NoiseMap.h

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// Copyright 2019-2020 CERN and copyright holders of ALICE O2.
// See https://alice-o2.web.cern.ch/copyright for details of the copyright holders.
// All rights not expressly granted are reserved.
//
// This software is distributed under the terms of the GNU General Public
// License v3 (GPL Version 3), copied verbatim in the file "COPYING".
//
// In applying this license CERN does not waive the privileges and immunities
// granted to it by virtue of its status as an Intergovernmental Organization
// or submit itself to any jurisdiction.
 
#ifndef ALICEO2_ITSMFT_NOISEMAP_H
#define ALICEO2_ITSMFT_NOISEMAP_H
 
#include "Rtypes.h" // for Double_t, ULong_t, etc
#include <iostream>
#include <climits>
#include <cassert>
#include <vector>
#include <map>
#include "Framework/Logger.h"
#include "gsl/span"
 
namespace o2
{
 
namespace itsmft
{
 
class CompClusterExt;
 
 
class NoiseMap
{
 
 public:
  NoiseMap(std::vector<std::map<int, int>>& noise) { mNoisyPixels.swap(noise); }
 
  NoiseMap() = default;
  NoiseMap(int nchips)
  {
    mNoisyPixels.assign(nchips, std::map<int, int>());
  }
  ~NoiseMap() = default;
 
  float getNoiseLevel(int chip, int row, int col) const
  {
    assert(chip < (int)mNoisyPixels.size());
    const auto keyIt = mNoisyPixels[chip].find(getKey(row, col));
    if (keyIt != mNoisyPixels[chip].end()) {
      return keyIt->second;
    }
    return 0;
  }
 
  void increaseNoiseCount(int chip, int row, int col)
  {
    assert(chip < (int)mNoisyPixels.size());
    mNoisyPixels[chip][getKey(row, col)]++;
  }
 
  void increaseNoiseCount(int chip, const std::vector<int>& rowcolKey)
  {
    assert(chip < (int)mNoisyPixels.size());
    auto& ch = mNoisyPixels[chip];
    for (const auto k : rowcolKey) {
      ch[k]++;
    }
  }
 
  int dumpAboveThreshold(int t = 3) const
  {
    int n = 0;
    auto chipID = mNoisyPixels.size();
    while (chipID--) {
      const auto& map = mNoisyPixels[chipID];
      for (const auto& pair : map) {
        if (pair.second <= t) {
          continue;
        }
        n++;
        auto key = pair.first;
        auto row = key2Row(key);
        auto col = key2Col(key);
        std::cout << "chip, row, col, noise: " << chipID << ' ' << row << ' ' << col << ' ' << pair.second << '\n';
      }
    }
    return n;
  }
  int dumpAboveProbThreshold(float p = 1e-7) const
  {
    return dumpAboveThreshold(p * mNumOfStrobes);
  }
 
  void applyProbThreshold(float t, long int n, float relErr = 0.2f, int minChipID = 0, int maxChipID = 24119)
  {
    // Remove from the maps all pixels with the firing probability below the threshold
    // Apply the cut only for chips between minChipID and maxChipID (included)
    if (n < 1) {
      LOGP(alarm, "Cannot apply threshold with {} ROFs scanned", n);
      return;
    }
    mProbThreshold = t;
    mNumOfStrobes = n;
    float minFiredForErr = 0.f;
    if (relErr > 0) {
      minFiredForErr = relErr * relErr - 1. / n;
      if (minFiredForErr <= 0.f) {
        LOGP(alarm, "Noise threshold {} with relative error {} is not reachable with {} ROFs processed, mask all permanently fired pixels", t, relErr, n);
        minFiredForErr = n;
      } else {
        minFiredForErr = 1. / minFiredForErr;
      }
    }
    int minFired = std::ceil(std::max(t * mNumOfStrobes, minFiredForErr)); // min number of fired pixels exceeding requested threshold
    auto req = getMinROFs(t, relErr);
    if (n < req) {
      mProbThreshold = float(minFired) / n;
      LOGP(alarm, "Requested relative error {} with prob.threshold {} needs > {} ROFs, {} provided: pixels with noise >{} will be masked", relErr, t, req, n, mProbThreshold);
    }
 
    int currChipID = 0;
    for (auto& map : mNoisyPixels) {
      if (currChipID < minChipID || currChipID > maxChipID) { // chipID range
        currChipID++;
        continue;
      }
      for (auto it = map.begin(); it != map.end();) {
        if (it->second < minFired) {
          it = map.erase(it);
        } else {
          ++it;
        }
      }
      currChipID++;
    }
  }
  float getProbThreshold() const { return mProbThreshold; }
  long int getNumOfStrobes() const { return mNumOfStrobes; }
 
  bool isNoisy(int chip, int row, int col) const
  {
    assert(chip < (int)mNoisyPixels.size());
    return (mNoisyPixels[chip].find(getKey(row, col)) != mNoisyPixels[chip].end());
  }
 
  bool isNoisyOrFullyMasked(int chip, int row, int col) const
  {
    assert(chip < (int)mNoisyPixels.size());
    return isNoisy(chip, row, col) || isFullChipMasked(chip);
  }
 
  bool isNoisy(int chip) const
  {
    assert(chip < (int)mNoisyPixels.size());
    return !mNoisyPixels[chip].empty();
  }
 
  // Methods required by the calibration framework
  void print();
  void fill(const gsl::span<const CompClusterExt> data);
 
  const std::map<int, int>* getChipMap(int chip) const { return chip < (int)mNoisyPixels.size() ? &mNoisyPixels[chip] : nullptr; }
 
  std::map<int, int>& getChip(int chip) { return mNoisyPixels[chip]; }
  const std::map<int, int>& getChip(int chip) const { return mNoisyPixels[chip]; }
 
  void maskFullChip(int chip, bool cleanNoisyPixels = false)
  {
    if (cleanNoisyPixels) {
      resetChip(chip);
    }
    increaseNoiseCount(chip, -1, -1);
  }
 
  bool isFullChipMasked(int chip) const
  {
    return isNoisy(chip, -1, -1);
  }
 
  void resetChip(int chip)
  {
    assert(chip < (int)mNoisyPixels.size());
    mNoisyPixels[chip].clear();
  }
 
  static long getMinROFs(float t, float relErr)
  {
    // calculate min number of ROFs needed to reach threshold t with relative error relErr
    relErr = relErr >= 0.f ? relErr : 0.1;
    t = t >= 0.f ? t : 1e-6;
    return std::ceil((1. + 1. / t) / (relErr * relErr));
  }
 
  NoiseMap merge(const NoiseMap* prev)
  {
    int incre = 0;
    for (size_t i = 0; i < (int)mNoisyPixels.size(); ++i) {
      for (const auto& prev_np : prev->mNoisyPixels[i]) { // only enters this for loop if the "i" chip exists.
        if (mNoisyPixels[i].find(prev_np.first) == mNoisyPixels[i].end()) {
          mNoisyPixels[i][prev_np.first] = prev_np.second;
          incre++;
        }
      } // end of for loop on elements of previous noise map
    } // end of for loop on i (chip ID)
    return (mNoisyPixels);
  } // end of void merge
 
  size_t size() const { return mNoisyPixels.size(); }
  void setNumOfStrobes(long n) { mNumOfStrobes = n; }
  void addStrobes(long n) { mNumOfStrobes += n; }
  long getNumberOfStrobes() const { return mNumOfStrobes; }
  static int getKey(int row, int col) { return (row << SHIFT) + col; }
  static int key2Row(int key) { return key >> SHIFT; }
  static int key2Col(int key) { return key & MASK; }
 
 private:
  static constexpr int SHIFT = 10, MASK = (0x1 << SHIFT) - 1;
  std::vector<std::map<int, int>> mNoisyPixels; 
  long int mNumOfStrobes = 0;                   
  float mProbThreshold = 0;                     
 
  ClassDefNV(NoiseMap, 2);
};
} // namespace itsmft
} // namespace o2
 
#endif /* ALICEO2_ITSMFT_NOISEMAP_H */