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lyDBAnalysis.py
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lyDBAnalysis.py
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import ROOT as R
import math as m
import numpy as np
import time
import os
from array import array
def Map(tf):
"""
Maps objets as dict[obj_name][0] using a TFile (tf) and TObject to browse.
"""
m = {}
for k in tf.GetListOfKeys():
n = k.GetName()
m[n] = tf.Get(n)
return m
def integral(g,xmin,xmax):
v=0
x=g.GetX()
y=g.GetY()
for i in range(0,g.GetN()):
if x[i]<xmin:
continue
if x[i]>xmax:
break
v=v+y[i]
return v
def LYAnalysis(crystal,run):
files={}
ly , dt, unixtime, b_2s_asym, b_3s_asym, b_rms, i0, i1, i2, i3 = array('d'), array('d'), array('d'), array('d'), array('d'), array('d'), array('d'), array('d'), array('d'), array('d')
for r in run['runs']:
files[r]=R.TFile.Open(args.data+"/SourceAnalysis/SourceAnalysis_"+r+".root")
objs=Map(files[r])
unixtime.append(files[r].GetCreationDate().Convert(R.kTRUE))
if not (('charge_spill0' in objs.keys()) or ('charge_spill1' in objs.keys())):
print "Bad Run (no charge histogram): "+r
continue
if not (('filteredWaveform_spill0' in objs.keys()) or ('filteredWaveform_spill1' in objs.keys())):
print "Bad Run (no waveform): "+r
continue
if not (('b_rms_spill0' in objs.keys()) or ('b_rms_spill1' in objs.keys())):
print "Bad Run (no baseline): "+r
continue
histoName='charge_spill0'
if not histoName in objs.keys():
histoName='charge_spill1'
if 'charge_spill10 'in objs.keys():
histoName='charge_spill10'
histoBaselineName='b_rms_spill0'
if not histoBaselineName in objs.keys():
histoBaselineName='b_rms_spill1'
if (objs[histoName].GetFunction('fTot').GetParameter(10)<1000) or (objs[histoName].GetFunction('fTot').GetParameter(10)>100000):
print "Bad Run (strange fit): "+r
continue
b_prob=np.array([0.01,0.05,0.32,0.5,0.68,0.95,0.99])
b_q=np.zeros([len(b_prob)])
objs[histoBaselineName].GetQuantiles(len(b_prob),b_q,b_prob)
ly.append(objs[histoName].GetFunction('fTot').GetParameter(10))
dt.append(objs['filteredWaveform_spill0'].GetFunction("f2").GetParameter(1))
i0.append(integral(objs['filteredWaveform_spill0'],0,30))
i1.append(integral(objs['filteredWaveform_spill0'],0,50))
i2.append(integral(objs['filteredWaveform_spill0'],0,300))
i3.append(integral(objs['filteredWaveform_spill0'],0,450))
b_2s_asym.append((b_q[3+2]-b_q[3])/(b_q[3]-b_q[3-2]))
b_3s_asym.append((b_q[3+3]-b_q[3])/(b_q[3]-b_q[3-3]))
b_rms.append(objs[histoBaselineName].GetRMS())
if len(ly)==0:
print "No good LY data for "+crystal
lyAvg=-9999
else:
lyAvg=sum(ly)/len(ly)
if len(dt)==0:
print "No good waveform for "+crystal
dtAvg=-9999
else:
dtAvg=sum(dt)/len(dt)
if len(b_2s_asym)==0:
print "No good waveform for "+crystal
b_2s_asymAvg=-9999
else:
b_2s_asymAvg=sum(b_2s_asym)/len(b_2s_asym)
if len(b_3s_asym)==0:
print "No good waveform for "+crystal
b_3s_asymAvg=-9999
else:
b_3s_asymAvg=sum(b_3s_asym)/len(b_3s_asym)
if len(b_rms)==0:
print "No good waveform for "+crystal
b_rmsAvg=-9999
else:
b_rmsAvg=sum(b_rms)/len(b_rms)
if len(i0)==0:
print "No good waveform for "+crystal
i0Avg=-9999
else:
i0Avg=sum(i0)/len(i0)
if len(i1)==0:
print "No good waveform for "+crystal
i1Avg=-9999
else:
i1Avg=sum(i1)/len(i1)
if len(i2)==0:
print "No good waveform for "+crystal
i2Avg=-9999
else:
i2Avg=sum(i2)/len(i2)
if len(i3)==0:
print "No good waveform for "+crystal
i3Avg=-9999
else:
i3Avg=sum(i3)/len(i3)
if len(unixtime)==0:
print "No good waveform for "+crystal
unixtimeAvg=-9999
else:
unixtimeAvg=int(sum(unixtime)/len(unixtime))
ref=array('d')
for r in run['refRuns']:
files[r]=R.TFile.Open(args.data+"/SourceAnalysis/SourceAnalysis_"+r+".root")
objs=Map(files[r])
if not (('charge_spill0' in objs.keys()) or ('charge_spill1' in objs.keys())):
print "Bad Run (no charge histogram): "+r
continue
if not (('filteredWaveform_spill0' in objs.keys()) or ('filteredWaveform_spill1' in objs.keys())):
print "Bad Run (no waveform): "+r
continue
histoName='charge_spill0'
if not histoName in objs.keys():
histoName='charge_spill1'
if (objs[histoName].GetFunction('fTot').GetParameter(10)<1000) or (objs[histoName].GetFunction('fTot').GetParameter(10)>100000):
print "Bad Run (strange fit): "+r
continue
ref.append(objs[histoName].GetFunction('fTot').GetParameter(10))
if len(ref)==0:
print "No good ref data for this crystal!"
refAvg=-9999
else:
refAvg=sum(ref)/len(ref)
# refAvg=11000.
ledAvg=LEDAnalysis(crystal,run['ledRuns'])
return { 'ly':lyAvg, 'dt':dtAvg, 'b_2s_asym':b_2s_asymAvg, 'b_3s_asym':b_3s_asymAvg, 'b_rms':b_rmsAvg, 'ref':refAvg, 'pe':ledAvg, 'time':unixtimeAvg, 'i0':i0Avg, 'i1':i1Avg, 'i2':i2Avg, 'i3':i3Avg }
def LEDAnalysis(crystal,ledRuns):
files={}
pe=array('d')
for r in ledRuns:
files[r]=R.TFile.Open(args.data+"/SinglePEAnalysis/"+r+"_simul_out.root")
objs=Map(files[r])
if not 'PMT_0' in objs.keys():
print "Bad LED Run (no fit function): "+r
continue
if ( abs(objs['PMT_0'].GetParameter(4)-35)<0.01 ):
print "Bad LED Run (fit not converging): "+r
continue
if ( objs['PMT_4'].GetParameter(1) < .5 ):
print "Bad LED Run (small LED amplitude): "+r
continue
pe.append(objs['PMT_0'].GetParameter(2))
if len(pe)==0:
print "No good LED data for "+crystal
peAvg=-9999
else:
peAvg=sum(pe)/len(pe)
return peAvg
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--output',dest='output')
parser.add_argument('--db',dest='db')
parser.add_argument('--data',dest='data')
parser.add_argument('--json',dest='json')
args = parser.parse_args()
import json
crystalsDB=json.load(open(args.db))
#exec "from %s import crystalsDB" % args.db
crystalsDB_withData = {}
for crystal,crystalInfo in crystalsDB.items():
print "Analysing crystal "+crystal
for runInfo in crystalInfo['runs']:
tag=runInfo['tag']
lyData=LYAnalysis(crystal,runInfo)
lyData.update({'tag':"%s"%tag})
data={}
data.update(crystalInfo)
data.pop('runs',None)
data.update(lyData)
crystalsDB_withData['%s_%s'%(crystal,tag)]=data
#Save CSV using Pandas DataFrame
import pandas as pd
df=pd.DataFrame.from_dict(crystalsDB_withData,orient='index')
#df=df.drop(columns=['runs'])
print(df)
df.to_csv(args.output,header=False)
if (args.json):
with open(args.json, 'w') as file:
file.write(json.dumps(json.loads(df.to_json(orient='records')), indent=4))