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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "7b82bb87", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import pandas as pd\n", | ||
"import matplotlib.pyplot as plt\n", | ||
"import mplhep as hep\n", | ||
"import matplotlib.ticker as mticker\n", | ||
"import numpy as np\n", | ||
"\n", | ||
"import uproot\n", | ||
"import awkward as ak\n", | ||
"from coffea import nanoevents\n", | ||
"\n", | ||
"from coffea.nanoevents.methods.base import NanoEventsArray\n", | ||
"from coffea.analysis_tools import Weights, PackedSelection\n", | ||
"from coffea.nanoevents.methods import nanoaod\n", | ||
"from coffea.nanoevents.methods import vector\n", | ||
"from coffea.lookup_tools.dense_lookup import dense_lookup\n", | ||
"\n", | ||
"from HHbbVV.processors.utils import pad_val\n", | ||
"\n", | ||
"plt.style.use(hep.style.CMS)\n", | ||
"hep.style.use(\"CMS\")\n", | ||
"formatter = mticker.ScalarFormatter(useMathText=True)\n", | ||
"formatter.set_powerlimits((-3, 3))\n", | ||
"plt.rcParams.update({\"font.size\": 24})" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "09429b8f", | ||
"metadata": {}, | ||
"source": [ | ||
"Look at single SM VBF HH signal NanoAOD file" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "42e7add7", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"events = nanoevents.NanoEventsFactory.from_root(\n", | ||
" \"root://cmseos.fnal.gov///store/user/lpcpfnano/cmantill/v2_3/2018/HH/VBF_HHTobbVV_CV_1_C2V_1_C3_1_TuneCP5_13TeV-madgraph-pythia8/VBF_HHTobbVV_CV_1_C2V_1_C3_1/220808_150149/0000/nano_mc2018_1-1.root\",\n", | ||
" schemaclass=nanoevents.NanoAODSchema,\n", | ||
").events()\n", | ||
"\n", | ||
"Z_PDGID = 23\n", | ||
"W_PDGID = 24\n", | ||
"HIGGS_PDGID = 25\n", | ||
"GEN_FLAGS = [\"fromHardProcess\", \"isLastCopy\"]" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "7f076483", | ||
"metadata": {}, | ||
"source": [ | ||
"Get generator-level Higgs and Vs" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "1dfff6ce", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"higgs = events.GenPart[\n", | ||
" (abs(events.GenPart.pdgId) == HIGGS_PDGID) * events.GenPart.hasFlags(GEN_FLAGS)\n", | ||
"]\n", | ||
"\n", | ||
"vs = events.GenPart[((abs(events.GenPart.pdgId) == 24)) * events.GenPart.hasFlags(GEN_FLAGS)]" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "398dfc82", | ||
"metadata": {}, | ||
"source": [ | ||
"Reproduce AK4 jet selections from skimmer" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "748e3109", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"ak4_jet_selection = { # noqa: RUF012\n", | ||
" \"pt\": 25,\n", | ||
" \"eta\": 2.7,\n", | ||
" \"jetId\": \"tight\",\n", | ||
" \"puId\": \"medium\",\n", | ||
" \"dR_fatjetbb\": 1.2,\n", | ||
" \"dR_fatjetVV\": 0.8,\n", | ||
"}\n", | ||
"\n", | ||
"# ak8 jet preselection\n", | ||
"preselection = { # noqa: RUF012\n", | ||
" \"pt\": 300.0,\n", | ||
" \"eta\": 2.4,\n", | ||
" \"VVmsd\": 50,\n", | ||
" # \"VVparticleNet_mass\": [50, 250],\n", | ||
" # \"bbparticleNet_mass\": [92.5, 162.5],\n", | ||
" \"bbparticleNet_mass\": 50,\n", | ||
" \"VVparticleNet_mass\": 50,\n", | ||
" \"bbFatJetParticleNetMD_Txbb\": 0.8,\n", | ||
" \"jetId\": 2, # tight ID bit\n", | ||
" \"DijetMass\": 800, # TODO\n", | ||
" # \"nGoodElectrons\": 0,\n", | ||
"}\n", | ||
"\n", | ||
"num_jets = 2" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "7b03b61b", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"fatjets = events.FatJet\n", | ||
"\n", | ||
"# particlenet xbb vs qcd\n", | ||
"\n", | ||
"txbb = pad_val(\n", | ||
" fatjets.particleNetMD_Xbb / (fatjets.particleNetMD_QCD + fatjets.particleNetMD_Xbb),\n", | ||
" num_jets,\n", | ||
" axis=1,\n", | ||
")\n", | ||
"\n", | ||
"# bb VV assignment\n", | ||
"\n", | ||
"bb_mask = txbb[:, 0] >= txbb[:, 1]\n", | ||
"bb_mask = np.stack((bb_mask, ~bb_mask)).T" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "629523e9", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"jets = events.Jet\n", | ||
"\n", | ||
"# dR_fatjetVV = 0.8 used from last two cells of VBFgenInfoTests.ipynb with data generated from SM signal vbf\n", | ||
"# https://github.com/rkansal47/HHbbVV/blob/vbf_systematics/src/HHbbVV/VBF_binder/VBFgenInfoTests.ipynb\n", | ||
"# (0-14R1R2study.parquet) has columns of different nGoodVBFJets corresponding to R1 and R2 cuts\n", | ||
"vbf_jet_mask = (\n", | ||
" jets.isTight\n", | ||
" & (jets.pt > ak4_jet_selection[\"pt\"])\n", | ||
" & (np.abs(jets.eta) < 4.7)\n", | ||
" # medium puId https://twiki.cern.ch/twiki/bin/viewauth/CMS/PileupJetIDUL\n", | ||
" & ((jets.pt > 50) | ((jets.puId & 2) == 2))\n", | ||
" & (\n", | ||
" ak.all(\n", | ||
" jets.metric_table(\n", | ||
" ak.singletons(ak.pad_none(fatjets, num_jets, axis=1, clip=True)[bb_mask])\n", | ||
" )\n", | ||
" > ak4_jet_selection[\"dR_fatjetbb\"],\n", | ||
" axis=-1,\n", | ||
" )\n", | ||
" )\n", | ||
" & (\n", | ||
" ak.all(\n", | ||
" jets.metric_table(\n", | ||
" ak.singletons(ak.pad_none(fatjets, num_jets, axis=1, clip=True)[~bb_mask])\n", | ||
" )\n", | ||
" > ak4_jet_selection[\"dR_fatjetVV\"],\n", | ||
" axis=-1,\n", | ||
" )\n", | ||
" )\n", | ||
")\n", | ||
"\n", | ||
"vbf_jets = jets[vbf_jet_mask]" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "d2998910", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"etas = pad_val(vbf_jets.eta, 2, axis=1)\n", | ||
"\n", | ||
"plt.rcParams.update({\"font.size\": 24})\n", | ||
"plt.figure(figsize=(12, 12))\n", | ||
"plt.hist(np.abs(etas[:, 0] - etas[:, 1]), np.arange(0, 6, 0.25), histtype=\"step\", density=True)\n", | ||
"plt.xlabel(r\"$\\eta_{jj}$\")\n", | ||
"plt.ylabel(\"Events (A. U.)\")\n", | ||
"plt.show()" | ||
] | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "Python 3 (ipykernel)", | ||
"language": "python", | ||
"name": "python3" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 3 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython3", | ||
"version": "3.9.15" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 5 | ||
} |