Belle II Software  release-05-02-19
SVDCoGTimeCalibrationAlgorithm.cc
1 /**************************************************************************
2  * BASF2 (Belle Analysis Framework 2) *
3  * Copyright(C) 2017 - Belle II Collaboration *
4  * *
5  * Author: The Belle II Collaboration *
6  * Contributors: Luigi Corona, Giulia Casarosa *
7  * *
8  * This software is provided "as is" without any warranty. *
9  **************************************************************************/
10 #include <svd/calibration/SVDCoGTimeCalibrationAlgorithm.h>
11 
12 #include <svd/dbobjects/SVDCoGCalibrationFunction.h>
13 #include <svd/calibration/SVDCoGTimeCalibrations.h>
14 
15 #include <TF1.h>
16 #include <TProfile.h>
17 #include <TH2F.h>
18 #include <framework/logging/Logger.h>
19 #include <iostream>
20 #include <TString.h>
21 #include <TFitResult.h>
22 
23 using namespace std;
24 using namespace Belle2;
25 
26 SVDCoGTimeCalibrationAlgorithm::SVDCoGTimeCalibrationAlgorithm(const std::string& str) :
27  CalibrationAlgorithm("SVDTimeCalibrationCollector")
28 {
29  setDescription("SVDCoGTimeCalibration calibration algorithm");
30  m_id = str;
31 }
32 
34 {
35 
36  gROOT->SetBatch(true);
37 
38  int ladderOfLayer[4] = {7, 10, 12, 16};
39  int sensorOnLayer[4] = {2, 3, 4, 5};
40 
41  auto timeCal = new Belle2::SVDCoGCalibrationFunction();
42  auto payload = new Belle2::SVDCoGTimeCalibrations::t_payload(*timeCal, m_id);
43 
44  std::unique_ptr<TF1> pol1(new TF1("pol1", "[0] + [1]*x", -10, 80));
45  pol1->SetParameters(-40, 0.9);
46  std::unique_ptr<TF1> pol3(new TF1("pol3", "[0] + [1]*x + [2]*x*x + [3]*x*x*x", -10, 80));
47  pol3->SetParLimits(0, -200, 0);
48  pol3->SetParLimits(1, 0, 10);
49  pol3->SetParLimits(2, -1, 0);
50  pol3->SetParLimits(3, 0, 1);
51  std::unique_ptr<TF1> pol5(new TF1("pol5", "[0] + [1]*x + [2]*x*x + [3]*x*x*x + [4]*x*x*x*x + [5]*x*x*x*x*x", -100, 100));
52  pol5->SetParameters(-50, 1.5, 0.01, 0.0001, 0.00001, 0.000001);
53 
54  FileStat_t info;
55  int cal_rev = 1;
56  while (gSystem->GetPathInfo(Form("algorithm_6SampleCoG_output_rev_%d.root", cal_rev), info) == 0)
57  cal_rev++;
58  std::unique_ptr<TFile> f(new TFile(Form("algorithm_6SampleCoG_output_rev_%d.root", cal_rev), "RECREATE"));
59 
60  auto m_tree = new TTree(Form("rev_%d", cal_rev), "RECREATE");
61  int layer_num, ladder_num, sensor_num, view, ndf;
62  float a, b, c, d, a_err, b_err, c_err, d_err, chi2, p;
63  m_tree->Branch("layer", &layer_num, "layer/I");
64  m_tree->Branch("ladder", &ladder_num, "ladder/I");
65  m_tree->Branch("sensor", &sensor_num, "sensor/I");
66  m_tree->Branch("isU", &view, "isU/I");
67  m_tree->Branch("a", &a, "a/F");
68  m_tree->Branch("b", &b, "b/F");
69  m_tree->Branch("c", &c, "c/F");
70  m_tree->Branch("d", &d, "d/F");
71  m_tree->Branch("a_err", &a_err, "a_err/F");
72  m_tree->Branch("b_err", &b_err, "b_err/F");
73  m_tree->Branch("c_err", &c_err, "c_err/F");
74  m_tree->Branch("d_err", &d_err, "d_err/F");
75  m_tree->Branch("chi2", &chi2, "chi2/F");
76  m_tree->Branch("ndf", &ndf, "ndf/I");
77  m_tree->Branch("p", &p, "p/F");
78 
79  for (int layer = 0; layer < 4; layer++) {
80  layer_num = layer + 3;
81  for (int ladder = 0; ladder < (int)ladderOfLayer[layer]; ladder++) {
82  ladder_num = ladder + 1;
83  for (int sensor = 0; sensor < (int)sensorOnLayer[layer]; sensor++) {
84  sensor_num = sensor + 1;
85  for (view = 1; view > -1; view--) {
86  char side = 'U';
87  if (view == 0)
88  side = 'V';
89  auto hEventT0vsCoG = getObjectPtr<TH2F>(Form("eventT0vsCoG__L%dL%dS%d%c", layer_num, ladder_num, sensor_num, side));
90  auto hEventT0 = getObjectPtr<TH1F>(Form("eventT0__L%dL%dS%d%c", layer_num, ladder_num, sensor_num, side));
91  auto hEventT0nosync = getObjectPtr<TH1F>(Form("eventT0nosync__L%dL%dS%d%c", layer_num, ladder_num, sensor_num, side));
92  B2INFO("Histogram: " << hEventT0vsCoG->GetName() <<
93  " Entries (n. clusters): " << hEventT0vsCoG->GetEntries());
94  if (layer_num == 3 && hEventT0vsCoG->GetEntries() < m_minEntries) {
95  B2INFO("Histogram: " << hEventT0vsCoG->GetName() <<
96  " Entries (n. clusters): " << hEventT0vsCoG->GetEntries() <<
97  " Entries required: " << m_minEntries);
98  B2WARNING("Not enough data, adding one run to the collector");
99  f->Close();
100  gSystem->Unlink(Form("algorithm_6SampleCoG_output_rev_%d.root", cal_rev));
101  return c_NotEnoughData;
102  }
103  for (int i = 1; i <= hEventT0vsCoG->GetNbinsX(); i++) {
104  for (int j = 1; j <= hEventT0vsCoG->GetNbinsY(); j++) {
105  if (hEventT0vsCoG->GetBinContent(i, j) < max(2, int(hEventT0vsCoG->GetEntries() * 0.001))) {
106  hEventT0vsCoG->SetBinContent(i, j, 0);
107  }
108  }
109  }
110  TProfile* pfx = hEventT0vsCoG->ProfileX();
111  std::string name = "pfx_" + std::string(hEventT0vsCoG->GetName());
112  pfx->SetName(name.c_str());
113  TFitResultPtr tfr = pfx->Fit("pol3", "RQS");
114  double par[4];
115  pol3->GetParameters(par);
117  /*
118  pfx->Fit("pol1", "RQ");
119  double par[4];
120  pol1->GetParameters(par);
121  par[2] = 0;
122  par[3] = 0;
123  */
124  // double meanT0 = hEventT0->GetMean();
125  // double meanT0NoSync = hEventT0nosync->GetMean();
126  timeCal->set_current(1);
127  // timeCal->set_current(2);
128  timeCal->set_pol3parameters(par[0], par[1], par[2], par[3]);
129  payload->set(layer_num, ladder_num, sensor_num, bool(view), 1, *timeCal);
130  f->cd();
131  hEventT0->Write();
132  hEventT0vsCoG->Write();
133  hEventT0nosync->Write();
134  pfx->Write();
135 
136  a = par[0]; b = par[1]; c = par[2]; d = par[3];
137  a_err = tfr->ParError(0); b_err = tfr->ParError(1); c_err = tfr->ParError(2); d_err = tfr->ParError(3);
138  chi2 = tfr->Chi2();
139  ndf = tfr->Ndf();
140  p = tfr->Prob();
141  m_tree->Fill();
142 
143  }
144  }
145  }
146  }
147  m_tree->Write();
148  f->Close();
149  saveCalibration(payload, "SVDCoGTimeCalibrations");
150 
151  //delete f;
152 
153  // probably not needed - would trigger re-doing the collection
154  // if ( ... too large corrections ... ) return c_Iterate;
155  return c_OK;
156 }
157 
158 bool SVDCoGTimeCalibrationAlgorithm::isBoundaryRequired(const Calibration::ExpRun& currentRun)
159 {
160  float meanRawTimeL3V = 0;
161  // auto eventT0Hist = getObjectPtr<TH1F>("hEventT0FromCDC");
162  auto rawTimeL3V = getObjectPtr<TH1F>("hRawTimeL3V");
163  // float meanEventT0 = eventT0Hist->GetMean();
164  if (!rawTimeL3V) {
166  meanRawTimeL3V = m_previousRawTimeMeanL3V.value();
167  } else {
168  if (rawTimeL3V->GetEntries() > m_minEntries)
169  meanRawTimeL3V = rawTimeL3V->GetMean();
170  else {
172  meanRawTimeL3V = m_previousRawTimeMeanL3V.value();
173  }
174  }
176  B2INFO("Setting start payload boundary to be the first run ("
177  << currentRun.first << "," << currentRun.second << ")");
178  m_previousRawTimeMeanL3V.emplace(meanRawTimeL3V);
179 
180  return true;
181  } else if (abs(meanRawTimeL3V - m_previousRawTimeMeanL3V.value()) > m_allowedTimeShift) {
182  B2INFO("Histogram mean has shifted from " << m_previousRawTimeMeanL3V.value()
183  << " to " << meanRawTimeL3V << ". We are requesting a new payload boundary for ("
184  << currentRun.first << "," << currentRun.second << ")");
185  m_previousRawTimeMeanL3V.emplace(meanRawTimeL3V);
186  return true;
187  } else {
188  return false;
189  }
190 }
Belle2::SVDCoGTimeCalibrationAlgorithm::isBoundaryRequired
virtual bool isBoundaryRequired(const Calibration::ExpRun &currentRun) override
If the event T0 changes significantly return true.
Definition: SVDCoGTimeCalibrationAlgorithm.cc:158
Belle2::CalibrationAlgorithm::saveCalibration
void saveCalibration(TClonesArray *data, const std::string &name)
Store DBArray payload with given name with default IOV.
Definition: CalibrationAlgorithm.cc:290
Belle2::SVDCoGTimeCalibrationAlgorithm::m_allowedTimeShift
float m_allowedTimeShift
Allowed EventT0 shift.
Definition: SVDCoGTimeCalibrationAlgorithm.h:75
Belle2::CalibrationAlgorithm::c_OK
@ c_OK
Finished successfuly =0 in Python.
Definition: CalibrationAlgorithm.h:51
Belle2::CalibrationAlgorithm::setDescription
void setDescription(const std::string &description)
Set algorithm description (in constructor)
Definition: CalibrationAlgorithm.h:331
Belle2::SVDCoGTimeCalibrationAlgorithm::m_previousRawTimeMeanL3V
std::optional< float > m_previousRawTimeMeanL3V
CoG time mean of the previous run for V side of layer 3.
Definition: SVDCoGTimeCalibrationAlgorithm.h:73
Belle2::SVDCoGTimeCalibrations::t_payload
SVDCalibrationsBase< SVDCalibrationsScalar< SVDCoGCalibrationFunction > > t_payload
typedef for the SVDCoGCalibrationFunction payload of all SVD sensors
Definition: SVDCoGTimeCalibrations.h:44
Belle2
Abstract base class for different kinds of events.
Definition: MillepedeAlgorithm.h:19
Belle2::SVDCoGTimeCalibrationAlgorithm::calibrate
virtual EResult calibrate() override
Run algo on data.
Definition: SVDCoGTimeCalibrationAlgorithm.cc:33
Belle2::SVDCoGTimeCalibrationAlgorithm::m_id
std::string m_id
Parameter given to set the UniqueID of the payload.
Definition: SVDCoGTimeCalibrationAlgorithm.h:72
Belle2::SVDCoGTimeCalibrationAlgorithm::m_minEntries
float m_minEntries
Set the minimun number of entries required in the histograms of layer 3.
Definition: SVDCoGTimeCalibrationAlgorithm.h:76
Belle2::CalibrationAlgorithm::EResult
EResult
The result of calibration.
Definition: CalibrationAlgorithm.h:50
Belle2::CalibrationAlgorithm::c_NotEnoughData
@ c_NotEnoughData
Needs more data =2 in Python.
Definition: CalibrationAlgorithm.h:53
Belle2::CalibrationAlgorithm
Base class for calibration algorithms.
Definition: CalibrationAlgorithm.h:47
Belle2::SVDCoGCalibrationFunction
class to contain the CoG Time calibrations
Definition: SVDCoGCalibrationFunction.h:33