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save_to_root.py
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save_to_root.py
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#!/usr/bin/env python3
import hist
from coffea import util
from coffea.processor import accumulate
import numpy as np
import uproot
import os
from ttgamma.utils.plotting import RebinHist, SetRangeHist, GroupBy
# NOTE: your timestamps will differ!
outputMC = accumulate(
[
util.load("Outputs/output_MCOther_run20230110_162217.coffea"),
util.load("Outputs/output_MCSingleTop_run20230110_170719.coffea"),
util.load("Outputs/output_MCTTbar1l_run20230110_164315.coffea"),
util.load("Outputs/output_MCTTbar2l_run20230110_170012.coffea"),
util.load("Outputs/output_MCTTGamma_run20230110_171615.coffea"),
util.load("Outputs/output_MCWJets_run20230110_161311.coffea"),
util.load("Outputs/output_MCZJets_run20230110_155614.coffea"),
]
)
outputData = util.load("Outputs/output_Data_run20230110_172734.coffea")
groupingCategory = {
"NonPrompt": [3j,4j],
"MisID": [2j],
"Prompt": [1j],
}
groupingMCDatasets = {
"ZG": [
"ZGamma_01J_5f_lowMass",
],
"WG": [
"WGamma",
],
"other": [
"TTbarPowheg_Dilepton",
"TTbarPowheg_Semilept",
"TTbarPowheg_Hadronic",
"W2jets",
"W3jets",
"W4jets",
"DYjetsM50",
"ST_s_channel",
"ST_tW_channel",
"ST_tbarW_channel",
"ST_tbar_channel",
"ST_t_channel",
"TTWtoLNu",
"TTWtoQQ",
"TTZtoLL",
"GJets_HT200To400",
"GJets_HT400To600",
"GJets_HT600ToInf",
"ZZ",
"WZ",
"WW",
"TGJets"
],
"ttgamma": [
"TTGamma_Dilepton",
"TTGamma_SingleLept",
"TTGamma_Hadronic",
],
}
s = hist.tag.Slicer()
if __name__ == "__main__":
# Group MC histograms
histList = []
for samp, sampList in groupingMCDatasets.items():
histList += [outputMC[s] for s in sampList]
outputMCHist = accumulate(histList)
for key, histo in outputMCHist.items():
if isinstance(histo, hist.Hist):
outputMCHist[key] = GroupBy(histo, 'dataset', 'dataset', groupingMCDatasets)
# Group data histograms
outputDataHist = accumulate([histo for key, histo in outputData.items()])
h = outputMCHist['M3']
h = h[{'lepFlavor':sum}]
h = GroupBy(h, "category", "category", groupingCategory)
h = h[{'M3':s[::hist.rebin(10)]}]
h = SetRangeHist(h, 'M3', 50, 550)
hData = outputDataHist['M3'][{'lepFlavor':sum,'category':sum,'systematic':sum,'dataset':sum}]
hData = hData[{'M3':s[::hist.rebin(10)]}]
hData = SetRangeHist(hData, 'M3', 50, 550)
outdir = "RootFiles"
if not os.path.exists(outdir):
os.makedirs(outdir)
outputFile = uproot.recreate(os.path.join(outdir, "M3_Output.root"))
outputFile["data_obs"] = hData
systematics = h.axes["systematic"]
for _category in ["MisID", "NonPrompt"]:
for _systematic in systematics:
histname = f"{_category}_{_systematic}" if (not f"{_systematic}" == 'nominal') else f"{_category}"
outputFile[histname] = h[{'dataset':sum,'category':_category,'systematic':_systematic}]
for _dataset in ["ttgamma", "WG", "ZG", "other"]:
for _systematic in systematics:
histname = f"{_dataset}_{_systematic}" if (not f"{_systematic}" == 'nominal') else f"{_dataset}"
outputFile[histname] = h[{'dataset':_dataset,'category':'Prompt','systematic':_systematic}]
outputFile.close()
'''
nonprompt control region
'''
# regroup for the different photon categories, summing over all data sets.
h = outputMCHist['photon_chIso']
h = h[{"lepFlavor":sum}]
h = GroupBy(h, "category", "category", groupingCategory)
new_bins = np.array([1.15, 2.5, 4.9, 9, 14.9, 20]) # 1.14 is in the cutbased medium ID.
chIso_axis = hist.axis.Variable(new_bins, name='chIso', label=r"Charged Hadron Isolation");
hData = outputDataHist['photon_chIso'][{'lepFlavor':sum}]
hData = hData[{'category':sum,'systematic':sum,'dataset':sum}]
outputFile = uproot.recreate(os.path.join(outdir, "Isolation_Output.root"))
outputFile["data_obs"] = hData
for _category in ["MisID", "NonPrompt"]:
for _systematic in systematics:
histname = f"{_category}_{_systematic}" if (not f"{_systematic}" == 'nominal') else f"{_category}"
outputFile[histname] = RebinHist(h[{'dataset':sum,'category':_category,'systematic':_systematic}],chIso=chIso_axis)
for _dataset in ["ttgamma", "WG", "ZG", "other"]:
for _systematic in systematics:
histname = f"{_dataset}_{_systematic}" if (not f"{_systematic}" == 'nominal') else f"{_dataset}"
outputFile[histname] = RebinHist(h[{'dataset':_dataset,'category':'Prompt','systematic':_systematic}],chIso=chIso_axis)
outputFile.close()
'''
Mis-ID control region
'''
h = outputMCHist['photon_lepton_mass_3j0t']
h = GroupBy(h, 'category', 'category', groupingCategory)
h = h[{'mass':s[::hist.rebin(20)]}]
h = SetRangeHist(h,'mass',40,200)
hData = outputDataHist['photon_lepton_mass_3j0t']
hData = hData[{'category':sum,'systematic':sum,'dataset':sum}]
hData = hData[{'mass':s[::hist.rebin(20)]}]
hData = SetRangeHist(hData,'mass',40,200)
for _lepton in ["electron", "muon"]:
outputFile = uproot.recreate(os.path.join(outdir, f"MisID_Output_{_lepton}.root"))
outputFile["data_obs"] = hData[{"lepFlavor":_lepton}]
systematics = h.axes["systematic"]
for _category in ["MisID", "NonPrompt"]:
for _systematic in systematics:
histname = f"{_category}_{_systematic}" if (not f"{_systematic}" == 'nominal') else f"{_category}"
outputFile[histname] = h[{'category':_category,'systematic':_systematic,'lepFlavor':_lepton,'dataset':sum}]
for _dataset in ["ttgamma", "WG", "ZG", "other"]:
for _systematic in systematics:
histname = f"{_dataset}_{_systematic}" if (not f"{_systematic}" == 'nominal') else f"{_dataset}"
outputFile[histname] = h[{'category':'Prompt','systematic':_systematic,'lepFlavor':_lepton,'dataset':_dataset}]
outputFile.close()