ProcessBankTask.cpp

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// Mantid Repository : https://github.com/mantidproject/mantid
//
// Copyright © 2025 ISIS Rutherford Appleton Laboratory UKRI,
//   NScD Oak Ridge National Laboratory, European Spallation Source,
//   Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
// SPDX - License - Identifier: GPL - 3.0 +
 
#include "MantidDataHandling/AlignAndFocusPowderSlim/ProcessBankTask.h"
#include "MantidDataHandling/AlignAndFocusPowderSlim/ProcessEventsTask.h"
#include "MantidKernel/Logger.h"
#include "MantidKernel/ParallelMinMax.h"
#include "MantidKernel/Timer.h"
#include "MantidNexus/H5Util.h"
#include "tbb/parallel_for.h"
#include "tbb/parallel_reduce.h"
 
namespace Mantid::DataHandling::AlignAndFocusPowderSlim {
 
namespace {
 
// Logger for this class
auto g_log = Kernel::Logger("ProcessBankTask");
 
} // namespace
ProcessBankTask::ProcessBankTask(std::vector<std::string> &bankEntryNames, H5::H5File &h5file,
                                 std::shared_ptr<NexusLoader> loader, SpectraProcessingData &processingData,
                                 const BankCalibrationFactory &calibFactory, const size_t events_per_chunk,
                                 const size_t grainsize_event, std::shared_ptr<API::Progress> &progress)
    : ProcessBankTaskBase(bankEntryNames, loader, calibFactory), m_h5file(h5file), m_processingData(processingData),
      m_events_per_chunk(events_per_chunk), m_grainsize_event(grainsize_event), m_progress(progress) {}
 
void ProcessBankTask::operator()(const tbb::blocked_range<size_t> &range) const {
  auto entry = m_h5file.openGroup("entry"); // type=NXentry
  for (size_t bank_index = range.begin(); bank_index < range.end(); ++bank_index) {
    const auto &bankName = this->bankName(bank_index);
 
    // empty bank names indicate spectra to skip; control should never get here, but just in case
    if (bankName.empty())
      continue;
 
    Kernel::Timer timer;
    g_log.debug() << bankName << " start" << std::endl;
 
    // open the bank
    auto event_group = entry.openGroup(bankName); // type=NXevent_data
 
    // skip empty dataset
    auto tof_SDS = event_group.openDataSet(NxsFieldNames::TIME_OF_FLIGHT);
    const int64_t total_events = static_cast<size_t>(tof_SDS.getSpace().getSelectNpoints());
    if (total_events == 0) {
      m_progress->report();
      g_log.debug() << bankName << " empty\n";
      continue;
    }
    // and the units
    std::string tof_unit;
    Nexus::H5Util::readStringAttribute(tof_SDS, "units", tof_unit);
    // now the calibration for the output group can be created
    // which detectors go into the current group - assumes ouput spectrum number is one more than workspace index
    const auto calibrations = this->getCalibrations(tof_unit, bank_index);
    if (calibrations.empty()) {
      m_progress->report();
      g_log.debug() << "skipping " << bankName << " because calibration is empty\n";
      continue;
    }
 
    auto eventRanges = this->getEventIndexRanges(event_group, total_events);
 
    // get handle to the detector IDs
    auto detID_SDS = event_group.openDataSet(NxsFieldNames::DETID);
 
    // declare arrays once so memory can be reused
    auto event_detid = std::make_unique<std::vector<uint32_t>>();       // uint32 for ORNL nexus file
    auto event_time_of_flight = std::make_unique<std::vector<float>>(); // float for ORNL nexus files
 
    // read parts of the bank at a time until all events are processed
    while (!eventRanges.empty()) {
      // Create offsets and slab sizes for the next chunk of events.
      // This will read at most m_events_per_chunk events from the file
      // and will split the ranges if necessary for the next iteration.
      std::vector<size_t> offsets;
      std::vector<size_t> slabsizes;
 
      size_t total_events_to_read = 0;
      // Process the event ranges until we reach the desired number of events to read or run out of ranges
      while (!eventRanges.empty() && total_events_to_read < m_events_per_chunk) {
        // Get the next event range from the stack
        auto eventRange = eventRanges.top();
        eventRanges.pop();
 
        size_t range_size = eventRange.second - eventRange.first;
        size_t remaining_chunk = m_events_per_chunk - total_events_to_read;
 
        // If the range size is larger than the remaining chunk, we need to split it
        if (range_size > remaining_chunk) {
          // Split the range: process only part of it now, push the rest back for later
          offsets.push_back(eventRange.first);
          slabsizes.push_back(remaining_chunk);
          total_events_to_read += remaining_chunk;
          // Push the remainder of the range back to the front for next iteration
          eventRanges.emplace(eventRange.first + remaining_chunk, eventRange.second);
          break;
        } else {
          offsets.push_back(eventRange.first);
          slabsizes.push_back(range_size);
          total_events_to_read += range_size;
          // Continue to next range
        }
      }
 
      // log the event ranges being processed
      g_log.debug(toLogString(bankName, total_events_to_read, offsets, slabsizes));
 
      if (total_events_to_read == 0) {
        continue; // nothing to do
      }
 
      // load detid and tof at the same time
      this->loadEvents(detID_SDS, tof_SDS, offsets, slabsizes, event_detid, event_time_of_flight);
 
      // Loop over all output spectra / groups
      tbb::parallel_for(
          tbb::blocked_range<size_t>(0, m_processingData.counts.size()),
          [&](const tbb::blocked_range<size_t> &output_range) {
            for (size_t output_index = output_range.begin(); output_index < output_range.end(); ++output_index) {
              // Create a local task for this thread
              ProcessEventsTask task(event_detid.get(), event_time_of_flight.get(), &calibrations.at(output_index),
                                     m_processingData.binedges[output_index]);
 
              const tbb::blocked_range<size_t> range_info(0, event_time_of_flight->size(), m_grainsize_event);
              tbb::parallel_reduce(range_info, task);
 
              // Accumulate results into shared y_temp to combine local histograms
              // Use atomic fetch_add to accumulate results into shared vectors
              for (size_t i = 0; i < m_processingData.counts[output_index].size(); ++i) {
                m_processingData.counts[output_index][i].fetch_add(task.y_temp[i], std::memory_order_relaxed);
              }
            }
          });
    }
 
    g_log.debug() << bankName << " stop " << timer << std::endl;
    m_progress->report();
  }
}
}; // namespace Mantid::DataHandling::AlignAndFocusPowderSlim