def FiltFunc(args):
with open(args.cfgFileName, 'r') as ymlCfgFile:
inputCfg = yaml.load(ymlCfgFile, yaml.FullLoader)
with open(args.cutSetFileNames[0], 'r') as ymlCutSetFile:
cutSetCfg = yaml.load(ymlCutSetFile, yaml.FullLoader)
cutVars = cutSetCfg['cutvars']
axesToKeep = cutSetCfg['axestokeep']
infilenames = inputCfg['filename']
if not isinstance(infilenames, list):
infilenames = [infilenames]
for iFile, infilename in enumerate(infilenames):
sparseReco, sparseGen = LoadSparseFromTask(infilename, inputCfg)
# filter sparses
sparseFiltReco = FilterSparses(sparseReco, cutVars, axesToKeep)
if inputCfg['isMC']:
sparseFiltGen = FilterSparses(sparseGen, cutVars, axesToKeep)
# plot filtered sparses (each variable vs pt)
if args.plot:
PlotFiltVarsVsPt(sparseFiltReco, 'cReco{0}'.format(iFile))
if inputCfg['isMC']:
PlotFiltVarsVsPt(sparseFiltGen, 'cGen{0}'.format(iFile))
# get other objects from original file
inlist = LoadListFromTask(infilename, inputCfg)
_, normCounter = LoadNormObjFromTask(infilename, inputCfg)
cutObj, cutObjName = LoadCutObjFromTask(infilename, inputCfg)
for sparse in sparseFiltReco.values():
sparsetodel = inlist.FindObject(sparse.GetName())
inlist.Remove(sparsetodel)
inlist.Add(sparse)
if inputCfg['isMC']:
for sparse in sparseFiltGen.values():
sparsetodel = inlist.FindObject(sparse.GetName())
inlist.Remove(sparsetodel)
inlist.Add(sparse)
# save new file with filtered sparses
outfilename = infilename
if args.suffix:
outfilename = outfilename.replace(
'.root', '{0}.root'.format(args.suffix))
print('Saving filtered ThnSparses in file', outfilename)
outfile = TFile(outfilename, 'recreate')
outdir = TDirectoryFile(inputCfg['dirname'], inputCfg['dirname'])
outdir.Write(inputCfg['dirname'])
outdir.cd()
inlist.Write(inputCfg['listname'], 1)
cutObj.Write(cutObjName)
normCounter.Write()
outfile.Close()
def FiltFuncV2(args):
with open(args.cfgFileName, 'r') as ymlCfgFile:
inputCfg = yaml.load(ymlCfgFile, yaml.FullLoader)
cutSetsCfg = []
for cutFile in args.cutSetFileNames:
with open(cutFile, 'r') as file:
cutCfg = yaml.load(file, yaml.FullLoader)
cutSetsCfg.append(cutCfg)
if not len(cutSetsCfg) == len(inputCfg['dirname']) == len(
inputCfg['listname']):
print('Wrong number of cut sets, dir names or list names')
return
sparseList = LoadSparseFromTaskV2(inputCfg)
sparseListFilt = []
for sparse, cutSet in zip(sparseList, cutSetsCfg):
sparseFilt = FilterSparsesV2(sparse, cutSet['cutvars'],
cutSet['axestokeep'])
sparseListFilt.append(sparseFilt)
for sparse in sparseListFilt[1:]:
sparseListFilt[0].Add(sparse)
# get other objects from original file
inlist = LoadListFromTaskV2(inputCfg['filename'], inputCfg['dirname'][0],
inputCfg['listname'][0])
sparsetodel = inlist.FindObject(sparseList[0].GetName())
inlist.Remove(sparsetodel)
inlist.Add(sparseListFilt[0])
# save new file with filtered sparses
outfilename = inputCfg['outfilename']
print('Saving filtered ThnSparses in file', outfilename)
outfile = TFile(outfilename, 'recreate')
outdir = TDirectoryFile(inputCfg['outdirname'], inputCfg['outdirname'])
outdir.Write(inputCfg['outdirname'])
outdir.cd()
inlist.Write(inputCfg['outlistname'], 1)
outfile.Close()
1: '#it{p}_{T} (GeV/#it{c})',
2: '#Delta#it{M}_{KK} (MeV/#it{c})',
3: 'decay length (#mum #times 0.1)',
4: 'decay length xy (#mum #times 0.1)',
5: 'normalised decay length xy',
6: 'cos(#theta_{p}) #times 100',
7: 'cos(#theta_{p}^{xy}) #times 100',
8: 'sigma vertex (#mum #times 0.1)',
10: '|cos^{3}(#piK#phi)|',
11: 'max norm #it{d}_{0}-#it{d}_{0}^{exp}',
12: 'impact parameter xy'
}
outfile = TFile(ARGS.outFileName, 'recreate')
dir1D = TDirectoryFile('Distr1D', 'Distr1D')
dir1D.Write()
outfile.cd()
dirVsPt = TDirectoryFile('DistrVsPt', 'DistrVsPt')
dirVsPt.Write()
outfile.cd()
dirVsML = TDirectoryFile('DistrVsML', 'DistrVsML')
dirVsML.Write()
cVars, cVarsNorm, cVarsVsPt, cVarsVsML = {}, {}, {}, {}
hVars, hVarsSel, hVarsNorm, hVarsSelNorm, hVarsVsPt, hVarsSelVsPt, hVarsVsML, hVarsSelVsML = (
{} for iDic in range(8))
listoffigures = []
for iPt, (ptmin,
ptmax) in enumerate(zip(cutVars['Pt']['min'], cutVars['Pt']['max'])):
cVars[f'Pt{ptmin:.0f}_{ptmax:.0f}'] = TCanvas(
RaaFD = RaaFD_config
# load constant terms
nExpEv = inputCfg['nExpectedEvents']
Taa = inputCfg['Taa']
sigmaMB = inputCfg['sigmaMB']
# set batch mode if enabled
if args.batch:
gROOT.SetBatch(True)
gROOT.ProcessLine("gErrorIgnoreLevel = kFatal;")
# output file with TNtuple
outFile = TFile(args.outFileName, 'recreate')
outDirFitSB = TDirectoryFile('SBfits', 'SBfits')
outDirFitSB.Write()
outDirFitSBPt = []
outFile.cd()
outDirPlots = TDirectoryFile('plots', 'plots')
outDirPlots.Write()
outDirPlotsPt = []
estNames = {
'Signif': 'expected significance',
'SoverB': 'S/B',
'S': 'expected signal',
'B': 'expected background',
'EffAccPrompt': '(Acc#times#font[152]{e})_{prompt}',
'EffAccFD': '(Acc#times#font[152]{e})_{FD}',
'fPrompt': '#it{f}_{ prompt}^{ fc}',
hRawYieldsSecPeak.Write()
hRawYieldsMeanSecPeak.Write()
hRawYieldsSigmaSecPeak.Write()
hRawYieldsSignificanceSecPeak.Write()
hRawYieldsSigmaRatioSecondFirstPeak.Write()
hRawYieldsSoverBSecPeak.Write()
hRawYieldsSignalSecPeak.Write()
hRawYieldsBkgSecPeak.Write()
hRawYieldsTrue.Write()
hRawYieldsSecPeakTrue.Write()
hRelDiffRawYieldsFitTrue.Write()
hRelDiffRawYieldsSecPeakFitTrue.Write()
hEv.Write()
if not args.isMC:
dirSB = TDirectoryFile('SandBDiffNsigma', 'SandBDiffNsigma')
dirSB.Write()
dirSB.cd()
for iS, _ in enumerate(nSigma4SandB):
hRawYieldsSignalDiffSigma[iS].Write()
hRawYieldsBkgDiffSigma[iS].Write()
hRawYieldsSoverBDiffSigma[iS].Write()
hRawYieldsSignifDiffSigma[iS].Write()
dirSB.Close()
outFile.Close()
outFileNamePDF = args.outFileName.replace('.root', '.pdf')
outFileNameResPDF = outFileNamePDF.replace('.pdf', '_Residuals.pdf')
for iCanv, (cM, cR) in enumerate(zip(cMass, cResiduals)):
if iCanv == 0 and nCanvases > 1:
cM.SaveAs(f'{outFileNamePDF}[')
cM.SaveAs(outFileNamePDF)
hBkg[-1].SetDirectory(0)
hSgnMin[-1].SetDirectory(0)
hSgnMax[-1].SetDirectory(0)
hSignif[-1].SetDirectory(0)
hSignifMin[-1].SetDirectory(0)
hSignifMax[-1].SetDirectory(0)
hSoverB[-1].SetDirectory(0)
hSoverBMin[-1].SetDirectory(0)
hSoverBMax[-1].SetDirectory(0)
hEff[-1].SetDirectory(0)
hAcc[-1].SetDirectory(0)
hEffAcc[-1].SetDirectory(0)
outFile.cd()
outDir = TDirectoryFile(meson, meson)
outDir.Write()
outDir.cd()
hSgn[-1].Write()
hSgnMin[-1].Write()
hSgnMax[-1].Write()
for iPt, _ in enumerate(hMassSignal):
hMassSignal[iPt].Write()
hMassSignalMin[iPt].Write()
hMassSignalMax[iPt].Write()
hBkg[-1].Write()
for iPt, _ in enumerate(hMassSignal):
hMassBkg[iPt].Write()
hMassBkgMin[iPt].Write()
hMassBkgMax[iPt].Write()
hSignif[-1].Write()
hSignifMin[-1].Write()