def trgForRange(schema,inputRange,trgbitname=None,trgbitnamepattern=None,withL1Count=False,withPrescale=False,tableName=None,branchName=None):
'''
input :
inputRange {run:[cmsls]} (required)
trgbitname exact match trgbitname (optional)
trgbitnamepattern match trgbitname (optional)
tableName : trgdata table name
branchName : data version
output
result {run:[cmslsnum,deadfrac,deadtimecount,bitzero_count,bitzero_prescale,[(bitname,prescale,counts)]]}
'''
#if tableName is None:
# tableName=nameDealer.trgdataTableName()
#if branchName is None:
# branchName='DATA'
result={}
withprescaleblob=True
withtrgblob=True
for run in inputRange.keys():
lslist=inputRange[run]
if lslist is not None and len(lslist)==0:
result[run]=[]#if no LS is selected for a run
continue
trgdataid=dataDML.guessTrgDataIdByRunInBranch(schema,run)
if trgdataid is None:
result[run]=None
continue #run non exist
trgdata=dataDML.trgLSById(schema,trgdataid,trgbitname=trgbitname,trgbitnamepattern=trgbitnamepattern,withL1Count=withL1Count,withPrescale=withPrescale)
#(runnum,{cmslsnum:[deadtimecount(0),bitzerocount(1),bitzeroprescale(2),deadfrac(3),[(bitname,trgcount,prescale)](4)]})
result[run]=[]
if trgdata and trgdata[1]:
lsdict={}
for cmslsnum in sorted(trgdata[1]):
if lslist is not None and cmslsnum not in lslist:
continue
lsdata=[]
deadtimecount=trgdata[1][cmslsnum][0]
bitzerocount=trgdata[1][cmslsnum][1]
bitzeroprescale=trgdata[1][cmslsnum][2]
#if float(bitzerocount)*float(bitzeroprescale)==0.0:
# deadfrac=1.0
#else:
# deadfrac=float(deadtimecount)/(float(bitzerocount)*float(bitzeroprescale))
deadfrac=trgdata[1][cmslsnum][3]
if deadfrac<0 or deadfrac>1.0:
deadfrac=1.0
allbitsinfo=trgdata[1][cmslsnum][4]
lsdata.append(cmslsnum)
lsdata.append(deadfrac)
lsdata.append(deadtimecount)
lsdata.append(bitzerocount)
lsdata.append(bitzeroprescale)
lsdata.append(allbitsinfo)
result[run].append(lsdata)
return result
def trgForIds(schema,irunlsdict,dataidmap,trgbitname=None,trgbitnamepattern=None,withL1Count=False,withPrescale=False):
'''
input :
irunlsdict {run:[cmsls]} (required)
dataidmap: {run:(lumiid,trgid,hltid)}
trgbitname exact match trgbitname (optional)
trgbitnamepattern match trgbitname (optional)
output
result {run:[[cmslsnum(0),deadfrac(1),deadtimecount(2),bitzero_count(3),bitzero_prescale(4),[(bitname,prescale,counts,mask)](5)]]}
'''
result={}
for run in irunlsdict.keys():
result[run]=[]
lslist=irunlsdict[run]
if lslist is not None and len(lslist)==0:
#if no LS is selected for a run
continue
if run not in dataidmap:
continue
trgdataid=dataidmap[run][1]
if trgdataid is None:
result[run]=None
continue #if run non exist
if trgdataid==0:
continue
trgdata=dataDML.trgLSById(schema,trgdataid,trgbitname=trgbitname,trgbitnamepattern=trgbitnamepattern,withL1Count=withL1Count,withPrescale=withPrescale)
#(runnum,{cmslsnum:[deadtimecount(0),bitzerocount(1),bitzeroprescale(2),deadfrac(3),[(bitname,trgcount,prescale)](4)]})
if trgdata and trgdata[1]:
lsdict={}
for cmslsnum in sorted(trgdata[1]):
if lslist is not None and cmslsnum not in lslist:
continue
lsdata=[]
#print trgdata[1][cmslsnum]
deadtimecount=trgdata[1][cmslsnum][0]
#bitzerocount=trgdata[1][cmslsnum][1]
#bitzeroprescale=trgdata[1][cmslsnum][2]
bitzerocount=0
bitzeroprescale=0
deadfrac=trgdata[1][cmslsnum][3]
if deadfrac<0 or deadfrac>1.0:
deadfrac=1.0
allbitsinfo=trgdata[1][cmslsnum][4]
lsdata.append(cmslsnum)
lsdata.append(deadfrac)
lsdata.append(deadtimecount)
lsdata.append(bitzerocount)
lsdata.append(bitzeroprescale)
lsdata.append(allbitsinfo)
result[run].append(lsdata)
return result
runsummary = dataDML.runsummary(schema, myrun)
print(runsummary)
normid = dataDML.guessnormIdByContext(schema, 'PROTPHYS', 3500)
normval = dataDML.luminormById(schema, normid)[2]
print('norm in use ', normval)
(lumidataid, trgdataid,
hltdataid) = dataDML.guessDataIdByRun(schema, myrun)
print('all dataids ', lumidataid, trgdataid, hltdataid)
(runnum, lumiLSdata) = dataDML.lumiLSById(schema, lumidataid)
lumils = sorted(lumiLSdata.keys())
for lsnum in lumils:
print('lumilsnum,cmslsnum,instlumi ', lsnum, lumiLSdata[lsnum][0],
lumiLSdata[lsnum][1] * normval)
(runnum, trgLSdata) = dataDML.trgLSById(schema, trgdataid)
cmsls = trgLSdata.keys()
cmsls.sort()
for lsnum in cmsls:
print('cmslsnum,deadtime,bizerocount,bitzeroprescale,deadfrac ', lsnum,
trgLSdata[lsnum][0], trgLSdata[lsnum][1], trgLSdata[lsnum][2],
trgLSdata[lsnum][3])
[runnum, datasource, npath,
pathnames] = dataDML.hltRunById(schema, hltdataid)
print('npath,pathnames ', npath, pathnames)
pathnameList = pathnames.split(',')
(runnum, hltLSdata) = dataDML.hltLSById(schema, hltdataid)
cmsls = hltLSdata.keys()
cmsls.sort()
for lsnum in cmsls:
prescaleblob = hltLSdata[lsnum][0]
myrun=runs[0]
runsummary=dataDML.runsummary(schema,myrun)
print runsummary
normid=dataDML.guessnormIdByContext(schema,'PROTPHYS',3500)
normval=dataDML.luminormById(schema,normid)[2]
print 'norm in use ',normval
(lumidataid,trgdataid,hltdataid)=dataDML.guessDataIdByRun(schema,myrun)
print 'all dataids ',lumidataid,trgdataid,hltdataid
(runnum,lumiLSdata)=dataDML.lumiLSById(schema,lumidataid)
lumils=lumiLSdata.keys()
lumils.sort()
for lsnum in lumils:
print 'lumilsnum,cmslsnum,instlumi ',lsnum,lumiLSdata[lsnum][0],lumiLSdata[lsnum][1]*normval
(runnum,trgLSdata)=dataDML.trgLSById(schema,trgdataid)
cmsls=trgLSdata.keys()
cmsls.sort()
for lsnum in cmsls:
print 'cmslsnum,deadtime,bizerocount,bitzeroprescale,deadfrac ',lsnum,trgLSdata[lsnum][0],trgLSdata[lsnum][1],trgLSdata[lsnum][2],trgLSdata[lsnum][3]
[runnum,datasource,npath,pathnames]=dataDML.hltRunById(schema,hltdataid)
print 'npath,pathnames ',npath,pathnames
pathnameList=pathnames.split(',')
(runnum,hltLSdata)=dataDML.hltLSById(schema,hltdataid)
cmsls=hltLSdata.keys()
cmsls.sort()
for lsnum in cmsls:
prescaleblob=hltLSdata[lsnum][0]
print 'lsnum ',lsnum
if prescaleblob:
hltprescales=CommonUtil.unpackBlobtoArray(prescaleblob,'h')
def effectiveLumiForRange(schema,inputRange,hltpathname=None,hltpathpattern=None,amodetag=None,beamstatus=None,egev=None,withBXInfo=False,xingMinLum=0.0,bxAlgo=None,withBeamIntensity=False,norm=None,finecorrections=None,driftcorrections=None,usecorrectionv2=False,lumitype='HF',branchName=None):
'''
input:
inputRange {run:[cmsls]} (required)
hltpathname: selected hltpathname
hltpathpattern: regex select hltpaths
amodetag: amodetag for picking norm(optional)
egev: beamenergy for picking norm(optional)
withBXInfo: get per bunch info (optional)
bxAlgo: algoname for bx values (optional) ['OCC1','OCC2','ET']
xingMinLum: cut on bx lumi value (optional)
withBeamIntensity: get beam intensity info (optional)
normname: norm factor name to use (optional)
branchName: data version
output:
result {run:[lumilsnum(0),cmslsnum(1),timestamp(2),beamstatus(3),beamenergy(4),deliveredlumi(5),recordedlumi(6),calibratedlumierror(7),{hltpath:[l1name,l1prescale,hltprescale,efflumi]},bxdata,beamdata,fillnum]}
lumi unit: 1/ub
'''
if lumitype not in ['HF','PIXEL']:
raise ValueError('unknown lumitype '+lumitype)
if branchName is None:
branchName='DATA'
lumitableName=''
lumilstableName=''
if lumitype=='HF':
lumitableName=nameDealer.lumidataTableName()
lumilstableName=nameDealer.lumisummaryv2TableName()
else:
lumitableName=nameDealer.pixellumidataTableName()
lumilstableName=nameDealer.pixellumisummaryv2TableName()
numbx=3564
result = {}
normval=None
perbunchnormval=None
if norm:
normval=_getnorm(schema,norm)
perbunchnormval=float(normval)/float(1000)
elif amodetag and egev:
normval=_decidenormFromContext(schema,amodetag,egev)
perbunchnormval=float(normval)/float(1000)
c=lumiTime.lumiTime()
lumip=lumiParameters.ParametersObject()
for run in inputRange.keys():
lslist=inputRange[run]
if lslist is not None and len(lslist)==0:#no selected ls, do nothing for this run
result[run]=[]
continue
cmsrunsummary=dataDML.runsummary(schema,run)
if len(cmsrunsummary)==0:#non existing run
result[run]=None
continue
startTimeStr=cmsrunsummary[6]
fillnum=cmsrunsummary[4]
lumidataid=None
trgdataid=None
hltdataid=None
lumidataid=dataDML.guessLumiDataIdByRun(schema,run,lumitableName)
trgdataid=dataDML.guessTrgDataIdByRun(schema,run)
hltdataid=dataDML.guessHltDataIdByRun(schema,run)
if lumidataid is None or trgdataid is None or hltdataid is None:
result[run]=None
continue
(lumirunnum,lumidata)=dataDML.lumiLSById(schema,lumidataid,beamstatus,tableName=lumilstableName)
(trgrunnum,trgdata)=dataDML.trgLSById(schema,trgdataid,withPrescale=True)
(hltrunnum,hltdata)=dataDML.hltLSById(schema,hltdataid,hltpathname=hltpathname,hltpathpattern=hltpathpattern)
hlttrgmap=dataDML.hlttrgMappingByrun(schema,run)
if not normval:#if norm cannot be decided , look for it according to context per run
normval=_decidenormForRun(schema,run)
perbunchnormval=float(normval)/float(1000)
if not normval:#still not found? resort to global default (should never come here)
normval=6370
perbunchnormval=6.37
print '[Warning] using default normalization '+str(normval)
perrunresult=[]
for lumilsnum,perlsdata in lumidata.items():
cmslsnum=perlsdata[0]
triggeredls=perlsdata[0]
if lslist is not None and cmslsnum not in lslist:
#cmslsnum=0
triggeredls=0
recordedlumi=0.0
instlumi=perlsdata[1]
instlumierror=perlsdata[2]
avglumi=instlumi*normval
calibratedlumi=avglumi
if lumitype=='HF' and finecorrections and finecorrections[run]:
if usecorrectionv2:
if driftcorrections and driftcorrections[run]:
calibratedlumi=lumiCorrections.applyfinecorrectionV2(avglumi,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2],finecorrections[run][3],finecorrections[run][4],driftcorrections[run])
else:
calibratedlumi=lumiCorrections.applyfinecorrectionV2(avglumi,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2],finecorrections[run][3],finecorrections[run][4],1.0)
else:
calibratedlumi=lumiCorrections.applyfinecorrection(avglumi,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2])
if lumitype=='PIXEL' and finecorrections is not None:
calibratedlumi=finecorrections[run]*avglumi
calibratedlumierror=instlumierror*normval
bstatus=perlsdata[4]
begev=perlsdata[5]
numorbit=perlsdata[6]
startorbit=perlsdata[7]
timestamp=c.OrbitToTime(startTimeStr,startorbit,0)
lslen=lumip.lslengthsec()
deliveredlumi=calibratedlumi*lslen
recordedlumi=0.0
trgprescalemap={}#trgprescalemap for this ls
efflumidict={}
if triggeredls!=0:
if not trgdata.has_key(cmslsnum):
#triggeredls=0 #if no trigger, set back to non-cms-active ls
recordedlumi=0.0 # no trigger->nobeam recordedlumi=None
else:
deadcount=trgdata[cmslsnum][0] ##subject to change !!
bitzerocount=trgdata[cmslsnum][1]
bitzeroprescale=trgdata[cmslsnum][2]
deadfrac=trgdata[cmslsnum][3]
if deadfrac<0 or deadfrac>1.0:
deadfrac=1.0
#if float(bitzerocount)*float(bitzeroprescale)==0.0:
# deadfrac=1.0
#else:
# deadfrac=float(deadcount)/(float(bitzerocount)*float(bitzeroprescale))
#if deadfrac>1.0:
# deadfrac=1.0 #artificial correction in case of deadfrac>1
recordedlumi=deliveredlumi*(1.0-deadfrac)
l1bitinfo=trgdata[cmslsnum][4]
if l1bitinfo:
for thisbitinfo in l1bitinfo:
thisbitname=thisbitinfo[0]
thisbitprescale=thisbitinfo[2]
#trgprescalemap['"'+thisbitname+'"']=thisbitprescale#note:need to double quote bit name!
trgprescalemap['"'+thisbitname+'"']=thisbitprescale
del trgdata[cmslsnum][:]
if hltdata.has_key(cmslsnum):
hltpathdata=hltdata[cmslsnum]
#print 'hltpathdata ',hltpathdata
for pathidx,thispathinfo in enumerate(hltpathdata):
efflumi=0.0
thispathname=thispathinfo[0]
thisprescale=thispathinfo[1]
thisl1seed=None
l1bitname=None
l1prescale=None
try:
thisl1seed=hlttrgmap[thispathname]
except KeyError:
thisl1seed=None
# print 'hltpath, l1seed, hltprescale ',thispathname,thisl1seed,thisprescale
if thisl1seed:
try:
l1bitname=hltTrgSeedMapper.findUniqueSeed(thispathname,thisl1seed)
if l1bitname :
l1prescale=trgprescalemap[l1bitname]#need to match double quoted string!
else:
l1prescale=None
except KeyError:
l1prescale=None
if l1prescale and thisprescale :#normal both prescaled
efflumi=recordedlumi/(float(l1prescale)*float(thisprescale))
efflumidict[thispathname]=[l1bitname,l1prescale,thisprescale,efflumi]
elif l1prescale and thisprescale==0: #hltpath in menu but masked
efflumi=0.0
efflumidict[thispathname]=[l1bitname,l1prescale,thisprescale,efflumi]
else:
efflumi=0.0
efflumidict[thispathname]=[None,0,thisprescale,efflumi]
bxvaluelist=[]
bxerrorlist=[]
bxdata=None
beamdata=None
if withBXInfo:
bxinfo=lumidata[8]
bxvalueArray=None
bxerrArray=None
if bxinfo:
bxvalueArray=bxinfo[0]
bxerrArray=bxinfo[1]
for idx,bxval in enumerate(bxvalueArray):
if finecorrections and finecorrections[run]:
if usecorrectionv2:
if driftcorrections and driftcorrections[run]:
mybxval=lumiCorrections.applyfinecorrectionBXV2(bxval,avglumi,perbunchnormval,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2],finecorrections[run][3],finecorrections[run][4],driftcorrections[run])
else:
mybxval=lumiCorrections.applyfinecorrectionBXV2(bxval,avglumi,perbunchnormval,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2],finecorrections[run][3],finecorrections[run][4],1.0)
else:
mybxval=lumiCorrections.applyfinecorrectionBX(bxval,avglumi,perbunchnormval,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2])
else:
mybxval=bxval*perbunchnormval
if mybxval>xingMinLum:
bxidxlist.append(idx)
bxvaluelist.append(bxval)
bxerrorlist.append(bxerrArray[idx])
del bxvalueArray[:]
del bxerrArray[:]
bxdata=(bxidxlist,bxvaluelist,bxerrorlist)
if withBeamIntensity:
beaminfo=perlsdata[9]
bxindexlist=[]
b1intensitylist=[]
b2intensitylist=[]
if beaminfo:
bxindexarray=beaminfo[0]
beam1intensityarray=beaminfo[1]
beam2intensityarray=beaminfo[2]
bxindexlist=bxindexarray.tolist()
b1intensitylist=beam1intensityarray.tolist()
b2intensitylist=beam2intensityarray.tolist()
del bxindexarray[:]
del beam1intensityarray[:]
del beam2intensityarray[:]
beamdata=(bxindexlist,b1intensitylist,b2intensitylist)
# print cmslsnum,deliveredlumi,recordedlumi,efflumidict
perrunresult.append([lumilsnum,triggeredls,timestamp,bstatus,begev,deliveredlumi,recordedlumi,calibratedlumierror,efflumidict,bxdata,beamdata,fillnum])
del perlsdata[:]
result[run]=perrunresult
#print result
return result
def lumiForRange(schema,inputRange,beamstatus=None,amodetag=None,egev=None,withBXInfo=False,bxAlgo=None,xingMinLum=0.0,withBeamIntensity=False,norm=None,datatag='DATA',finecorrections=None,driftcorrections=None,usecorrectionv2=False,lumitype='HF',branchName=None):
'''
delivered/recorded lumi
input:
inputRange {run:[cmsls]} (required)
beamstatus: LS filter on beamstatus (optional)
amodetag: amodetag for picking norm(optional)
egev: beamenergy for picking norm(optional)
withBXInfo: get per bunch info (optional)
bxAlgo: algoname for bx values (optional) ['OCC1','OCC2','ET']
xingMinLum: cut on bx lumi value (optional)
withBeamIntensity: get beam intensity info (optional)
normname: norm factor name to use (optional)
branchName: data version
output:
result {run:[lumilsnum(0),cmslsnum(1),timestamp(2),beamstatus(3),beamenergy(4),deliveredlumi(5),recordedlumi(6),calibratedlumierror(7),(bxidx,bxvalues,bxerrs)(8),(bxidx,b1intensities,b2intensities)(9),fillnum(10)]}
lumi unit: 1/ub
'''
if lumitype not in ['HF','PIXEL']:
raise ValueError('unknown lumitype '+lumitype)
#if branchName is None:
# branchName='DATA'
lumip=lumiParameters.ParametersObject()
lumitableName=''
lumilstableName=''
if lumitype=='HF':
lumitableName=nameDealer.lumidataTableName()
lumilstableName=nameDealer.lumisummaryv2TableName()
else:
lumitableName=nameDealer.pixellumidataTableName()
lumilstableName=nameDealer.pixellumisummaryv2TableName()
numbx=lumip.NBX
result = {}
normval=None
perbunchnormval=None
if norm:
normval=_getnorm(schema,norm)
perbunchnormval=float(normval)/float(1000)
elif amodetag and egev:
normval=_decidenormFromContext(schema,amodetag,egev)
perbunchnormval=float(normval)/float(1000)
c=lumiTime.lumiTime()
for run in inputRange.keys():#loop over run
lslist=inputRange[run]
if lslist is not None and len(lslist)==0:#no selected ls, do nothing for this run
result[run]=[]
continue
cmsrunsummary=dataDML.runsummary(schema,run)
if len(cmsrunsummary)==0:#non existing run
result[run]=None
continue
startTimeStr=cmsrunsummary[6]
fillnum=cmsrunsummary[4]
lumidataid=None
trgdataid=None
lumidataid=dataDML.guessLumiDataIdByRun(schema,run,lumitableName)
if lumidataid is None :
result[run]=None
continue
trgdataid=dataDML.guessTrgDataIdByRun(schema,run)
(lumirunnum,lumidata)=dataDML.lumiLSById(schema,lumidataid,beamstatus=beamstatus,withBXInfo=withBXInfo,bxAlgo=bxAlgo,withBeamIntensity=withBeamIntensity,tableName=lumilstableName)
if trgdataid is None :
trgdata={}
else:
(trgrunnum,trgdata)=dataDML.trgLSById(schema,trgdataid)
if not normval:#if norm cannot be decided , look for it according to context per run
normval=_decidenormForRun(schema,run)
perbunchnormval=float(normval)/float(1000)
if not normval:#still not found? resort to global default (should never come here)
normval=6370
perbunchnormval=6.37
print '[Warning] using default normalization '+str(normval)
perrunresult=[]
for lumilsnum,perlsdata in lumidata.items():
cmslsnum=perlsdata[0]
triggeredls=perlsdata[0]
if lslist is not None and cmslsnum not in lslist:
#cmslsnum=0
triggeredls=0
recordedlumi=0.0
instlumi=perlsdata[1]
instlumierror=perlsdata[2]
avglumi=instlumi*normval
calibratedlumi=avglumi
if lumitype=='HF' and finecorrections and finecorrections[run]:
if usecorrectionv2:
if driftcorrections and driftcorrections[run]:
calibratedlumi=lumiCorrections.applyfinecorrectionV2(avglumi,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2],finecorrections[run][3],finecorrections[run][4],driftcorrections[run])
else:
calibratedlumi=lumiCorrections.applyfinecorrectionV2(avglumi,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2],finecorrections[run][3],finecorrections[run][4],1.0)
else:
calibratedlumi=lumiCorrections.applyfinecorrection(avglumi,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2])
if lumitype=='PIXEL' and finecorrections is not None:
calibratedlumi=finecorrections[run]*avglumi
calibratedlumierror=instlumierror*normval
bstatus=perlsdata[4]
begev=perlsdata[5]
numorbit=perlsdata[6]
startorbit=perlsdata[7]
timestamp=c.OrbitToTime(startTimeStr,startorbit,0)
lslen=lumip.lslengthsec()
deliveredlumi=calibratedlumi*lslen
recordedlumi=0.0
if triggeredls!=0:
if not trgdata.has_key(cmslsnum):
# triggeredls=0 #if no trigger, set back to non-cms-active ls
recordedlumi=0.0 # no trigger->nobeam recordedlumi=None
else:
deadcount=trgdata[cmslsnum][0] ##subject to change !!
bitzerocount=trgdata[cmslsnum][1]
bitzeroprescale=trgdata[cmslsnum][2]
deadfrac=trgdata[cmslsnum][3]
if deadfrac<0 or deadfrac>1.0:
deadfrac=1.0
#if float(bitzerocount)*float(bitzeroprescale)==0.0:
# deadfrac=1.0
#else:
# deadfrac=float(deadcount)/(float(bitzerocount)*float(bitzeroprescale))
#if deadfrac>1.0:
# deadfrac=1.0 #artificial correction in case of deadfrac>1
recordedlumi=deliveredlumi*(1.0-deadfrac)
del trgdata[cmslsnum][:]
bxdata=None
if withBXInfo:
bxinfo=perlsdata[8]
bxvalueArray=None
bxerrArray=None
bxidxlist=[]
bxvaluelist=[]
bxerrorlist=[]
if bxinfo:
bxvalueArray=bxinfo[0]
bxerrArray=bxinfo[1]
#if cmslsnum==1:
# print 'bxvalueArray ',bxvalueArray
for idx,bxval in enumerate(bxvalueArray):
if finecorrections and finecorrections[run]:
if usecorrectionv2:
if driftcorrections and driftcorrections[run]:
mybxval=lumiCorrections.applyfinecorrectionBXV2(bxval,avglumi,perbunchnormval,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2],finecorrections[run][3],finecorrections[run][4],driftcorrections[run])
else:
mybxval=lumiCorrections.applyfinecorrectionBXV2(bxval,avglumi,perbunchnormval,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2],finecorrections[run][3],finecorrections[run][4],1.0)
else:
mybxval=lumiCorrections.applyfinecorrectionBX(bxval,avglumi,perbunchnormval,finecorrections[run][0],finecorrections[run][1],finecorrections[run][2])
else:
mybxval=bxval*perbunchnormval
if mybxval>xingMinLum:
bxidxlist.append(idx)
bxvaluelist.append(mybxval)
bxerrorlist.append(bxerrArray[idx]*perbunchnormval)#no correciton on errors
del bxvalueArray[:]
del bxerrArray[:]
bxdata=(bxidxlist,bxvaluelist,bxerrorlist)
beamdata=None
if withBeamIntensity:
beaminfo=perlsdata[9]
bxindexlist=[]
b1intensitylist=[]
b2intensitylist=[]
if beaminfo:
bxindexarray=beaminfo[0]
beam1intensityarray=beaminfo[1]
beam2intensityarray=beaminfo[2]
bxindexlist=bxindexarray.tolist()
b1intensitylist=beam1intensityarray.tolist()
b2intensitylist=beam2intensityarray.tolist()
del bxindexarray[:]
del beam1intensityarray[:]
del beam2intensityarray[:]
beamdata=(bxindexlist,b1intensitylist,b2intensitylist)
perrunresult.append([lumilsnum,triggeredls,timestamp,bstatus,begev,deliveredlumi,recordedlumi,calibratedlumierror,bxdata,beamdata,fillnum])
del perlsdata[:]
result[run]=perrunresult
return result
