Scalar AdaptiveSparseGrid<Scalar,UserVector>::refine_grid(
typename std::multimap<Scalar,std::vector<int> > & indexSet,
UserVector & integralValue,
AdaptiveSparseGridInterface<Scalar,UserVector> & problem_data) {
int dimension = problem_data.getDimension();
std::vector<EIntrepidBurkardt> rule1D; problem_data.getRule(rule1D);
std::vector<EIntrepidGrowth> growth1D; problem_data.getGrowth(growth1D);
// Copy Multimap into a Set for ease of use
typename std::multimap<Scalar,std::vector<int> >::iterator it;
std::set<std::vector<int> > oldSet;
std::set<std::vector<int> >::iterator it1(oldSet.begin());
for (it=indexSet.begin(); it!=indexSet.end(); it++) {
oldSet.insert(it1,it->second);
it1++;
}
indexSet.clear();
// Find Possible Active Points
int flag = 1;
std::vector<int> index(dimension,0);
typename std::multimap<Scalar,std::vector<int> > activeSet;
for (it1=oldSet.begin(); it1!=oldSet.end(); it1++) {
index = *it1;
for (int i=0; i<dimension; i++) {
index[i]++;
flag = (int)(!oldSet.count(index));
index[i]--;
if (flag) {
activeSet.insert(std::pair<Scalar,std::vector<int> >(1.0,index));
oldSet.erase(it1);
break;
}
}
}
// Compute local and global error indicators for active set
typename std::multimap<Scalar,std::vector<int> >::iterator it2;
Scalar eta = 0.0;
Scalar G = 0.0;
Teuchos::RCP<UserVector> s = integralValue.Create();
for (it2=activeSet.begin(); it2!=activeSet.end(); it2++) {
// Build Differential Quarature Rule
index = it2->second;
CubatureTensorSorted<Scalar> diffRule(0,dimension);
build_diffRule(diffRule,index,problem_data);
// Apply Rule to function
problem_data.eval_cubature(*s,diffRule);
// Update local error indicator and index set
G = problem_data.error_indicator(*s);
activeSet.erase(it2);
activeSet.insert(it2,std::pair<Scalar,std::vector<int> >(G,index));
eta += G;
}
// Refine Sparse Grid
eta = refine_grid(activeSet,oldSet,integralValue,eta,
dimension,rule1D,growth1D);
// Insert New Active and Old Index sets into indexSet
indexSet.insert(activeSet.begin(),activeSet.end());
for (it1=oldSet.begin(); it1!=oldSet.end(); it1++) {
index = *it1;
indexSet.insert(std::pair<Scalar,std::vector<int> >(-1.0,index));
}
return eta;
}
Scalar AdaptiveSparseGrid<Scalar,UserVector>::refine_grid(
typename std::multimap<Scalar,std::vector<int> > & activeIndex,
std::set<std::vector<int> > & oldIndex,
UserVector & integralValue,
CubatureTensorSorted<Scalar> & cubRule,
Scalar globalErrorIndicator,
AdaptiveSparseGridInterface<Scalar,UserVector> & problem_data) {
TEUCHOS_TEST_FOR_EXCEPTION((activeIndex.empty()),std::out_of_range,
">>> ERROR (AdaptiveSparseGrid): Active Index set is empty.");
int dimension = problem_data.getDimension();
std::vector<EIntrepidBurkardt> rule1D; problem_data.getRule(rule1D);
std::vector<EIntrepidGrowth> growth1D; problem_data.getGrowth(growth1D);
// Initialize Flags
bool maxLevelFlag = true;
bool isAdmissibleFlag = true;
// Initialize Cubature Rule
Teuchos::RCP<UserVector> s = integralValue.Create();
// Initialize iterator at end of inOldIndex
std::set<std::vector<int> >::iterator it1(oldIndex.end());
// Initialize iterator at end of inActiveIndex
typename std::multimap<Scalar,std::vector<int> >::iterator it;
// Obtain Global Error Indicator as sum of key values of inActiveIndex
Scalar eta = globalErrorIndicator;
// Select Index to refine
it = activeIndex.end(); it--; // Decrement to position of final value
Scalar G = it->first; // Largest Error Indicator is at End
eta -= G; // Update global error indicator
std::vector<int> index = it->second; // Get Corresponding index
activeIndex.erase(it); // Erase Index from active index set
// Insert Index into old index set
oldIndex.insert(it1,index); it1 = oldIndex.end();
// Refinement process
for (int k=0; k<dimension; k++) {
index[k]++; // index + ek
// Check Max Level
maxLevelFlag = problem_data.max_level(index);
if (maxLevelFlag) {
// Check Admissibility
isAdmissibleFlag = isAdmissible(index,k,oldIndex,problem_data);
if (isAdmissibleFlag) { // If admissible
// Build Differential Quarature Rule
CubatureTensorSorted<Scalar> diffRule(0,dimension);
build_diffRule(diffRule,index,problem_data);
// Apply Rule to function
problem_data.eval_cubature(*s,diffRule);
// Update integral value
integralValue.Update(*s);
// Update local error indicator and index set
G = problem_data.error_indicator(*s);
if (activeIndex.end()!=activeIndex.begin())
activeIndex.insert(activeIndex.end()--,
std::pair<Scalar,std::vector<int> >(G,index));
else
activeIndex.insert(std::pair<Scalar,std::vector<int> >(G,index));
// Update global error indicators
eta += G;
// Update adapted quadrature rule nodes and weights
cubRule.update(1.0,diffRule,1.0);
}
}
else { // Max Level Exceeded
//std::cout << "Maximum Level Exceeded" << std::endl;
}
index[k]--;
}
return eta;
}
void FindPeaksMD::findPeaks(typename MDEventWorkspace<MDE, nd>::sptr ws)
{
if (nd < 3)
throw std::invalid_argument("Workspace must have at least 3 dimensions.");
progress(0.01, "Refreshing Centroids");
// TODO: This might be slow, progress report?
// Make sure all centroids are fresh
ws->getBox()->refreshCentroid();
typedef IMDBox<MDE,nd>* boxPtr;
if (ws->getNumExperimentInfo() == 0)
throw std::runtime_error("No instrument was found in the MDEventWorkspace. Cannot find peaks.");
// TODO: Do we need to pick a different instrument info?
ExperimentInfo_sptr ei = ws->getExperimentInfo(0);
// Instrument associated with workspace
Geometry::Instrument_const_sptr inst = ei->getInstrument();
// Find the run number
int runNumber = ei->getRunNumber();
// Check that the workspace dimensions are in Q-sample-frame or Q-lab-frame.
eDimensionType dimType;
std::string dim0 = ws->getDimension(0)->getName();
if (dim0 == "H")
{
dimType = HKL;
throw std::runtime_error("Cannot find peaks in a workspace that is already in HKL space.");
}
else if (dim0 == "Q_lab_x")
{
dimType = QLAB;
}
else if (dim0 == "Q_sample_x")
dimType = QSAMPLE;
else
throw std::runtime_error("Unexpected dimensions: need either Q_lab_x or Q_sample_x.");
// Find the goniometer rotation matrix
Mantid::Kernel::Matrix<double> goniometer(3,3, true); // Default IDENTITY matrix
try
{
goniometer = ei->mutableRun().getGoniometerMatrix();
}
catch (std::exception & e)
{
g_log.warning() << "Error finding goniometer matrix. It will not be set in the peaks found." << std::endl;
g_log.warning() << e.what() << std::endl;
}
/// Arbitrary scaling factor for density to make more manageable numbers, especially for older file formats.
signal_t densityScalingFactor = 1e-6;
// Calculate a threshold below which a box is too diffuse to be considered a peak.
signal_t thresholdDensity = 0.0;
thresholdDensity = ws->getBox()->getSignalNormalized() * DensityThresholdFactor * densityScalingFactor;
g_log.notice() << "Threshold signal density: " << thresholdDensity << std::endl;
// We will fill this vector with pointers to all the boxes (up to a given depth)
typename std::vector<boxPtr> boxes;
// Get all the MDboxes
progress(0.10, "Getting Boxes");
ws->getBox()->getBoxes(boxes, 1000, true);
// TODO: Here keep only the boxes > e.g. 3 * mean.
typedef std::pair<double, boxPtr> dens_box;
// Map that will sort the boxes by increasing density. The key = density; value = box *.
typename std::multimap<double, boxPtr> sortedBoxes;
progress(0.20, "Sorting Boxes by Density");
typename std::vector<boxPtr>::iterator it1;
typename std::vector<boxPtr>::iterator it1_end = boxes.end();
for (it1 = boxes.begin(); it1 != it1_end; it1++)
{
boxPtr box = *it1;
double density = box->getSignalNormalized() * densityScalingFactor;
// Skip any boxes with too small a signal density.
if (density > thresholdDensity)
sortedBoxes.insert(dens_box(density,box));
}
// List of chosen possible peak boxes.
std::vector<boxPtr> peakBoxes;
prog = new Progress(this, 0.30, 0.95, MaxPeaks);
int64_t numBoxesFound = 0;
// Now we go (backwards) through the map
// e.g. from highest density down to lowest density.
typename std::multimap<double, boxPtr>::reverse_iterator it2;
typename std::multimap<double, boxPtr>::reverse_iterator it2_end = sortedBoxes.rend();
for (it2 = sortedBoxes.rbegin(); it2 != it2_end; it2++)
{
signal_t density = it2->first;
boxPtr box = it2->second;
#ifndef MDBOX_TRACK_CENTROID
coord_t boxCenter[nd];
box->calculateCentroid(boxCenter);
#else
const coord_t * boxCenter = box->getCentroid();
#endif
// Compare to all boxes already picked.
bool badBox = false;
for (typename std::vector<boxPtr>::iterator it3=peakBoxes.begin(); it3 != peakBoxes.end(); it3++)
{
#ifndef MDBOX_TRACK_CENTROID
coord_t otherCenter[nd];
(*it3)->calculateCentroid(otherCenter);
#else
const coord_t * otherCenter = (*it3)->getCentroid();
#endif
// Distance between this box and a box we already put in.
coord_t distSquared = 0.0;
for (size_t d=0; d<nd; d++)
{
coord_t dist = otherCenter[d] - boxCenter[d];
distSquared += (dist * dist);
}
// Reject this box if it is too close to another previously found box.
if (distSquared < peakRadiusSquared)
{
badBox = true;
break;
}
}
// The box was not rejected for another reason.
if (!badBox)
{
if (numBoxesFound++ >= MaxPeaks)
{
g_log.notice() << "Number of peaks found exceeded the limit of " << MaxPeaks << ". Stopping peak finding." << std::endl;
break;
}
peakBoxes.push_back(box);
g_log.information() << "Found box at ";
for (size_t d=0; d<nd; d++)
g_log.information() << (d>0?",":"") << boxCenter[d];
g_log.information() << "; Density = " << density << std::endl;
// Report progres for each box found.
prog->report("Finding Peaks");
}
}
prog->resetNumSteps(numBoxesFound, 0.95, 1.0);
// Copy the instrument, sample, run to the peaks workspace.
peakWS->copyExperimentInfoFrom(ei.get());
// --- Convert the "boxes" to peaks ----
for (typename std::vector<boxPtr>::iterator it3=peakBoxes.begin(); it3 != peakBoxes.end(); it3++)
{
// The center of the box = Q in the lab frame
boxPtr box = *it3;
#ifndef MDBOX_TRACK_CENTROID
coord_t boxCenter[nd];
box->calculateCentroid(boxCenter);
#else
const coord_t * boxCenter = box->getCentroid();
#endif
V3D Q(boxCenter[0], boxCenter[1], boxCenter[2]);
// Create a peak and add it
// Empty starting peak.
Peak p;
try
{
if (dimType == QLAB)
{
// Build using the Q-lab-frame constructor
p = Peak(inst, Q);
// Save gonio matrix for later
p.setGoniometerMatrix(goniometer);
}
else if (dimType == QSAMPLE)
{
// Build using the Q-sample-frame constructor
p = Peak(inst, Q, goniometer);
}
}
catch (std::exception &e)
{
g_log.notice() << "Error creating peak at " << Q << " because of '" << e.what() << "'. Peak will be skipped." << std::endl;
continue;
}
try
{ // Look for a detector
p.findDetector();
}
catch (...)
{ /* Ignore errors in ray-tracer TODO: Handle for WISH data later */ }
// The "bin count" used will be the box density.
p.setBinCount( box->getSignalNormalized() * densityScalingFactor);
// Save the run number found before.
p.setRunNumber(runNumber);
peakWS->addPeak(p);
// Report progres for each box found.
prog->report("Adding Peaks");
} // for each box found
}
