void interruptible_wait(std::condition_variable& cv, std::unique_lock<std::mutex>& lk)
{
interruption_point();
this_thread_interrupt_flag.set_condition_variable(cv);
//std::this_thread::sleep_for(std::chrono::milliseconds(10000));
cv.wait(lk);
this_thread_interrupt_flag.clear_condition_variable();
interruption_point();
}
void interruptible_wait(std::condition_variable& cv, std::unique_lock<std::mutex>& lk)
{
interruption_point();
this_thread_interrupt_flag.set_condition_variable(cv);
clear_cv_on_destruct guard;
interruption_point();
cv.wait_for(lk, std::chrono::milliseconds(1));
interruption_point();
}
void interruptible_wait(std::condition_variable& cv, std::unique_lock<std::mutex>& lk, Predicate pred)
{
interruption_point();
this_thread_interrupt_flag.set_condition_variable(cv);
interrupt_flag::clear_cv_on_destruct guard;
while (!thie_thread_interrupt_flag.is_set() && !pred())
{
cv.wait_for(lk, std::chrono::milliseconds(1));
}
interruption_point();
}
/**
* Execute the algorithm.
*/
void FakeISISHistoDAE::exec()
{
Mutex::ScopedLock lock(m_mutex);
Poco::Net::ServerSocket socket(6789);
socket.listen();
int nper = getProperty("NPeriods");
int nspec = getProperty("NSpectra");
int nbins = getProperty("NBins");
m_server = new Poco::Net::TCPServer(TestServerConnectionFactory::Ptr( new TestServerConnectionFactory(nper,nspec,nbins) ), socket );
m_server->start();
// Keep going until you get cancelled
while (true)
{
try
{
// Exit if the user presses cancel
interruption_point();
}
catch(...)
{
break;
}
progress( 0.0, "Fake DAE" );
// Sleep for 50 msec
Poco::Thread::sleep(50);
}
if ( m_server )
{
m_server->stop();
m_server = NULL;
}
socket.close();
}
void contractor_sample::prune(contractor_status & cs) {
DREAL_LOG_DEBUG << "contractor_sample::prune";
// Sample n points
set<box> points = cs.m_box.sample_points(m_num_samples);
// If ∃p. ∀c. eval(c, p) = true, return 'SAT'
unsigned count = 0;
for (box const & p : points) {
interruption_point();
DREAL_LOG_DEBUG << "contractor_sample::prune -- sample " << ++count << "th point = " << p;
bool check = true;
for (shared_ptr<constraint> const ctr : m_ctrs) {
if (ctr->get_type() == constraint_type::Nonlinear) {
auto const nl_ctr = dynamic_pointer_cast<nonlinear_constraint>(ctr);
pair<lbool, ibex::Interval> eval_result = nl_ctr->eval(p);
if (eval_result.first == l_False) {
check = false;
DREAL_LOG_DEBUG << "contractor_sample::prune -- sampled point = " << p << " does not satisfy " << *ctr;
break;
}
}
}
if (check) {
DREAL_LOG_DEBUG << "contractor_sample::prune -- sampled point = " << p << " satisfies all constraints";
cs.m_box = p;
cs.m_output = ibex::BitSet::all(cs.m_box.size());
cs.m_used_constraints.insert(m_ctrs.begin(), m_ctrs.end());
return;
}
}
return;
}
/// Update the percentage complete estimate assuming that the algorithm has completed a task with estimated RunTime toAdd
void GetEi::advanceProgress(double toAdd)
{
m_fracCompl += toAdd;
progress(m_fracCompl);
// look out for user cancel messgages
interruption_point();
}
void contractor_aggressive::prune(contractor_status & cs) {
DREAL_LOG_DEBUG << "contractor_eval::aggressive";
// TODO(soonhok): set input & output
// Sample n points
set<box> points = cs.m_box.sample_points(m_num_samples);
// ∃c. ∀p. eval(c, p) = false ===> UNSAT
for (shared_ptr<constraint> const ctr : m_ctrs) {
interruption_point();
if (ctr->get_type() == constraint_type::Nonlinear) {
auto const nl_ctr = dynamic_pointer_cast<nonlinear_constraint>(ctr);
bool check = false;
for (box const & p : points) {
pair<lbool, ibex::Interval> eval_result = nl_ctr->eval(p);
if (eval_result.first != l_False) {
check = true;
break;
}
}
if (!check) {
cs.m_used_constraints.insert(ctr);
pair<lbool, ibex::Interval> eval_result = nl_ctr->eval(cs.m_box);
DREAL_LOG_DEBUG << "Constraint: " << *nl_ctr << " is violated by all " << points.size() << " points";
DREAL_LOG_DEBUG << "FYI, the interval evaluation gives us : " << eval_result.second;
cs.m_box.set_empty();
return;
}
}
}
return;
}
void contractor_fixpoint::worklist_fixpoint_alg(contractor_status & cs) {
thread_local static queue<unsigned> q;
q = queue<unsigned>(); // empty queue
thread_local static ibex::BitSet ctc_bitset = ibex::BitSet::empty(m_clist.size());
ctc_bitset.clear();
// Add all contractors to the queue.
for (int i = m_clist.size() - 1; i >= 0; --i) {
contractor & c_i = m_clist[i];
contractor_status_guard csg(cs);
c_i.prune(cs);
if (cs.m_box.is_empty()) { return; }
ibex::BitSet const & output_i = cs.m_output;
if (output_i.empty()) {
continue;
}
q.push(i);
ctc_bitset.add(i);
}
if (q.size() == 0) { return; }
// Fixed Point Loop
thread_local static box old_box(cs.m_box);
do {
interruption_point();
old_box = cs.m_box;
unsigned const idx = q.front();
q.pop();
ctc_bitset.remove(idx);
assert(idx < m_clist.size());
contractor & c = m_clist[idx];
contractor_status_guard csg(cs);
c.prune(cs);
if (cs.m_box.is_empty()) {
return;
}
auto const & c_output = cs.m_output;
if (!c_output.empty()) {
// j-th dimension is changed as a result of pruning
// need to add a contractor which takes j-th dim as an input
for (int j = c_output.min(); j <= c_output.max(); ++j) {
if (!c_output.contain(j)) {
continue;
}
for (unsigned k = 0; k < m_clist.size(); ++k) {
// Only add if it's not in the current queue
if (!ctc_bitset.contain(k)) {
contractor const & c_k = m_clist[k];
if (c_k.get_input().contain(j)) {
q.push(k);
ctc_bitset.add(k);
}
}
}
}
}
} while (q.size() > 0 && cs.m_box.max_diam() >= cs.m_config.nra_precision && !m_term_cond(old_box, cs.m_box));
return;
}
/** Update the percentage complete estimate assuming that the algorithm
* has completed a task with the given estimated run time
* @param toAdd :: the estimated additional run time passed since the last update,
* where m_TotalTime holds the total algorithm run time
* @return estimated fraction of algorithm runtime that has passed so far
*/
double DetectorDiagnostic::advanceProgress(double toAdd)
{
m_fracDone += toAdd/m_TotalTime;
// it could go negative as sometimes the percentage is re-estimated backwards,
// this is worrying about if a small negative value will cause a problem some where
m_fracDone = std::abs(m_fracDone);
interruption_point();
return m_fracDone;
}
void contractor_seq::prune_naive(contractor_status & cs) {
DREAL_LOG_DEBUG << "contractor_seq::prune";
for (contractor & c : m_vec) {
interruption_point();
c.prune(cs);
if (cs.m_box.is_empty()) {
return;
}
}
return;
}
/** A memory efficient function that adjusts the X-value bin boundaries that only creates a new
* cow_ptr array when the offset has changed
* @param offsets :: an array of times to adjust all the bins in each workspace histogram by
* @param spectraList :: a list of spectra numbers in the same order as the offsets
* @param specs2index :: a map that allows finding a spectra indexes from spectra numbers
* @param missingDetectors :: this will be filled with the array indices of the detector offsets that we can't find spectra indices for
*/
void LoadDetectorInfo::adjustXsCommon(const std::vector<float> &offsets, const std::vector<specid_t> &spectraList,
spec2index_map &specs2index, std::vector<detid_t> missingDetectors)
{
// space for cached values
float cachedOffSet = UNSETOFFSET;
MantidVecPtr monitorXs;
MantidVecPtr cachedXs;
double fracCompl = 1.0/3.0;
for ( std::vector<int>::size_type j = 0; j < spectraList.size(); ++j )
{// first check that our spectranumber to spectra index map is working for us
if ( specs2index.find(spectraList[j]) == specs2index.end() )
{// we can't find the spectrum associated the detector prepare to log that
missingDetectors.push_back(static_cast<int>(j));
// and then move on to the next detector in the loop
continue;
}
const size_t specIndex = specs2index[spectraList[j]];
// check if we dealing with a monitor as these are dealt by a different function
const std::set<detid_t> & dets = m_workspace->getSpectrum(specIndex)->getDetectorIDs();
if ( dets.size() > 0 )
{// is it in the monitors list
if ( m_monitors.find(*dets.begin()) == m_monitors.end() )
{// it's not a monitor, it's a regular detector
if ( offsets[j] != cachedOffSet )
{
setUpXArray(cachedXs, specIndex, offsets[j]);
cachedOffSet = offsets[j];
}
else m_workspace->setX(specIndex, cachedXs);
}
else
{// it's a monitor
if ( (*monitorXs).empty() )
{
// negative because we add the monitor offset, not take away as for detectors, the difference between the monitor delay and the detectors that counts
setUpXArray(monitorXs, specIndex, -m_monitOffset);
}
else m_workspace->setX(specIndex, monitorXs);
}
}
if ( j % INTERVAL == INTERVAL/2 )
{
fracCompl += (2.0*INTERVAL/3.0)/static_cast<double>(spectraList.size());
progress( fracCompl );
interruption_point();
}
}
}
void wait(std::condition_variable_any& cv, Lockable& lk)
{
struct custom_lock
{
interrupt_flag* self;
Lockable& lk;
custom_lock(interrupt_flag* self_,
std::condition_variable_any& cond,
Lockable& lk_)
: self(self_)
, lk(lk_)
{
self->set_clear_mutex.lock();
self->thread_cond_any = &cond;
}
void unlock()
{
lk.unlock();
self->set_clear_mutex.unlock();
}
void lock()
{
std::lock(self->set_clear_mutex, lk);
}
~custom_lock()
{
self->thread_cond_any = 0;
self->set_clear_mutex.unlock();
}
};
custom_lock cl(this, cv, lk);
interruption_point();
cv.wait(cl);
interruption_point();
}
/** Called while reading input file to report progress (doesn't update m_FracCompl ) and
* check for algorithm cancel messages, doesn't look at file size to estimate progress
* @param numGroupsRead :: number of groups read from the file so far (not the number of spectra)
* @param numInHists :: the total number of histograms in the input workspace
* @return estimate of the amount of algorithm progress obtained by reading from the file
*/
double GroupDetectors2::fileReadProg(DataHandling::GroupDetectors2::storage_map::size_type numGroupsRead,
DataHandling::GroupDetectors2::storage_map::size_type numInHists)
{
// I'm going to guess that there are half as many groups as spectra
double progEstim = 2.*static_cast<double>(numGroupsRead)/static_cast<double>(numInHists);
// but it might be more, in which case this complex function always increases but slower and slower
progEstim = READFILE*progEstim/(1+progEstim);
// now do the reporting
progress(m_FracCompl + progEstim );
// check for a (user) cancel message
interruption_point();
return progEstim;
}
void contractor_fixpoint::naive_fixpoint_alg(contractor_status & cs) {
// First Iteration (run always)
for (contractor & c : m_clist) {
interruption_point();
c.prune(cs);
if (cs.m_box.is_empty()) {
return;
}
}
unsigned i = 0;
// Next Iterations: stop when 1) a box is smaller enough or 2) termination condition holds
do {
interruption_point();
m_old_box = cs.m_box;
contractor & c = m_clist[i];
c.prune(cs);
if (cs.m_box.is_empty()) {
return;
}
i = (i + 1) % m_clist.size();
} while (m_old_box != cs.m_box && cs.m_box.is_bisectable(cs.m_config.nra_precision) && !m_term_cond(m_old_box, cs.m_box));
return;
}
/** Executes the algorithm
* @throw NullPointerException if a getDetector() returns NULL or pressure or wall thickness is not set
* @throw invalid_argument if the shape of a detector is isn't a cylinder aligned on axis or there is no baseInstrument
* @throw runtime_error if the SpectraDetectorMap had not been filled
*/
void DetectorEfficiencyCor::exec()
{
//gets and checks the values passed to the algorithm
retrieveProperties();
// wave number that the neutrons originally had
m_ki = std::sqrt(m_Ei/KSquaredToE);
// Store some information about the instrument setup that will not change
m_samplePos = m_inputWS->getInstrument()->getSample()->getPos();
int64_t numHists = m_inputWS->getNumberHistograms();
double numHists_d = static_cast<double>(numHists);
const int64_t progStep = static_cast<int64_t>(ceil(numHists_d/100.0));
PARALLEL_FOR2(m_inputWS,m_outputWS)
for (int64_t i = 0; i < numHists; ++i )
{
PARALLEL_START_INTERUPT_REGION
m_outputWS->setX(i, m_inputWS->refX(i));
try
{
correctForEfficiency(i);
}
catch (Exception::NotFoundError &)
{
// if we don't have all the data there will be spectra we can't correct, avoid leaving the workspace part corrected
MantidVec& dud = m_outputWS->dataY(i);
std::transform(dud.begin(),dud.end(),dud.begin(), std::bind2nd(std::multiplies<double>(),0));
PARALLEL_CRITICAL(deteff_invalid)
{
m_spectraSkipped.push_back(m_inputWS->getAxis(1)->spectraNo(i));
}
}
// make regular progress reports and check for cancelling the algorithm
if ( i % progStep == 0 )
{
progress(static_cast<double>(i)/numHists_d);
interruption_point();
}
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
logErrors();
setProperty("OutputWorkspace", m_outputWS);
}
void contractor_fixpoint::worklist_fixpoint_alg(contractor_status & cs) {
queue<int> q;
ibex::BitSet ctc_bitset(m_clist.size());
// Add all contractors to the queue.
for (unsigned i = 0; i < m_clist.size(); ++i) {
contractor & c_i = m_clist[i];
contractor_status_guard csg(cs);
c_i.prune(cs);
if (cs.m_box.is_empty()) { return; }
ibex::BitSet const & output_i = cs.m_output;
if (!output_i.empty()) {
assert(!ctc_bitset.contain(i));
q.push(i);
ctc_bitset.add(i);
}
}
if (q.size() == 0) { return; }
// Fixed Point Loop
do {
interruption_point();
unsigned const idx = q.front();
q.pop();
ctc_bitset.remove(idx);
assert(!ctc_bitset.contain(idx));
assert(idx < m_clist.size());
contractor & c = m_clist[idx];
m_old_box = cs.m_box;
contractor_status_guard csg(cs);
c.prune(cs);
if (cs.m_box.is_empty()) { return; }
auto const & c_output = cs.m_output;
if (!c_output.empty()) {
// j-th dimension is changed as a result of pruning
// need to add a contractor which takes j-th dim as an input
int j = c_output.min();
do {
if (!c_output.contain(j)) { continue; }
for (int const dependent_ctc_id : m_dep_map[j]) {
if (!ctc_bitset.contain(dependent_ctc_id)) {
q.push(dependent_ctc_id);
ctc_bitset.add(dependent_ctc_id);
}
}
j = c_output.next(j);
} while (j < c_output.max());
}
} while (q.size() > 0 && (m_old_box != cs.m_box) && cs.m_box.is_bisectable(cs.m_config.nra_precision) && !m_term_cond(m_old_box, cs.m_box));
return;
}
/**
* Only to be used if the KeepUnGrouped property is true, moves the spectra that were not selected
* to be in a group to the end of the output spectrum
* @param unGroupedSet :: list of WORKSPACE indexes that were included in a group
* @param inputWS :: user selected input workspace for the algorithm
* @param outputWS :: user selected output workspace for the algorithm
* @param outIndex :: the next spectra index available after the grouped spectra
*/
void GroupDetectors2::moveOthers(const std::set<int64_t> &unGroupedSet, API::MatrixWorkspace_const_sptr inputWS, API::MatrixWorkspace_sptr outputWS,
size_t outIndex)
{
g_log.debug() << "Starting to copy the ungrouped spectra" << std::endl;
double prog4Copy = (1. - 1.*static_cast<double>(m_FracCompl))/static_cast<double>(unGroupedSet.size());
std::set<int64_t>::const_iterator copyFrIt = unGroupedSet.begin();
// go thorugh all the spectra in the input workspace
for ( ; copyFrIt != unGroupedSet.end(); ++copyFrIt )
{
if( *copyFrIt == USED ) continue; //Marked as not to be used
size_t sourceIndex = static_cast<size_t>(*copyFrIt);
// The input spectrum we'll copy
const ISpectrum * inputSpec = inputWS->getSpectrum(sourceIndex);
// Destination of the copying
ISpectrum * outputSpec = outputWS->getSpectrum(outIndex);
// Copy the data
outputSpec->dataX() = inputSpec->dataX();
outputSpec->dataY() = inputSpec->dataY();
outputSpec->dataE() = inputSpec->dataE();
// Spectrum numbers etc.
outputSpec->setSpectrumNo(inputSpec->getSpectrumNo());
outputSpec->clearDetectorIDs();
outputSpec->addDetectorIDs( inputSpec->getDetectorIDs() );
// go to the next free index in the output workspace
outIndex ++;
// make regular progress reports and check for cancelling the algorithm
if ( outIndex % INTERVAL == 0 )
{
m_FracCompl += INTERVAL*prog4Copy;
if ( m_FracCompl > 1.0 )
{
m_FracCompl = 1.0;
}
progress(m_FracCompl);
interruption_point();
}
}
// Refresh the spectraDetectorMap
outputWS->generateSpectraMap();
g_log.debug() << name() << " copied " << unGroupedSet.size()-1 << " ungrouped spectra\n";
}
void sleep_until( chrono::time_point< Clock, Duration > const& sleep_time)
{
if ( 0 != fibers::fm_active() )
{
fibers::detail::spinlock splk;
unique_lock< fibers::detail::spinlock > lk( splk);
fibers::fm_wait_until( sleep_time, lk);
// check if fiber was interrupted
interruption_point();
}
else
{
while ( chrono::high_resolution_clock::now() <= sleep_time)
fibers::fm_run();
}
}
void LoadRaw3::separateMonitors(FILE *file, const int64_t &period,
const std::vector<specnum_t> &monitorList,
DataObjects::Workspace2D_sptr ws_sptr,
DataObjects::Workspace2D_sptr mws_sptr) {
int64_t histCurrent = -1;
int64_t wsIndex = 0;
int64_t mwsIndex = 0;
double histTotal = static_cast<double>(m_total_specs * m_numberOfPeriods);
// loop through spectra
for (specnum_t i = 1; i <= m_numberOfSpectra; ++i) {
int64_t histToRead = i + period * (m_numberOfSpectra + 1);
if ((i >= m_spec_min && i < m_spec_max) ||
(m_list &&
find(m_spec_list.begin(), m_spec_list.end(), i) !=
m_spec_list.end())) {
progress(m_prog, "Reading raw file data...");
// read spectrum from raw file
if (!readData(file, histToRead)) {
throw std::runtime_error("Error reading raw file");
}
// if this a monitor store that spectrum to monitor workspace
if (isMonitor(monitorList, i)) {
setWorkspaceData(mws_sptr, m_timeChannelsVec, mwsIndex, i,
m_noTimeRegimes, m_lengthIn, 1);
++mwsIndex;
} else {
// not a monitor,store the spectrum to normal output workspace
setWorkspaceData(ws_sptr, m_timeChannelsVec, wsIndex, i,
m_noTimeRegimes, m_lengthIn, 1);
++wsIndex;
}
if (m_numberOfPeriods == 1) {
if (++histCurrent % 100 == 0) {
setProg(static_cast<double>(histCurrent) / histTotal);
}
interruption_point();
}
} else {
skipData(file, histToRead);
}
}
}
/** This method creates outputworkspace excluding monitors
*@param file :: -pointer to file
*@param period :: period number
*@param monitorList :: a list containing the spectrum numbers for monitors
*@param ws_sptr :: shared pointer to workspace
*/
void LoadRaw3::excludeMonitors(FILE *file, const int &period,
const std::vector<specnum_t> &monitorList,
DataObjects::Workspace2D_sptr ws_sptr) {
int64_t histCurrent = -1;
int64_t wsIndex = 0;
double histTotal = static_cast<double>(m_total_specs * m_numberOfPeriods);
// loop through the spectra
for (specnum_t i = 1; i <= m_numberOfSpectra; ++i) {
specnum_t histToRead = i + period * (m_numberOfSpectra + 1);
if ((i >= m_spec_min && i < m_spec_max) ||
(m_list &&
find(m_spec_list.begin(), m_spec_list.end(), i) !=
m_spec_list.end())) {
progress(m_prog, "Reading raw file data...");
// skip monitor spectrum
if (isMonitor(monitorList, i)) {
skipData(file, histToRead);
continue;
}
// read spectrum
if (!readData(file, histToRead)) {
throw std::runtime_error("Error reading raw file");
}
// set the workspace data
setWorkspaceData(ws_sptr, m_timeChannelsVec, wsIndex, i, m_noTimeRegimes,
m_lengthIn, 1);
// increment workspace index
++wsIndex;
if (m_numberOfPeriods == 1) {
if (++histCurrent % 100 == 0) {
setProg(static_cast<double>(histCurrent) / histTotal);
}
interruption_point();
}
} // end of if loop for spec min,max check
else {
skipData(file, histToRead);
}
} // end of for loop
}
/** Calls CropWorkspace as a sub-algorithm and passes to it the InputWorkspace property
* @param specInd :: the index number of the histogram to extract
* @param start :: the number of the first bin to include (starts counting bins at 0)
* @param end :: the number of the last bin to include (starts counting bins at 0)
* @throw out_of_range if start, end or specInd are set outside of the vaild range for the workspace
* @throw runtime_error if the algorithm just falls over
* @throw invalid_argument if the input workspace does not have common binning
*/
void GetEi::extractSpec(int64_t specInd, double start, double end)
{
IAlgorithm_sptr childAlg =
createSubAlgorithm("CropWorkspace", 100*m_fracCompl, 100*(m_fracCompl+CROP) );
m_fracCompl += CROP;
childAlg->setPropertyValue( "InputWorkspace",
getPropertyValue("InputWorkspace") );
childAlg->setProperty( "XMin", start);
childAlg->setProperty( "XMax", end);
childAlg->setProperty( "StartWorkspaceIndex", specInd);
childAlg->setProperty( "EndWorkspaceIndex", specInd);
childAlg->executeAsSubAlg();
m_tempWS = childAlg->getProperty("OutputWorkspace");
//DEBUGGING CODE uncomment out the line below if you want to see the TOF window that was analysed
//AnalysisDataService::Instance().addOrReplace("croped_dist_del", m_tempWS);
progress(m_fracCompl);
interruption_point();
}
/**This method creates outputworkspace including monitors
*@param file :: -pointer to file
*@param period :: period number
*@param ws_sptr :: shared pointer to workspace
*/
void LoadRaw3::includeMonitors(FILE *file, const int64_t &period,
DataObjects::Workspace2D_sptr ws_sptr) {
int64_t histCurrent = -1;
int64_t wsIndex = 0;
double histTotal = static_cast<double>(m_total_specs * m_numberOfPeriods);
// loop through spectra
for (specnum_t i = 1; i <= m_numberOfSpectra; ++i) {
int64_t histToRead = i + period * (m_numberOfSpectra + 1);
if ((i >= m_spec_min && i < m_spec_max) ||
(m_list &&
find(m_spec_list.begin(), m_spec_list.end(), i) !=
m_spec_list.end())) {
progress(m_prog, "Reading raw file data...");
// read spectrum from raw file
if (!readData(file, histToRead)) {
throw std::runtime_error("Error reading raw file");
}
// set workspace data
setWorkspaceData(ws_sptr, m_timeChannelsVec, wsIndex, i, m_noTimeRegimes,
m_lengthIn, 1);
++wsIndex;
if (m_numberOfPeriods == 1) {
if (++histCurrent % 100 == 0) {
setProg(double(histCurrent) / histTotal);
}
interruption_point();
}
} else {
skipData(file, histToRead);
}
}
// loadSpectra(file,period,m_total_specs,ws_sptr,m_timeChannelsVec);
}
/** Read the spectra numbers in from the input file (the file format is in the
* source file "GroupDetectors2.h" and make an array of spectra indexes to group
* @param fname :: the full path name of the file to open
* @param workspace :: a pointer to the input workspace, used to get spectra indexes from numbers
* @param unUsedSpec :: the list of spectra indexes that have been included in a group (so far)
* @throw FileError if there's any problem with the file or its format
*/
void GroupDetectors2::processFile(std::string fname,
API::MatrixWorkspace_const_sptr workspace, std::vector<int64_t> &unUsedSpec)
{
// tring to open the file the user told us exists, skip down 20 lines to find out what happens if we can read from it
g_log.debug() << "Opening input file ... " << fname;
std::ifstream File(fname.c_str(), std::ios::in);
std::string firstLine;
std::getline( File, firstLine );
// for error reporting keep a count of where we are reading in the file
size_t lineNum = 1;
if (File.fail())
{
g_log.debug() << " file state failbit set after read attempt\n";
throw Exception::FileError("Couldn't read file", fname);
}
g_log.debug() << " success opening input file " << fname << std::endl;
progress(m_FracCompl += OPENINGFILE);
// check for a (user) cancel message
interruption_point();
// allow spectra number to spectra index look ups
spec2index_map specs2index;
const SpectraAxis* axis = dynamic_cast<const SpectraAxis*>(workspace->getAxis(1));
if (axis)
{
axis->getSpectraIndexMap(specs2index);
}
try
{
// we don't use the total number of groups report at the top of the file but we'll tell them later if there is a problem with it for their diagnostic purposes
int totalNumberOfGroups = readInt(firstLine);
// Reading file now ...
while ( totalNumberOfGroups == EMPTY_LINE )
{
if ( ! File ) throw Exception::FileError("The input file doesn't appear to contain any data", fname);
std::getline( File, firstLine ), lineNum ++;
totalNumberOfGroups = readInt(firstLine);
}
readFile(specs2index, File, lineNum, unUsedSpec);
if ( m_GroupSpecInds.size() != static_cast<size_t>(totalNumberOfGroups) )
{
g_log.warning() << "The input file header states there are " << totalNumberOfGroups << " but the file contains " << m_GroupSpecInds.size() << " groups\n";
}
}
// add some more info to the error messages, including the line number, to help users correct their files. These problems should cause the algorithm to stop
catch (std::invalid_argument &e)
{
g_log.debug() << "Exception thrown: " << e.what() << std::endl;
File.close();
std::string error(e.what() + std::string(" near line number ") + boost::lexical_cast<std::string>(lineNum));
if (File.fail())
{
error = "Input output error while reading file ";
}
throw Exception::FileError(error, fname);
}
catch (boost::bad_lexical_cast &e)
{
g_log.debug() << "Exception thrown: " << e.what() << std::endl;
File.close();
std::string error(std::string("Problem reading integer value \"") + e.what() + std::string("\" near line number ") + boost::lexical_cast<std::string>(lineNum));
if (File.fail())
{
error = "Input output error while reading file ";
}
throw Exception::FileError(error, fname);
}
File.close();
g_log.debug() << "Closed file " << fname << " after reading in " << m_GroupSpecInds.size() << " groups\n";
m_FracCompl += fileReadProg( m_GroupSpecInds.size(), specs2index.size() );
return;
}
void GroupDetectors2::execEvent()
{
// Get the input workspace
const MatrixWorkspace_const_sptr matrixInputWS = getProperty("InputWorkspace");
EventWorkspace_const_sptr inputWS= boost::dynamic_pointer_cast<const EventWorkspace>(matrixInputWS);
const size_t numInHists = inputWS->getNumberHistograms();
progress( m_FracCompl = CHECKBINS );
interruption_point();
// some values loaded into this vector can be negative so this needs to be a signed type
std::vector<int64_t> unGroupedInds;
//the ungrouped list could be very big but might be none at all
unGroupedInds.reserve(numInHists);
for( size_t i = 0; i < numInHists ; i++ )
{
unGroupedInds.push_back(i);
}
// read in the input parameters to make that map, if KeepUngroupedSpectra was set we'll need a list of the ungrouped spectrra too
getGroups(inputWS, unGroupedInds);
// converting the list into a set gets rid of repeated values, here the multiple GroupDetectors2::USED become one USED at the start
const std::set<int64_t> unGroupedSet(unGroupedInds.begin(), unGroupedInds.end());
// Check what the user asked to be done with ungrouped spectra
const bool keepAll = getProperty("KeepUngroupedSpectra");
// ignore the one USED value in set or ignore all the ungrouped if the user doesn't want them
const size_t numUnGrouped = keepAll ? unGroupedSet.size()-1 : 0;
//Make a brand new EventWorkspace
EventWorkspace_sptr outputWS = boost::dynamic_pointer_cast<EventWorkspace>(
WorkspaceFactory::Instance().create("EventWorkspace", m_GroupSpecInds.size()+ numUnGrouped,
inputWS->readX(0).size(), inputWS->blocksize()));
//Copy geometry over.
WorkspaceFactory::Instance().initializeFromParent(inputWS, outputWS, true);
// prepare to move the requested histograms into groups, first estimate how long for progress reporting. +1 in the demonator gets rid of any divide by zero risk
double prog4Copy=( (1.0 - m_FracCompl)/(static_cast<double>(numInHists-unGroupedSet.size())+1.) )*
(keepAll ? static_cast<double>(numInHists-unGroupedSet.size())/static_cast<double>(numInHists): 1.);
// Build a new map
const size_t outIndex = formGroupsEvent(inputWS, outputWS, prog4Copy);
// If we're keeping ungrouped spectra
if (keepAll)
{
// copy them into the output workspace
moveOthersEvent(unGroupedSet, inputWS, outputWS, outIndex);
}
//Set all X bins on the output
cow_ptr<MantidVec> XValues;
XValues.access() = inputWS->readX(0);
outputWS->setAllX(XValues);
g_log.information() << name() << " algorithm has finished\n";
setProperty("OutputWorkspace",outputWS);
}
/** Executes the algorithm. Reading in the file and creating and populating
* the output workspace
*
* @throw Exception::FileError If the RAW file cannot be found/opened
* @throw std::invalid_argument If the optional properties are set to invalid values
*/
void LoadRaw::exec()
{
// Retrieve the filename from the properties
m_filename = getPropertyValue("Filename");
LoadRawHelper *helper = new LoadRawHelper;
FILE* file = helper->openRawFile(m_filename);
ISISRAW iraw;
iraw.ioRAW(file, true);
std::string title(iraw.r_title, 80);
g_log.information("**** Run title: "+title+ "***");
// Read in the number of spectra in the RAW file
m_numberOfSpectra = iraw.t_nsp1;
// Read the number of periods in this file
m_numberOfPeriods = iraw.t_nper;
// Need to extract the user-defined output workspace name
Property *ws = getProperty("OutputWorkspace");
std::string localWSName = ws->value();
// Call private method to validate the optional parameters, if set
checkOptionalProperties();
// Read the number of time channels (i.e. bins) from the RAW file
const int channelsPerSpectrum = iraw.t_ntc1;
// Read in the time bin boundaries
const int lengthIn = channelsPerSpectrum + 1;
float* timeChannels = new float[lengthIn];
iraw.getTimeChannels(timeChannels, lengthIn);
// Put the read in array into a vector (inside a shared pointer)
boost::shared_ptr<MantidVec> timeChannelsVec
(new MantidVec(timeChannels, timeChannels + lengthIn));
// Create an array to hold the read-in data
int* spectrum = new int[lengthIn];
// Calculate the size of a workspace, given its number of periods & spectra to read
specid_t total_specs;
if( m_interval || m_list)
{
total_specs = static_cast<specid_t>(m_spec_list.size());
if (m_interval)
{
total_specs += (m_spec_max-m_spec_min+1);
m_spec_max += 1;
}
}
else
{
total_specs = m_numberOfSpectra;
// In this case want all the spectra, but zeroth spectrum is garbage so go from 1 to NSP1
m_spec_min = 1;
m_spec_max = m_numberOfSpectra + 1;
}
double histTotal = static_cast<double>(total_specs * m_numberOfPeriods);
int32_t histCurrent = -1;
// Create the 2D workspace for the output
DataObjects::Workspace2D_sptr localWorkspace = boost::dynamic_pointer_cast<DataObjects::Workspace2D>
(WorkspaceFactory::Instance().create("Workspace2D",total_specs,lengthIn,lengthIn-1));
localWorkspace->getAxis(0)->unit() = UnitFactory::Instance().create("TOF");
localWorkspace->setTitle(title);
// Run parameters
helper->loadRunParameters(localWorkspace, &iraw);
delete helper;
helper = NULL;
// Loop over the number of periods in the raw file, putting each period in a separate workspace
for (int period = 0; period < m_numberOfPeriods; ++period) {
if ( period > 0 ) localWorkspace = boost::dynamic_pointer_cast<DataObjects::Workspace2D>
(WorkspaceFactory::Instance().create(localWorkspace));
specid_t counter = 0;
for (specid_t i = m_spec_min; i < m_spec_max; ++i)
{
// Shift the histogram to read if we're not in the first period
int32_t histToRead = i + period*total_specs;
loadData(timeChannelsVec,counter,histToRead,iraw,lengthIn,spectrum,localWorkspace );
counter++;
if (++histCurrent % 100 == 0) progress(static_cast<double>(histCurrent)/histTotal);
interruption_point();
}
// Read in the spectra in the optional list parameter, if set
if (m_list)
{
for(size_t i=0; i < m_spec_list.size(); ++i)
{
loadData(timeChannelsVec,counter,m_spec_list[i],iraw,lengthIn,spectrum, localWorkspace );
counter++;
if (++histCurrent % 100 == 0) progress(static_cast<double>(histCurrent)/histTotal);
interruption_point();
}
}
// Just a sanity check
assert(counter == total_specs);
std::string outputWorkspace = "OutputWorkspace";
if (period == 0)
{
// Only run the Child Algorithms once
runLoadInstrument(localWorkspace );
runLoadMappingTable(localWorkspace );
runLoadLog(localWorkspace );
const int period_number = 1;
Property* log=createPeriodLog(period_number);
if(log)
{
localWorkspace->mutableRun().addLogData(log);
localWorkspace->mutableRun().addLogData(createCurrentPeriodLog(period_number));
}
// Set the total proton charge for this run
// (not sure how this works for multi_period files)
localWorkspace->mutableRun().setProtonCharge(iraw.rpb.r_gd_prtn_chrg);
}
else // We are working on a higher period of a multiperiod raw file
{
// Create a WorkspaceProperty for the new workspace of a higher period
// The workspace name given in the OutputWorkspace property has _periodNumber appended to it
// (for all but the first period, which has no suffix)
std::stringstream suffix;
suffix << (period+1);
outputWorkspace += suffix.str();
std::string WSName = localWSName + "_" + suffix.str();
declareProperty(new WorkspaceProperty<DataObjects::Workspace2D>(outputWorkspace,WSName,Direction::Output));
g_log.information() << "Workspace " << WSName << " created. \n";
}
if (localWorkspace)
localWorkspace->updateSpectraUsingMap();
// Assign the result to the output workspace property
setProperty(outputWorkspace,localWorkspace);
} // loop over periods
// Clean up
delete[] timeChannels;
delete[] spectrum;
}
/**
* Move the user selected spectra in the input workspace into groups in the output workspace
* @param inputWS :: user selected input workspace for the algorithm
* @param outputWS :: user selected output workspace for the algorithm
* @param prog4Copy :: the amount of algorithm progress to attribute to moving a single spectra
* @return number of new grouped spectra
*/
size_t GroupDetectors2::formGroups( API::MatrixWorkspace_const_sptr inputWS, API::MatrixWorkspace_sptr outputWS,
const double prog4Copy)
{
// get "Behaviour" string
const std::string behaviour = getProperty("Behaviour");
int bhv = 0;
if ( behaviour == "Average" ) bhv = 1;
API::MatrixWorkspace_sptr beh = API::WorkspaceFactory::Instance().create(
"Workspace2D", static_cast<int>(m_GroupSpecInds.size()), 1, 1);
g_log.debug() << name() << ": Preparing to group spectra into " << m_GroupSpecInds.size() << " groups\n";
// where we are copying spectra to, we start copying to the start of the output workspace
size_t outIndex = 0;
// Only used for averaging behaviour. We may have a 1:1 map where a Divide would be waste as it would be just dividing by 1
bool requireDivide(false);
for ( storage_map::const_iterator it = m_GroupSpecInds.begin(); it != m_GroupSpecInds.end() ; ++it )
{
// This is the grouped spectrum
ISpectrum * outSpec = outputWS->getSpectrum(outIndex);
// The spectrum number of the group is the key
outSpec->setSpectrumNo(it->first);
// Start fresh with no detector IDs
outSpec->clearDetectorIDs();
// Copy over X data from first spectrum, the bin boundaries for all spectra are assumed to be the same here
outSpec->dataX() = inputWS->readX(0);
// the Y values and errors from spectra being grouped are combined in the output spectrum
// Keep track of number of detectors required for masking
size_t nonMaskedSpectra(0);
beh->dataX(outIndex)[0] = 0.0;
beh->dataE(outIndex)[0] = 0.0;
for( std::vector<size_t>::const_iterator wsIter = it->second.begin(); wsIter != it->second.end(); ++wsIter)
{
const size_t originalWI = *wsIter;
// detectors to add to firstSpecNum
const ISpectrum * fromSpectrum = inputWS->getSpectrum(originalWI);
// Add up all the Y spectra and store the result in the first one
// Need to keep the next 3 lines inside loop for now until ManagedWorkspace mru-list works properly
MantidVec &firstY = outSpec->dataY();
MantidVec::iterator fYit;
MantidVec::iterator fEit = outSpec->dataE().begin();
MantidVec::const_iterator Yit = fromSpectrum->dataY().begin();
MantidVec::const_iterator Eit = fromSpectrum->dataE().begin();
for (fYit = firstY.begin(); fYit != firstY.end(); ++fYit, ++fEit, ++Yit, ++Eit)
{
*fYit += *Yit;
// Assume 'normal' (i.e. Gaussian) combination of errors
*fEit = std::sqrt( (*fEit)*(*fEit) + (*Eit)*(*Eit) );
}
// detectors to add to the output spectrum
outSpec->addDetectorIDs(fromSpectrum->getDetectorIDs() );
try
{
Geometry::IDetector_const_sptr det = inputWS->getDetector(originalWI);
if( !det->isMasked() ) ++nonMaskedSpectra;
}
catch(Exception::NotFoundError&)
{
// If a detector cannot be found, it cannot be masked
++nonMaskedSpectra;
}
}
if( nonMaskedSpectra == 0 ) ++nonMaskedSpectra; // Avoid possible divide by zero
if(!requireDivide) requireDivide = (nonMaskedSpectra > 1);
beh->dataY(outIndex)[0] = static_cast<double>(nonMaskedSpectra);
// make regular progress reports and check for cancelling the algorithm
if ( outIndex % INTERVAL == 0 )
{
m_FracCompl += INTERVAL*prog4Copy;
if ( m_FracCompl > 1.0 )
m_FracCompl = 1.0;
progress(m_FracCompl);
interruption_point();
}
outIndex ++;
}
// Refresh the spectraDetectorMap
outputWS->generateSpectraMap();
if ( bhv == 1 && requireDivide )
{
g_log.debug() << "Running Divide algorithm to perform averaging.\n";
Mantid::API::IAlgorithm_sptr divide = createChildAlgorithm("Divide");
divide->initialize();
divide->setProperty<API::MatrixWorkspace_sptr>("LHSWorkspace", outputWS);
divide->setProperty<API::MatrixWorkspace_sptr>("RHSWorkspace", beh);
divide->setProperty<API::MatrixWorkspace_sptr>("OutputWorkspace", outputWS);
divide->execute();
}
g_log.debug() << name() << " created " << outIndex << " new grouped spectra\n";
return outIndex;
}
/**
* Move the user selected spectra in the input workspace into groups in the output workspace
* @param inputWS :: user selected input workspace for the algorithm
* @param outputWS :: user selected output workspace for the algorithm
* @param prog4Copy :: the amount of algorithm progress to attribute to moving a single spectra
* @return number of new grouped spectra
*/
size_t GroupDetectors2::formGroupsEvent( DataObjects::EventWorkspace_const_sptr inputWS, DataObjects::EventWorkspace_sptr outputWS,
const double prog4Copy)
{
// get "Behaviour" string
const std::string behaviour = getProperty("Behaviour");
int bhv = 0;
if ( behaviour == "Average" ) bhv = 1;
API::MatrixWorkspace_sptr beh = API::WorkspaceFactory::Instance().create(
"Workspace2D", static_cast<int>(m_GroupSpecInds.size()), 1, 1);
g_log.debug() << name() << ": Preparing to group spectra into " << m_GroupSpecInds.size() << " groups\n";
// where we are copying spectra to, we start copying to the start of the output workspace
size_t outIndex = 0;
// Only used for averaging behaviour. We may have a 1:1 map where a Divide would be waste as it would be just dividing by 1
bool requireDivide(false);
for ( storage_map::const_iterator it = m_GroupSpecInds.begin(); it != m_GroupSpecInds.end() ; ++it )
{
// This is the grouped spectrum
EventList & outEL = outputWS->getEventList(outIndex);
// The spectrum number of the group is the key
outEL.setSpectrumNo(it->first);
// Start fresh with no detector IDs
outEL.clearDetectorIDs();
// the Y values and errors from spectra being grouped are combined in the output spectrum
// Keep track of number of detectors required for masking
size_t nonMaskedSpectra(0);
beh->dataX(outIndex)[0] = 0.0;
beh->dataE(outIndex)[0] = 0.0;
for( std::vector<size_t>::const_iterator wsIter = it->second.begin(); wsIter != it->second.end(); ++wsIter)
{
const size_t originalWI = *wsIter;
const EventList & fromEL=inputWS->getEventList(originalWI);
//Add the event lists with the operator
outEL += fromEL;
// detectors to add to the output spectrum
outEL.addDetectorIDs(fromEL.getDetectorIDs() );
try
{
Geometry::IDetector_const_sptr det = inputWS->getDetector(originalWI);
if( !det->isMasked() ) ++nonMaskedSpectra;
}
catch(Exception::NotFoundError&)
{
// If a detector cannot be found, it cannot be masked
++nonMaskedSpectra;
}
}
if( nonMaskedSpectra == 0 ) ++nonMaskedSpectra; // Avoid possible divide by zero
if(!requireDivide) requireDivide = (nonMaskedSpectra > 1);
beh->dataY(outIndex)[0] = static_cast<double>(nonMaskedSpectra);
// make regular progress reports and check for cancelling the algorithm
if ( outIndex % INTERVAL == 0 )
{
m_FracCompl += INTERVAL*prog4Copy;
if ( m_FracCompl > 1.0 )
m_FracCompl = 1.0;
progress(m_FracCompl);
interruption_point();
}
outIndex ++;
}
// Refresh the spectraDetectorMap
outputWS->doneAddingEventLists();
if ( bhv == 1 && requireDivide )
{
g_log.debug() << "Running Divide algorithm to perform averaging.\n";
Mantid::API::IAlgorithm_sptr divide = createChildAlgorithm("Divide");
divide->initialize();
divide->setProperty<API::MatrixWorkspace_sptr>("LHSWorkspace", outputWS);
divide->setProperty<API::MatrixWorkspace_sptr>("RHSWorkspace", beh);
divide->setProperty<API::MatrixWorkspace_sptr>("OutputWorkspace", outputWS);
divide->execute();
}
g_log.debug() << name() << " created " << outIndex << " new grouped spectra\n";
return outIndex;
}
/** Execute the algorithm.
*/
void MaxEnt::exec() {
// MaxEnt parameters
// Complex data?
bool complex = getProperty("ComplexData");
// Image must be positive?
bool positiveImage = getProperty("PositiveImage");
// Autoshift
bool autoShift = getProperty("AutoShift");
// Increase the number of points in the image by this factor
size_t densityFactor = getProperty("DensityFactor");
// Background (default level, sky background, etc)
double background = getProperty("A");
// Chi target
double chiTarget = getProperty("ChiTarget");
// Required precision for Chi arget
double chiEps = getProperty("ChiEps");
// Maximum degree of non-parallelism between S and C
double angle = getProperty("MaxAngle");
// Distance penalty for current image
double distEps = getProperty("DistancePenalty");
// Maximum number of iterations
size_t niter = getProperty("MaxIterations");
// Maximum number of iterations in alpha chop
size_t alphaIter = getProperty("AlphaChopIterations");
// Number of spectra and datapoints
// Read input workspace
MatrixWorkspace_sptr inWS = getProperty("InputWorkspace");
// Number of spectra
size_t nspec = inWS->getNumberHistograms();
// Number of data points
size_t npoints = inWS->blocksize() * densityFactor;
// Number of X bins
size_t npointsX = inWS->isHistogramData() ? npoints + 1 : npoints;
// The type of entropy we are going to use (depends on the type of image,
// positive only, or positive and/or negative)
MaxentData_sptr maxentData;
if (positiveImage) {
maxentData = boost::make_shared<MaxentData>(
boost::make_shared<MaxentEntropyPositiveValues>());
} else {
maxentData = boost::make_shared<MaxentData>(
boost::make_shared<MaxentEntropyNegativeValues>());
}
// Output workspaces
MatrixWorkspace_sptr outImageWS;
MatrixWorkspace_sptr outDataWS;
MatrixWorkspace_sptr outEvolChi;
MatrixWorkspace_sptr outEvolTest;
nspec = complex ? nspec / 2 : nspec;
outImageWS =
WorkspaceFactory::Instance().create(inWS, 2 * nspec, npointsX, npoints);
outDataWS =
WorkspaceFactory::Instance().create(inWS, 2 * nspec, npointsX, npoints);
outEvolChi = WorkspaceFactory::Instance().create(inWS, nspec, niter, niter);
outEvolTest = WorkspaceFactory::Instance().create(inWS, nspec, niter, niter);
npoints *= 2;
for (size_t s = 0; s < nspec; s++) {
// Start distribution (flat background)
std::vector<double> image(npoints, background);
if (complex) {
auto dataRe = inWS->readY(s);
auto dataIm = inWS->readY(s + nspec);
auto errorsRe = inWS->readE(s);
auto errorsIm = inWS->readE(s + nspec);
maxentData->loadComplex(dataRe, dataIm, errorsRe, errorsIm, image,
background);
} else {
auto data = inWS->readY(s);
auto error = inWS->readE(s);
maxentData->loadReal(data, error, image, background);
}
// To record the algorithm's progress
std::vector<double> evolChi(niter, 0.);
std::vector<double> evolTest(niter, 0.);
// Progress
Progress progress(this, 0, 1, niter);
// Run maxent algorithm
for (size_t it = 0; it < niter; it++) {
// Calculate quadratic model coefficients
// (SB eq. 21 and 24)
maxentData->calculateQuadraticCoefficients();
double currAngle = maxentData->getAngle();
double currChisq = maxentData->getChisq();
auto coeffs = maxentData->getQuadraticCoefficients();
// Calculate delta to construct new image (SB eq. 25)
auto delta = move(coeffs, chiTarget / currChisq, chiEps, alphaIter);
// Apply distance penalty (SB eq. 33)
image = maxentData->getImage();
delta = applyDistancePenalty(delta, coeffs, image, background, distEps);
// Update image according to 'delta' and calculate the new Chi-square
maxentData->updateImage(delta);
currChisq = maxentData->getChisq();
// Record the evolution of Chi-square and angle(S,C)
evolChi[it] = currChisq;
evolTest[it] = currAngle;
// Stop condition, solution found
if ((std::abs(currChisq / chiTarget - 1.) < chiEps) &&
(currAngle < angle)) {
break;
}
// Check for canceling the algorithm
if (!(it % 1000)) {
interruption_point();
}
progress.report();
} // iterations
// Get calculated data
auto solData = maxentData->getReconstructedData();
auto solImage = maxentData->getImage();
// Populate the output workspaces
populateDataWS(inWS, s, nspec, solData, outDataWS);
populateImageWS(inWS, s, nspec, solImage, outImageWS, autoShift);
// Populate workspaces recording the evolution of Chi and Test
// X values
for (size_t it = 0; it < niter; it++) {
outEvolChi->dataX(s)[it] = static_cast<double>(it);
outEvolTest->dataX(s)[it] = static_cast<double>(it);
}
// Y values
outEvolChi->dataY(s).assign(evolChi.begin(), evolChi.end());
outEvolTest->dataY(s).assign(evolTest.begin(), evolTest.end());
// No errors
} // Next spectrum
setProperty("EvolChi", outEvolChi);
setProperty("EvolAngle", outEvolTest);
setProperty("ReconstructedImage", outImageWS);
setProperty("ReconstructedData", outDataWS);
}
void GroupDetectors2::exec()
{
// Get the input workspace
const MatrixWorkspace_const_sptr inputWS = getProperty("InputWorkspace");
//Check if it is an event workspace
const bool preserveEvents = getProperty("PreserveEvents");
EventWorkspace_const_sptr eventW = boost::dynamic_pointer_cast<const EventWorkspace>(inputWS);
if (eventW != NULL && preserveEvents)
{
this->execEvent();
return;
}
const size_t numInHists = inputWS->getNumberHistograms();
// Bin boundaries need to be the same, so do the full check on whether they actually are
if (!API::WorkspaceHelpers::commonBoundaries(inputWS))
{
g_log.error() << "Can only group if the histograms have common bin boundaries\n";
throw std::invalid_argument("Can only group if the histograms have common bin boundaries");
}
progress( m_FracCompl = CHECKBINS );
interruption_point();
// some values loaded into this vector can be negative so this needs to be a signed type
std::vector<int64_t> unGroupedInds;
//the ungrouped list could be very big but might be none at all
unGroupedInds.reserve(numInHists);
for( size_t i = 0; i < numInHists ; i++ )
{
unGroupedInds.push_back(i);
}
// read in the input parameters to make that map, if KeepUngroupedSpectra was set we'll need a list of the ungrouped spectrra too
getGroups(inputWS, unGroupedInds);
// converting the list into a set gets rid of repeated values, here the multiple GroupDetectors2::USED become one USED at the start
const std::set<int64_t> unGroupedSet(unGroupedInds.begin(), unGroupedInds.end());
// Check what the user asked to be done with ungrouped spectra
const bool keepAll = getProperty("KeepUngroupedSpectra");
// ignore the one USED value in set or ignore all the ungrouped if the user doesn't want them
const size_t numUnGrouped = keepAll ? unGroupedSet.size()-1 : 0;
MatrixWorkspace_sptr outputWS =
WorkspaceFactory::Instance().create(inputWS, m_GroupSpecInds.size()+ numUnGrouped,
inputWS->readX(0).size(), inputWS->blocksize());
// prepare to move the requested histograms into groups, first estimate how long for progress reporting. +1 in the demonator gets rid of any divide by zero risk
double prog4Copy=( (1.0 - m_FracCompl)/(static_cast<double>(numInHists-unGroupedSet.size())+1.) )*
(keepAll ? static_cast<double>(numInHists-unGroupedSet.size())/static_cast<double>(numInHists): 1.);
// Build a new map
const size_t outIndex = formGroups(inputWS, outputWS, prog4Copy);
// If we're keeping ungrouped spectra
if (keepAll)
{
// copy them into the output workspace
moveOthers(unGroupedSet, inputWS, outputWS, outIndex);
}
g_log.information() << name() << " algorithm has finished\n";
setProperty("OutputWorkspace",outputWS);
}
/** Executes the rebin algorithm
*
* @throw runtime_error Thrown if
*/
void Rebunch::exec()
{
// retrieve the properties
int n_bunch=getProperty("NBunch");
// Get the input workspace
MatrixWorkspace_const_sptr inputW = getProperty("InputWorkspace");
bool dist = inputW->isDistribution();
// workspace independent determination of length
int histnumber = static_cast<int>(inputW->size()/inputW->blocksize());
/*
const std::vector<double>& Xold = inputW->readX(0);
const std::vector<double>& Yold = inputW->readY(0);
int size_x=Xold.size();
int size_y=Yold.size();
*/
int size_x = static_cast<int>(inputW->readX(0).size());
int size_y = static_cast<int>(inputW->readY(0).size());
//signal is the same length for histogram and point data
int ny=(size_y/n_bunch);
if(size_y%n_bunch >0)ny+=1;
// default is for hist
int nx=ny+1;
bool point=false;
if (size_x==size_y)
{
point=true;
nx=ny;
}
// make output Workspace the same type is the input, but with new length of signal array
API::MatrixWorkspace_sptr outputW = API::WorkspaceFactory::Instance().create(inputW,histnumber,nx,ny);
int progress_step = histnumber / 100;
if (progress_step == 0) progress_step = 1;
PARALLEL_FOR2(inputW,outputW)
for (int hist=0; hist < histnumber;hist++)
{
PARALLEL_START_INTERUPT_REGION
// Ensure that axis information are copied to the output workspace if the axis exists
try
{
outputW->getAxis(1)->spectraNo(hist)=inputW->getAxis(1)->spectraNo(hist);
}
catch( Exception::IndexError& )
{
// Not a Workspace2D
}
// get const references to input Workspace arrays (no copying)
const MantidVec& XValues = inputW->readX(hist);
const MantidVec& YValues = inputW->readY(hist);
const MantidVec& YErrors = inputW->readE(hist);
//get references to output workspace data (no copying)
MantidVec& XValues_new=outputW->dataX(hist);
MantidVec& YValues_new=outputW->dataY(hist);
MantidVec& YErrors_new=outputW->dataE(hist);
// output data arrays are implicitly filled by function
if(point)
{
rebunch_point(XValues,YValues,YErrors,XValues_new,YValues_new,YErrors_new,n_bunch);
}
else
{
rebunch_hist(XValues,YValues,YErrors,XValues_new,YValues_new,YErrors_new,n_bunch, dist);
}
if (hist % progress_step == 0)
{
progress(double(hist)/histnumber);
interruption_point();
}
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
outputW->isDistribution(dist);
// Copy units
if (outputW->getAxis(0)->unit().get())
outputW->getAxis(0)->unit() = inputW->getAxis(0)->unit();
try
{
if (inputW->getAxis(1)->unit().get())
outputW->getAxis(1)->unit() = inputW->getAxis(1)->unit();
}
catch(Exception::IndexError&) {
// OK, so this isn't a Workspace2D
}
// Assign it to the output workspace property
setProperty("OutputWorkspace",outputW);
return;
}
