import numpy as np
outputDict = dict()
for idx, tuningName in enumerate(tuningNameList):
files = expandFolders(basepath + '/' + pathList[idx])
crossValGrid = []
for path in files:
if path.endswith('.pic'):
crossValGrid.append(path)
pprint(crossValGrid)
pprint(configList[idx])
pprint(refBenchmarkList[idx])
c = CrossValidStatAnalysis.exportDiscrFiles(
crossValGrid,
RingerOperation.L2,
triggerChains=tuningName,
refBenchCol=refBenchmarkList[idx],
EtBins=etBins,
EtaBins=etaBins,
configCol=configList[idx])
mainLogger.info('%d bins found in this tuning: %s',
len(c[tuningName].keys()), tuningName)
for etIdx in range(len(etBins) - 1):
for etaIdx in range(len(etaBins) - 1):
thr = c[tuningName][('et%d_eta%d') %
(etIdx, etaIdx)]['discriminator']['threshold']
if np.abs(thrRelax[idx]) > 0:
if (np.abs(thr + thrRelax[idx]) < 0.95):
c[tuningName][('et%d_eta%d') % (
etIdx,
import numpy as np
outputDict=dict()
for idx, tuningName in enumerate(tuningNameList):
files = expandFolders(basepath+'/'+pathList[idx])
crossValGrid=[]
for path in files:
if path.endswith('.pic'):
crossValGrid.append(path)
pprint(crossValGrid)
pprint(configList[idx])
pprint(refBenchmarkList[idx])
c = CrossValidStatAnalysis.exportDiscrFiles(crossValGrid,
RingerOperation.L2,
triggerChains=tuningName,
refBenchCol=refBenchmarkList[idx],
EtBins = etBins,
EtaBins = etaBins,
configCol=configList[idx])
mainLogger.info('%d bins found in this tuning: %s',len(c[tuningName].keys()),tuningName)
for etIdx in range(len(etBins)-1):
for etaIdx in range(len(etaBins)-1):
thr = c[tuningName][('et%d_eta%d')%(etIdx,etaIdx)]['discriminator']['threshold']
if np.abs(thrRelax[idx])>0:
if (np.abs(thr+thrRelax[idx])<0.95):
c[tuningName][('et%d_eta%d')%(etIdx,etaIdx)]['discriminator']['threshold'] += thrRelax[idx]
mainLogger.warning('Relax threshold %f of (etBin = %d, etaBin = %d) to %f', thr, etIdx, etaIdx, thr+thrRelax[idx])
referenceBenchCol = [['Pd','SP','Pf'],
['Pd','SP','Pf'],
['Pd','SP','Pf']]
# Et Bins
etBins = [ 20, 30, 40, 50, 500000 ]
# Eta bins
etaBins = [ 0, 0.8 , 1.37, 1.54, 2.5 ]
# [Tight, Medium, Loose and VeryLoose]
thrRelax = [0,0,0,0]
####################### Extract Ringer Configuration #########################
import numpy as np
for path, referenceBench, configCol in zip(pathList, referenceBenchCol, configList):
files = expandFolders( os.path.join( basepath, path ), '*.pic')
for conf, ref in zip(configCol, referenceBench):
refBenchmark = [[ref] * len(conf)]*len(conf[0])
c = CrossValidStatAnalysis.exportDiscrFiles( sorted(files)
, RingerOperation.Offline
, refBenchCol = ref
, EtBins = etBins
, EtaBins = etaBins
, configCol = conf
#, level = LoggingLevel.VERBOSE
)
###########################################################################
referenceBenchCol = [['Pd','SP','Pf'],
['Pd','SP','Pf'],
['Pd','SP','Pf']]
# Et Bins
etBins = [ 20, 30, 40, 50, 500000 ]
# Eta bins
etaBins = [ 0, 0.8 , 1.37, 1.54, 2.5 ]
# [Tight, Medium, Loose and VeryLoose]
thrRelax = [0,0,0,0]
####################### Extract Ringer Configuration #########################
import numpy as np
for path, referenceBench, configCol in zip(pathList, referenceBenchCol, configList):
files = expandFolders( os.path.join( basepath, path ), '*.pic.gz')
for conf, ref in zip(configCol, referenceBench):
refBenchmark = [[ref] * len(conf)]*len(conf[0])
c = CrossValidStatAnalysis.exportDiscrFiles( sorted(files)
, RingerOperation.Offline
, refBenchCol = ref
, EtBins = etBins
, EtaBins = etaBins
, configCol = conf
#, level = LoggingLevel.VERBOSE
)
###########################################################################
import numpy as np
outputDict = dict()
files = expandFolders(basepath)
crossValGrid = []
for path in files:
if path.endswith('.pic.gz'):
crossValGrid.append(path)
pprint(crossValGrid)
pprint(configList[0])
pprint(refBenchmarkList[0])
d = CrossValidStatAnalysis.exportDiscrFiles(crossValGrid,
RingerOperation.L2,
triggerChains=tuningNameList[0],
refBenchCol=refBenchmarkList[0],
nEtBins=len(etBins),
nEtaBins=len(etaBins),
configCol=configList[0])
print d.keys()
from copy import copy
for tuningName in tuningNameList:
c = {tuningName: copy(d[tuningNameList[0]])}
mainLogger.info('%d bins found in this tuning: %s',
len(c[tuningName].keys()), tuningName)
outputDict.update(c)
####################### Write Ringer Configuration #########################