Belle II Software development
eclAutocovarianceCalibrationC3Algorithm.cc
1/**************************************************************************
2 * basf2 (Belle II Analysis Software Framework) *
3 * Author: The Belle II Collaboration *
4 * *
5 * See git log for contributors and copyright holders. *
6 * This file is licensed under LGPL-3.0, see LICENSE.md. *
7 **************************************************************************/
8
9/* Own header. */
10#include <ecl/calibration/eclAutocovarianceCalibrationC3Algorithm.h>
11
12/* ECL headers. */
13#include <ecl/dataobjects/ECLElementNumbers.h>
14#include <ecl/dbobjects/ECLAutoCovariance.h>
15
16/* ROOT headers. */
17#include <TFile.h>
18#include <TGraph.h>
19#include <TH2I.h>
20#include"TMatrixDSym.h"
21#include"TDecompChol.h"
22
23using namespace Belle2;
24using namespace ECL;
25
28 CalibrationAlgorithm("eclAutocovarianceCalibrationC3Collector")
29{
31 "Computes the covariance matrix for each crystal"
32 );
33}
34
36{
37
38
40 gROOT->SetBatch();
41
43 std::vector<double> cryIDs;
44 std::vector<double> invertStatusVector;
45 std::vector<double> noiseMatrix00Vector;
46 std::vector<double> totalCountsVector;
47
50 auto CovarianceMatrixInfoVsCrysID = getObjectPtr<TH2F>("CovarianceMatrixInfoVsCrysID");
51
52 ECLAutoCovariance* Autocovariances = new ECLAutoCovariance();
53
54 for (int ID = 0; ID < ECLElementNumbers::c_NCrystals; ID++) {
55
56 float totalCounts = CovarianceMatrixInfoVsCrysID->GetBinContent(CovarianceMatrixInfoVsCrysID->GetBin(ID + 1,
58
59 if (totalCounts < m_TotalCountsThreshold) {
60 B2INFO("eclAutocovarianceCalibrationC3Algorithm: warning total entries for cell ID " << ID + 1 << " is only: " << totalCounts <<
61 " Requirement is m_TotalCountsThreshold: " << m_TotalCountsThreshold);
63 return c_NotEnoughData;
64 }
65
66 TMatrixDSym NoiseMatrix;
67 NoiseMatrix.ResizeTo(m_numberofADCPoints, m_numberofADCPoints);
68 for (int i = 0; i < m_numberofADCPoints; i++) {
69 for (int j = 0; j < m_numberofADCPoints; j++) {
70 int index = abs(i - j);
71 NoiseMatrix(i, j) = float(CovarianceMatrixInfoVsCrysID->GetBinContent(CovarianceMatrixInfoVsCrysID->GetBin(ID + 1,
72 index + 1))) / (totalCounts - 1) / (float(m_numberofADCPoints - index));
73 }
74 }
75
76 double tempAutoCov[m_numberofADCPoints];
77 for (int i = 0; i < m_numberofADCPoints; i++) tempAutoCov[i] = NoiseMatrix(0, i);
78
79 TDecompChol dc(NoiseMatrix);
80 bool InvertStatus = dc.Invert(NoiseMatrix);
81 if (InvertStatus == false && ID > 0) {
82 B2INFO("eclAutocovarianceCalibrationC3Algorithm iD InvertStatus [0][0] totalCounts: " << ID << " " << InvertStatus << " " <<
83 NoiseMatrix(0, 0) << " " << totalCounts);
84 B2INFO("eclAutocovarianceCalibrationC3Algorithm Setting ID " << ID << " Autocovariance to Autocovariance from ID " << ID - 1);
85 B2INFO("eclAutocovarianceCalibrationC3Algorithm B: " << tempAutoCov[0]);
86 Autocovariances->getAutoCovariance(ID + 1 - 1, tempAutoCov);
87 B2INFO("eclAutocovarianceCalibrationC3Algorithm A: " << tempAutoCov[0]);
88 }
89
90 Autocovariances->setAutoCovariance(ID + 1, tempAutoCov);
91
92 cryIDs.push_back(ID + 1);
93 invertStatusVector.push_back(InvertStatus);
94 noiseMatrix00Vector.push_back(NoiseMatrix(0, 0));
95 totalCountsVector.push_back(totalCounts);
96
97 }
98
100 saveCalibration(Autocovariances, "ECLAutoCovariance");
101
103 auto ginvertStatusVector = new TGraph(cryIDs.size(), cryIDs.data(), invertStatusVector.data());
104 ginvertStatusVector->SetName("ginvertStatusVector");
105 ginvertStatusVector->SetMarkerStyle(20);
106 auto gnoiseMatrix00Vector = new TGraph(cryIDs.size(), cryIDs.data(), noiseMatrix00Vector.data());
107 gnoiseMatrix00Vector->SetName("gnoiseMatrix00Vector");
108 gnoiseMatrix00Vector->SetMarkerStyle(20);
109 auto gtotalCountsVector = new TGraph(cryIDs.size(), cryIDs.data(), totalCountsVector.data());
110 gtotalCountsVector->SetName("gtotalCountsVector");
111 gtotalCountsVector->SetMarkerStyle(20);
112
114 TString fName = m_outputName;
115 TDirectory::TContext context;
116 TFile* histfile = new TFile(fName, "recreate");
117 histfile->cd();
118 ginvertStatusVector->Write();
119 gnoiseMatrix00Vector->Write();
120 gtotalCountsVector->Write();
121 histfile->Close();
122 delete histfile;
123
124 return c_OK;
125}
Base class for calibration algorithms.
void saveCalibration(TClonesArray *data, const std::string &name)
Store DBArray payload with given name with default IOV.
void setDescription(const std::string &description)
Set algorithm description (in constructor)
EResult
The result of calibration.
@ c_OK
Finished successfully =0 in Python.
@ c_NotEnoughData
Needs more data =2 in Python.
Covariance matrices for offline ECL waveform fit.
void getAutoCovariance(const int cellID, double acov[31]) const
Get auto covariance for a channel.
void setAutoCovariance(const int cellID, const double acov[31])
Set auto covariance for a channel.
int m_TotalCountsThreshold
min number of counts needed to compute calibration
virtual EResult calibrate() override
..Run algorithm on events
const int c_NCrystals
Number of crystals.
Abstract base class for different kinds of events.