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89 lines
3.3 KiB
89 lines
3.3 KiB
# Renata Kopecna
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import uproot
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import numpy as np
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import matplotlib.pyplot as plt
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import sys
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sys.path.insert(0,'/home/lhcb/kopecna/B2KstarMuMu_clean/Code/Selection/ComparisonTool')
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#import Utils
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from Utils3 import getTreeList
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def plotMultiple(year, Run, Reference, PHSP, verbose):
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#Check if 2015
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is2015 = (year == 2015 and Run == 0)
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#Load the branch
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dataTM = uproot.lazyarray(getTreeList(2016 if (is2015) else year, Run, True, True, Reference, PHSP, verbose),"DecayTreeTruthMatched","IsAloneAt_TMed_rndGamma")
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dataMC = uproot.lazyarray(getTreeList(2016 if (is2015) else year, Run, True, True, Reference, PHSP, verbose),"DecayTreeTruthMatched","IsAloneAtNotTM")
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data = uproot.lazyarray(getTreeList(year, Run, False, True, Reference, PHSP, verbose),"DecayTree","IsAloneAt")
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#Switch to numpy array (check if neded)
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arr_MLPresponse = np.array(data, dtype=float)
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arr_MLPresponseMC = np.array(dataMC, dtype=float)
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arr_MLPresponseTM = np.array(dataTM, dtype=float)
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nEvts = arr_MLPresponse.size
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nMCEvts = arr_MLPresponseMC.size
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nTMEvts = arr_MLPresponseTM[arr_MLPresponseTM!=2].size
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if (verbose):
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print ("nEvts: ", nEvts)
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print ("nMCEvts: ", nMCEvts)
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print ("nTMEvts: ", nTMEvts)
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#Define a figure
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fig = plt.figure()
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#Define steps in x-axis
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arr_steps = np.arange(0.9,1.0,0.001)
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multiple_fraction = []
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multiple_fraction_MC = []
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multiple_fraction_TM = []
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if (verbose): print("Steps in MLP:",arr_steps)
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#Get the fractions
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for m in arr_steps:
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multiple_fraction.append(1-arr_MLPresponse[arr_MLPresponse<=m].size / float(nEvts))
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multiple_fraction_MC.append(1-arr_MLPresponseMC[arr_MLPresponseMC<=m].size / float(nMCEvts))
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multiple_fraction_TM.append(1-arr_MLPresponseTM[arr_MLPresponseTM<=m].size / float(nTMEvts))
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plt.plot(arr_steps,multiple_fraction,marker=".",label = "Data")
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plt.plot(arr_steps,multiple_fraction_MC,marker=".",label = "MC")
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plt.plot(arr_steps,multiple_fraction_TM,marker=".",label = "TM MC")
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plt.ylim(0.0,0.21)
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plt.legend(loc="upper right", prop={'size': 14})
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tag = "Run " + str(Run) if (Run != 0) else "Year " + str(year)
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plt.text(0.905,0.175,tag, fontsize=24)
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plt.xlabel('MVA response cut',fontsize=14)
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plt.ylabel('Multiple candidates fraction',fontsize=14)
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name = "Run_" + str(Run) if (Run != 0) else "year_" + str(year)
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fig.savefig(name,dpi = fig.dpi, bbox_inches='tight')
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return
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def plotKplusmumu(year,Run,MC,Reference,PHSP,verbose):
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#Check if 2015
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is2015 = (year == 2015 and Run == 0)
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if (Reference or PHSP): MC = True
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treeName = "DecayTreeTruthMatched" if (MC) else "DecayTree"
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#Load the branch
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branch_list = ["PX", "PY", "PZ", "PE"]
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particle_list = ["K_plus", "mu_plus", "mu_minus"]
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array_list = []
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for part in particle_list:
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for branch in branch_list:
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branchName = part+"_"+branch+"_DTF"
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array_list.append(np.array(uproot.lazyarray(getTreeList(2016 if (is2015) else year, Run, MC, MC, Reference, PHSP, verbose),treeName,branchName)),dtype=float)
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nEvts = array_list[0].size
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#plotMultiple(2011,1,False, False,True)
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#plotMultiple(2016,2,False, False,True)
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for yr in [2011,2012,2015,2016,2017,2018]:
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plotMultiple(yr,0,False,False,True)
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