HoughFinder2DAlgo.hpp

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/*
 * HoughFinder2DAlgo.hpp
 *
 *  Created on: 20 Nov 2018
 *      Author: Valerio Formato
 */

#include "algorithms/tracking/HoughFinder/HoughFinder2DAlgo.h"

namespace Herd {

template <RefFrame::View T> void HoughFinder2DAlgo::FillVotingSpace(const HFClusters &clusters) {
  const std::string routineName("HoughFinder2DAlgo::FillVotingSpace");

  RefFrame::ViewAxes<T> axes;
  RefFrame::Axis dir1 = axes.Dir1;
  RefFrame::Axis dir2 = axes.Dir2;

  float r = 0, theta = 0;
  for (size_t iLayer = 0; iLayer < clusters.size() - 1; iLayer++) {
    for (auto _cl1 : clusters[iLayer]) {
      for (size_t jLayer = iLayer + 1; jLayer < clusters.size(); jLayer++) {
        for (auto _cl2 : clusters[jLayer]) {

          HoughTrackStub trStub(_cl1, _cl2, dir1, dir2);
          theta = trStub.Theta();
          r = trStub.R();

          // { // DEBUG
          //   int iTheta = floor(theta / M_PI * _nThetaDiv + 0.5);
          //   int iR = floor((r / _RMax + 1) * _nRDiv / 2 + 0.5);
          //   int iBin = _debugHist->GetBin(iTheta + 1, iR + 1);
          //   _debugHist->SetBinContent(iBin, _debugHist->GetBinContent(iBin) + 1);
          // }

          int vspIndex = GetVotingIndex(r, theta);

          _votingSpace[vspIndex].emplace_back(trStub);
        }
      }
    }
  }

  // { //DEBUG
  //   _debugCanv->cd();
  //   _debugHist->Draw("colz");
  //   _debugCanv->Print("testHist.pdf");
  // }
}

template <RefFrame::View T> void HoughFinder2DAlgo::FindTracks(const HFClusters &clusters) {
  const std::string routineName("HoughFinder2DAlgo::FindTracks");
  COUT(DEBUG) << "Start!" << ENDL;

  _trackColl.clear();
  int nClusters = 0;
  for (auto layerClusters : clusters) {
    nClusters += layerClusters.size();
  }
  if (nClusters < 1)
    return;

  // _debugHist->Reset();

  // Clear up the voting space
  ClearVotingSpace();

  // Fill the voting space according to the event clusters
  FillVotingSpace<T>(clusters);
  // return;
  auto vIndex = FindCandidateTrack();
  if (vIndex < 0)
    return;

  // Group up clustered votes
  auto votes = AccumulateVotes(vIndex);

  // If the track candidate has enough votes...
  while (votes.size() >= _nVotes) {
    // Build it, clean up spurious hits, and remove the track clusters from the voting space
    BuildTrackFromVotes(votes, clusters);
    // break;
    // move to the next candidate
    vIndex = FindCandidateTrack();
    if (vIndex < 0)
      break;

    // rinse and repeat
    votes = AccumulateVotes(vIndex);
  }
}

} // namespace Herd