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dv2_processor.py
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dv2_processor.py
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from coffea.nanoevents import NanoEventsFactory, BaseSchema, PFNanoAODSchema
import json
import fastjet
import numpy as np
import awkward as ak
from coffea import processor
import hist
import coffea.nanoevents.methods.vector as vector
import warnings
import hist.dask as dhist
import dask
import pickle
import os
import distributed
from ndcctools.taskvine import DaskVine
import time
full_start = time.time()
if __name__ == '__main__':
m = DaskVine([9123,9128], name="hgg", run_info_path='/project01/ndcms/cmoore24/vine-run-info')
warnings.filterwarnings("ignore", "Found duplicate branch")
warnings.filterwarnings("ignore", "Missing cross-reference index for")
warnings.filterwarnings("ignore", "dcut")
warnings.filterwarnings("ignore", "Please ensure")
warnings.filterwarnings("ignore", "The necessary")
hgg_files = os.listdir('/project01/ndcms/cmoore24/signal/hgg')
hbb_files = os.listdir('/project01/ndcms/cmoore24/signal/hbb')
q347_files = os.listdir('/project01/ndcms/cmoore24/qcd/300to470')
q476_files = os.listdir('/project01/ndcms/cmoore24/qcd/470to600')
q68_files = os.listdir('/project01/ndcms/cmoore24/qcd/600to800')
q810_files = os.listdir('/project01/ndcms/cmoore24/qcd/800to1000')
q1014_files = os.listdir('/project01/ndcms/cmoore24/qcd/1000to1400')
q1418_files = os.listdir('/project01/ndcms/cmoore24/qcd/1400to1800')
q1824_files = os.listdir('/project01/ndcms/cmoore24/qcd/1800to2400')
q2432_files = os.listdir('/project01/ndcms/cmoore24/qcd/2400to3200')
q32inf_files = os.listdir('/project01/ndcms/cmoore24/qcd/3200toInf')
hgg = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/signal/hgg/' + fn: "/Events"} for fn in hgg_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "Hgg"},
).events()
hbb = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/signal/hbb/' + fn: "/Events"} for fn in hbb_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "Hbb"},
).events()
q347 = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/qcd/300to470/' + fn: "/Events"} for fn in q347_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "QCD_Pt_300to470"},
).events()
q476 = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/qcd/470to600/' + fn: "/Events"} for fn in q476_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "QCD_Pt_470to600"},
).events()
q68 = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/qcd/600to800/' + fn: "/Events"} for fn in q68_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "QCD_Pt_600to800"},
).events()
q810 = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/qcd/800to1000/' + fn: "/Events"} for fn in q810_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "QCD_Pt_800to1000"},
).events()
q1014 = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/qcd/1000to1400/' + fn: "/Events"} for fn in q1014_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "QCD_Pt_1000to1400"},
).events()
q1418 = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/qcd/1400to1800/' + fn: "/Events"} for fn in q1418_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "QCD_Pt_1400to1800"},
).events()
q1824 = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/qcd/1800to2400/' + fn: "/Events"} for fn in q1824_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "QCD_Pt_1800to2400"},
).events()
q2432 = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/qcd/2400to3200/' + fn: "/Events"} for fn in q2432_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "QCD_Pt_2400to3200"},
).events()
q32Inf = NanoEventsFactory.from_root(
[{'/project01/ndcms/cmoore24/qcd/3200toInf/' + fn: "/Events"} for fn in q32inf_files],
permit_dask=True,
schemaclass=PFNanoAODSchema,
metadata={"dataset": "QCD_Pt_3200toInf"},
).events()
def color_ring(fatjet):
jetdef = fastjet.JetDefinition(fastjet.cambridge_algorithm, 0.8) # make this C/A at 0.8
pf = ak.flatten(fatjet.constituents.pf, axis=1)
cluster = fastjet.ClusterSequence(pf, jetdef)
subjets = cluster.exclusive_subjets_up_to(data=cluster.exclusive_jets(n_jets=1), nsub=3) #uncomment this when using C/A
#subjets = cluster.inclusive_jets()
vec = ak.zip({
"x": subjets.px,
"y": subjets.py,
"z": subjets.pz,
"t": subjets.E,
},
with_name = "LorentzVector",
behavior=vector.behavior,
)
vec = ak.pad_none(vec, 3)
vec["norm3"] = np.sqrt(vec.dot(vec))
vec["idx"] = ak.local_index(vec)
i, j = ak.unzip(ak.combinations(vec, 2))
best = ak.argmax((i + j).mass, axis=1, keepdims=True)
leg1, leg2 = ak.firsts(i[best]), ak.firsts(j[best])
#assert ak.all((leg1 + leg2).mass == ak.max((i + j).mass, axis=1))
#leg3 = vec[(best == 0)*2 + (best == 1)*1 + (best == 2)*0]
leg3 = ak.firsts(vec[(vec.idx != leg1.idx) & (vec.idx != leg2.idx)])
#assert ak.all(leg3.x != leg1.x)
#assert ak.all(leg3.x != leg2.x)
a12 = np.arccos(leg1.dot(leg2) / (leg1.norm3 * leg2.norm3))
a13 = np.arccos(leg1.dot(leg3) / (leg1.norm3 * leg3.norm3))
a23 = np.arccos(leg2.dot(leg3) / (leg2.norm3 * leg3.norm3))
color_ring = ((a13**2 + a23**2)/(a12**2))
return color_ring
def d2_calc(fatjet):
jetdef = fastjet.JetDefinition(fastjet.cambridge_algorithm, 0.8) # make this C/A at 0.8
pf = ak.flatten(fatjet.constituents.pf, axis=1)
cluster = fastjet.ClusterSequence(pf, jetdef)
softdrop = cluster.exclusive_jets_softdrop_grooming()
softdrop_cluster = fastjet.ClusterSequence(softdrop.constituents, jetdef)
d2 = softdrop_cluster.exclusive_jets_energy_correlator(func='D2')
return d2
class MyProcessor_Signal(processor.ProcessorABC):
def __init__(self):
pass
def process(self, events):
dataset = events.metadata['dataset']
fatjet = events.FatJet
genhiggs = (events.GenPart[
(events.GenPart.pdgId==25)
& events.GenPart.hasFlags(["fromHardProcess", "isLastCopy"])
])
parents = events.FatJet.nearest(genhiggs, threshold=0.1)
higgs_jets = ~ak.is_none(parents, axis=1)
cut = ((fatjet.pt > 300) & (fatjet.msoftdrop > 110) &
(fatjet.msoftdrop < 140) & (abs(fatjet.eta) < 2.5)) & (higgs_jets) & (fatjet.btagDDBvLV2 > 0.65)
boosted_fatjet = fatjet[cut]
uf_cr = ak.unflatten(color_ring(boosted_fatjet), counts=ak.num(boosted_fatjet))
d2 = ak.unflatten(d2_calc(boosted_fatjet), counts=ak.num(boosted_fatjet))
boosted_fatjet['color_ring'] = uf_cr
boosted_fatjet['d2b1'] = d2
hcr = (
dhist.Hist.new
.Reg(40, 0, 10, name='color_ring', label='Color_Ring')
.Weight()
)
d2b1 = (
dhist.Hist.new
.Reg(40, 0, 3, name='D2B1', label='D2B1')
.Weight()
)
cmssw_n2 = (
dhist.Hist.new
.Reg(40, 0, 0.5, name='cmssw_n2', label='CMSSW_N2')
.Weight()
)
cmssw_n3 = (
dhist.Hist.new
.Reg(40, 0, 3, name='cmssw_n3', label='CMSSW_N3')
.Weight()
)
ncons = (
dhist.Hist.new
.Reg(40, 0, 200, name='constituents', label='nConstituents')
.Weight()
)
mass = (
dhist.Hist.new
.Reg(40, 0, 250, name='mass', label='Mass')
.Weight()
)
sdmass = (
dhist.Hist.new
.Reg(40, 0, 250, name='sdmass', label='SDmass')
.Weight()
)
btag = (
dhist.Hist.new
.Reg(40, 0, 1, name='Btag', label='Btag')
.Weight()
)
fill_cr = ak.fill_none(ak.flatten(boosted_fatjet.color_ring), 0)
hcr.fill(color_ring=fill_cr)
d2b1.fill(D2B1=ak.flatten(boosted_fatjet.d2b1))
cmssw_n2.fill(cmssw_n2=ak.flatten(boosted_fatjet.n2b1))
cmssw_n3.fill(cmssw_n3=ak.flatten(boosted_fatjet.n3b1))
ncons.fill(constituents=ak.flatten(boosted_fatjet.nConstituents))
mass.fill(mass=ak.flatten(boosted_fatjet.mass))
sdmass.fill(sdmass=ak.flatten(boosted_fatjet.msoftdrop))
btag.fill(Btag=ak.flatten(boosted_fatjet.btagDDBvLV2))
return {
dataset: {
"entries": ak.count(events.event, axis=None),
"Color_Ring": hcr,
"N2": cmssw_n2,
"N3": cmssw_n3,
"nConstituents": ncons,
"Mass": mass,
"SDmass": sdmass,
"Btag": btag,
"D2": d2b1,
}
}
def postprocess(self, accumulator):
pass
class MyProcessor_Background(processor.ProcessorABC):
def __init__(self):
pass
def process(self, events):
dataset = events.metadata['dataset']
fatjet = events.FatJet
cut = ((fatjet.pt > 300) & (fatjet.msoftdrop > 110) &
(fatjet.msoftdrop < 140) & (abs(fatjet.eta) < 2.5)) & (fatjet.btagDDBvLV2 > 0.65)
boosted_fatjet = fatjet[cut]
uf_cr = ak.unflatten(color_ring(boosted_fatjet), counts=ak.num(boosted_fatjet))
d2 = ak.unflatten(d2_calc(boosted_fatjet), counts=ak.num(boosted_fatjet))
boosted_fatjet['color_ring'] = uf_cr
boosted_fatjet['d2b1'] = d2
hcr = (
dhist.Hist.new
.Reg(40, 0, 10, name='color_ring', label='Color_Ring')
.Weight()
)
d2b1 = (
dhist.Hist.new
.Reg(40, 0, 3, name='D2B1', label='D2B1')
.Weight()
)
cmssw_n2 = (
dhist.Hist.new
.Reg(40, 0, 0.5, name='cmssw_n2', label='CMSSW_N2')
.Weight()
)
cmssw_n3 = (
dhist.Hist.new
.Reg(40, 0, 3, name='cmssw_n3', label='CMSSW_N3')
.Weight()
)
ncons = (
dhist.Hist.new
.Reg(40, 0, 200, name='constituents', label='nConstituents')
.Weight()
)
mass = (
dhist.Hist.new
.Reg(40, 0, 250, name='mass', label='Mass')
.Weight()
)
sdmass = (
dhist.Hist.new
.Reg(40, 0, 250, name='sdmass', label='SDmass')
.Weight()
)
btag = (
dhist.Hist.new
.Reg(40, 0, 1, name='Btag', label='Btag')
.Weight()
)
fill_cr = ak.fill_none(ak.flatten(boosted_fatjet.color_ring), 0)
hcr.fill(color_ring=fill_cr)
d2b1.fill(D2B1=ak.flatten(boosted_fatjet.d2b1))
cmssw_n2.fill(cmssw_n2=ak.flatten(boosted_fatjet.n2b1))
cmssw_n3.fill(cmssw_n3=ak.flatten(boosted_fatjet.n3b1))
ncons.fill(constituents=ak.flatten(boosted_fatjet.nConstituents))
mass.fill(mass=ak.flatten(boosted_fatjet.mass))
sdmass.fill(sdmass=ak.flatten(boosted_fatjet.msoftdrop))
btag.fill(Btag=ak.flatten(boosted_fatjet.btagDDBvLV2))
return {
dataset: {
"entries": ak.count(events.event, axis=None),
"Color_Ring": hcr,
"N2": cmssw_n2,
"N3": cmssw_n3,
"nConstituents": ncons,
"Mass": mass,
"SDmass": sdmass,
"Btag": btag,
"D2": d2b1,
}
}
def postprocess(self, accumulator):
pass
start = time.time()
result = {}
result['Hgg'] = MyProcessor_Signal().process(hgg)
print('hbb')
result['Hbb'] = MyProcessor_Signal().process(hbb)
print('300')
result['QCD_Pt_300to470_TuneCP5_13TeV_pythia8'] = MyProcessor_Background().process(q347)
print('470')
result['QCD_Pt_470to600_TuneCP5_13TeV_pythia8'] = MyProcessor_Background().process(q476)
print('600')
result['QCD_Pt_600to800_TuneCP5_13TeV_pythia8'] = MyProcessor_Background().process(q68)
print('800')
result['QCD_Pt_800to1000_TuneCP5_13TeV_pythia8'] = MyProcessor_Background().process(q810)
print('1000')
result['QCD_Pt_1000to1400_TuneCP5_13TeV_pythia8'] = MyProcessor_Background().process(q1014)
print('1400')
result['QCD_Pt_1400to1800_TuneCP5_13TeV_pythia8'] = MyProcessor_Background().process(q1418)
print('1800')
result['QCD_Pt_1800to2400_TuneCP5_13TeV_pythia8'] = MyProcessor_Background().process(q1824)
print('2400')
result['QCD_Pt_2400to3200_TuneCP5_13TeV_pythia8'] = MyProcessor_Background().process(q2432)
print('3200')
result['QCD_Pt_3200toInf_TuneCP5_13TeV_pythia8'] = MyProcessor_Background().process(q32Inf)
stop = time.time()
print(stop-start)
print('computing')
computed = dask.compute(result, scheduler=m.get, resources={"cores": 1}, resources_mode=None, lazy_transfers=True)
with open('outputs/big_btagged_result.pkl', 'wb') as f:
pickle.dump(computed, f)
full_stop = time.time()
print('full run time is ' + str((full_stop - full_start)/60))