checkHVCorrections.py

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#!/bin/env python
#
# Copyright (C) 2002-2020 CERN for the benefit of the ATLAS collaboration
#
 
 
import ROOT
import os
 
import PlotCalibrationGains
 
import PlotCalibrationHV
 
from optparse import OptionParser
 
import numpy as np
import matplotlib.pyplot as plt
 
plt.xkcd()
 
if __name__ == "__main__":
 
  print ("Starting checkHVCorrections script")
 
  parser = OptionParser()
  
  parser.add_option("-f","--InputFile",action="store",type="string",dest="input_file_name",help="Name of input file")
  (options, args) = parser.parse_args()
 
 
  geometry_convertor = PlotCalibrationGains.L1CaloGeometryConvertor()
  receiver_gains     = PlotCalibrationGains.GainReader()
  geometry_convertor.LoadReceiverPPMMap()
 
  ROOT.gStyle.SetPalette(1)
  ROOT.gStyle.SetOptStat(111111)
  ROOT.gStyle.SetCanvasColor(10)
  
  c1 = ROOT.TCanvas('c1','Example',200,10,700,500)
  c2 = ROOT.TCanvas('c2','Example Partitions',200,10,700,500)
  c2.Divide(3,2)
 
# now define histograms
 
  h_gains_em  = PlotCalibrationGains.L1CaloMap("Eta-phi map of EM gains","#eta bin","#phi bin")
  h_gains_had = PlotCalibrationGains.L1CaloMap("Eta-phi map of HAD gains","#eta bin","#phi bin")
 
  h_gains_em_noHV  = PlotCalibrationGains.L1CaloMap("Eta-phi map of EM gains without HV corrections","#eta bin","#phi bin")
  h_gains_had_noHV = PlotCalibrationGains.L1CaloMap("Eta-phi map of HAD gains without HV corrections","#eta bin","#phi bin")
 
  h_gains_em_ratio  = PlotCalibrationGains.L1CaloMap("ratio of EM gains with and without HV corrections","#eta bin","#phi bin")
  h_gains_had_ratio = PlotCalibrationGains.L1CaloMap("ratio of HAD gains with and without HV corrections","#eta bin","#phi bin")
 
  h1D_gains_em_ratio  = PlotCalibrationGains.EmPartitionPlots("ratio of EM gains with and without HV corrections",40,0.,2.5,"gain/gain(no HV)","N")
  h1D_gains_had_ratio = PlotCalibrationGains.HadPartitionPlots("ratio of HAD gains with and without HV corrections",40,0.,2.5,"gain/gain(no HV)","N")
 
  h_corr_em  = PlotCalibrationGains.L1CaloMap("Eta-phi map of mean HV corrections in EM layer","#eta bin","#phi bin")
  h_corr_had = PlotCalibrationGains.L1CaloMap("Eta-phi map of mean HV corrections in HAD layer","#eta bin","#phi bin")
 
  h_corrGainPredictor_em  = PlotCalibrationGains.L1CaloMap("Eta-phi map of HV corrections from Gain Predictor in EM layer","#eta bin","#phi bin")
  h_corrGainPredictor_had = PlotCalibrationGains.L1CaloMap("Eta-phi map of HV corrections from Gain Predictor in HAD layer","#eta bin","#phi bin")
 
 
  h1D_corr_em  = PlotCalibrationGains.EmPartitionPlots("mean HV corrections in EM layer",40,0.,2.5,"mean HV correction","N")
  h1D_corr_had = PlotCalibrationGains.HadPartitionPlots("mean HV corrections in HAD layer",40,0.,2.5,"mean HV correction","N")
 
  h_corrHVdiff_em  = PlotCalibrationGains.L1CaloMap("(ratio-meanHV)/meanHV in EM layer","#eta bin","#phi bin")
  h_corrHVdiff_had = PlotCalibrationGains.L1CaloMap("(ratio-meanHV)/meanHV in HAD layer","#eta bin","#phi bin")
 
  h1D_corrHVdiff_em  = PlotCalibrationGains.EmPartitionPlots("(ratio-meanHV)/meanHV in EM layer",40,-0.1,0.1,"(ratio-meanHV)/meanHV","N")
  h1D_corrHVdiff_had = PlotCalibrationGains.HadPartitionPlots("(ratio-meanHV)/meanHV in HAD layer",40,-0.1,0.1,"(ratio-meanHV)/meanHV","N")
 
  h_corrHVdiffGainPredictor_em  = PlotCalibrationGains.L1CaloMap("(ratio-GainPredictor)/GainPredictor in EM layer","#eta bin","#phi bin")
  h_corrHVdiffGainPredictor_had = PlotCalibrationGains.L1CaloMap("(ratio-GainPredictor)/GainPredictor in HAD layer","#eta bin","#phi bin")
 
 
# input files are define here
 
  fileDefault = '/afs/cern.ch/work/j/juraj/public/testarea/21.0.18/CalibrationProcessing/326189_HV/energyscanresults.sqlite'
  fileNoHV    = '/afs/cern.ch/work/j/juraj/public/testarea/21.0.18/CalibrationProcessing/326189/energyscanresults.sqlite'
 
  hvCorrFile = '/afs/cern.ch/work/j/juraj/public/testarea/20.7.8.3/HVDumps/hvcorrections_9jun17.sqlite'
 
  hvGainPredictor = '/afs/cern.ch/work/j/juraj/public/testarea/20.7.8.3/HVDumps/hvUpdate_9jun17_0p.txt'
 
  strategyString = 'GainOneOvEmecFcalLowEta'       # defines receiver to TT mapping for EMB/EMEC overlap and hadronic FCAL
#  strategyString = 'GainOneOvEmbFcalHighEta'
 
 
  receiver_gains.LoadGainsSqlite(fileDefault)
  receiver_gains.LoadReferenceSqlite(fileNoHV)
 
  hv_status = PlotCalibrationHV.L1CaloHVReader(hvCorrFile)
 
  strange_channel_file = open('checkHVCorrections.txt','w')
 
  gpReceiver,gpCool,gpEta,gpPhi,gpCorrection = np.genfromtxt(hvGainPredictor,unpack=True,dtype='str')
 
  gainPredictorCorrections = {}
 
  for iii in range(len(gpReceiver)):
     gainPredictorCorrections[gpReceiver[iii]] = float(gpCorrection[iii])
 
  for i_eta in range(-49,45):
     for i_phi in range(0,64):
     
       coolEm  = geometry_convertor.getCoolEm(i_eta,i_phi)
       coolHad = geometry_convertor.getCoolHad(i_eta,i_phi)
       
 
       if not coolEm == '':                           # there is a channel for this eta-phi
       
         gain   = receiver_gains.getGain(coolEm)
         reference_gain = receiver_gains.getReferenceGain(coolEm)
         receiverEm  = geometry_convertor.getReceiverfromPPM(coolEm,strategyString)
 
         try:
           meanEmHVCorrection = (hv_status.GetMeanCorections())[receiverEm]
         except KeyError:
           meanEmHVCorrection = 1.
 
         try:
           gainPredictorEmHVCorrection = gainPredictorCorrections[receiverEm]
         except KeyError:
           gainPredictorEmHVCorrection = 1.
 
         if (not gain == '') and (not reference_gain == ''):        # both  gains should be available
 
           h_gains_em.Fill(i_eta,i_phi,gain)
           h_gains_em_noHV.Fill(i_eta,i_phi,reference_gain)
           h_corr_em.Fill(i_eta,i_phi,meanEmHVCorrection)
           h_corrGainPredictor_em.Fill(i_eta,i_phi,gainPredictorEmHVCorrection)
 
           h1D_corr_em.Fill(i_eta,meanEmHVCorrection)
           if reference_gain > 0.1 :
             if gain/reference_gain > 0.01:                            # to make histo look nicer
               h_gains_em_ratio.Fill(i_eta,i_phi,gain/reference_gain)
             h1D_gains_em_ratio.Fill(i_eta,gain/reference_gain)
 
             if gainPredictorEmHVCorrection > 0.00001:                    # just to avoid division by zero, usually >=1.
               relDifference = (gain/reference_gain - gainPredictorEmHVCorrection)/gainPredictorEmHVCorrection
 
               if relDifference > 0.001:                               # to make histo look nicer
                 h_corrHVdiffGainPredictor_em.Fill(i_eta,i_phi,relDifference)
               if relDifference > 0.05:                               #  print out interesting channels
                 strange_channel_file.write('%s %s %i %i EM  corr(RampMaker)= %.4f  corr(GainPredictor)= %.4f  diff= %.4f  \n' % (coolEm , receiverEm, \
                                             i_eta , i_phi, gain/reference_gain,gainPredictorEmHVCorrection,relDifference) )  
 
             if meanEmHVCorrection > 0.00001:                              # just to avoid division by zero, usually >=1.
               relDifference = (gain/reference_gain - meanEmHVCorrection)/meanEmHVCorrection
               if relDifference > 0.01:                               # to make histo look nicer
                 h_corrHVdiff_em.Fill(i_eta,i_phi,relDifference)
 
               h1D_corrHVdiff_em.Fill(i_eta,relDifference)
 
       if not coolHad == '':                         # there is a channel for this eta-phi
 
         gain = receiver_gains.getGain(coolHad)
         reference_gain = receiver_gains.getReferenceGain(coolHad)
         receiverHad = geometry_convertor.getReceiverfromPPM(coolHad,strategyString)
 
         try:
           meanHadHVCorrection = (hv_status.GetMeanCorections())[receiverHad]
         except KeyError:
           meanHadHVCorrection = 1.
 
         try:
           gainPredictorHadHVCorrection = gainPredictorCorrections[receiverHad]
         except KeyError:
           gainPredictorHadHVCorrection = 1.
 
 
         if (not gain == '') and (not reference_gain == ''):       # both gains should be available
 
           h_gains_had.Fill(i_eta,i_phi,gain)
           h_gains_had_noHV.Fill(i_eta,i_phi,reference_gain)
           h_corr_had.Fill(i_eta,i_phi,meanHadHVCorrection) 
           h_corrGainPredictor_had.Fill(i_eta,i_phi,gainPredictorHadHVCorrection) 
 
           h1D_corr_had.Fill(i_eta,meanHadHVCorrection)
 
           if reference_gain > 0.1 :
             if gain/reference_gain > 0.01:                            # to make histo look nicer
               h_gains_had_ratio.Fill(i_eta,i_phi,gain/reference_gain)
             h1D_gains_had_ratio.Fill(i_eta,gain/reference_gain)
 
             if gainPredictorHadHVCorrection > 0.00001:                      # to avoid accidental zeros
               relDifference = (gain/reference_gain - gainPredictorHadHVCorrection)/gainPredictorHadHVCorrection
               if relDifference > 0.001:                               # to make histo look nicer
                 h_corrHVdiffGainPredictor_had.Fill(i_eta,i_phi,relDifference)
               if relDifference > 0.05:                               # print interesting channels
                 strange_channel_file.write('%s %s %i %i HAD  corr(RampMaker)= %.4f  corr(GainPredictor)= %.4f  diff= %.4f  \n' % (coolHad,receiverHad, \
                                             i_eta , i_phi, gain/reference_gain,gainPredictorHadHVCorrection,relDifference) )  
 
 
             if meanHadHVCorrection > 0.00001:
               relDifference = (gain/reference_gain - meanHadHVCorrection)/meanHadHVCorrection
               if relDifference > 0.01:                               # to make histo look nicer
                 h_corrHVdiff_had.Fill(i_eta,i_phi,relDifference)
               h1D_corrHVdiff_had.Fill(i_eta,relDifference)
 
 
  c1.cd()
  ROOT.gPad.SetLogy(0)
 
  h_gains_em.SetMinimum(0.6)
  h_gains_em.SetMaximum(1.4)
  h_gains_em.Draw()
  c1.Print("checkHVCorrections.ps(")
 
  h_gains_had.SetMinimum(0.6)
  h_gains_had.SetMaximum(1.4)
  h_gains_had.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_gains_em_noHV.SetMinimum(0.6)
  h_gains_em_noHV.SetMaximum(1.4)
  h_gains_em_noHV.Draw()
  c1.Print("checkHVCorrections.ps")
  
  h_gains_had_noHV.SetMinimum(0.6)
  h_gains_had_noHV.SetMaximum(1.4)
  h_gains_had_noHV.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_gains_em_ratio.SetMinimum(1.05)
  h_gains_em_ratio.SetMaximum(2.2)
  h_gains_em_ratio.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_gains_had_ratio.SetMinimum(1.05)
  h_gains_had_ratio.SetMaximum(2.2)
  h_gains_had_ratio.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corr_em.SetMinimum(1.05)
  h_corr_em.SetMaximum(2.2)
  h_corr_em.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corr_had.SetMinimum(1.05)
  h_corr_had.SetMaximum(2.2)
  h_corr_had.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corrGainPredictor_em.SetMinimum(1.0)
  h_corrGainPredictor_em.SetMaximum(2.1)
  h_corrGainPredictor_em.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corrGainPredictor_had.SetMinimum(1.0)
  h_corrGainPredictor_had.SetMaximum(2.1)
  h_corrGainPredictor_had.Draw()
  c1.Print("checkHVCorrections.ps")
 
 
  h_corrHVdiff_em.SetMinimum(-.1)
  h_corrHVdiff_em.SetMaximum( .1)
  h_corrHVdiff_em.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corrHVdiff_had.SetMinimum(-.1)
  h_corrHVdiff_had.SetMaximum( .1)
  h_corrHVdiff_had.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corrHVdiffGainPredictor_em.SetMinimum(-.5)
  h_corrHVdiffGainPredictor_em.SetMaximum( .5)
  h_corrHVdiffGainPredictor_em.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corrHVdiffGainPredictor_had.SetMinimum(-.5)
  h_corrHVdiffGainPredictor_had.SetMaximum( .5)
  h_corrHVdiffGainPredictor_had.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corrHVdiffGainPredictor_em.SetMinimum(-.1)
  h_corrHVdiffGainPredictor_em.SetMaximum( .1)
  h_corrHVdiffGainPredictor_em.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corrHVdiffGainPredictor_had.SetMinimum(-.1)
  h_corrHVdiffGainPredictor_had.SetMaximum( .1)
  h_corrHVdiffGainPredictor_had.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corrHVdiffGainPredictor_em.SetMinimum(-.05)
  h_corrHVdiffGainPredictor_em.SetMaximum( .05)
  h_corrHVdiffGainPredictor_em.Draw()
  c1.Print("checkHVCorrections.ps")
 
  h_corrHVdiffGainPredictor_had.SetMinimum(-.05)
  h_corrHVdiffGainPredictor_had.SetMaximum( .05)
  h_corrHVdiffGainPredictor_had.Draw()
  c1.Print("checkHVCorrections.ps")
 
  c2.Clear()
  c2.Divide(3,2)
  for i_p in range(0,h1D_gains_em_ratio.nPartitions):
    c2.cd(i_p+1)
    if h1D_gains_em_ratio.his_partitions[i_p].GetEntries() > 0:
      ROOT.gPad.SetLogy()
    else:
      ROOT.gPad.SetLogy(0)
    h1D_gains_em_ratio.his_partitions[i_p].Draw()
  
  c2.Print("checkHVCorrections.ps")
  
  #c2.cd()
  c2.Clear()
  c2.Divide(3,2)
  for i_p in range(0,h1D_gains_had_ratio.nPartitions):
    c2.cd(i_p+1)
    if h1D_gains_had_ratio.his_partitions[i_p].GetEntries() > 0:
      ROOT.gPad.SetLogy()
    else:
      ROOT.gPad.SetLogy(0)
    h1D_gains_had_ratio.his_partitions[i_p].Draw()
  
  c2.Print("checkHVCorrections.ps")
 
  c2.Clear()
  c2.Divide(3,2)
  for i_p in range(0,h1D_corr_em.nPartitions):
    c2.cd(i_p+1)
    if h1D_corr_em.his_partitions[i_p].GetEntries() > 0:
      ROOT.gPad.SetLogy()
    else:
      ROOT.gPad.SetLogy(0)
    h1D_corr_em.his_partitions[i_p].Draw()
  
  c2.Print("checkHVCorrections.ps")
  
  #c2.cd()
  c2.Clear()
  c2.Divide(3,2)
  for i_p in range(0,h1D_corr_had.nPartitions):
    c2.cd(i_p+1)
    if h1D_corr_had.his_partitions[i_p].GetEntries() > 0:
      ROOT.gPad.SetLogy()
    else:
      ROOT.gPad.SetLogy(0)
    h1D_corr_had.his_partitions[i_p].Draw()
  
  c2.Print("checkHVCorrections.ps")
  c2.Clear()
  c2.Divide(3,2)
  for i_p in range(0,h1D_corrHVdiff_em.nPartitions):
    c2.cd(i_p+1)
    if h1D_corrHVdiff_em.his_partitions[i_p].GetEntries() > 0:
      ROOT.gPad.SetLogy()
    else:
      ROOT.gPad.SetLogy(0)
    h1D_corrHVdiff_em.his_partitions[i_p].Draw()
  
  c2.Print("checkHVCorrections.ps")
  
  #c2.cd()
  c2.Clear()
  c2.Divide(3,2)
  for i_p in range(0,h1D_corrHVdiff_had.nPartitions):
    c2.cd(i_p+1)
    if h1D_corrHVdiff_had.his_partitions[i_p].GetEntries() > 0:
      ROOT.gPad.SetLogy()
    else:
      ROOT.gPad.SetLogy(0)
    h1D_corrHVdiff_had.his_partitions[i_p].Draw()
  
  c2.Print("checkHVCorrections.ps)")
 
  os.system("ps2pdf checkHVCorrections.ps")
 
  strange_channel_file.close()