pointing to an element whose child nodes contain t...
Defines a track as a start point and a direction.
Definition Track.h:165
LType::reference front()
Returns a reference to the first link.
Definition Track.h:211
const Kernel::V3D & startPoint() const
Returns the starting point.
Definition Track.h:191
void clearIntersectionResults()
Clear the current set of intersection results.
Definition Track.cpp:55
int count() const
Returns the number of links.
Definition Track.h:219
const Kernel::V3D & direction() const
Returns the direction as a unit vector.
Definition Track.h:193
LType::const_iterator cbegin() const
Returns an interator to the start of the set of links (const version)
Definition Track.h:206
LType::const_iterator cend() const
Returns an interator to one-past-the-end of the set of links (const version)
Definition Track.h:209
void reset(const Kernel::V3D &startPoint, const Kernel::V3D &direction)
Set a starting point and direction.
Definition Track.cpp:45
EqualBinsChecker : Checks for evenly spaced bins.
virtual std::string validate() const
Perform validation of the given X array.
IPropertyManager * setProperty(const std::string &name, const T &value)
Templated method to set the value of a PropertyWithValue.
void warning(const std::string &msg)
Logs at warning level.
Definition Logger.cpp:117
bool is(int level) const
Returns true if at least the given log level is set.
Definition Logger.cpp:177
void information(const std::string &msg)
Logs at information level.
Definition Logger.cpp:136
A material is defined as being composed of a given element, defined as a PhysicalConstants::NeutronAt...
Definition Material.h:50
double absorbXSection(const double lambda=PhysicalConstants::NeutronAtom::ReferenceLambda) const
Get the absorption cross section at a given wavelength in barns.
Definition Material.cpp:260
const std::string & name() const
Returns the name of the material.
Definition Material.cpp:181
double totalScatterXSection() const
Return the total scattering cross section for a given wavelength in barns.
Definition Material.cpp:252
This implements the Mersenne Twister 19937 pseudo-random number generator algorithm as a specialzatio...
void report()
Increments the loop counter by 1, then sends the progress notification on behalf of its algorithm.
void setNotifyStep(double notifyStepPct)
Override the frequency at which notifications are sent out.
Defines a 1D pseudo-random number generator, i.e.
virtual double nextValue()=0
Return the next double in the sequence.
static T & Instance()
Return a reference to the Singleton instance, creating it if it does not already exist Creation is do...
Class for 3D vectors.
Definition V3D.h:34
double normalize()
Make a normalized vector (return norm value)
Definition V3D.cpp:129
double norm() const noexcept
Definition V3D.h:269
EXPORT_OPT_MANTIDQT_COMMON std::string getEMode(const Mantid::API::MatrixWorkspace_sptr &ws)
Gets the energy mode from a workspace based on the X unit.
std::unique_ptr< MatrixWorkspace > MatrixWorkspace_uptr
unique pointer to Mantid::API::MatrixWorkspace
std::shared_ptr< Workspace > Workspace_sptr
shared pointer to Mantid::API::Workspace
std::shared_ptr< MatrixWorkspace > MatrixWorkspace_sptr
shared pointer to the matrix workspace base class
std::shared_ptr< SparseWorkspace > SparseWorkspace_sptr
std::shared_ptr< const IComponent > IComponent_const_sptr
Typdef of a shared pointer to a const IComponent.
Definition IComponent.h:167
std::shared_ptr< const IObject > IObject_const_sptr
Typdef for a shared pointer to a const object.
Definition IObject.h:95
void MANTID_KERNEL_DLL convertToBinCentre(const std::vector< double > &bin_edges, std::vector< double > &bin_centres)
Convert an array of bin boundaries to bin center values.
void MANTID_KERNEL_DLL convertToBinBoundary(const std::vector< double > &bin_centers, std::vector< double > &bin_edges)
Convert an array of bin centers to bin boundary values.
int MANTID_KERNEL_DLL indexOfValueFromCentersNoThrow(const std::vector< double > &bin_centers, const double value)
Gets the bin of a value from a vector of bin centers and returns -1 if out of range.
std::enable_if< std::is_pointer< Arg >::value, bool >::type threadSafe(Arg workspace)
Thread-safety check Checks the workspace to ensure it is suitable for multithreaded access.
MANTID_KERNEL_DLL V3D normalize(V3D v)
Normalizes a V3D.
Definition V3D.h:352
A namespace containing physical constants that are required by algorithms and unit routines.
Definition Atom.h:14
static constexpr double E_mev_toNeutronWavenumberSq
Transformation coefficient to transform neutron energy into neutron wavevector: K-neutron[m^-10] = sq...
static constexpr double h
Planck constant in J*s.
Helper class which provides the Collimation Length for SANS instruments.
constexpr int EMPTY_INT() noexcept
Returns what we consider an "empty" integer within a property.
Definition EmptyValues.h:24
int32_t detid_t
Typedef for a detector ID.
std::vector< double > MantidVec
typedef for the data storage used in Mantid matrix workspaces
Definition cow_ptr.h:172
int32_t specnum_t
Typedef for a spectrum Number.
Definition IDTypes.h:14
STL namespace.
std::string to_string(const wide_integer< Bits, Signed > &n)
static std::string asString(const Type mode)
Return a string representation of the given mode.
Type
Define the available energy transfer modes It is important to assign enums proper numbers,...
Definition DeltaEMode.h:29
@ Input
An input workspace.
Definition Property.h:53
@ Output
An output workspace.
Definition Property.h:54